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The authors have declared that no competing interests exist.

Conceived and designed the experiments: KAD RET. Performed the experiments: KAD RET. Analyzed the data: KAD RET. Contributed reagents/materials/analysis tools: KAD RET SDH MLF PRM. Wrote the paper: KAD RET.

Medical management of critically ill equine neonates (foals) can be expensive and labor intensive. Predicting the odds of foal survival using clinical information could facilitate the decision-making process for owners and clinicians. Numerous prognostic indicators and mathematical models to predict outcome in foals have been published; however, a validated scoring method to predict survival in sick foals has not been reported. The goal of this study was to develop and validate a scoring system that can be used by clinicians to predict likelihood of survival of equine neonates based on clinical data obtained on admission.

Data from 339 hospitalized foals of less than four days of age admitted to three equine hospitals were included to develop the model. Thirty seven variables including historical information, physical examination and laboratory findings were analyzed by generalized boosted regression modeling (GBM) to determine which ones would be included in the survival score. Of these, six variables were retained in the final model. The weight for each variable was calculated using a generalized linear model and the probability of survival for each total score was determined. The highest (7) and the lowest (0) scores represented 97% and 3% probability of survival, respectively. Accuracy of this survival score was validated in a prospective study on data from 283 hospitalized foals from the same three hospitals. Sensitivity, specificity, positive and negative predictive values for the survival score in the prospective population were 96%, 71%, 91%, and 85%, respectively.

The survival score developed in our study was validated in a large number of foals with a wide range of diseases and can be easily implemented using data available in most equine hospitals. GBM was a useful tool to develop the survival score. Further evaluations of this scoring system in field conditions are needed.

Equine neonates are highly susceptible to life-threatening conditions such as sepsis, hypoxic-ischemic encephalopathy, prematurity, and postpartum trauma that result in high mortality rates (20-60%)

Multiple statistical methods can be used to build mathematical models to predict survival. These methods have advantages and disadvantages, and in veterinary medicine, the fