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<journal-meta>
<journal-id journal-id-type="nlm-ta">PLoS ONE</journal-id>
<journal-id journal-id-type="publisher-id">plos</journal-id>
<journal-id journal-id-type="pmc">plosone</journal-id>
<journal-title-group>
<journal-title>PLOS ONE</journal-title>
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<issn pub-type="epub">1932-6203</issn>
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<publisher-name>Public Library of Science</publisher-name>
<publisher-loc>San Francisco, CA USA</publisher-loc>
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<article-meta>
<article-id pub-id-type="doi">10.1371/journal.pone.0274287</article-id>
<article-id pub-id-type="publisher-id">PONE-D-21-38539</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Research Article</subject>
</subj-group>
<subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Epidemiology</subject><subj-group><subject>Medical risk factors</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Cardiology</subject><subj-group><subject>Heart failure</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Surgical and invasive medical procedures</subject><subj-group><subject>Cardiovascular procedures</subject><subj-group><subject>Coronary artery bypass grafting</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Surgical and invasive medical procedures</subject><subj-group><subject>Cardiovascular procedures</subject><subj-group><subject>Coronary stenting</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Surgical and invasive medical procedures</subject><subj-group><subject>Stent implantation</subject><subj-group><subject>Coronary stenting</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Medical conditions</subject><subj-group><subject>Cardiovascular diseases</subject><subj-group><subject>Coronary heart disease</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Cardiology</subject><subj-group><subject>Cardiovascular medicine</subject><subj-group><subject>Cardiovascular diseases</subject><subj-group><subject>Coronary heart disease</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Vascular medicine</subject><subj-group><subject>Coronary heart disease</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Cardiology</subject><subj-group><subject>Arrhythmia</subject><subj-group><subject>Atrial fibrillation</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Hematology</subject><subj-group><subject>Anemia</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Medical conditions</subject><subj-group><subject>Cardiovascular diseases</subject><subj-group><subject>Cardiovascular disease risk</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Medicine and health sciences</subject><subj-group><subject>Cardiology</subject><subj-group><subject>Cardiovascular medicine</subject><subj-group><subject>Cardiovascular diseases</subject><subj-group><subject>Cardiovascular disease risk</subject></subj-group></subj-group></subj-group></subj-group></subj-group></article-categories>
<title-group>
<article-title>Clinical usefulness of the pattern of non-adherence to anti-platelet regimen in stented patients (PARIS) thrombotic risk score to predict long-term all-cause mortality and heart failure hospitalization after percutaneous coronary intervention</article-title>
<alt-title alt-title-type="running-head">Clinical usefulness of the PARIS thrombotic risk score to predict long-term prognosis after PCI</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes" equal-contrib="yes" xlink:type="simple">
<contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0002-2544-042X</contrib-id>
<name name-style="western">
<surname>Akama</surname>
<given-names>Joh</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role content-type="http://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role content-type="http://credit.niso.org/contributor-roles/writing-original-draft/">Writing – original draft</role>
<xref ref-type="aff" rid="aff001"/>
<xref ref-type="corresp" rid="cor001">*</xref>
</contrib>
<contrib contrib-type="author" equal-contrib="yes" xlink:type="simple">
<name name-style="western">
<surname>Shimizu</surname>
<given-names>Takeshi</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role content-type="http://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role content-type="http://credit.niso.org/contributor-roles/writing-original-draft/">Writing – original draft</role>
<xref ref-type="aff" rid="aff001"/>
</contrib>
<contrib contrib-type="author" equal-contrib="yes" xlink:type="simple">
<name name-style="western">
<surname>Ando</surname>
<given-names>Takuya</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<xref ref-type="aff" rid="aff001"/>
</contrib>
<contrib contrib-type="author" equal-contrib="yes" xlink:type="simple">
<name name-style="western">
<surname>Anzai</surname>
<given-names>Fumiya</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<xref ref-type="aff" rid="aff001"/>
</contrib>
<contrib contrib-type="author" equal-contrib="yes" xlink:type="simple">
<name name-style="western">
<surname>Muto</surname>
<given-names>Yuuki</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<xref ref-type="aff" rid="aff001"/>
</contrib>
<contrib contrib-type="author" equal-contrib="yes" xlink:type="simple">
<name name-style="western">
<surname>Kimishima</surname>
<given-names>Yusuke</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<xref ref-type="aff" rid="aff001"/>
</contrib>
<contrib contrib-type="author" equal-contrib="yes" xlink:type="simple">
<name name-style="western">
<surname>Kiko</surname>
<given-names>Takatoyo</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<xref ref-type="aff" rid="aff001"/>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Yoshihisa</surname>
<given-names>Akiomi</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role content-type="http://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<xref ref-type="aff" rid="aff001"/>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Yamaki</surname>
<given-names>Takayoshi</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<xref ref-type="aff" rid="aff001"/>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Kunii</surname>
<given-names>Hiroyuki</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<xref ref-type="aff" rid="aff001"/>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Nakazato</surname>
<given-names>Kazuhiko</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<xref ref-type="aff" rid="aff001"/>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Ishida</surname>
<given-names>Takafumi</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role content-type="http://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<xref ref-type="aff" rid="aff001"/>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Takeishi</surname>
<given-names>Yasuchika</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role content-type="http://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff001"/>
</contrib>
</contrib-group>
<aff id="aff001"><addr-line>Department of Cardiovascular Medicine, Fukushima Medical University, Fukushima, Japan</addr-line></aff>
<contrib-group>
<contrib contrib-type="editor" xlink:type="simple">
<name name-style="western">
<surname>Lazzeri</surname>
<given-names>Chiara</given-names>
</name>
<role>Editor</role>
<xref ref-type="aff" rid="edit1"/>
</contrib>
</contrib-group>
<aff id="edit1"><addr-line>Azienda Ospedaliero Universitaria Careggi, ITALY</addr-line></aff>
<author-notes>
<fn fn-type="conflict" id="coi001">
<p>The authors have declared that no competing interests exist.</p>
</fn>
<corresp id="cor001">* E-mail: <email xlink:type="simple">joeakama@fmu.ac.jp</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>13</day>
<month>9</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>17</volume>
<issue>9</issue>
<elocation-id>e0274287</elocation-id>
<history>
<date date-type="received">
<day>6</day>
<month>12</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>24</day>
<month>8</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-year>2022</copyright-year>
<copyright-holder>Akama et al</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">
<license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">Creative Commons Attribution License</ext-link>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
<self-uri content-type="pdf" xlink:href="info:doi/10.1371/journal.pone.0274287"/>
<abstract>
<sec id="sec001">
<title>Background</title>
<p>The Patterns of non-Adherence to Anti-Platelet Regimen in Stented Patients (PARIS) thrombotic risk score has been proposed to estimate the risk of stent thrombotic events after percutaneous coronary intervention (PCI). However, the prognostic value of the PARIS thrombotic risk score for long term all-cause and cardiac mortalities, as well as hospitalization due to heart failure, has not yet been evaluated. Therefore, the aim of the present study was to evaluate the prognostic value of the PARIS thrombotic risk score for all-cause and cardiac mortalities and hospitalization due to heart failure following PCI.</p>
</sec>
<sec id="sec002">
<title>Methods and results</title>
<p>Consecutive 1,061 patients who underwent PCI were divided into three groups based on PARIS thrombotic risk score; low- (n = 320), intermediate- (n = 469) and high-risk (n = 272) groups. We followed up on all three groups for all-cause mortality, cardiac mortality and hospitalization due to heart failure. Kaplan-Meier analysis showed that all outcomes were highest in the high-risk group (P &lt; 0.001, P = 0.022 and P &lt; 0.001, respectively). Multivariate Cox proportional hazard analysis, adjusted for confounding factors, showed that the risk of all-cause mortality and hospitalization due to heart failure of the high-risk group were higher than those of the low-risk group (hazard ratios 1.76 and 2.14, P = 0.005 and P = 0.017, respectively).</p>
</sec>
<sec id="sec003">
<title>Conclusion</title>
<p>The PARIS thrombotic risk score is a significant prognostic indicator for all-cause mortality and hospitalization due to heart failure in patients after PCI.</p>
</sec>
</abstract>
<funding-group>
<funding-statement>The author(s) received no specific funding for this work.</funding-statement>
</funding-group>
<counts>
<fig-count count="4"/>
<table-count count="8"/>
<page-count count="17"/>
</counts>
<custom-meta-group>
<custom-meta id="data-availability">
<meta-name>Data Availability</meta-name>
<meta-value>All relevant data are within the manuscript and its <xref ref-type="sec" rid="sec019">Supporting Information</xref> files.</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="sec004" sec-type="intro">
<title>Introduction</title>
<p>Percutaneous coronary intervention (PCI) is a well-established therapy for patients suffering from coronary artery disease (CAD), and has developed into one of the most popular treatments in modern cardiovascular disease. A number of risk stratification tools or risk scores have been developed with the purpose of estimating prognosis after PCI over the years. Three well-known risk scores are the Global Registry of Acute Coronary Events (GRACE) score [<xref ref-type="bibr" rid="pone.0274287.ref001">1</xref>–<xref ref-type="bibr" rid="pone.0274287.ref003">3</xref>], the Thrombolysis in Myocardial Infarction (TIMI) score [<xref ref-type="bibr" rid="pone.0274287.ref004">4</xref>], and the Controlled Abciximab and Device Investigation to Lower Late Angioplasty Complications (CADILLAC) score [<xref ref-type="bibr" rid="pone.0274287.ref005">5</xref>]. These scores combine and weigh various predictors to calculate the risk of acute coronary syndrome (ACS) for an individual patient [<xref ref-type="bibr" rid="pone.0274287.ref006">6</xref>].</p>
<p>International guidelines focus on accurately predicting adverse events after PCIs such as stent thrombosis or bleeding events, because the magnitude of risk can aid in therapy selection and form the basis for a precise preprocedural informed consent practice [<xref ref-type="bibr" rid="pone.0274287.ref007">7</xref>–<xref ref-type="bibr" rid="pone.0274287.ref009">9</xref>]. Despite substantial improvements in PCIs with novel stent platforms and more potent P2Y12 inhibitors, coronary thrombotic events, such as myocardial infarction, stent thrombosis and revascularization, remain harmful complications with high rates of mortality [<xref ref-type="bibr" rid="pone.0274287.ref010">10</xref>].</p>
<p>The Pattern of non-Adherence to Anti-Platelet Regimen in Stented Patients (PARIS) thrombotic risk score [<xref ref-type="bibr" rid="pone.0274287.ref011">11</xref>] is a reliable tool for estimating the risks of stent thrombotic events in patients who have undergone PCI. Compared to the GRACE score, TIMI score and CADILLAC score, the advantage of the PARIS thrombotic risk score is that it is composed of simple risk scores of baseline clinical variables [<xref ref-type="bibr" rid="pone.0274287.ref011">11</xref>].</p>
<p>Death is an even more detrimental event than stent thrombosis as a potential complication following PCI. However, the clinical usefulness of the PARIS thrombotic risk score for long term all-cause and cardiac mortalities, as well as hospitalization due to heart failure, has not yet been evaluated. Therefore, we assessed the clinical usefulness of the PARIS thrombotic risk score for predicting long-term all-cause mortality, cardiac mortality and hospitalization due to heart failure in patients after undergoing PCI.</p>
</sec>
<sec id="sec005" sec-type="materials|methods">
<title>Materials and methods</title>
<sec id="sec006">
<title>Subjects and study protocol</title>
<p>This was an observational study, which enrolled a total of 1,061 consecutive patients who underwent their initial PCI due to stable angina pectoris or acute coronary syndrome (ACS) at Fukushima Medical University Hospital between January 2010 and May 2018. The exclusion criteria was defined as death at discharge. The diagnosis of stable angina pectoris and ACS was made by several cardiologists based on the definition in the cardiovascular disease guidelines [<xref ref-type="bibr" rid="pone.0274287.ref009">9</xref>, <xref ref-type="bibr" rid="pone.0274287.ref012">12</xref>, <xref ref-type="bibr" rid="pone.0274287.ref013">13</xref>]. The PARIS thrombotic risk score in the present study was calculated with six components including diabetes mellitus, ACS, current smoking, creatinine clearance &lt; 60 ml/min, history of PCI and history of coronary artery bypass grafting (CABG), according to the original report [<xref ref-type="bibr" rid="pone.0274287.ref011">11</xref>]. We added 0–3 points depending on diabetes mellitus, 0–2 points depending on ACS, 0 or 1 points depending on current smoking, 2 points if creatinine clearance was less than 60 ml/min, and 2 points if the patients had a history of PCI or CABG. The range of integer scores was 0–12. We divided the patients into three groups based on their PARIS thrombotic risk score; low- (PARIS thrombotic risk score &lt; 2, n = 320), intermediate- (PARIS thrombotic risk score 3–4, n = 469) and high-risk (PARIS thrombotic risk score ≥ 5, n = 272) groups. We compared the clinical features, laboratory data and parameters of echocardiography, as well as the characteristics of lesions, among the three groups.</p>
<p>The patients were followed up until April 2020 for all-cause death, cardiac death and hospitalization due to heart failure. All-cause death included cardiac death and death from respiratory failure, infection, sepsis, cancer, renal failure, stroke, digestive hemorrhage, and others. Cardiac death was confirmed by independent experienced cardiologists as death either from worsened heart failure, acute coronary syndrome, ventricular fibrillation documented by electrocardiograph or implantable devices, or sudden cardiac death. Status and dates of death were obtained from the patients’ medical records, the attending physicians at the patients’ referring hospital, the patients, or the patients’ families via telephone. Physicians other than the attending physicians, who were blinded to the analyses of this study, conducted an investigation. Survival time was calculated from the date of PCI until the date of death or hospitalization due to heart failure. We were able to follow-up on all patients, and written informed consent was obtained from all of them. The study protocol was approved by the Ethics Committee of Fukushima Medical University (approved number 823), and was carried out in accordance with the principles outlined in the Declaration of Helsinki. Reporting of the study conforms to Strengthening the Reporting of Observational Studies in Epidemiology, along with references to Strengthening the Reporting of Observational Studies in Epidemiology and the broader Enhancing the Quality and Transparency of Health Research guidelines [<xref ref-type="bibr" rid="pone.0274287.ref014">14</xref>].</p>
</sec>
<sec id="sec007">
<title>Co-morbidities and previous history</title>
<p>Comorbidities were assessed by the patients’ attending physicians. A smoker was defined as a patient with a current smoking habit or a habit that had been discontinued ≤ 6 months before hospitalization. Hypertension was defined as the recent use of antihypertensive drugs, a systolic blood pressure of ≥ 140 mmHg, and/or a diastolic pressure of ≥ 90 mmHg. Diabetes was defined as the recent use of insulin or antidiabetic drugs, a fasting blood glucose value of ≥ 126 mg/dL, and/or a hemoglobin A1c value of ≥ 6.5%. Dyslipidemia was defined as the recent use of cholesterol-lowering drugs, a triglyceride value of ≥ 150 mg/dL, a low-density lipoprotein (LDL) cholesterol value of ≥ 140 mg/dL, and/or a high-density lipoprotein (HDL) cholesterol value of &lt; 40 mg/dL. Chronic kidney disease (CKD) was defined as an estimated glomerular filtration rate (eGFR) of &lt; 60 mL/min/1.73 m<sup>2</sup> according to the Modification of Diet in Renal Disease formula [<xref ref-type="bibr" rid="pone.0274287.ref015">15</xref>, <xref ref-type="bibr" rid="pone.0274287.ref016">16</xref>]. Anemia was defined as a hemoglobin level of &lt; 12.0 g/dL in females and &lt; 13.0 g/dL in males [<xref ref-type="bibr" rid="pone.0274287.ref017">17</xref>]. Atrial fibrillation was identified by an electrocardiogram performed during hospitalization and/or from medical records. The diagnosis of heart failure was made by several cardiologists based on the guidelines [<xref ref-type="bibr" rid="pone.0274287.ref017">17</xref>].</p>
</sec>
<sec id="sec008">
<title>Laboratory data and echocardiography</title>
<p>Blood samples were obtained at admission. Echocardiography was performed using standard techniques by experienced echocardiographers who were blinded to the present study. Left ventricular ejection fraction (LVEF) was calculated by using the modified Simpson’s biplane method. All measurements were performed using ultrasound systems (ACUSON Sequoia, Siemens Medical Solutions USA, Inc, Mountain View, CA, USA).</p>
</sec>
<sec id="sec009">
<title>Lesions and therapies</title>
<p>Multivessel disease is defined as significant stenosis (&gt; 75%) in two or more major coronary arteries (of ≥ 2.5 mm diameter) [<xref ref-type="bibr" rid="pone.0274287.ref018">18</xref>]. Since the present study was an observational cohort study, a revascularization strategy of PCI and optimal medical therapy were selected at each physician’s discretion. Unless serious bleeding complications occurred, the durations of dual anti-platelet therapy (DAPT) periods were three months after bare-metal stent implantation and one year after drug-eluting stent (DES) implantation, regardless of anticoagulation therapy. After that, an aspirin or P2Y12 inhibitor monotherapy was continued. Triple therapy is defined as the prescription of both DAPT and oral anticoagulants.</p>
</sec>
<sec id="sec010">
<title>Statistical analysis</title>
<p>Statistical analysis was performed using SPSS version 25.0 (SPSS, Armonk, NY, USA) and EZR (Saitama Medical Center, Jichi Medical University, Saitama, Japan), which is a graphical user interface for R (The R Foundation for Statistical Computing, Vienna, Austria) [<xref ref-type="bibr" rid="pone.0274287.ref019">19</xref>]. In all analyses, a P value of &lt; 0.05 was taken to indicate statistical significance. Continuous variables are presented as mean ± SD and compared by one-way ANOVA. The categorical variables are expressed as numbers and percentages, and the chi-square test was used for comparisons. The Kaplan-Meier method was used for presenting the mortality and the incidence of hospitalization due to heart failure, and statistical significance was analyzed using a log-rank test. The prognostic value of the PARIS bleeding risk score was tested by both univariate and multivariate Cox proportional hazard analyses. In the multivariate Cox proportional hazard analyses, the PARIS bleeding risk score was forcedly entered, and thereafter adjusted for clinical factors that were significantly different among the three groups in the univariate models, and were not included in the criteria of the PARIS bleeding risk score.</p>
<p>The cumulative incidence competing risk method was used for presenting the cardiac mortality and the incidence of hospitalization due to heart failure after adjusting competing risks such as non-cardiac death or all-cause death. To analyze differences in the cumulative incidence among the three groups, Gray’s test was used. The model proposed by Fine and Gray was performed to reveal the hazard of the subdistribution and the relationship between covariates and cumulative incidence.</p>
<p>To compare the predictive ability for all-cause death over the first 6 months following PCI between PARIS thrombotic risk score and GRACE score, a receiver operating curve (ROC) analysis was performed for patients with ACS. The areas under the curve (AUC) of these two scores were compared using the DeLong test.</p>
</sec>
</sec>
<sec id="sec011" sec-type="results">
<title>Results</title>
<sec id="sec012">
<title>Clinical characteristics</title>
<p>Of the 1,061 patients, 834 were male (78.6%) and had a mean age of 68.8 years. Comparisons of clinical characteristics in the low-, intermediate-, and high-risk groups are shown in <xref ref-type="table" rid="pone.0274287.t001">Table 1</xref>. The high-risk group was significantly older and had a higher prevalence of histories of PCI, CABG, and old myocardial infarction. Additionally, the high-risk group had higher prevalence of insulin-treated diabetes mellitus, anemia, CKD, dialysis, peripheral artery disease and atrial fibrillation. Moreover, the high-risk group had a higher white blood cell count and hemoglobin A1c, and had lower hemoglobin, eGFR, albumin, LDL cholesterol and LVEF levels. Regarding medications, in the high-risk group, significantly more patients were prescribed β-blockers, renin-angiotensin-aldosterone system inhibitors and proton pump inhibitors compared to the other groups.</p>
<table-wrap id="pone.0274287.t001" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0274287.t001</object-id>
<label>Table 1</label> <caption><title>Baseline characteristics of patients according to PARIS thrombotic risk score.</title></caption>
<alternatives>
<graphic id="pone.0274287.t001g" mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.t001" xlink:type="simple"/>
<table>
<colgroup>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
</colgroup>
<thead>
<tr>
<th align="left" rowspan="2"/>
<th align="center">Total</th>
<th align="center">Low-risk group</th>
<th align="center">Intermediate-risk group</th>
<th align="center">High-risk group</th>
<th align="center" rowspan="2">P-value</th>
</tr>
<tr>
<th align="center">n = 1,061</th>
<th align="center">n = 320</th>
<th align="center">n = 469</th>
<th align="center">n = 272</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">PARIS thrombotic risk score</td>
<td align="center">3.4 ± 1.8</td>
<td align="center">1.4 ± 0.7</td>
<td align="center">3.4 ± 0.4</td>
<td align="center">5.8 ± 1.0</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Age, years</td>
<td align="center">68.8 ± 11.3</td>
<td align="center">69.7 ± 10.9</td>
<td align="center">67.4 ± 12.1</td>
<td align="center">70.2 ± 10.2</td>
<td align="center">0.001</td>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">834 (78.6%)</td>
<td align="center">224 (70.0%)</td>
<td align="center">384 (82.5%)</td>
<td align="center">223 (82.0%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Body mass index, kg/m<sup>2</sup></td>
<td align="center">24.2 ± 3.6</td>
<td align="center">24.0 ± 3.6</td>
<td align="center">24.2 ± 3.7</td>
<td align="center">24.3 ± 3.6</td>
<td align="center">0.545</td>
</tr>
<tr>
<td align="left">Smoking</td>
<td align="center">702 (66.7%)</td>
<td align="center">142 (45.7%)</td>
<td align="center">364 (77.6%)</td>
<td align="center">196 (72.1%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">History of PCI</td>
<td align="center">180 (17.0%)</td>
<td align="center">12 (3.8%)</td>
<td align="center">66 (14.1%)</td>
<td align="center">102 (37.5%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">History of CABG</td>
<td align="center">37 (3.5%)</td>
<td align="center">2 (0.6%)</td>
<td align="center">4 (0.9%)</td>
<td align="center">31 (11.4%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">History of OMI</td>
<td align="center">89 (8.4%)</td>
<td align="center">19 (5.9%)</td>
<td align="center">28 (6.0%)</td>
<td align="center">42 (15.4%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left" colspan="6">Co-morbidities</td>
</tr>
<tr>
<td align="left">Hypertension</td>
<td align="center">902 (85.7%)</td>
<td align="center">261 (83.9%)</td>
<td align="center">402 (85.7%)</td>
<td align="center">239 (87.8%)</td>
<td align="center">0.397</td>
</tr>
<tr>
<td align="left">Diabetes mellitus</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left"> Non-insulin-treated</td>
<td align="center">476 (44.9%)</td>
<td align="center">109 (34.1%)</td>
<td align="center">233 (49.7%)</td>
<td align="center">134 (49.3%)</td>
<td align="center"/>
</tr>
<tr>
<td align="left"> Insulin-treated</td>
<td align="center">65 (6.1%)</td>
<td align="center">0 (0%)</td>
<td align="center">10 (2.1%)</td>
<td align="center">55 (20.2%)</td>
<td align="center"/>
</tr>
<tr>
<td align="left">Dyslipidemia</td>
<td align="center">972 (92.5%)</td>
<td align="center">286 (92.0%)</td>
<td align="center">435 (92.9%)</td>
<td align="center">251 (92.2%)</td>
<td align="center">0.828</td>
</tr>
<tr>
<td align="left">Anemia</td>
<td align="center">483 (45.9%)</td>
<td align="center">110 (35.4%)</td>
<td align="center">206 (43.9%)</td>
<td align="center">167 (61.4%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Chronic kidney disease</td>
<td align="center">461 (43.8%)</td>
<td align="center">27 (8.7%)</td>
<td align="center">194 (41.4%)</td>
<td align="center">240 (88.2%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Dialysis</td>
<td align="center">62 (5.9%)</td>
<td align="center">5 (1.6%)</td>
<td align="center">28 (6.0%)</td>
<td align="center">29 (10.7%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Peripheral artery disease</td>
<td align="center">132 (12.5%)</td>
<td align="center">31 (10.0%)</td>
<td align="center">46 (9.8%)</td>
<td align="center">55 (20.3%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Heart failure</td>
<td align="center">204 (19.2%)</td>
<td align="center">61 (19.1%)</td>
<td align="center">91 (19.4%)</td>
<td align="center">52 (19.1%)</td>
<td align="center">0.887</td>
</tr>
<tr>
<td align="left">Atrial fibrillation</td>
<td align="center">160 (15.2%)</td>
<td align="center">39 (12.5%)</td>
<td align="center">66 (14.1%)</td>
<td align="center">55 (20.2%)</td>
<td align="center">0.024</td>
</tr>
<tr>
<td align="left">Clinical presentations</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left"> Stable angina pectoris</td>
<td align="center">535 (50.4%)</td>
<td align="center">241 (75.3%)</td>
<td align="center">208 (44.3%)</td>
<td align="center">86 (31.6%)</td>
<td align="center"/>
</tr>
<tr>
<td align="left"> STEMI</td>
<td align="center">316 (29.8%)</td>
<td align="center">34 (10.6%)</td>
<td align="center">164 (35.0%)</td>
<td align="center">118 (43.4%)</td>
<td align="center"/>
</tr>
<tr>
<td align="left"> NSTEMI</td>
<td align="center">91 (8.6%)</td>
<td align="center">6 (1.9%)</td>
<td align="center">45 (9.6%)</td>
<td align="center">40 (14.7%)</td>
<td align="center"/>
</tr>
<tr>
<td align="left"> Unstable angina pectoris</td>
<td align="center">119 (11.2%)</td>
<td align="center">39 (12.1%)</td>
<td align="center">52 (11.0%)</td>
<td align="center">28 (10.2%)</td>
<td align="center"/>
</tr>
<tr>
<td align="left">Multivessel disease</td>
<td align="center">517 (48.7%)</td>
<td align="center">136 (42.5%)</td>
<td align="center">218 (46.5%)</td>
<td align="center">163 (59.9%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Target lesion</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center">0.001</td>
</tr>
<tr>
<td align="left"> RCA</td>
<td align="center">340 (32.0%)</td>
<td align="center">89 (32.7%)</td>
<td align="center">169 (36.0%)</td>
<td align="center">82 (25.6%)</td>
<td align="center"/>
</tr>
<tr>
<td align="left"> LAD</td>
<td align="center">492 (46.4%)</td>
<td align="center">115 (42.3%)</td>
<td align="center">198 (42.2%)</td>
<td align="center">179 (55.9%)</td>
<td align="center"/>
</tr>
<tr>
<td align="left"> LCX</td>
<td align="center">189 (17.8%)</td>
<td align="center">50 (18.4%)</td>
<td align="center">88 (18.8%)</td>
<td align="center">51 (15.9%)</td>
<td align="center"/>
</tr>
<tr>
<td align="left"> LMT</td>
<td align="center">36 (3.4%)</td>
<td align="center">15 (5.5%)</td>
<td align="center">14 (3.0%)</td>
<td align="center">7 (2.2%)</td>
<td align="center"/>
</tr>
<tr>
<td align="left"> Graft</td>
<td align="center">3 (0.3%)</td>
<td align="center">3 (0.6%)</td>
<td align="center">0</td>
<td align="center">0</td>
<td align="center"/>
</tr>
<tr>
<td align="left" colspan="6">Laboratory data</td>
</tr>
<tr>
<td align="left">White blood cell, × 10<sup>3</sup>/μl</td>
<td align="center">8.2 ± 3.6</td>
<td align="center">6.8 ± 2.4</td>
<td align="center">8.4 ± 3.6</td>
<td align="center">9.2 ± 4.2</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Hemoglobin, g/dl</td>
<td align="center">13.2 ± 1.9</td>
<td align="center">13.5 ± 1.6</td>
<td align="center">13.3 ± 1.9</td>
<td align="center">12.7 ± 2.2</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">eGFR, ml/min/1.73 m<sup>2</sup></td>
<td align="center">64.0 ± 24.4</td>
<td align="center">74.5 ± 16.4</td>
<td align="center">65.8 ± 25.1</td>
<td align="center">49.7 ± 23.7</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">CrCl, mL/min</td>
<td align="center">70.7 ± 34.4</td>
<td align="center">79.1 ± 27.5</td>
<td align="center">74.1 ± 37.4</td>
<td align="center">54.9 ± 31.0</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Albumin, g/dl</td>
<td align="center">3.8 ± 0.5</td>
<td align="center">4.0 ± 0.4</td>
<td align="center">3.8 ± 0.5</td>
<td align="center">3.7 ± 0.5</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">LDL cholesterol, mg/dl</td>
<td align="center">105.5 ± 35.7</td>
<td align="center">106.8 ± 35.4</td>
<td align="center">108.0 ± 35.8</td>
<td align="center">98.6 ± 35.5</td>
<td align="center">0.037</td>
</tr>
<tr>
<td align="left">HDL cholesterol, mg/dl</td>
<td align="center">49.6 ± 18.8</td>
<td align="center">51.7 ± 21.5</td>
<td align="center">48.4 ± 16.0</td>
<td align="center">47.9 ± 18.2</td>
<td align="center">0.082</td>
</tr>
<tr>
<td align="left">Triglyceride, mg/dl</td>
<td align="center">139.1 ± 116.2</td>
<td align="center">141.2 ± 85.4</td>
<td align="center">140.7 ± 142.2</td>
<td align="center">132.3 ± 109.4</td>
<td align="center">0.741</td>
</tr>
<tr>
<td align="left">HbA1c, %</td>
<td align="center">6.1 ± 1.0</td>
<td align="center">5.9 ± 0.8</td>
<td align="center">6.1 ± 1.0</td>
<td align="center">6.5 ± 1.3</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left" colspan="6">Echocardiography</td>
</tr>
<tr>
<td align="left">LVEF, %</td>
<td align="center">56.3 ± 12.0</td>
<td align="center">58.6 ± 10.4</td>
<td align="center">55.0 ± 12.8</td>
<td align="center">52.0 ± 12.6</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left" colspan="6">Procedural characteristics</td>
</tr>
<tr>
<td align="left">BMS</td>
<td align="center">128 (12.1%)</td>
<td align="center">30 (9.4%)</td>
<td align="center">71 (15.1%)</td>
<td align="center">27 (9.9%)</td>
<td align="center">0.023</td>
</tr>
<tr>
<td align="left">DES</td>
<td align="center">820 (77.3%)</td>
<td align="center">265 (82.8%)</td>
<td align="center">348 (74.2%)</td>
<td align="center">207 (76.1%)</td>
<td align="center">0.016</td>
</tr>
<tr>
<td align="left">DCB</td>
<td align="center">18 (1.7%)</td>
<td align="center">3 (0.9%)</td>
<td align="center">8 (1.7%)</td>
<td align="center">7 (2.5%)</td>
<td align="center">0.459</td>
</tr>
<tr>
<td align="left">POBA</td>
<td align="center">63 (5.9%)</td>
<td align="center">15 (4.7%)</td>
<td align="center">26 (5.5%)</td>
<td align="center">22 (8.1%)</td>
<td align="center">0.194</td>
</tr>
<tr>
<td align="left">Use of imaging device</td>
<td align="center">1031 (97.2%)</td>
<td align="center">313 (97.8%)</td>
<td align="center">458 (97.7%)</td>
<td align="center">260 (95.6%)</td>
<td align="center">0.149</td>
</tr>
<tr>
<td align="left">Use of physiologic guidance</td>
<td align="center">241 (22.7%)</td>
<td align="center">104 (32.5%)</td>
<td align="center">96 (20.5%)</td>
<td align="center">41 (15.1%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left" colspan="6">Medications</td>
</tr>
<tr>
<td align="left">β-blockers</td>
<td align="center">670 (63.1%)</td>
<td align="center">154 (49.5%)</td>
<td align="center">310 (66.2%)</td>
<td align="center">206 (75.7%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">RAS inhibitors</td>
<td align="center">797 (75.8%)</td>
<td align="center">193 (62.1%)</td>
<td align="center">382 (81.6%)</td>
<td align="center">222 (81.6%)</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Statins</td>
<td align="center">879 (83.6%)</td>
<td align="center">256 (80.0%)</td>
<td align="center">401 (85.5%)</td>
<td align="center">222 (81.6%)</td>
<td align="center">0.164</td>
</tr>
<tr>
<td align="left">Proton pump inhibitors</td>
<td align="center">792 (75.4%)</td>
<td align="center">218 (70.1%)</td>
<td align="center">353 (75.4%)</td>
<td align="center">221 (81.3%)</td>
<td align="center">0.008</td>
</tr>
<tr>
<td align="left">Triple therapy at discharge</td>
<td align="center">120 (11.3%)</td>
<td align="center">29 (9.0%)</td>
<td align="center">50 (10.6%)</td>
<td align="center">41 (15.0%)</td>
<td align="center">0.064</td>
</tr>
</tbody>
</table>
</alternatives>
<table-wrap-foot>
<fn id="t001fn001"><p>PARIS, the patterns of non-adherence to anti-platelet regimen in stented patients; PCI, percutaneous coronary intervention; CABG, coronary artery bypass grafting; OMI, old myocardial infarction; STEMI, ST elevation myocardial infarction; NSTEMI, non-ST elevation myocardial infarction; RCA, right coronary artery; LAD, left anterior descending coronary artery; LCX, left circumflex coronary artery LMT, left main trunk; eGFR, estimated glomerular filtration rate; CrCl, creatine clearance; LDL, low density lipoprotein; HDL, high density lipoprotein; HbA1c, hemoglobin A1c; LVEF, left ventricular ejection fraction; BMS, bare metal stent; DES, drug eluting stent; DCB, drug coated balloon; POBA, plain old balloon angioplasty; RAS, Renin-Angiotensin-Aldosterone System.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec013">
<title>Follow-up</title>
<p>During the follow-up period (mean 1,809 days), there were 205 all-cause deaths, including 64 cardiac deaths, and 100 hospitalizations due to heart failure. The 64 cardiac deaths included 48 deaths from heart failure, 10 deaths from acute myocardial infarction, and six deaths from ventricular arrhythmias. In the Kaplan-Meier analysis (<xref ref-type="fig" rid="pone.0274287.g001">Fig 1</xref>), all outcomes were highest in the high-risk group among the three groups (P &lt; 0.001, P = 0.022 and P &lt; 0.001, respectively). Regarding cumulative incidence competing risk method (<xref ref-type="fig" rid="pone.0274287.g002">Fig 2</xref>), hospitalization due to heart failure after adjusting for competing risk was highest in high-risk group, compared to the other two groups (P &lt; 0.001).</p>
<fig id="pone.0274287.g001" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0274287.g001</object-id>
<label>Fig 1</label>
<caption>
<title/>
<p>Kaplan-Meier curves for all-cause mortality (A), cardiac mortality (B) and hospitalization due to heart failure (C) in the high, intermediate, and low PARIS thrombotic risk score groups. PARIS, the Patterns of non-Adherence to anti-platelet Regimen in Stented patient.</p>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.g001" xlink:type="simple"/>
</fig>
<fig id="pone.0274287.g002" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0274287.g002</object-id>
<label>Fig 2</label>
<caption>
<title/>
<p>The cumulative incidence curves for cardiac mortality (A) and hospitalization due to heart failure (B) in the high, intermediate, and low PARIS thrombotic risk score groups. PARIS, the Patterns of non-Adherence to anti-platelet Regimen in Stented patient.</p>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.g002" xlink:type="simple"/>
</fig>
</sec>
<sec id="sec014">
<title>Cox proportional hazard regression analysis</title>
<p>The Cox proportional hazard analysis of the associations between PARIS thrombotic score, presented as categorical variables (groups), with all-cause mortality, cardiac mortality, and hospitalization due to heart failure, are presented in Tables <xref ref-type="table" rid="pone.0274287.t002">2</xref>–<xref ref-type="table" rid="pone.0274287.t004">4</xref>. The PARIS thrombotic risk score was revealed as an independent prognostic factor, and the Cox proportional hazard analysis demonstrated that the high-risk group had a higher risk of all-cause mortality and hospitalization due to heart failure compared with the low-risk group (hazard ratio 1.76, 95% confidence intervals 1.18–2.61, P = 0.005; hazard ratio 2.14, 95% confidence intervals 1.14–4.00, P = 0.017, respectively).</p>
<table-wrap id="pone.0274287.t002" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0274287.t002</object-id>
<label>Table 2</label> <caption><title>Cox proportional hazard model of PARIS thrombotic score for all-cause mortality.</title></caption>
<alternatives>
<graphic id="pone.0274287.t002g" mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.t002" xlink:type="simple"/>
<table>
<colgroup>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
</colgroup>
<thead>
<tr>
<th align="center" rowspan="2">Variable</th>
<th align="center" colspan="3">Univariate analysis</th>
<th align="center" colspan="3">Multivariate analysis<xref ref-type="table-fn" rid="t002fn001"><sup>#</sup></xref></th>
</tr>
<tr>
<th align="center">Hazard ratio</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
<th align="center">Hazard ratio</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">PARIS thrombotic score (low-risk group)</td>
<td align="center">Ref.</td>
<td align="center"/>
<td align="center"/>
<td align="center">Ref.</td>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Intermediate-risk group (vs. low-risk group)</td>
<td align="center">1.32</td>
<td align="center">0.92–1.88</td>
<td align="center">0.120</td>
<td align="center">1.42</td>
<td align="center">0.97–2.07</td>
<td align="center">0.066</td>
</tr>
<tr>
<td align="left">High-risk group (vs. low-risk group)</td>
<td align="center">2.34</td>
<td align="center">1.62–3.37</td>
<td align="center">&lt; 0.001</td>
<td align="center">1.76</td>
<td align="center">1.18–2.61</td>
<td align="center">0.005</td>
</tr>
<tr>
<td align="left">Age (per 1-year increase)</td>
<td align="center">1.06</td>
<td align="center">1.04–1.07</td>
<td align="center">&lt; 0.001</td>
<td align="center">1.04</td>
<td align="center">1.03–1.06</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">0.90</td>
<td align="center">0.70–1.36</td>
<td align="center">0.902</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Smoking</td>
<td align="center">0.97</td>
<td align="center">0.72–1.29</td>
<td align="center">0.851</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of PCI</td>
<td align="center">1.03</td>
<td align="center">0.86–1.23</td>
<td align="center">0.739</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of CABG</td>
<td align="center">0.70</td>
<td align="center">0.52–0.95</td>
<td align="center">0.026</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of OMI</td>
<td align="center">0.99</td>
<td align="center">0.79–1.25</td>
<td align="center">0.995</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Diabetes mellitus</td>
<td align="center">1.13</td>
<td align="center">0.86–1.49</td>
<td align="center">0.359</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Anemia</td>
<td align="center">3.58</td>
<td align="center">2.62–4.89</td>
<td align="center">&lt; 0.001</td>
<td align="center">2.22</td>
<td align="center">1.59–3.08</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Chronic kidney disease</td>
<td align="center">2.65</td>
<td align="center">1.99–3.52</td>
<td align="center">&lt; 0.001</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Dialysis</td>
<td align="center">3.45</td>
<td align="center">2.32–5.11</td>
<td align="center">&lt; 0.001</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Peripheral artery disease</td>
<td align="center">1.76</td>
<td align="center">1.24–2.50</td>
<td align="center">0.001</td>
<td align="center">1.22</td>
<td align="center">0.85–1.75</td>
<td align="center">0.272</td>
</tr>
<tr>
<td align="left">Atrial fibrillation</td>
<td align="center">2.06</td>
<td align="center">1.50–2.84</td>
<td align="center">&lt; 0.001</td>
<td align="center">1.54</td>
<td align="center">1.12–2.13</td>
<td align="center">0.008</td>
</tr>
<tr>
<td align="left">Acute coronary syndrome</td>
<td align="center">1.14</td>
<td align="center">0.86–1.50</td>
<td align="center">0.339</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Multivessel disease</td>
<td align="center">1.54</td>
<td align="center">1.16–2.04</td>
<td align="center">0.002</td>
<td align="center">1.12</td>
<td align="center">0.84–1.50</td>
<td align="center">0.429</td>
</tr>
<tr>
<td align="left">Target lesion (RCA)</td>
<td align="center">0.98</td>
<td align="center">0.73–1.31</td>
<td align="center">0.912</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LAD)</td>
<td align="center">0.15</td>
<td align="center">0.62–1.07</td>
<td align="center">0.818</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LCX)</td>
<td align="center">1.24</td>
<td align="center">0.88–1.74</td>
<td align="center">0.210</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LMT)</td>
<td align="center">1.52</td>
<td align="center">0.78–2.97</td>
<td align="center">0.216</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">LVEF (per 1% increase)</td>
<td align="center">0.97</td>
<td align="center">0.95–0.98</td>
<td align="center">&lt; 0.001</td>
<td align="center">0.98</td>
<td align="center">0.96–0.99</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">BMS</td>
<td align="center">0.95</td>
<td align="center">0.65–1.37</td>
<td align="center">0.795</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">DES</td>
<td align="center">0.88</td>
<td align="center">0.65–1.20</td>
<td align="center">0.442</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">β-blockers</td>
<td align="center">1.28</td>
<td align="center">0.95–1.73</td>
<td align="center">0.094</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">RAS inhibitors</td>
<td align="center">0.92</td>
<td align="center">0.67–1.28</td>
<td align="center">0.649</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Proton pump inhibitor</td>
<td align="center">1.45</td>
<td align="center">1.05–1.99</td>
<td align="center">0.023</td>
<td align="center">1.19</td>
<td align="center">0.85–1.64</td>
<td align="center">0.296</td>
</tr>
</tbody>
</table>
</alternatives>
<table-wrap-foot>
<fn id="t002fn001"><p>#. In the multivariate analysis, PARIS thrombotic score was forcedly entered, and thereafter adjusted for age, anemia, peripheral artery disease, atrial fibrillation, multivessel disease, LVEF and proton pump inhibitor with the forced entry method.</p></fn>
<fn id="t002fn002"><p>PARIS, the patterns of non-adherence to anti-platelet regimen in stented patients; PCI, percutaneous coronary intervention; CABG, coronary artery bypass grafting; OMI, old myocardial infarction; RCA, right coronary artery; LAD, left anterior descending coronary artery; LCX, left circumflex coronary artery LMT, left main trunk; LVEF, left ventricular ejection fraction; BMS, bare metal stent; DES, drug eluting stent; RAS, Renin-Angiotensin-Aldosterone System.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="pone.0274287.t003" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0274287.t003</object-id>
<label>Table 3</label> <caption><title>Cox proportional hazard model of PARIS thrombotic score for cardiac mortality.</title></caption>
<alternatives>
<graphic id="pone.0274287.t003g" mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.t003" xlink:type="simple"/>
<table>
<colgroup>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
</colgroup>
<thead>
<tr>
<th align="center" rowspan="2">Variable</th>
<th align="center" colspan="3">Univariate analysis</th>
<th align="center" colspan="3">Multivariate analysis<xref ref-type="table-fn" rid="t003fn001"><sup>#</sup></xref></th>
</tr>
<tr>
<th align="center">Hazard ratio</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
<th align="center">Hazard ratio</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">PARIS thrombotic score (low-risk group)</td>
<td align="center">Ref.</td>
<td align="center"/>
<td align="center"/>
<td align="center">Ref.</td>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Intermediate-risk group (vs. low-risk group)</td>
<td align="center">1.46</td>
<td align="center">0.79–2.71</td>
<td align="center">0.226</td>
<td align="center">1.76</td>
<td align="center">0.85–3.64</td>
<td align="center">0.128</td>
</tr>
<tr>
<td align="left">High-risk group (vs. low-risk group)</td>
<td align="center">2.10</td>
<td align="center">1.09–4.04</td>
<td align="center">0.025</td>
<td align="center">1.51</td>
<td align="center">0.69–3.30</td>
<td align="center">0.293</td>
</tr>
<tr>
<td align="left">Age (per 1-year increase)</td>
<td align="center">1.04</td>
<td align="center">1.01–1.06</td>
<td align="center">0.001</td>
<td align="center">1.03</td>
<td align="center">1.00–1.06</td>
<td align="center">0.012</td>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">1.07</td>
<td align="center">0.58–1.97</td>
<td align="center">0.814</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Smoking</td>
<td align="center">1.16</td>
<td align="center">0.68–1.99</td>
<td align="center">0.579</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of PCI</td>
<td align="center">0.82</td>
<td align="center">0.45–1.48</td>
<td align="center">0.518</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of CABG</td>
<td align="center">0.67</td>
<td align="center">0.40–1.11</td>
<td align="center">0.124</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of OMI</td>
<td align="center">1.06</td>
<td align="center">0.46–2.46</td>
<td align="center">0.877</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Diabetes mellitus</td>
<td align="center">1.17</td>
<td align="center">0.71–1.92</td>
<td align="center">0.524</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Anemia</td>
<td align="center">3.20</td>
<td align="center">1.86–5.53</td>
<td align="center">&lt; 0.001</td>
<td align="center">1.87</td>
<td align="center">1.04–3.34</td>
<td align="center">0.034</td>
</tr>
<tr>
<td align="left">Chronic kidney disease</td>
<td align="center">3.04</td>
<td align="center">1.80–5.14</td>
<td align="center">&lt; 0.001</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Dialysis</td>
<td align="center">3.73</td>
<td align="center">1.90–7.34</td>
<td align="center">&lt; 0.001</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Peripheral artery disease</td>
<td align="center">2.06</td>
<td align="center">1.14–3.74</td>
<td align="center">0.016</td>
<td align="center">1.40</td>
<td align="center">0.75–2.59</td>
<td align="center">0.286</td>
</tr>
<tr>
<td align="left">Atrial fibrillation</td>
<td align="center">2.45</td>
<td align="center">1.42–4.22</td>
<td align="center">0.001</td>
<td align="center">1.71</td>
<td align="center">0.98–2.97</td>
<td align="center">0.057</td>
</tr>
<tr>
<td align="left">Acute coronary syndrome</td>
<td align="center">0.92</td>
<td align="center">0.56–1.51</td>
<td align="center">0.754</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Multivessel disease</td>
<td align="center">2.46</td>
<td align="center">1.44–4.21</td>
<td align="center">0.001</td>
<td align="center">1.70</td>
<td align="center">0.97–2.97</td>
<td align="center">0.061</td>
</tr>
<tr>
<td align="left">Target lesion (RCA)</td>
<td align="center">0.65</td>
<td align="center">0.37–1.12</td>
<td align="center">0.127</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LAD)</td>
<td align="center">0.93</td>
<td align="center">0.57–1.49</td>
<td align="center">0.764</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LCX)</td>
<td align="center">1.63</td>
<td align="center">0.94–2.83</td>
<td align="center">0.077</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LMT)</td>
<td align="center">1.99</td>
<td align="center">0.72–5.47</td>
<td align="center">0.181</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">LVEF (per 1% increase)</td>
<td align="center">0.94</td>
<td align="center">0.93–0.96</td>
<td align="center">&lt; 0.001</td>
<td align="center">0.95</td>
<td align="center">0.94–0.97</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">BMS</td>
<td align="center">0.32</td>
<td align="center">0.11–0.89</td>
<td align="center">0.029</td>
<td align="center">0.37</td>
<td align="center">0.13–1.04</td>
<td align="center">0.060</td>
</tr>
<tr>
<td align="left">DES</td>
<td align="center">1.22</td>
<td align="center">0.69–2.18</td>
<td align="center">0.483</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">β-blockers</td>
<td align="center">2.02</td>
<td align="center">1.12–3.66</td>
<td align="center">0.019</td>
<td align="center">1.39</td>
<td align="center">0.74–2.63</td>
<td align="center">0.301</td>
</tr>
<tr>
<td align="left">RAS inhibitors</td>
<td align="center">1.14</td>
<td align="center">0.62–2.10</td>
<td align="center">0.659</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Proton pump inhibitor</td>
<td align="center">1.67</td>
<td align="center">0.91–3.04</td>
<td align="center">0.094</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
</tbody>
</table>
</alternatives>
<table-wrap-foot>
<fn id="t003fn001"><p>#. In the multivariate analysis, PARIS thrombotic score was forcedly entered, and thereafter adjusted for age, anemia, peripheral artery disease, atrial fibrillation, multivessel disease, LVEF, BMS and β-blockers with the forced entry method.</p></fn>
<fn id="t003fn002"><p>PARIS, the patterns of non-adherence to anti-platelet regimen in stented patients; PCI, percutaneous coronary intervention; CABG, coronary artery bypass grafting; OMI, old myocardial infarction; RCA, right coronary artery; LAD, left anterior descending coronary artery; LCX, left circumflex coronary artery LMT, left main trunk; LVEF, left ventricular ejection fraction; BMS, bare metal stent; DES, drug eluting stent; RAS, Renin-Angiotensin-Aldosterone System.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="pone.0274287.t004" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0274287.t004</object-id>
<label>Table 4</label> <caption><title>Cox proportional hazard model of PARIS thrombotic score for hospitalization due to heart failure.</title></caption>
<alternatives>
<graphic id="pone.0274287.t004g" mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.t004" xlink:type="simple"/>
<table>
<colgroup>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
</colgroup>
<thead>
<tr>
<th align="center" rowspan="2">Variable</th>
<th align="center" colspan="3">Univariate analysis</th>
<th align="center" colspan="3">Multivariate analysis<xref ref-type="table-fn" rid="t004fn001"><sup>#</sup></xref></th>
</tr>
<tr>
<th align="center">Hazard ratio</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
<th align="center">Hazard ratio</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">PARIS thrombotic score (low-risk group)</td>
<td align="center">Ref.</td>
<td align="center"/>
<td align="center"/>
<td align="center">Ref.</td>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Intermediate-risk group (vs. low-risk group)</td>
<td align="center">1.58</td>
<td align="center">0.85–2.94</td>
<td align="center">0.142</td>
<td align="center">1.28</td>
<td align="center">0.68–2.41</td>
<td align="center">0.439</td>
</tr>
<tr>
<td align="left">High-risk group (vs. low-risk group)</td>
<td align="center">4.05</td>
<td align="center">2.23–7.33</td>
<td align="center">&lt; 0.001</td>
<td align="center">2.14</td>
<td align="center">1.14–4.00</td>
<td align="center">0.017</td>
</tr>
<tr>
<td align="left">Age (per 1-year increase)</td>
<td align="center">1.05</td>
<td align="center">1.03–1.07</td>
<td align="center">&lt; 0.001</td>
<td align="center">1.03</td>
<td align="center">1.00–1.05</td>
<td align="center">0.004</td>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">0.68</td>
<td align="center">0.44–1.05</td>
<td align="center">0.087</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Smoking</td>
<td align="center">0.73</td>
<td align="center">0.49–1.09</td>
<td align="center">0.133</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of PCI</td>
<td align="center">0.94</td>
<td align="center">0.57–1.56</td>
<td align="center">0.832</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of CABG</td>
<td align="center">0.33</td>
<td align="center">0.16–0.69</td>
<td align="center">0.003</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of OMI</td>
<td align="center">0.83</td>
<td align="center">0.45–1.52</td>
<td align="center">0.551</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Diabetes mellitus</td>
<td align="center">1.43</td>
<td align="center">0.95–2.15</td>
<td align="center">0.084</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Anemia</td>
<td align="center">3.56</td>
<td align="center">2.28–5.58</td>
<td align="center">&lt; 0.001</td>
<td align="center">1.99</td>
<td align="center">1.23–3.20</td>
<td align="center">0.005</td>
</tr>
<tr>
<td align="left">Chronic kidney disease</td>
<td align="center">5.55</td>
<td align="center">3.43–9.00</td>
<td align="center">&lt; 0.001</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Dialysis</td>
<td align="center">1.69</td>
<td align="center">0.79–3.38</td>
<td align="center">0.181</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Peripheral artery disease</td>
<td align="center">2.24</td>
<td align="center">1.39–3.61</td>
<td align="center">0.001</td>
<td align="center">1.26</td>
<td align="center">0.75–2.09</td>
<td align="center">0.372</td>
</tr>
<tr>
<td align="left">Atrial fibrillation</td>
<td align="center">3.10</td>
<td align="center">2.06–4.69</td>
<td align="center">&lt; 0.001</td>
<td align="center">2.17</td>
<td align="center">1.42–3.32</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">Acute coronary syndrome</td>
<td align="center">1.11</td>
<td align="center">0.75–1.64</td>
<td align="center">0.600</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Multivessel disease</td>
<td align="center">1.66</td>
<td align="center">1.10–2.50</td>
<td align="center">0.015</td>
<td align="center">1.07</td>
<td align="center">0.69–1.66</td>
<td align="center">0.742</td>
</tr>
<tr>
<td align="left">Target lesion (RCA)</td>
<td align="center">0.95</td>
<td align="center">0.63–1.44</td>
<td align="center">0.828</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LAD)</td>
<td align="center">1.09</td>
<td align="center">0.73–1.61</td>
<td align="center">0.665</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LCX)</td>
<td align="center">0.75</td>
<td align="center">0.41–1.37</td>
<td align="center">0.350</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LMT)</td>
<td align="center">1.62</td>
<td align="center">0.51–5.16</td>
<td align="center">0.408</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">LVEF (per 1% increase)</td>
<td align="center">0.95</td>
<td align="center">0.94–0.96</td>
<td align="center">&lt; 0.001</td>
<td align="center">0.96</td>
<td align="center">0.95–0.98</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">BMS</td>
<td align="center">0.37</td>
<td align="center">0.18–0.74</td>
<td align="center">0.005</td>
<td align="center">0.44</td>
<td align="center">0.18–1.07</td>
<td align="center">0.071</td>
</tr>
<tr>
<td align="left">DES</td>
<td align="center">1.71</td>
<td align="center">1.05–2.78</td>
<td align="center">0.030</td>
<td align="center">0.97</td>
<td align="center">0.51–1.81</td>
<td align="center">0.923</td>
</tr>
<tr>
<td align="left">β-blockers</td>
<td align="center">2.01</td>
<td align="center">1.23–3.29</td>
<td align="center">0.005</td>
<td align="center">1.21</td>
<td align="center">0.71–2.05</td>
<td align="center">0.478</td>
</tr>
<tr>
<td align="left">RAS inhibitors</td>
<td align="center">1.17</td>
<td align="center">0.71–1.93</td>
<td align="center">0.531</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Proton pump inhibitor</td>
<td align="center">2.22</td>
<td align="center">1.33–3.69</td>
<td align="center">0.002</td>
<td align="center">1.57</td>
<td align="center">0.92–2.69</td>
<td align="center">0.095</td>
</tr>
</tbody>
</table>
</alternatives>
<table-wrap-foot>
<fn id="t004fn001"><p>#. In the multivariate analysis, PARIS thrombotic score was forcedly entered, and thereafter adjusted for age, anemia, peripheral artery disease, atrial fibrillation, multivessel disease, LVEF, BMS, DES, β-blockers and proton pump inhibitor with the forced entry method.</p></fn>
<fn id="t004fn002"><p>PARIS, the patterns of non-adherence to anti-platelet regimen in stented patients; PCI, percutaneous coronary intervention; CABG, coronary artery bypass grafting; OMI, old myocardial infarction; RCA, right coronary artery; LAD, left anterior descending coronary artery; LCX, left circumflex coronary artery LMT, left main trunk; LVEF, left ventricular ejection fraction; BMS, bare metal stent; DES, drug eluting stent; RAS, Renin-Angiotensin-Aldosterone System.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Furthermore, to assess the prognostic value of the PARIS thrombosis risk score for all-cause mortality, cardiac mortality, and incidence of hospitalization due to heart failure by clinical presentations, we conducted subgroup analysis (<xref ref-type="fig" rid="pone.0274287.g003">Fig 3</xref>). The incidence in the high-risk group was compared with that in the low-risk group in ACS subgroup. The hazard ratios of the PARIS thrombotic risk score on all-cause mortality in patients with stable angina pectoris and acute coronary syndrome were 1.72 (95% confidence intervals 1.01–2.93) and 3.30 (95% confidence intervals 1.63–6.67), respectively. The hazard ratios of the PARIS thrombotic risk score on cardiac mortality in patients presenting stable angina pectoris and acute coronary syndrome were 1.55 (95% confidence intervals 0.62–3.84) and 7.92 (95% confidence intervals 1.05–59.80), respectively. The hazard ratios of the PARIS thrombotic risk score on the incidence of hospitalization due to heart failure in patients presenting stable angina and acute coronary syndrome were 3.66 (95% confidence intervals 1.69–7.90) and 4.99 (95% confidence intervals 1.53–16.29), respectively. There were no interactions.</p>
<fig id="pone.0274287.g003" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0274287.g003</object-id>
<label>Fig 3</label>
<caption>
<title>Forest plot of hazard ratios by clinical presentations.</title>
<p>HR, hazard ratio; CI, confidence interval; AP, angina pectoris; ACS, acute coronary syndrome.</p>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.g003" xlink:type="simple"/>
</fig>
<p>Moreover, we performed a Cox proportional hazard analysis for examining the association of the PARIS thrombotic risk score, presented as continuous variables (per 1-point increase), with all-cause and cardiac mortalities, and hospitalization due to heart failure as sensitivity analyses (<xref ref-type="table" rid="pone.0274287.t005">Table 5</xref>). In the multivariable analysis, a high PARIS thrombotic score was determined to be an independent predictor of all-cause mortality and hospitalization due to heart failure after adjusting for other confounding factors (hazard ratio 1.12 per 1-point increase, 95% confidence intervals 1.04–1.20, P = 0.003; hazard ratio 1.21 per 1-point increase, 95% confidence intervals 1.09–1.35, P &lt; 0.001, respectively).</p>
<table-wrap id="pone.0274287.t005" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0274287.t005</object-id>
<label>Table 5</label> <caption><title>Cox proportional hazard model of PARIS thrombotic score (continuous variables) for all-cause and cardiac mortalities and hospitalization due to heart failure.</title></caption>
<alternatives>
<graphic id="pone.0274287.t005g" mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.t005" xlink:type="simple"/>
<table>
<colgroup>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
</colgroup>
<thead>
<tr>
<th align="center" rowspan="2">Variable</th>
<th align="center" colspan="3">Univariate analysis</th>
<th align="center" colspan="3">Multivariate analysis</th>
</tr>
<tr>
<th align="center">Hazard ratio</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
<th align="center">Hazard ratio</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left"><bold>All-cause mortality</bold></td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left"> PARIS thrombotic score (per 1-point increase) <xref ref-type="table-fn" rid="t005fn002"><sup>#1</sup></xref></td>
<td align="center">1.18</td>
<td align="center">1.10–1.27</td>
<td align="center">&lt; 0.001</td>
<td align="center">1.12</td>
<td align="center">1.04–1.20</td>
<td align="center">0.003</td>
</tr>
<tr>
<td align="left"><bold>Cardiac mortality</bold></td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left"> PARIS thrombotic score (per 1-point increase) <xref ref-type="table-fn" rid="t005fn003"><sup>#2</sup></xref></td>
<td align="center">1.18</td>
<td align="center">1.04–1.34</td>
<td align="center">0.007</td>
<td align="center">1.09</td>
<td align="center">0.96–1.25</td>
<td align="center">0.173</td>
</tr>
<tr>
<td align="left"><bold>Hospitalization due to heart failure</bold></td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left"> PARIS thrombotic score (per 1-point increase) <xref ref-type="table-fn" rid="t005fn004"><sup>#3</sup></xref></td>
<td align="center">1.38</td>
<td align="center">1.25–1.52</td>
<td align="center">&lt; 0.001</td>
<td align="center">1.21</td>
<td align="center">1.09–1.35</td>
<td align="center">&lt; 0.001</td>
</tr>
</tbody>
</table>
</alternatives>
<table-wrap-foot>
<fn id="t005fn001"><p>In the multivariate analysis, PARIS thrombotic score was adjusted for clinically important variables as shown below with the forced entry method.</p></fn>
<fn id="t005fn002"><p>#1: age, anemia, peripheral artery disease, atrial fibrillation, multivessel disease, LVEF and proton pump inhibitor</p></fn>
<fn id="t005fn003"><p>#2: age, anemia, peripheral artery disease, atrial fibrillation, multivessel disease, LVEF, BMS and β-blockers</p></fn>
<fn id="t005fn004"><p>#3: age, anemia, peripheral artery disease, atrial fibrillation, multivessel disease, LVEF, BMS, DES, β-blockers and proton pump inhibitor</p></fn>
<fn id="t005fn005"><p>PARIS, the patterns of non-adherence to anti-platelet regimen in stented patients; LVEF, left ventricular ejection fraction; BMS, bare metal stent; DES, drug eluting stent</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec015">
<title>Fine and Gray model (subdistribution hazard model)</title>
<p>The Fine and Gray model (subdistribution hazard model) for the associations of the PARIS thrombotic score, presented as categorical variables (groups), with cardiac mortalities and hospitalization due to heart failure are presented in Tables <xref ref-type="table" rid="pone.0274287.t006">6</xref> and <xref ref-type="table" rid="pone.0274287.t007">7</xref>.</p>
<table-wrap id="pone.0274287.t006" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0274287.t006</object-id>
<label>Table 6</label> <caption><title>Fine and Gray model (subdistribution hazard model) for cardiac mortality.</title></caption>
<alternatives>
<graphic id="pone.0274287.t006g" mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.t006" xlink:type="simple"/>
<table>
<colgroup>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
</colgroup>
<thead>
<tr>
<th align="center" rowspan="2">Variable</th>
<th align="center" colspan="3">Univariate analysis</th>
<th align="center" colspan="3">Multivariate analysis<xref ref-type="table-fn" rid="t006fn001"><sup>#</sup></xref></th>
</tr>
<tr>
<th align="center">sHR</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
<th align="center">sHR</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">PARIS thrombotic score (low-risk group)</td>
<td align="center">Ref.</td>
<td align="center"/>
<td align="center"/>
<td align="center">Ref.</td>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Intermediate-risk group (vs. low-risk group)</td>
<td align="center">1.50</td>
<td align="center">0.79–2.85</td>
<td align="center">0.210</td>
<td align="center">1.78</td>
<td align="center">0.83–3.81</td>
<td align="center">0.130</td>
</tr>
<tr>
<td align="left">High-risk group (vs. low-risk group)</td>
<td align="center">2.07</td>
<td align="center">1.06–4.04</td>
<td align="center">0.032</td>
<td align="center">1.49</td>
<td align="center">0.66–3.32</td>
<td align="center">0.330</td>
</tr>
<tr>
<td align="left">Age (per 1-year increase)</td>
<td align="center">1.04</td>
<td align="center">1.01–1.06</td>
<td align="center">0.002</td>
<td align="center">1.02</td>
<td align="center">1.00–1.05</td>
<td align="center">0.050</td>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">0.95</td>
<td align="center">0.53–1.71</td>
<td align="center">0.890</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Smoking</td>
<td align="center">1.23</td>
<td align="center">0.71–2.13</td>
<td align="center">0.460</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of PCI</td>
<td align="center">1.27</td>
<td align="center">0.71–2.29</td>
<td align="center">0.410</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of CABG</td>
<td align="center">2.44</td>
<td align="center">0.98–6.06</td>
<td align="center">0.054</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of OMI</td>
<td align="center">0.97</td>
<td align="center">0.42–2.22</td>
<td align="center">0.960</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Diabetes mellitus</td>
<td align="center">1.16</td>
<td align="center">0.70–1.93</td>
<td align="center">0.540</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Anemia</td>
<td align="center">3.01</td>
<td align="center">1.72–5.27</td>
<td align="center">&lt; 0.001</td>
<td align="center">1.83</td>
<td align="center">1.02–3.28</td>
<td align="center">0.042</td>
</tr>
<tr>
<td align="left">Chronic kidney disease</td>
<td align="center">2.86</td>
<td align="center">1.68–4.88</td>
<td align="center">&lt; 0.001</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Dialysis</td>
<td align="center">3.36</td>
<td align="center">1.70–6.61</td>
<td align="center">&lt; 0.001</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Peripheral artery disease</td>
<td align="center">1.84</td>
<td align="center">1.00–3.38</td>
<td align="center">0.047</td>
<td align="center">1.22</td>
<td align="center">0.63–2.36</td>
<td align="center">0.550</td>
</tr>
<tr>
<td align="left">Atrial fibrillation</td>
<td align="center">2.19</td>
<td align="center">1.26–3.82</td>
<td align="center">0.005</td>
<td align="center">1.63</td>
<td align="center">0.93–2.83</td>
<td align="center">0.084</td>
</tr>
<tr>
<td align="left">Acute coronary syndrome</td>
<td align="center">0.83</td>
<td align="center">0.51–1.34</td>
<td align="center">0.450</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Multivessel disease</td>
<td align="center">2.25</td>
<td align="center">1.34–3.76</td>
<td align="center">0.002</td>
<td align="center">1.96</td>
<td align="center">1.08–3.56</td>
<td align="center">0.027</td>
</tr>
<tr>
<td align="left">Target lesion (RCA)</td>
<td align="center">0.62</td>
<td align="center">0.35–1.09</td>
<td align="center">0.098</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LAD)</td>
<td align="center">0.93</td>
<td align="center">0.57–1.51</td>
<td align="center">0.800</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LCX)</td>
<td align="center">1.67</td>
<td align="center">0.96–2.91</td>
<td align="center">0.065</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LMT)</td>
<td align="center">2.04</td>
<td align="center">0.73–5.70</td>
<td align="center">0.170</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">LVEF (per 1% increase)</td>
<td align="center">0.94</td>
<td align="center">0.93–0.96</td>
<td align="center">&lt; 0.001</td>
<td align="center">0.95</td>
<td align="center">0.94–0.97</td>
<td align="center">&lt; 0.001</td>
</tr>
<tr>
<td align="left">BMS</td>
<td align="center">0.33</td>
<td align="center">0.12–0.95</td>
<td align="center">0.041</td>
<td align="center">0.40</td>
<td align="center">0.13–1.20</td>
<td align="center">0.100</td>
</tr>
<tr>
<td align="left">DES</td>
<td align="center">1.18</td>
<td align="center">0.66–2.12</td>
<td align="center">0.560</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">β-blockers</td>
<td align="center">2.36</td>
<td align="center">1.26–4.42</td>
<td align="center">0.007</td>
<td align="center">1.69</td>
<td align="center">0.86–3.30</td>
<td align="center">0.130</td>
</tr>
<tr>
<td align="left">RAS inhibitors</td>
<td align="center">1.24</td>
<td align="center">0.66–2.34</td>
<td align="center">0.500</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Proton pump inhibitor</td>
<td align="center">1.52</td>
<td align="center">0.83–2.77</td>
<td align="center">0.170</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
</tbody>
</table>
</alternatives>
<table-wrap-foot>
<fn id="t006fn001"><p>#. In the multivariate analysis, PARIS thrombotic score was forcedly entered, and thereafter adjusted for age, anemia, peripheral artery disease, atrial fibrillation, multivessel disease, LVEF, BMS and β-blockers with the forced entry method.</p></fn>
<fn id="t006fn002"><p>sHR, subdistribution hazard ratio; PARIS, the patterns of non-adherence to anti-platelet regimen in stented patients; PCI, percutaneous coronary intervention; CABG, coronary artery bypass grafting; OMI, old myocardial infarction; RCA, right coronary artery; LAD, left anterior descending coronary artery; LCX, left circumflex coronary artery LMT, left main trunk; LVEF, left ventricular ejection fraction; BMS, bare metal stent; DES, drug eluting stent; RAS, Renin-Angiotensin-Aldosterone System.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="pone.0274287.t007" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0274287.t007</object-id>
<label>Table 7</label> <caption><title>Fine and Gray model (subdistribution hazard model) for hospitalization due to heart failure.</title></caption>
<alternatives>
<graphic id="pone.0274287.t007g" mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.t007" xlink:type="simple"/>
<table>
<colgroup>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
</colgroup>
<thead>
<tr>
<th align="center" rowspan="2">Variable</th>
<th align="center" colspan="3">Univariate analysis</th>
<th align="center" colspan="3">Multivariate analysis<xref ref-type="table-fn" rid="t007fn001"><sup>#</sup></xref></th>
</tr>
<tr>
<th align="center">sHR</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
<th align="center">sHR</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">PARIS thrombotic score (low-risk group)</td>
<td align="center">Ref.</td>
<td align="center"/>
<td align="center"/>
<td align="center">Ref.</td>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Intermediate-risk group (vs. low-risk group)</td>
<td align="center">1.18</td>
<td align="center">0.51–2.72</td>
<td align="center">0.700</td>
<td align="center">0.99</td>
<td align="center">0.42–2.32</td>
<td align="center">0.980</td>
</tr>
<tr>
<td align="left">High-risk group (vs. low-risk group)</td>
<td align="center">3.23</td>
<td align="center">1.47–7.09</td>
<td align="center">0.003</td>
<td align="center">2.10</td>
<td align="center">0.89–4.95</td>
<td align="center">0.088</td>
</tr>
<tr>
<td align="left">Age (per 1-year increase)</td>
<td align="center">1.01</td>
<td align="center">0.98–1.04</td>
<td align="center">0.330</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Male</td>
<td align="center">0.52</td>
<td align="center">0.29–0.91</td>
<td align="center">0.022</td>
<td align="center">0.55</td>
<td align="center">0.30–1.00</td>
<td align="center">0.051</td>
</tr>
<tr>
<td align="left">Smoking</td>
<td align="center">0.82</td>
<td align="center">0.47–1.44</td>
<td align="center">0.500</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of PCI</td>
<td align="center">1.40</td>
<td align="center">0.75–2.60</td>
<td align="center">0.280</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of CABG</td>
<td align="center">3.16</td>
<td align="center">1.31–7.63</td>
<td align="center">0.010</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">History of OMI</td>
<td align="center">1.38</td>
<td align="center">0.66–2.89</td>
<td align="center">0.380</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Diabetes mellitus</td>
<td align="center">1.78</td>
<td align="center">0.99–3.20</td>
<td align="center">0.054</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Anemia</td>
<td align="center">2.28</td>
<td align="center">1.25–4.16</td>
<td align="center">0.006</td>
<td align="center">1.40</td>
<td align="center">0.74–2.64</td>
<td align="center">0.300</td>
</tr>
<tr>
<td align="left">Chronic kidney disease</td>
<td align="center">3.85</td>
<td align="center">2.02–7.33</td>
<td align="center">&lt; 0.001</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Dialysis</td>
<td align="center">0.80</td>
<td align="center">0.27–2.37</td>
<td align="center">0.690</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Peripheral artery disease</td>
<td align="center">2.06</td>
<td align="center">1.09–3.89</td>
<td align="center">0.025</td>
<td align="center">1.23</td>
<td align="center">0.62–2.41</td>
<td align="center">0.550</td>
</tr>
<tr>
<td align="left">Atrial fibrillation</td>
<td align="center">3.12</td>
<td align="center">1.82–5.35</td>
<td align="center">&lt; 0.001</td>
<td align="center">2.37</td>
<td align="center">1.34–4.19</td>
<td align="center">0.003</td>
</tr>
<tr>
<td align="left">Acute coronary syndrome</td>
<td align="center">1.07</td>
<td align="center">0.62–1.85</td>
<td align="center">0.780</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Multivessel disease</td>
<td align="center">1.57</td>
<td align="center">0.89–2.79</td>
<td align="center">0.120</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (RCA)</td>
<td align="center">0.92</td>
<td align="center">0.51–1.65</td>
<td align="center">0.800</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LAD)</td>
<td align="center">1.24</td>
<td align="center">0.72–2.14</td>
<td align="center">0.430</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LCX)</td>
<td align="center">0.56</td>
<td align="center">0.22–1.38</td>
<td align="center">0.210</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Target lesion (LMT)</td>
<td align="center">1.77</td>
<td align="center">0.42–7.34</td>
<td align="center">0.430</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">LVEF (per 1% increase)</td>
<td align="center">0.96</td>
<td align="center">0.95–0.96</td>
<td align="center">&lt; 0.001</td>
<td align="center">0.98</td>
<td align="center">0.96–0.99</td>
<td align="center">0.044</td>
</tr>
<tr>
<td align="left">BMS</td>
<td align="center">0.31</td>
<td align="center">0.11–0.84</td>
<td align="center">0.021</td>
<td align="center">0.66</td>
<td align="center">0.18–2.38</td>
<td align="center">0.530</td>
</tr>
<tr>
<td align="left">DES</td>
<td align="center">2.18</td>
<td align="center">1.10–4.34</td>
<td align="center">0.026</td>
<td align="center">1.69</td>
<td align="center">0.66–4.37</td>
<td align="center">0.270</td>
</tr>
<tr>
<td align="left">β-blockers</td>
<td align="center">2.28</td>
<td align="center">1.10–4.72</td>
<td align="center">0.026</td>
<td align="center">1.48</td>
<td align="center">0.70–3.13</td>
<td align="center">0.300</td>
</tr>
<tr>
<td align="left">RAS inhibitors</td>
<td align="center">1.33</td>
<td align="center">0.65–2.73</td>
<td align="center">0.420</td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left">Proton pump inhibitor</td>
<td align="center">2.05</td>
<td align="center">1.06–3.98</td>
<td align="center">0.032</td>
<td align="center">1.32</td>
<td align="center">0.69–2.52</td>
<td align="center">0.390</td>
</tr>
</tbody>
</table>
</alternatives>
<table-wrap-foot>
<fn id="t007fn001"><p>#. In the multivariate analysis, PARIS thrombotic score was forcedly entered, and thereafter adjusted for male, anemia, peripheral artery disease, atrial fibrillation, LVEF, BMS, DES, β-blockers and proton pump inhibitor with the forced entry method.</p></fn>
<fn id="t007fn002"><p>sHR, subdistribution hazard ratio; PARIS, the patterns of non-adherence to anti-platelet regimen in stented patients; PCI, percutaneous coronary intervention; CABG, coronary artery bypass grafting; OMI, old myocardial infarction; RCA, right coronary artery; LAD, left anterior descending coronary artery; LCX, left circumflex coronary artery LMT, left main trunk; LVEF, left ventricular ejection fraction; BMS, bare metal stent; DES, drug eluting stent; RAS, Renin-Angiotensin-Aldosterone System.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Moreover, we performed the Fine and Gray model (subdistribution hazard model) of the associations of the PARIS thrombotic risk score, presented as continuous variables (per 1-point increase), with cardiac mortality and hospitalization due to heart failure as sensitivity analyses (<xref ref-type="table" rid="pone.0274287.t008">Table 8</xref>). In the subdistribution multivariable models, a high PARIS thrombotic score was determined to be an independent predictor of hospitalization due to heart failure after adjusting for other confounding factors (hazard ratio 1.28 per 1-point increase, 95% confidence intervals 1.10–1.50, P = 0.001).</p>
<table-wrap id="pone.0274287.t008" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0274287.t008</object-id>
<label>Table 8</label> <caption><title>Fine and Gray model (subdistribution hazard model) of PARIS thrombotic score (continuous variables) for cardiac mortality and hospitalization due to heart failure.</title></caption>
<alternatives>
<graphic id="pone.0274287.t008g" mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.t008" xlink:type="simple"/>
<table>
<colgroup>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
</colgroup>
<thead>
<tr>
<th align="center" rowspan="2">Variable</th>
<th align="center" colspan="3">Univariate analysis</th>
<th align="center" colspan="3">Multivariate analysis</th>
</tr>
<tr>
<th align="center">sHR</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
<th align="center">sHR</th>
<th align="center">95% Cl</th>
<th align="center"><italic>P</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left"><bold>Cardiac mortality</bold></td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left"> PARIS thrombotic score (per 1-point increase) <xref ref-type="table-fn" rid="t008fn002"><sup>#1</sup></xref></td>
<td align="center">1.17</td>
<td align="center">1.03–1.33</td>
<td align="center">0.014</td>
<td align="center">1.08</td>
<td align="center">0.95–1.23</td>
<td align="center">0.210</td>
</tr>
<tr>
<td align="left"><bold>Hospitalization due to heart failure</bold></td>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
<td align="center"/>
</tr>
<tr>
<td align="left"> PARIS thrombotic score (per 1-point increase) <xref ref-type="table-fn" rid="t008fn003"><sup>#2</sup></xref></td>
<td align="center">1.36</td>
<td align="center">1.19–1.56</td>
<td align="center">&lt; 0.001</td>
<td align="center">1.28</td>
<td align="center">1.10–1.50</td>
<td align="center">0.001</td>
</tr>
</tbody>
</table>
</alternatives>
<table-wrap-foot>
<fn id="t008fn001"><p>In the multivariate analysis, PARIS thrombotic score was adjusted for clinically important variables as shown below with the forced entry method.</p></fn>
<fn id="t008fn002"><p>#1. age, anemia, peripheral artery disease, atrial fibrillation, multivessel disease, LVEF, BMS and β-blockers</p></fn>
<fn id="t008fn003"><p>#2. male, anemia, peripheral artery disease, atrial fibrillation, LVEF, BMS, DES, β-blockers and proton pump inhibitor</p></fn>
<fn id="t008fn004"><p>PARIS, the patterns of non-adherence to anti-platelet regimen in stented patients; sHR, subdistribution hazard ration; LVEF, left ventricular ejection fraction; BMS, bare metal stent; DES, drug eluting stent</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec016">
<title>ROC analysis</title>
<p>The AUC values of the PARIS thrombotic risk score and the GRACE score for predicting all-cause death in the first six months after PCI were 0.69 (95% confidence intervals 0.57–0.80) and 0.68 (95% confidence intervals 0.52–0.84), respectively. There was no significant difference in AUC values between these two scores (<xref ref-type="fig" rid="pone.0274287.g004">Fig 4</xref>).</p>
<fig id="pone.0274287.g004" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0274287.g004</object-id>
<label>Fig 4</label>
<caption>
<title>Receiving operating curves (ROC) to predict mortality in 6 months in patients with acute coronary syndrome.</title>
<p>PARIS, the Patterns of non-Adherence to anti-platelet Regimen in Stented patient; GRACE, Global Registry of Acute Coronary Events; AUC, area under the curve; CI, confidence interval.</p>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.g004" xlink:type="simple"/>
</fig>
</sec>
</sec>
<sec id="sec017" sec-type="conclusions">
<title>Discussion</title>
<p>In the present study, of 1,061 patients who had undergone PCIs, we investigated the prognostic value of the PARIS thrombotic risk score for all-cause and cardiac mortalities, as well as hospitalization due to heart failure. As far as we have investigated, this study is the first to reveal the prognostic value of PARIS thrombotic score for long term all-cause mortality and hospitalization due to heart failure in the patients who had undergone PCIs, regardless of comorbidity severity, clinical presentation, or medication at discharge [<xref ref-type="bibr" rid="pone.0274287.ref020">20</xref>].</p>
<p>The risk stratification tools for coronary artery disease after PCIs such as the GRACE score [<xref ref-type="bibr" rid="pone.0274287.ref001">1</xref>–<xref ref-type="bibr" rid="pone.0274287.ref003">3</xref>], the TIMI risk score [<xref ref-type="bibr" rid="pone.0274287.ref004">4</xref>], and the CADILLAC score [<xref ref-type="bibr" rid="pone.0274287.ref005">5</xref>] were reported to have predictive abilities for mortality in ACS patients after PCIs. However, there have been few risk scores that include patients with not only ACS, but also chronic coronary syndrome, and can be used to predict long term mortalities. The ability of PARIS thrombotic risk score to predict the 6-month mortality of patients with ACS was comparable to that of the GRACE score; hence, we examined the long-term prognostic value of PARIS thrombotic risk score for both ACS and chronic coronary syndrome. In addition, we have shown that the PARIS thrombotic risk score can predict events of heart failure hospitalization that the above scores do not. Heart failure remains a major cause of mortality, morbidity, hospitalization, and poor quality of life in patients with coronary artery disease [<xref ref-type="bibr" rid="pone.0274287.ref021">21</xref>]; thus, identifying patients at risk of heart failure is important to improve their prognosis after PCIs.</p>
<p>To date, some predictive scores for thrombotic events after PCIs also have been reported. The DAPT trial, TRA 2°P‐TIMI 50 (Thrombin Receptor Antagonist in Secondary Prevention of Atherothrombotic Ischemic Events–Thrombolysis in Myocardial Infarction 50) trial and CREDO-Kyoto thrombotic risk scores [<xref ref-type="bibr" rid="pone.0274287.ref022">22</xref>–<xref ref-type="bibr" rid="pone.0274287.ref024">24</xref>] have been developed to predict thrombotic events after PCIs. Compared to the thrombotic event risk predictive score mentioned above, the advantage of the PARIS thrombotic risk score is that its components only include patient characteristics without angiographical information. Therefore, it is easy to use in daily clinical practice. Present study has shown the possibility that physicians are able to apply the PARIS thrombotic score not only to estimate the risk of coronary thrombotic events, but also to assess the risk of death and worsening heart failure for patients after PCIs. The PARIS thrombotic risk score may be able to serve as a clinical tool for shared decision making to prevent thrombotic event, hospitalization due to heart failure and death in the clinical practice post PCI.</p>
<p>A few studies have reported on the association between PARIS thrombotic risk score and mortality in patients with PCIs. Zhao et al. reported that the PARIS thrombotic risk score was a significant independent predictor of 2-year mortality in patients after PCIs [<xref ref-type="bibr" rid="pone.0274287.ref025">25</xref>]. One of the advantages of the present study is that our follow-up period was much longer than that in Zhao et al.’s report. Their study population only included patients who had undergone drug eluting stent (DES) implantation, whereas the present study also included patients who had not undergone such implantation, which is useful in terms of stent-less PCI. Moreover, their study did not include a multivariate analysis in assessing the prognostic value of the PARIS thrombotic risk score for all-cause mortality. In contrast, in the present study we performed multivariate Cox proportional hazard analysis followed by competing risk analysis to assess the prognostic value of the PARIS thrombotic risk score. Therefore, the present study suggests that it may provide a new insight into the clinical usefulness of the PARIS thrombotic risk score.</p>
<p>The present study had several limitations. First, as a retrospective cohort study, the study may have inherent limitations regarding selection and ascertainment biases. Second, the clinical practices regarding medical treatment and interventional treatment in the present study may have some difference in the setting of each period. Especially, the achievement rate of guideline directed medical therapy for coronary artery disease and the presence or absence of interventional treatment may affect the rate of thrombotic events, death and heart failure hospitalization after PCI. Third, it may be difficult to determine the reproducibility and generalizability of PARIS thrombotic risk score to new patient or different outcome because the results of the present study have yet to undergo external validation Fourth, we used only variables with regard to hospitalization in this study, without taking into consideration changes in medical parameters or post-discharge treatment.</p>
</sec>
<sec id="sec018" sec-type="conclusions">
<title>Conclusions</title>
<p>In patients who underwent PCIs, a high PARIS thrombotic risk score was associated with an increased risk of long-term all-cause death and hospitalization due to heart failure. Therefore, the PARIS thrombotic risk score could be useful not only for the risk stratification of thrombotic events after PCIs, but also for predicting all-cause mortality and hospitalization due to heart failure in patients who have undergone PCIs.</p>
</sec>
<sec id="sec019" sec-type="supplementary-material">
<title>Supporting information</title>
<supplementary-material id="pone.0274287.s001" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" position="float" xlink:href="info:doi/10.1371/journal.pone.0274287.s001" xlink:type="simple">
<label>S1 File</label>
<caption>
<title/>
<p>(XLSX)</p>
</caption>
</supplementary-material>
</sec>
</body>
<back>
<ref-list>
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<named-content content-type="letter-date">24 Jan 2022</named-content>
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<p><!-- <div> -->PONE-D-21-38539<!-- </div> --><!-- <div> -->Clinical usefulness of the pattern of non-adherence to anti-platelet regimen in stented patients (PARIS) thrombotic risk score to predict long-term all-cause mortality and heart failure hospitalization after percutaneous coronary intervention.<!-- </div> --><!-- <div> -->PLOS ONE</p>
<p>Dear Dr. Akama,</p>
<p>Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. In particular, the authors need to make a compelling argument for why the PARIS score, which was designed to asses risk of thrombotic complications after PCI, should be used to assess mortality and heart failure risk over other risk scores that were designed for this purpose. The impact of the manuscript would be improved with a formal comparison with other appropriate risk scores. </p>
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<p>Jeffrey J. Rade, MD</p>
<p>Academic Editor</p>
<p>PLOS ONE</p>
<p>Journal Requirements:</p>
<p>When submitting your revision, we need you to address these additional requirements.</p>
<p>1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at </p>
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<p>2. We noticed you have some minor occurrence of overlapping text with the following previous publication(s), which needs to be addressed:</p>
<p>- Ando T, Nakazato K, Kimishima Y, Kiko T, Shimizu T, Misaka T, Yamada S, Kaneshiro T, Yoshihisa A, Yamaki T, Kunii H, Takeishi Y. The clinical value of the PRECISE-DAPT score in predicting long-term prognosis in patients with acute myocardial infarction. Int J Cardiol Heart Vasc. 2020 Jun 7;29:100552. doi: 10.1016/j.ijcha.2020.100552. PMID: 32551359; PMCID: PMC7287192.</p>
<p>This is regarding lines 259-263 in the Discussion section of your manuscript.</p>
<p>- Takuya Ando, Kazuhiko Nakazato, Yusuke Kimishima, Takatoyo Kiko, Takeshi Shimizu, Tomofumi Misaka, Shinya Yamada, Takashi Kaneshiro, Akiomi Yoshihisa, Takayoshi Yamaki, Hiroyuki Kunii, Yasuchika Takeishi, The clinical value of the PRECISE-DAPT score in predicting long-term prognosis in patients with acute myocardial infarction, IJC Heart &amp; Vasculature, Volume 29, 2020, 100552, ISSN 2352-9067, <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.1016/j.ijcha.2020.100552" xlink:type="simple">https://doi.org/10.1016/j.ijcha.2020.100552</ext-link>.</p>
<p>This is regarding lines 311 – 319 in the Discussion and Conclusion section of your manuscript.</p>
<p>In your revision ensure you cite all your sources (including your own works), and quote or rephrase any duplicated text outside the methods section. Further consideration is dependent on these concerns being addressed.</p>
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<p>[Note: HTML markup is below. Please do not edit.]</p>
<p>Reviewers' comments:</p>
<p>Reviewer's Responses to Questions</p>
<p><!-- <font color="black"> --><bold>Comments to the Author</bold></p>
<p>1. Is the manuscript technically sound, and do the data support the conclusions?</p>
<p>The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. <!-- </font> --></p>
<p>Reviewer #1: Yes</p>
<p>Reviewer #2: Partly</p>
<p>**********</p>
<p><!-- <font color="black"> -->2. Has the statistical analysis been performed appropriately and rigorously? <!-- </font> --></p>
<p>Reviewer #1: Yes</p>
<p>Reviewer #2: Yes</p>
<p>**********</p>
<p><!-- <font color="black"> -->3. Have the authors made all data underlying the findings in their manuscript fully available?</p>
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<p>Reviewer #1: Yes</p>
<p>Reviewer #2: No</p>
<p>**********</p>
<p><!-- <font color="black"> -->4. Is the manuscript presented in an intelligible fashion and written in standard English?</p>
<p>PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.<!-- </font> --></p>
<p>Reviewer #1: Yes</p>
<p>Reviewer #2: No</p>
<p>**********</p>
<p><!-- <font color="black"> -->5. Review Comments to the Author</p>
<p>Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)<!-- </font> --></p>
<p>Reviewer #1: We congratulate the authors on a rigorous prospective cohort study albeit single center and observational. Completing the mammoth undertaking of long-term follow up of these patients is truly an accomplishment in itself. Clear definitions were provided of the parameters established. Looking at a thrombotic risk score having predictive value in CHF hospitalization has novel application and using a score that does not apply angiographic information has utility even to the general practitioner of medicine or cardiology. Noting that the study includes long-term follow up is key and is hat sets this apart.</p>
<p>That being said however the study is underpowered being that it is single centered and with few patients. Also as the authors have pointed out that nearly 80% of it study subjects are men. And being that these patients are from 2010-2018, there are certain caveats when applying any risk score that does take into account angiographic findings such as how the PCIs were done i.e. use of imaging and physiologic guidance, stent variety and generation, taking into account the usage of DCBs which are not applicable to coronaries in the US, the ~10% use of BMS, etc. Also of note and as mentioned by the authors in the lines 312 -315 variables only related to the hospitalization were taken into account for. Thus the large part of our therapy outside of PCI as related to medication optimization with goal directed dosage levels was not addressed with this study. The tables were extensive and had multiple different characteristics that were compiled. However, these issues we believe are minor and more critique of the content rather than any major issues.</p>
<p>Minor Issues are grammatical in lines 48-53 would suggest to better copyedit this part "...and has developed (into) one of the most popular treatment(s) in modern cardiovascular disease. It is necessary for (would take out "the") patients who under(go) PCI(no plural s required)..." Lastly also a minor issue in our opinion there is a lack of discussion regarding the findings of cardiac death in the Low, Intermediate, High Risk PARIS score patients as described in Graph B of Figure 1. The focus as it rightly should be on all-cause mortality and CHF events. It would be ideal and interesting to discuss the findings of cardiac death in particular perhaps why these grafts initially partial converge and then after one sees the high risk patients diverge from the intermediate and low risk patients around the ~800 days mark.</p>
<p>Again we congratulate the authors on a well done study with great long-term follow up.</p>
<p>Reviewer #2: The paper presented by Akama et al. on the prognostic utility of the PARIS score on outcomes post PCI is a decently done study with a good message and design. The authors show the PARIS score commonly used to predict thrombotic complications post PCI can also be used to predict long-term mortality and heart failure hospitalizations. However, authors need to address some major limitations as described below before to substantially improve the quality of their work and the message delivered:</p>
<p>1- Study rationale and hypothesis: The authors chose to calculate the PARIS score for all subjects and present a study to justify its prognostic utility for long term outcomes. While the study population, follow-up duration, comprehensiveness of data and event rate is suitable for such goal, the choice of PARIS score over other available and widely used score for ACS and PCI such as GRACE, TIMI, CADILLAC, among others is not well justified in the introduction or the discussion. The authors highlighted the strengths of their study in comparison to those done by others in the discussion, but it is not true that GRACE and TIMI were not studied for longer term outcomes. Further, the PARIS score albeit simple and easy to use yet is limited with choice of variables (no age, gender, and co-morbidities such as anemia included in the score). Hence, in order to give validity to their study, I most certainly recommend comparing the prognostic value of PARIS score in this population against GRACE and TIMI score and see if it outperforms either one. By doing so, you will give your study more clinical meaning and strength to your chosen score.</p>
<p>2- Study design and methodology: This is a retrospective cohort study not a prospective one as highlighted in the limitations section. The authors nicely outlined all the steps they undertook to ascertain their outcomes and all the clinical variables of the study, all of which are strengths that can be highlighted in the limitation section.</p>
<p>Recommendations:</p>
<p>- However, there has to be data provided on (1) the type of ACS (STEMI, NSTEMI, UA) and (2) any exclusion criteria (did you include consecutive patients, exclude those with unavailable data on follow-up or STEMI, etc.).</p>
<p>- Give the presence of competing risk between HF hospitalization and cardiac mortality, the authors are urged to present competing risks survival analysis in their Cox regression for the HF hospitalization and cardiac mortality outcomes.</p>
<p>- I recommend to do a stratified analysis on the basis on presentation (ACS vs stable angina) as it is important to see if the PARIS score's prognostic potential holds for either presentation. Comparing the score with GRACE and TIMI is invalid for those with stable angina.</p>
<p>3- Limitations: The biggest limitation of the study is not the small sample size as authors mentioned but (1) retrospective design with inherent limitation to selection and ascertainment biases, (2) the absence of external validation of the proposed score, (3) absence of comparison of PARIS score with other widely used and validated risk scores such as GRACE and TIMI.</p>
<p>4- Language, technical terms and design: The authors need to improve the writing of the paper in terms of English language, particularly in the introduction. The words "dependable" and "helpful" to describe PCI are not appropriate, and repeating the aims statement with the previous sentence of what's missing in the literature (i.e. the long-term prognostic use of PARIS score) is also not needed. I suggest getting the help of a native English language speaker to proofread the paper.</p>
<p>Further, I could not fully read the tables presented as they were embedded in the text and truncated on the right, making half the tables missing to me. The KM curves are also of very poor quality and need to be presented in a higher resolution.</p>
<p>**********</p>
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<p>Reviewer #2: No</p>
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<sub-article article-type="author-comment" id="pone.0274287.r002">
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<article-id pub-id-type="doi">10.1371/journal.pone.0274287.r002</article-id>
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<article-title>Author response to Decision Letter 0</article-title>
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<p>
<named-content content-type="author-response-date">3 Mar 2022</named-content>
</p>
<p>Responses to Academic Editor‘s comment</p>
<p>Editor’s comment</p>
<p>In particular, the authors need to make a compelling argument for why the PARIS score, which was designed to asses risk of thrombotic complications after PCI, should be used to assess mortality and heart failure risk over other risk scores that were designed for this purpose. The impact of the manuscript would be improved with a formal comparison with other appropriate risk scores.</p>
<p>Auther’s Reply</p>
<p>Thank you for your helpful comment. We received a similar comment from Reviewer#2. As you pointed out, the descriptions of conventional risk scores to estimate mortality including GRACE, TIMI and CADILLAC were lacking in our original manuscript. According to your suggestion, we have revised the Introduction that firstly described the characteristics of those well-known risk scores, which could estimate the short- to mid-term outcomes of ACS patients (GRACE predicts 6 months mortality, TIMI predicts 14 days, and CADILLAC predicts 1 month and 1-year mortalities). To assess the prognostic ability of PARIS thrombotic risk score for predicting mortality, we additionally conducted the receiver operating curve analysis for PARIS thrombotic risk score and GRACE risk score in patients with ACS and compared the areas under the curves (AUC) between two scores. The AUC for predicting 6 months mortality was 0.69 in PARIS thrombotic risk score, which was comparable to 0.68 in GRACE score, as described below. The equivalence of PARIS thrombotic score to GRACE score for predicting mid-term mortality gives validity to the study, therefore we highlighted the long-term prognostic value of PARIS thrombotic risk score for not only all-cause mortality but also cardiac mortality and heart failure event, in addition to the original role for prediction of thrombotic event.</p>
<p>We have added the result of ROC analysis in the revised manuscript (page　34, line 336 – 339 and Fig. 4), and described about GRACE, TIMI and CADILLAC in Introduction (page 3, line55 – 60) and Discussion (page 34 – 35, line 348 – 373). </p>
<p>“The AUC values of the PARIS thrombotic risk score and the GRACE score for all-cause mortality in 6 months were 0.69 (95% confidence intervals 0.57–0.80) and 0.68 (95% confidence intervals 0.52–0.84). ROC analysis demonstrated that there was no significant difference between these two scores (Fig. 4).” (page 34, line 336 - 339)</p>
<p>Figure 4. ROC to predict all-cause mortality for 6 months in patients with acute coronary syndrome (ACS). </p>
<p>“Three well-known risk scores are the Global Registry of Acute Coronary Events (GRACE) score [1-3], the Thrombolysis in Myocardial Infarction (TIMI) score[4] and the Controlled Abciximab and Device Investigation to Lower Late Angioplasty Complications (CADILLIAC) score[5]. These scores combine and weigh various predictors to calculate the risk of acute coronary syndrome (ACS) for an individual patient[6].” (page 3, line55 - 60)</p>
<p>“The risk stratification tools for coronary artery disease after PCIs such as the GRACE score[1-3] ,the TIMI[4] and the CADILLIAC score[5] were reported to have predictive abilities for mortality in patients after PCIs. The GRACE score, which is used for overall risk assessment in patients with ACS, including ST elevation myocardial infarction (STEMI) and non-ST elevation ACS (NSTE-ACS) was designed to calculate the probability of death or myocardial infarction during admission and at 6 months by weighting 8 risk factors: age, heart rate, systolic blood pressure, initial serum creatine, Killip class, hospitalization due to cardiac arrest, positive cardiac biomarker, and ST-segment deviation[1-3, 22]. The TIMI risk score, which is often used for risk assessment in patients with NSTE-ACS, is calculated by using 7 factors: age (≥65 years); at least 3 coronary risk factors (family history, hypertension, dyslipidemia, diabetes mellitus, and smoking); known significant (≥50%) coronary stenosis; ST changes ≥ 0.5 mm on electrocardiogram; at least 2 episodes of angina in 24 hours; aspirin use in the past 7 days; and increased cardiac markers. Most of these factors can be assessed immediately after the admission. As the score increases, the incidence of major cardiovascular complications in the following 2 weeks increases synergistically[4, 22]. The CADILLIAC score, which is often used for risk assessment in patients with STEMI, evaluates several different prognostic variables including LVEF, creatinine clearance, Killip class, final TIMI flow, age, anemia and presence of three vessel disease. Utilizing the CADILLIAC risk score patients were stratified by low (CADILLIAC score 0-2), intermediate (CADILLIAC score 3-5), and high (CADILLIAC score ≥ 6) risk groups. The CADILLIAC score accurately predict 30-day and 1-year mortality after primary PCI[5].” (page 34 - 35, line 348 - 373)</p>
<p>We have cited the following papers as new references (#1-6, 22).</p>
<p>[1] Granger CB, Goldberg RJ, Dabbous O, Pieper KS, Eagle KA, Cannon CP, et al. Predictors of hospital mortality in the global registry of acute coronary events. Arch Intern Med. 2003;163:2345-53.</p>
<p>[2] Eagle KA, Lim MJ, Dabbous OH, Pieper KS, Goldberg RJ, Van de Werf F, et al. A validated prediction model for all forms of acute coronary syndrome: estimating the risk of 6-month postdischarge death in an international registry. Jama. 2004;291:2727-33.</p>
<p>[3] Fox KA, Dabbous OH, Goldberg RJ, Pieper KS, Eagle KA, Van de Werf F, et al. Prediction of risk of death and myocardial infarction in the six months after presentation with acute coronary syndrome: prospective multinational observational study (GRACE). Bmj. 2006;333:1091.</p>
<p>[4] Antman EM, Cohen M, Bernink PJ, McCabe CH, Horacek T, Papuchis G, et al. The TIMI risk score for unstable angina/non-ST elevation MI: A method for prognostication and therapeutic decision making. Jama. 2000;284:835-42.</p>
<p>[5] Halkin A, Singh M, Nikolsky E, Grines CL, Tcheng JE, Garcia E, et al. Prediction of mortality after primary percutaneous coronary intervention for acute myocardial infarction: the CADILLAC risk score. J Am Coll Cardiol. 2005;45:1397-405.</p>
<p>[6] Poldervaart JM, Langedijk M, Backus BE, Dekker IMC, Six AJ, Doevendans PA, et al. Comparison of the GRACE, HEART and TIMI score to predict major adverse cardiac events in chest pain patients at the emergency department. Int J Cardiol. 2017;227:656-61.</p>
<p>[22] Kimura K, Kimura T, Ishihara M, Nakagawa Y, Nakao K, Miyauchi K, et al. JCS 2018 Guideline on Diagnosis and Treatment of Acute Coronary Syndrome. Circ J. 2019;83:1085-196.</p>
<p> </p>
<p>Responses to Reviewer #1</p>
<p>We appreciate your detailed reviews on our manuscript. We have revised our manuscript according to your comments. </p>
<p>Reviewer’s comment</p>
<p>That being said however the study is underpowered being that it is single centered and with few patients. Also as the authors have pointed out that nearly 80% of it study subjects are men. And being that these patients are from 2010-2018, there are certain caveats when applying any risk score that does take into account angiographic findings such as how the PCIs were done i.e. use of imaging and physiologic guidance, stent variety and generation, taking into account the usage of DCBs which are not applicable to coronaries in the US, the ~10% use of BMS, etc. Also of note and as mentioned by the authors in the lines 312 -315 variables only related to the hospitalization were taken into account for. Thus the large part of our therapy outside of PCI as related to medication optimization with goal directed dosage levels was not addressed with this study. The tables were extensive and had multiple different characteristics that were compiled. However, these issues we believe are minor and more critique of the content rather than any major issues.</p>
<p>Author’s Reply</p>
<p>Thank you for your important comments. As you mentioned, 78.6% of patients in our study are men, which may reflect the true prevalence in Japanese population of patients with coronary artery disease. The other large registries of coronary artery disease patients who underwent percutaneous coronary intervention (PCI) in Japan showed that 78.3% were male in PENDULUM registry [Nakamura M, Kadota K, Nakao K, Nakagawa Y, Shite J, Yokoi H, et al. High bleeding risk and clinical outcomes in East Asian patients undergoing percutaneous coronary intervention: the PENDULUM registry. EuroIntervention 2021; 19: 1154-1162] and 73.0% were male in CREDO-Kyoto registry [Application of the Modified High Bleeding Risk Criteria for Japanese Patients in an All-Comers Registry of Percutaneous Coronary Intervention -From the CREDO-Kyoto Registry Cohort-3-. Circ J 2021; 85: 769-781]. The duration of enrollment in this study was relatively long, from 2010 to 2018, thus there might be some differences in strategies for treatment, as you mentioned. Hence, we have analyzed the proportion of use of imaging devices during PCI, which was over 95% in all three groups as additionally displayed in Table 1, so that showing the consistent imaging device-guided PCI was performed during all periods. However, unfortunately, data of stent generation and goal directed dosage levels of medication were not available, though those were very important information for understanding the patient background and relationship to the outcomes, as you pointed out. </p>
<p>Therefore, we have corrected the limitations as follow, reflecting your comments and also suggestions from Reviewer #2.</p>
<p>“The present study had several limitations. First, as a retrospective cohort study, the study may be with inherent limitation to selection and ascertainment biases. Second, clinical practices in PCI and medical treatment in the study may have some differences in the setting of each period. Third, it may be difficult to determine the reproducibility and generalizability of PARIS thrombotic risk score to new patient cohort because of the absence of external validation of this study. Fourth, we used only variables on hospitalization in this study, without taking into consideration changes in medical parameters and post discharge treatment.” (page 37, lines 421 - 428).</p>
<p>Reviewer’s comment</p>
<p>Minor Issues are grammatical in lines 48-53 would suggest to better copyedit this part "...and has developed (into) one of the most popular treatment(s) in modern cardiovascular disease. It is necessary for (would take out "the") patients who under(go) PCI (no plural s required)..." </p>
<p>Author’s Reply</p>
<p>We apologize for those mistakes and have corrected those mistakes in page 3, lines 52 - 53.</p>
<p>Reviewer’s comment</p>
<p>Lastly also a minor issue in our opinion there is a lack of discussion regarding the findings of cardiac death in the Low, Intermediate, High Risk PARIS score patients as described in Graph B of Figure 1. The focus as it rightly should be on all-cause mortality and CHF events. It would be ideal and interesting to discuss the findings of cardiac death in particular perhaps why these grafts initially partial converge and then after one sees the high risk patients diverge from the intermediate and low risk patients around the ~800 days mark.</p>
<p>Author’s Reply</p>
<p>Thank you for your helpful comment. The 64 cardiac deaths included 48 deaths from heart failure, therefore, the majority of cardiac deaths were heart failure death. Unfortunately, we could not fully explain the reason why the Kaplan-Meier curves for cardiac mortality initially partial converge and the high-risk group diverged from other two groups around 800 days. The Kaplan-Meier curves for hospitalization due to heart failure also initially partial converge and the high-risk group diverged from other two groups around 800 days. The worsening of heart failure with aging may be one of the reasons for the results that you pointed out. We have added the following sentences about these issues in page 35 - 36, lines 381 - 386. </p>
<p>“The reason why the Kaplan-Meier curves for cardiac mortality and hospitalization due to heart failure partial converge and the high-risk group diverged from other two groups around 800 days is not unclear. One possible reason is the 64 cardiac deaths included 48 deaths from heart failure, therefore, the majority of cardiac deaths were heart failure death. The worsening of heart failure with aging may be one of the reasons for the results.”</p>
<p>Thank you again for your invaluable comments to our manuscript.</p>
<p>Responses to Reviewer #2</p>
<p>We appreciate your detailed reviews on our manuscript. We have revised our manuscript according to your comments. </p>
<p>Reviewer’s comment</p>
<p>1- Study rationale and hypothesis: The authors chose to calculate the PARIS score for all subjects and present a study to justify its prognostic utility for long term outcomes. While the study population, follow-up duration, comprehensiveness of data and event rate is suitable for such goal, the choice of PARIS score over other available and widely used score for ACS and PCI such as GRACE, TIMI, CADILLAC, among others is not well justified in the introduction or the discussion. The authors highlighted the strengths of their study in comparison to those done by others in the discussion, but it is not true that GRACE and TIMI were not studied for longer term outcomes. Further, the PARIS score albeit simple and easy to use yet is limited with choice of variables (no age, gender, and co-morbidities such as anemia included in the score). Hence, in order to give validity to their study, I most certainly recommend comparing the prognostic value of PARIS score in this population against GRACE and TIMI score and see if it outperforms either one. By doing so, you will give your study more clinical meaning and strength to your chosen score.</p>
<p>Author’s Reply</p>
<p>Thank you for your helpful comment. As you pointed out, the descriptions of conventional risk scores including GRACE, TIMI and CADILLAC were lacking in our original manuscript. According to your suggestion, we have revised the Introduction that firstly described the characteristics of those well-known risk scores, which could estimate the short- to mid-term outcomes of ACS patients (GRACE predicts 6 months mortality, TIMI predicts 14 days and CADILLAC predicts 1 month and 1-year mortalities). To assess the prognostic ability of PARIS thrombotic risk score for predicting mortality, we additionally conducted the receiver operating curve analysis for PARIS thrombotic risk score and GRACE risk score in patients with ACS and compared the areas under the curves (AUC) between two scores, according to your recommendation. The AUC for predicting 6 months mortality was 0.69 in PARIS thrombotic risk score, which was comparable to 0.68 in GRACE score, as described below. Unfortunately, the comparing of PARIS thrombotic risk score to TIMI risk score could not be performed, since the data for calculating TIMI risk score were not available in this cohort. The equivalence of PARIS thrombotic score to GRACE score for predicting mid-term mortality gives validity to the study, therefore we highlighted the long-term prognostic value of PARIS thrombotic risk score for not only all-cause mortality but also cardiac mortality and heart failure event, in addition to the original role for prediction of thrombotic event. We have added the result of ROC analysis in the revised manuscript (page　34, line 336 – 339 and Fig. 4), and described about GRACE, TIMI and CADILLAC in Introduction (page 3, line 55 - 60) and Discussion (page 34 - 35, line 348 - 373). </p>
<p>“The AUC values of the PARIS thrombotic risk score and the GRACE score for all-cause mortality in 6 months were 0.69 (95% confidence intervals 0.57–0.80) and 0.68 (95% confidence intervals 0.52–0.84). ROC analysis demonstrated that there was no significant difference between these two scores (Fig. 4).” (page 34, line 336 – 339)</p>
<p>Figure 4. ROC to predict all-cause mortality for 6 months in patients with acute coronary syndrome (ACS). </p>
<p>“Three well-known risk scores are the Global Registry of Acute Coronary Events (GRACE) score [1-3], the Thrombolysis in Myocardial Infarction (TIMI) score[4] and the Controlled Abciximab and Device Investigation to Lower Late Angioplasty Complications (CADILLIAC) score[5]. These scores combine and weigh various predictors to calculate the risk of acute coronary syndrome (ACS) for an individual patient[6].” (page 3, line 55 - 60)</p>
<p>“The risk stratification tools for coronary artery disease after PCIs such as the GRACE score[1-3] ,the TIMI[4] and the CADILLIAC score[5] were reported to have predictive abilities for mortality in patients after PCIs. The GRACE score, which is used for overall risk assessment in patients with ACS, including ST elevation myocardial infarction (STEMI) and non-ST elevation ACS (NSTE-ACS) was designed to calculate the probability of death or myocardial infarction during admission and at 6 months by weighting 8 risk factors: age, heart rate, systolic blood pressure, initial serum creatine, Killip class, hospitalization due to cardiac arrest, positive cardiac biomarker, and ST-segment deviation[1-3, 22]. The TIMI risk score, which is often used for risk assessment in patients with NSTE-ACS, is calculated by using 7 factors: age (≥65 years); at least 3 coronary risk factors (family history, hypertension, dyslipidemia, diabetes mellitus, and smoking); known significant (≥50%) coronary stenosis; ST changes ≥ 0.5 mm on electrocardiogram; at least 2 episodes of angina in 24 hours; aspirin use in the past 7 days; and increased cardiac markers. Most of these factors can be assessed immediately after the admission. As the score increases, the incidence of major cardiovascular complications in the following 2 weeks increases synergistically[4, 22]. The CADILLIAC score, which is often used for risk assessment in patients with STEMI, evaluates several different prognostic variables including LVEF, creatinine clearance, Killip class, final TIMI flow, age, anemia and presence of three vessel disease. Utilizing the CADILLIAC risk score patients were stratified by low (CADILLIAC score 0-2), intermediate (CADILLIAC score 3-5), and high (CADILLIAC score ≥ 6) risk groups. The CADILLIAC score accurately predict 30-day and 1-year mortality after primary PCI[5].” (page 34 - 35, line 348 - 373)</p>
<p>We have cited the following papers as new references (#1-6, 22).</p>
<p>[1] Granger CB, Goldberg RJ, Dabbous O, Pieper KS, Eagle KA, Cannon CP, et al. Predictors of hospital mortality in the global registry of acute coronary events. Arch Intern Med. 2003;163:2345-53.</p>
<p>[2] Eagle KA, Lim MJ, Dabbous OH, Pieper KS, Goldberg RJ, Van de Werf F, et al. A validated prediction model for all forms of acute coronary syndrome: estimating the risk of 6-month postdischarge death in an international registry. Jama. 2004;291:2727-33.</p>
<p>[3] Fox KA, Dabbous OH, Goldberg RJ, Pieper KS, Eagle KA, Van de Werf F, et al. Prediction of risk of death and myocardial infarction in the six months after presentation with acute coronary syndrome: prospective multinational observational study (GRACE). Bmj. 2006;333:1091.</p>
<p>[4] Antman EM, Cohen M, Bernink PJ, McCabe CH, Horacek T, Papuchis G, et al. The TIMI risk score for unstable angina/non-ST elevation MI: A method for prognostication and therapeutic decision making. Jama. 2000;284:835-42.</p>
<p>[5] Halkin A, Singh M, Nikolsky E, Grines CL, Tcheng JE, Garcia E, et al. Prediction of mortality after primary percutaneous coronary intervention for acute myocardial infarction: the CADILLAC risk score. J Am Coll Cardiol. 2005;45:1397-405.</p>
<p>[6] Poldervaart JM, Langedijk M, Backus BE, Dekker IMC, Six AJ, Doevendans PA, et al. Comparison of the GRACE, HEART and TIMI score to predict major adverse cardiac events in chest pain patients at the emergency department. Int J Cardiol. 2017;227:656-61.</p>
<p>[22] Kimura K, Kimura T, Ishihara M, Nakagawa Y, Nakao K, Miyauchi K, et al. JCS 2018 Guideline on Diagnosis and Treatment of Acute Coronary Syndrome. Circ J. 2019;83:1085-196.</p>
<p>Reviewer’s comment</p>
<p>2- Study design and methodology: This is a retrospective cohort study not a prospective one as highlighted in the limitations section. The authors nicely outlined all the steps they undertook to ascertain their outcomes and all the clinical variables of the study, all of which are strengths that can be highlighted in the limitation section.</p>
<p>Recommendations:</p>
<p>- However, there has to be data provided on (1) the type of ACS (STEMI, NSTEMI, UA) and (2) any exclusion criteria (did you include consecutive patients, exclude those with unavailable data on follow-up or STEMI, etc.).</p>
<p>Author’s Reply</p>
<p>Thank you for your helpful comments.　We have showed the type of ACS in Table 1 and added exclusion criteria in page 4, line 88. </p>
<p>“Exclusion criteria were defined as death at discharge.”</p>
<p>Reviewer’s comment</p>
<p>- Give the presence of competing risk between HF hospitalization and cardiac mortality, the authors are urged to present competing risks survival analysis in their Cox regression for the HF hospitalization and cardiac mortality outcomes.</p>
<p>Author’s Reply</p>
<p>Thank you for pointing out this important issue. We have investigated cardiac mortality and hospitalization due to heart failure by cumulative incidence competing risk method. The cumulative incidence curves have revealed that hospitalization due to heart failure after adjusting competing risks was highest in high-risk group among the three groups as shown Figure 2(B). Furthermore, results from the Fine and Gray model (hazard of the subdistribution model) of association of PARIS thrombosis risk score with cardiac mortality and hospitalization due to heart failure were presented in Tables 6-8. We have added the result of cumulative incidence competing risk method and Fine and Gray model in the revised manuscript (page　15, line 210 – 212 and page 26 – 32, line 276 - 327). </p>
<p>“In cumulative incidence competing risk method (Fig 2), the hospitalization due to heart failure after adjusting competing risk was highest in high-risk group among the 3 groups (P &lt; 0.001).” (page 15, line 210 – 212)</p>
<p>Figure 2. The cumulative incidence curves for cardiac mortality (A) and hospitalization due to heart failure (B) in the high, intermediate, and low PARIS thrombotic risk score groups.</p>
<p>“Fine and Gray model (hazard of the subdistribution model) </p>
<p> The Fine and Gray model (hazard of the subdistribution model) of association of the PARIS thrombotic score, which are presented as categorical variables (groups), with cardiac mortalities and hospitalization due to heart failure are presented in Tables 6–7.”</p>
<p>“Moreover, we performed the Fine and Gray model (hazard of the subdistribution model) of association of the PARIS thrombotic risk score, which are presented as continuous variables (per 1-point increase), with cardiac mortalities and hospitalization due to heart failure as sensitivity analyses (Table 8). In the subdistribution multivariable models, a high PARIS thrombotic score was determined to be an independent predictor of hospitalization due to heart failure after adjusting for other confounding factors (hazard ratio 1.28 per 1-point increase, 95% confidence intervals 1.10–1.50, P = 0.001).” (page 26 – 32, line 276 - 327)</p>
<p>Table 6. Fine and Gray model (hazard of the subdistribution model) for cardiac mortality</p>
<p>Table 7. Fine and Gray model (hazard of the subdistribution model) for hospitalization due to heart failure</p>
<p>Table 8. Fine and Gray model (hazard of the subdistribution model) of PARIS thrombotic score (continuous variables) for cardiac mortalities and hospitalization due to heart failure</p>
<p>Reviewer’s comment</p>
<p>- I recommend to do a stratified analysis on the basis on presentation (ACS vs stable angina) as it is important to see if the PARIS score's prognostic potential holds for either presentation. Comparing the score with GRACE and TIMI is invalid for those with stable angina.</p>
<p>Author’s Reply</p>
<p>Thank you for your important comment. We have conducted subgroup analysis to assess the prognostic value of the PARIS thrombosis risk score for all-cause and cardiac mortality and incidence of hospitalization due to heart failure by clinical presentations. There was no interaction between ACS and stable AP. We have added this issue in page 15 - 16, line 223 – 235 and Figure 3. </p>
<p>“Furthermore, to assess the prognostic value of the PARIS thrombosis risk score for all-cause and cardiac mortality and incidence of hospitalization due to heart failure by clinical presentations, we conducted subgroup analysis (Fig. 3). Subgroup analysis was performed to compare the high-risk group with the low-risk group. The hazard ratios of the PARIS thrombotic risk score on all-cause mortality in patients presenting stable angina pectoris and acute coronary syndrome were 1.72 (95% confidence intervals 1.01–2.93) and 3.30 (95% confidence intervals 1.63–6.67). The hazard ratios of the PARIS thrombotic risk score on cardiac mortality in patients presenting stable angina pectoris and acute coronary syndrome were 1.55 (95% confidence intervals 0.62–3.84) and 7.92 (95% confidence intervals 1.05–59.80). The hazard ratios of the PARIS thrombotic risk score on the incidence of hospitalization due to heart failure in patients presenting stable angina and acute coronary syndrome were 3.66 (95% confidence intervals 1.69–7.90) and 4.99 (95% confidence intervals 1.53–16.29). There was no interaction.” (page 15 - 16, line 223 – 235)</p>
<p>Figure 3. Forest Plot of hazard ratios by clinical presentations.</p>
<p>Reviewer’s comment</p>
<p>3- Limitations: The biggest limitation of the study is not the small sample size as authors mentioned but (1) retrospective design with inherent limitation to selection and ascertainment biases, (2) the absence of external validation of the proposed score, (3) absence of comparison of PARIS score with other widely used and validated risk scores such as GRACE and TIMI.</p>
<p>Author’s Reply</p>
<p>Thank you for your important comments. We have corrected the limitations as below;</p>
<p>“The present study had several limitations. First, as a retrospective cohort study, the study may be with inherent limitation to selection and ascertainment biases. Second, clinical practices in PCI and medical treatment in the study may have some difference in the setting of each period. Third, it may be difficult to determine the reproducibility and generalizability of PARIS thrombotic risk score to new patient cohort because of the absence of external validation of this study. Fourth, we used only variables on hospitalization in this study, without taking into consideration changes in medical parameters and post discharge treatment.” (page 37, line 421 - 428). </p>
<p>Regarding the absence of comparison of PARIS thrombotic risk score with other risk score, we have described as above.</p>
<p>Reviewer’s comment</p>
<p>4- Language, technical terms and design: The authors need to improve the writing of the paper in terms of English language, particularly in the introduction. The words "dependable" and "helpful" to describe PCI are not appropriate, and repeating the aims statement with the previous sentence of what's missing in the literature (i.e. the long-term prognostic use of PARIS score) is also not needed. I suggest getting the help of a native English language speaker to proofread the paper.</p>
<p>Further, I could not fully read the tables presented as they were embedded in the text and truncated on the right, making half the tables missing to me. The KM curves are also of very poor quality and need to be presented in a higher resolution.</p>
<p>Author’s Reply</p>
<p>We apologize for mistakes of English language and careless of tables and figures. We have corrected “dependable and helpful” to “well-established” in page 3, line 55. In revised manuscript, you can read fully tables and high-resolution KM curves.</p>
<p>Thank you again for your invaluable comments to our manuscript.</p>
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<article-title>Decision Letter 1</article-title>
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<name name-style="western">
<surname>Rade</surname>
<given-names>Jeffrey J.</given-names>
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<role>Academic Editor</role>
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<copyright-year>2022</copyright-year>
<copyright-holder>Jeffrey J. Rade</copyright-holder>
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<named-content content-type="letter-date">4 Apr 2022</named-content>
</p>
<p><!-- <div> -->PONE-D-21-38539R1<!-- </div> --><!-- <div> -->Clinical usefulness of the pattern of non-adherence to anti-platelet regimen in stented patients (PARIS) thrombotic risk score to predict long-term all-cause mortality and heart failure hospitalization after percutaneous coronary intervention.<!-- </div> --><!-- <div> -->PLOS ONE</p>
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<p>Reviewer #2: The authors did an excellent job responding to all the comments raised, particularly ones related to the scientific rationale and statistical analysis of the data. I have no follow up comments to my previously raised one.</p>
<p>However, I do think that the data presented are elegantly tabulated and charted and deserve a better discussion.</p>
<p>The only major comment I currently have is that there is needs to be major improvement to the discussion section in terms of writeup. It is really hard to follow, with no clear flow of ideas of objective, a lot of redundancy and unnecessary details, and relatively weak critical thinking and reasoning of the data. Here are my suggestions:</p>
<p>1- You need to show why is your data important relative to prior studies (one in particular you cited by Zhao et al.). You need to go in detail about their patient population, how they validated their score against other ones, what makes you study better, etc. (you can't just say longer term follow up).</p>
<p>2- Avoid redundancy. Every paragraphs end by "we show that PARIS score predict outcomes...predict mortality...etc.". You need to put more thought into how your score can be used in the clinical setting (for example, can be used preoperatively, postop to allow for shared decision making and prevent HF hospitalization, etc.).</p>
<p>3- Need to have stronger arguments and better flow of paragraphs. Each paragraph needs to be linked to the one before, start and end with a compelling statement about a certain finding, and end with a concluding statement about the following paragraph or future applications/outlook of your findings.</p>
<p>In summary:</p>
<p>- For each paragraph, identify a study implication about why our study is novel, what it adds to the literature, what it suggestsPARIS score. Always start with a statement about that implication</p>
<p>- Expand on that implication (ie its application) with evidence for or against it, if it exists</p>
<p>- Close with strong statement about what that implication means in the grand scale of things</p>
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<article-title>Author response to Decision Letter 1</article-title>
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<named-content content-type="author-response-date">30 May 2022</named-content>
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<p>Responses to Academic Editor‘s comment</p>
<p>Editor’s comment</p>
<p>In addition to the points raised by Reviewer #2, the Editor asks that you review the manuscript for grammatical integrity. For example, there are several places where single sentences serve as stand-alone paragraphs. These should be incorporated into adjacent paragraphs. </p>
<p>Author’s Reply</p>
<p>Thank you for your helpful comment. We have found two places where single sentences server as stand-alone paragraphs (page 3, lines 62–64 and page 40, lines 474–475 in the revised manuscript with track changes). We have removed these sentences, as shown below, because they had previously caused some difficulties with regard to following the manuscript. Accordingly, the reference [7] as shown below has been removed. Additionally, we have asked the native English speaker to proofread and have also been modified to make the manuscript easier to understand and to correct any previous grammatical errors as described in “the revised manuscript with track changes”.</p>
<p>“Moreover, it is necessary for patients who undergo PCI or stent implantation to take a dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 receptor inhibitor in order to prevent serious stent-related thrombotic complications after PCIs [7].” (page 3, lines 62–64)</p>
<p>“Findings in this study indicate that the PARIS thrombotic risk score may be used clinically beyond its intended use.” (page 40, lines 474–475)</p>
<p>“[7] Mauri L, Kereiakes DJ, Yeh RW, Driscoll-Shempp P, Cutlip DE, Steg PG, et al. Twelve or 30 months of dual antiplatelet therapy after drug-eluting stents. N Engl J Med. 2014;371:2155-66.“</p>
<p>The following reference has been deleted because the content is supplemented by reference [17].</p>
<p>[18] Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS, et al. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC)Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J. 2016;37:2129-200.</p>
<p>Reference [15] has been added to correct reference [16].</p>
<p>[15] Correction: Using standardized serum creatinine values in the Modification of Diet in Renal Disease Study Equation. Ann Intern Med. 2021;174:584.</p>
<p>The following references have been delated as the manuscript has been revised.</p>
<p>[23] Tang EW, Wong CK, Herbison P. Global Registry of Acute Coronary Events (GRACE) hospital discharge risk score accurately predicts long-term mortality post acute coronary syndrome. Am Heart J. 2007;153:29-35.</p>
<p>[24] Valgimigli M, Bueno H, Byrne RA, Collet JP, Costa F, Jeppsson A, et al. 2017 ESC focused update on dual antiplatelet therapy in coronary artery disease developed in collaboration with EACTS: The Task Force for dual antiplatelet therapy in coronary artery disease of the European Society of Cardiology (ESC) and of the European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J. 2018;39:213-60.</p>
<p>[25] Tanaka S, Sakata R, Marui A, Furukawa Y, Kita T, Kimura T. Predicting long-term mortality after first coronary revascularization: – the Kyoto model –. Circ J. 2012;76:328-34.</p>
<p>[26] Nammas W, Kiviniemi T, Schlitt A, Rubboli A, Valencia J, Lip GYH, et al. Value of DAPT score to predict adverse outcome in patients with atrial fibrillation undergoing percutaneous coronary intervention: A post-hoc analysis from the AFCAS registry. Int J Cardiol. 2018;253:35-9.</p>
<p>Responses to Reviewer #2</p>
<p>We appreciate your detailed review of our manuscript. We believe we have revised the manuscript accordingly. </p>
<p>Reviewer’s comment</p>
<p>The authors did an excellent job responding to all the comments raised, particularly ones related to the scientific rationale and statistical analysis of the data. I have no follow up comments to my previously raised one.</p>
<p>However, I do think that the data presented are elegantly tabulated and charted and deserve a better discussion.</p>
<p>The only major comment I currently have is that there is needs to be major improvement to the discussion section in terms of writeup. It is really hard to follow, with no clear flow of ideas of objective, a lot of redundancy and unnecessary details, and relatively weak critical thinking and reasoning of the data. Here are my suggestions:</p>
<p>1- You need to show why is your data important relative to prior studies (one in particular you cited by Zhao et al.). You need to go in detail about their patient population, how they validated their score against other ones, what makes you study better, etc. (you can't just say longer term follow up).</p>
<p>Author’s Reply</p>
<p>Thank you for your helpful suggestions. We have described in detail about the differences between our study and the prior one. We have addressed this issue in the Discussion (page 36, line 391–page 37, line 403).</p>
<p>“A few studies have reported on the association between PARIS thrombotic risk score and mortality in patients with PCIs. Zhao et al. reported that the PARIS thrombotic risk score was a significant independent predictor of 2-year mortality in patients after PCIs [26]. One of the advantages of the present study is that our follow-up period was much longer than that in Zhao et al.’s report. Their study population only included patients who had undergone drug eluting stent (DES) implantation, whereas the present study also included patients who had not undergone such implantation, which is useful in terms of stent-less PCI. Moreover, their study did not include a multivariate analysis in assessing the prognostic value of the PARIS thrombotic risk score for all-cause mortality. In contrast, in the present study we performed multivariate Cox proportional hazard analysis followed by competing risk analysis to assess the prognostic value of the PARIS thrombotic risk score. Therefore, the present study provides a new insight into the clinical usefulness of the PARIS thrombotic risk score.” (page 36, line 391–page 37, line 403)</p>
<p>Reviewer’s comment</p>
<p>2- Avoid redundancy. Every paragraph end by "we show that PARIS score predict outcomes...predict mortality...etc.". You need to put more thought into how your score can be used in the clinical setting (for example, can be used preoperatively, postop to allow for shared decision making and prevent HF hospitalization, etc.).</p>
<p>Author’s Reply</p>
<p>According to your comment, we have added the following sentences, which include more insight how the PARIS score can be used in the clinical setting (page 36, lines 383–390).</p>
<p>“Heart failure remains a major cause of mortality, morbidity, hospitalization, and poor quality of life in patients with coronary artery disease [25], thus identifying patients at risk of heart failure is important to improve their prognosis after PCIs. The PARIS thrombotic risk score can be used to allow for shared decision making and prevent hospitalization due to heart failure pre- and post-operatively. We believe that the results of the current study will help clinicians to identify high-risk patients and to plan early examinations and interventions.” (page 36, lines 383–390)</p>
<p>Regarding avoiding redundancy, please see our next reply.</p>
<p>Reviewer’s comment</p>
<p>3- Need to have stronger arguments and better flow of paragraphs. Each paragraph needs to be linked to the one before, start and end with a compelling statement about a certain finding, and end with a concluding statement about the following paragraph or future applications/outlook of your findings.</p>
<p>Author’s Reply</p>
<p>We have reconsidered the flow of paragraphs and reconstructed the discussion. At first, we modified “However, these risk scores were estimated for predicting short to mid-term prognosis, thus the long-term follow-up after PCI were poorly documented[23]. Therefore, the present study has the advantages of enrolling all patients who underwent PCI and may aid in predicting long-term prognosis after PCI.” (page 37, lines 395–399 in the revised manuscript with track changes) to “However, there have been few risk scores that include patients with not only ACS, but also chronic coronary syndrome, and can be used to predict long term mortalities. The ability of PARIS thrombotic risk score to predict the 6-month mortality of patients with ACS was comparable to that of the GRACE score; hence, we examined the long-term prognostic value of PARIS thrombotic risk score for both ACS and chronic coronary syndrome” (page 35, lines 368–373). </p>
<p>Moreover, the following sentences have been removed to avoid redundancy and be linked to the one before, start and end with a compelling statement about a certain finding, and end with a concluding statement about the following paragraph or future applications/outlook of our findings.</p>
<p>“The results of this study … improve the prognosis after PCI.” (page 38, line 405–page 39, line 432 in the revised manuscript with track changes)</p>
<p>“Findings in this study indicate that the PARIS thrombotic risk score may be used clinically beyond its intended use.” (page 40, line 474–page 41, line 475 in the revised manuscript with track changes)</p>
<p>Moreover, we have added the sentences below to achieve the same purpose.</p>
<p>“Heart failure remains a major cause of mortality, morbidity, hospitalization, and poor quality of life in patients with coronary artery disease [25]; thus, identifying patients at risk of heart failure is important to improve their prognosis after PCIs. The PARIS thrombotic risk score can be used to allow for shared decision making and prevent hospitalization due to heart failure pre- and postoperatively. We believe that the results of the current study will help clinicians to identify high-risk patients and to plan early examinations and interventions.” (page 36, lines 383–390)</p>
<p>The text below has been repositioned on page 37, lines 411–416 to improve the flow of paragraphs.</p>
<p>“The reason why the Kaplan-Meier curves for cardiac mortality and hospitalization due to heart failure partially converge and the high-risk group diverged from those in the other two groups at around 800 days is unclear. One possible reason is that the 64 cardiac deaths included 48 deaths from heart failure; therefore, the majority of cardiac deaths were due to heart failure. The worsening of heart failure with age may be one of the reasons for these results.” (page 37, lines 411–416)</p>
<p>Accordingly, the following references have been removed.</p>
<p>[23] Tang EW, Wong CK, Herbison P. Global Registry of Acute Coronary Events (GRACE) hospital discharge risk score accurately predicts long-term mortality post acute coronary syndrome. Am Heart J. 2007;153:29-35.</p>
<p>[24] Valgimigli M, Bueno H, Byrne RA, Collet JP, Costa F, Jeppsson A, et al. 2017 ESC focused update on dual antiplatelet therapy in coronary artery disease developed in collaboration with EACTS: The Task Force for dual antiplatelet therapy in coronary artery disease of the European Society of Cardiology (ESC) and of the European Association for Cardio-Thoracic Surgery (EACTS). Eur Heart J. 2018;39:213-60.</p>
<p>[25] Tanaka S, Sakata R, Marui A, Furukawa Y, Kita T, Kimura T. Predicting long-term mortality after first coronary revascularization: – the Kyoto model –. Circ J. 2012;76:328-34.</p>
<p>[26] Nammas W, Kiviniemi T, Schlitt A, Rubboli A, Valencia J, Lip GYH, et al. Value of DAPT score to predict adverse outcome in patients with atrial fibrillation undergoing percutaneous coronary intervention: A post-hoc analysis from the AFCAS registry. Int J Cardiol. 2018;253:35-9.</p>
<p>We have asked the native English speaker to proofread and have also been modified to make the manuscript easier to understand and to correct any previous grammatical errors as described in “the revised manuscript with track changes”.</p>
<p>In summary: </p>
<p>- For each paragraph, identify a study implication about why our study is novel, what it adds to the literature, what it suggests PARIS score. Always start with a statement about that implication</p>
<p>- Expand on that implication (ie its application) with evidence for or against it, if it exists</p>
<p>- Close with strong statement about what that implication means in the grand scale of things</p>
<p>Author’s Reply</p>
<p>Thank you for putting together your comments. Please see our responses to your comments. Details are given above.</p>
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<name name-style="western">
<surname>Lazzeri</surname>
<given-names>Chiara</given-names>
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<role>Academic Editor</role>
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<copyright-year>2022</copyright-year>
<copyright-holder>Chiara Lazzeri</copyright-holder>
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<license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">Creative Commons Attribution License</ext-link>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
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<p>
<named-content content-type="letter-date">11 Jul 2022</named-content>
</p>
<p><!-- <div> -->PONE-D-21-38539R2<!-- </div> --><!-- <div> -->Clinical usefulness of the pattern of non-adherence to anti-platelet regimen in stented patients (PARIS) thrombotic risk score to predict long-term all-cause mortality and heart failure hospitalization after percutaneous coronary intervention.<!-- </div> --><!-- <div> -->PLOS ONE</p>
<p>Dear Dr. Akama,</p>
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<p>PLOS ONE</p>
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<p>Reviewers' comments:</p>
<p>Reviewer's Responses to Questions</p>
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<p>Reviewer #2: All comments have been addressed</p>
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<p>**********</p>
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<p>**********</p>
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<p>Reviewer #2: Thanks for your attempt at fixing the grammar and Discussion section with the help of native English speaker. Unfortunately, I still don't think it is a good discussion that conveys the importance of your findings. I think you need to spend more time showing the feasibility of using your score as it only includes clinical characteristics and remove all the unnecessary details of what the GRACE, TIMI and CADILLAC scores contain (basically remove the second paragraph).</p>
<p>You also need to remove strong conclusions such as this :"The PARIS thrombotic risk score can be used to allow for shared decision making and prevent hospitalization due to heart failure pre- and postoperatively. We believe that the results of the current study will help clinicians to identify high-risk patients and to plan early examinations and interventions." &amp; "Therefore, the present study provides a new insight into the clinical</p>
<p>403 usefulness of the PARIS thrombotic risk score" You need to tone down these concluding statements.</p>
<p>You need to spend most of the discussion highlighting the importance and feasibility of your score like you did in the third paragraph and end of second paragraph. The connection and flow of ideas between paragraphs need to improved as the last 3 paragraphs tackle completely unrelated ideas. I suggest you show what the score predict (mortality, HF, etc) and why is that important as other scores don't predict all of these, then move to discuss how feasible it is to use the score, and then write on the limitations. Remove paragraph with lines 404-410 as it doesn't add much to the discussion. Keep it simple and straightforward.</p>
<p>Reviewer #3: Authors tried to address all the previously raised points.</p>
<p>This Reviewer would like to perform the following further comments and criticisms:</p>
<p>1. Page 4. Study protocol. Overall, 1061 PCI patients were enrolled during a period longer than 8 years. The only exclusion criterium reported in the manuscript was death during hospitalization. On average, about 130 PCI patients per year were enrolled. This mean that the enrolling PCI center was a very low volume hospital (not aligned to the current international standards) and/or in-hospital mortality was very high and/or other exclusion criteria were adopted but not reported. Please review this major issue.</p>
<p>2. Page 5. Study protocol. How was considered deaths from unknow cause? How many deaths from unknown cause were reported?</p>
<p>3. Page 6. Co-morbidities. Dyslipidemia definition is not in line with current guidelines and therapeutic cut-offs. Please review.</p>
<p>4. Table 1. The use of coronary imaging devices was extremely high (97.2%). Was the study database based on a registry dedicated intracoronary imaging modalities during PCI?</p>
<p>5. Tables. The number of Tables and Figures is an issue, and it should be reduced.</p>
<p>6. Page 36 and 37. Discussion. Please better explain how the PARIS “thrombotic” risk score can predict both the deaths and the hospitalizations for heart failure, the later not always related to a thrombotic event (i.e., but to poor drug adherence). In addition, absence of data regarding long-term pharmacological and intervention treatments should be better discussed in the study limitation section.</p>
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<sub-article article-type="author-comment" id="pone.0274287.r006">
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<article-title>Author response to Decision Letter 2</article-title>
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<named-content content-type="author-response-date">21 Aug 2022</named-content>
</p>
<p>Responses to Reviewer #2 </p>
<p>We appreciate your detailed review of our manuscript (PONE-D-21-38539). We have revised our manuscript according to your comments.</p>
<p>Reviewer’s comment 1</p>
<p>Thanks for your attempt at fixing the grammar and Discussion section with the help of native English speaker. Unfortunately, I still don't think it is a good discussion that conveys the importance of your findings. I think you need to spend more time showing the feasibility of using your score as it only includes clinical characteristics and remove all the unnecessary details of what the GRACE, TIMI and CADILLAC scores contain (basically remove the second paragraph). You also need to remove strong conclusions such as this: "The PARIS thrombotic risk score can be used to allow for shared decision making and prevent hospitalization due to heart failure pre- and postoperatively. We believe that the results of the current study will help clinicians to identify high-risk patients and to plan early examinations and interventions." &amp; "Therefore, the present study provides a new insight into the clinical usefulness of the PARIS thrombotic risk score" You need to tone down these concluding statements. </p>
<p>Author’s Reply 1</p>
<p>Thank you for your helpful comment. In response to your indication, we have removed the second paragraph of the Discussion section which described details of GRACE, TIMI and CADILLAC scores. Below is the second paragraph that has been removed. </p>
<p>“The GRACE score, which is used for overall risk assessment in patients with ACS, including ST elevation myocardial infarction (STEMI) and non-ST elevation ACS (NSTE-ACS), was designed to calculate the probability of death or myocardial infarction at admission and at six months after undergoing PCI by weighting eight risk factors: age, heart rate, systolic blood pressure, initial serum creatine, Killip class, hospitalization due to cardiac arrest, positive cardiac biomarker, and ST-segment deviation [1-3, 21]. The TIMI risk score, which is often used for risk assessment in patients with NSTE-ACS, is calculated using seven factors: age (≥ 65 years); at least three coronary risk factors (family history, hypertension, dyslipidemia, diabetes mellitus, and smoking); known significant coronary stenosis (≥ 50%); ST changes ≥ 0.5 mm on electrocardiogram; at least two episodes of angina within the previous 24 hours, aspirin use in the past 7 days; and increased cardiac markers. Most of these factors can be assessed immediately after admission. As the score increases, the risk of major cardiovascular complications in the following 2 weeks increases synergistically [4, 21]. The CADILLAC score, which is often used for risk assessment in patients with STEMI, evaluates several different prognostic variables, including LVEF, creatinine clearance, Killip class, final TIMI flow, age, anemia and presence of three-vessel disease. Utilizing the CADILLAC risk score, the patients were stratified into low (CADILLAC score 0–2), intermediate (score 3–5), and high (score ≥ 6) risk groups. The CADILLAC score can be used to accurately predict 30-day and 1-year mortality after primary PCI [5].” </p>
<p>Also, in response to your comment that the tone of the results is too strong, we have revised the sentences in the Discussion section (page 35, lines 366–371 and page 36, lines 383–384), toning them down. The following sentences are the revised sentences.</p>
<p>“Present study has shown the possibility that physicians are able to apply the PARIS thrombotic score not only to estimate the risk of coronary thrombotic events, but also to assess the risk of death and worsening heart failure for patients after PCIs. The PARIS thrombotic risk score may be able to serve as a clinical tool for shared decision making to prevent thrombotic event, hospitalization due to heart failure and death in the clinical practice post PCI.” (page 35, lines 366–371)</p>
<p>“Therefore, the present study suggests that it may provide a new insight into the clinical usefulness of the PARIS thrombotic risk score.” (page 36, lines 383–384)</p>
<p>Reviewer’s comment 2</p>
<p>You need to spend most of the discussion highlighting the importance and feasibility of your score like you did in the third paragraph and end of second paragraph. The connection and flow of ideas between paragraphs need to improve as the last 3 paragraphs tackle completely unrelated ideas. I suggest you show what the score predict (mortality, HF, etc) and why is that important as other scores don't predict all of these, then move to discuss how feasible it is to use the score, and then write on the limitations. Remove paragraph with lines 404-410 as it doesn't add much to the discussion. Keep it simple and straightforward.</p>
<p>Author’s Reply 2</p>
<p>Thank you for your helpful comments and suggestions. In line with your suggestion, we highlighted that the PARIS thrombotic score in the present analysis included not only ACS patients but also patients with chronic coronary syndrome, and could predict the outcomes of death and heart failure hospitalization, which other risk scores do not. We have revised the sentences as below (page 34, line 350 – page 35, line 358).</p>
<p>“The ability of PARIS thrombotic risk score to predict the 6-month mortality of patients with ACS was comparable to that of the GRACE score; hence, we examined the long-term prognostic value of PARIS thrombotic risk score for both ACS and chronic coronary syndrome. In addition, we have shown that the PARIS thrombotic risk score can predict events of heart failure hospitalization that the above scores do not. Heart failure remains a major cause of mortality, morbidity, hospitalization, and poor quality of life in patients with coronary artery disease [21]; thus, identifying patients at risk of heart failure is important to improve their prognosis after PCIs.” (page 34, line 350 – page 35, line 358)</p>
<p>As you pointed out, the last 3 paragraphs of the Discussion section are irrelevant. According to your suggestion, the following 2 paragraph has been removed to keep the discussion simple and straightforward. </p>
<p>“In patients with coronary artery disease after PCIs, various prognostic factors on mortality have been reported previously [27-29]. Co-morbidities such as diabetes mellitus [30], history of acute coronary syndrome, current smoking [31], CKD [32], and history of PCI or CABG [33, 34] have already reported to be risk factors for poor prognosis in patients with coronary artery disease. Since these factors are also components of the PARIS thrombotic risk score, it is possible that this score could be used to predict all-cause death or hospitalization due to heart failure.” </p>
<p>“The reason why the Kaplan-Meier curves for cardiac mortality and hospitalization due to heart failure partially converge and the high-risk group diverged from those in the other two groups at around 800 days is unclear. One possible reason is that the 64 cardiac deaths included 48 deaths from heart failure; therefore, the majority of cardiac deaths were due to heart failure. The worsening of heart failure with age may be one of the reasons for these results.” </p>
<p>We thank you again for your valuable comments on our manuscript.</p>
<p>Responses to Reviewer #3 </p>
<p>We appreciate your detailed review of our manuscript (PONE-D-21-38539). We have revised our manuscript according to your comments.</p>
<p>Reviewer’s comment 1</p>
<p>Page 4. Study protocol. Overall, 1061 PCI patients were enrolled during a period longer than 8 years. The only exclusion criterium reported in the manuscript was death during hospitalization. On average, about 130 PCI patients per year were enrolled. This mean that the enrolling PCI center was a very low volume hospital (not aligned to the current international standards) and/or in-hospital mortality was very high and/or other exclusion criteria were adopted but not reported. Please review this major issue.</p>
<p>Author’s Reply 1</p>
<p>Thank you for your helpful comment. The present study has enrolled only patients who have undergone their initial PCI at our hospital. We apologize that we missed to write down about this indication. While, our hospital performed about 230 cases of PCI annually between 2010 and 2018 including target lesion or target vessel revascularization and staged PCI after initial one. We think this meets the criteria for adequate institutional volume achieving good outcomes, which is defined as over 200 PCIs per year (J Am Coll Cardiol. 2013; 62: 357-96). We have revised the manuscript about inclusion criteria in the Method section (page 4, lines 79–82). The below is the revised sentences.</p>
<p>“This was an observational study, which enrolled a total of 1,061 consecutive patients who underwent their initial PCI due to stable angina pectoris or acute coronary syndrome (ACS) at Fukushima Medical University Hospital between January 2010 and May 2018.” (page 4, lines 79–82)</p>
<p>Reviewer’s comment 2</p>
<p>Page 5. Study protocol. How was considered deaths from unknow cause? How many deaths from unknown cause were reported?</p>
<p>Author’s Reply 2</p>
<p>Thank you for your helpful comment. Deaths from unknow cause were counted as all cause death. 5 deaths from unknown cause have been reported.</p>
<p>Reviewer’s comment 3</p>
<p>Page 6. Co-morbidities. Dyslipidemia definition is not in line with current guidelines and therapeutic cut-offs. Please review.</p>
<p>Author’s Reply 3</p>
<p>Thank you for your valuable comment. As you mentioned, the definition of dyslipidemia used in the present study is not in line with current guidelines, since we do not know the initial cholesterol levels of patients who were on statins at the time of index PCI. Hence, we inevitably defined dyslipidemia as the recent use of cholesterol-lowering drugs, a triglyceride value of ≥ 150 mg/dL, a low-density lipoprotein (LDL) cholesterol value of ≥ 140 mg/dL, and/or a high-density lipoprotein (HDL) cholesterol value of &lt; 40 mg/dL, as described in the Method section.</p>
<p>Reviewer’s comment 4</p>
<p>Table 1. The use of coronary imaging devices was extremely high (97.2%). Was the study database based on a registry dedicated intracoronary imaging modalities during PCI?</p>
<p>Author’s Reply 4</p>
<p>Thank you for your important comment. This study is not based on any registry dedicated intracoronary imaging modalities. In Japan, intracoronary imaging is accepted in insured medical treatment, so that it is quite usual to use intracoronary imaging devices during daily PCI procedures. Therefore, the use of coronary imaging devices was extremely high.</p>
<p>Reviewer’s comment 5</p>
<p>Tables. The number of Tables and Figures is an issue, and it should be reduced.</p>
<p>Author’s Reply 5</p>
<p>Thank you for your valuable suggestion. As you noted, the number of tables has increased from the first draft. However, due to the meaningful peer review so far, detailed analysis has been performed, and the number of figures and tables has increased. There is no mention of the number of figures and tables in the submission instructions, and we would like to keep the number of figures and tables as they are for better understanding.</p>
<p>Reviewer’s comment 6</p>
<p>Page 36 and 37. Discussion. Please better explain how the PARIS “thrombotic” risk score can predict both the deaths and the hospitalizations for heart failure, the later not always related to a thrombotic event (i.e., but to poor drug adherence). In addition, absence of data regarding long-term pharmacological and intervention treatments should be better discussed in the study limitation section.</p>
<p>Author’s Reply 6</p>
<p>Thank you for your important suggestion. The possible reason why the PARIS thrombotic risk score can also predict all-cause mortality and heart failure due to hospitalization is that major predictors used in the PARIS thrombotic risk score were associated with the risk factors for a poor prognosis of coronary artery disease. It has already been reported that history of acute coronary syndrome and chronic kidney disease is also a risk factor for hospitalization due to heart failure. These explanations were firstly described in the Discussion section, however, the Reviewer 2 recommended us that the above content should not be included in the manuscript because it complicates the content of the discussion section. </p>
<p>While, as you mentioned, the achievement rate of guideline directed medical therapy and the presence or absence of any interventional treatment to the coronary artery disease and the heart failure may affect thrombotic events, death and heart failure hospitalization. We have revised the manuscript and described about this point in the Limitation section (page 36, lines 387–391). Following are the added sentences.</p>
<p>“Second, the clinical practices regarding medical treatment and interventional treatment in the present study may have some difference in the setting of each period. Especially, the achievement rate of guideline directed medical therapy for coronary artery disease and the presence or absence of interventional treatment may affect the rate of thrombotic events, death and heart failure hospitalization after PCI.” (page 36, lines 387–391)</p>
<p>We thank you again for your valuable comments on our manuscript.</p>
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<named-content content-type="letter-date">25 Aug 2022</named-content>
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<p>Clinical usefulness of the pattern of non-adherence to anti-platelet regimen in stented patients (PARIS) thrombotic risk score to predict long-term all-cause mortality and heart failure hospitalization after percutaneous coronary intervention.</p>
<p>PONE-D-21-38539R3</p>
<p>Dear Dr. Akama,</p>
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<named-content content-type="letter-date">5 Sep 2022</named-content>
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<p>PONE-D-21-38539R3 </p>
<p>Clinical usefulness of the pattern of non-adherence to anti-platelet regimen in stented patients (PARIS) thrombotic risk score to predict long-term all-cause mortality and heart failure hospitalization after percutaneous coronary intervention. </p>
<p>Dear Dr. Akama:</p>
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<p>on behalf of</p>
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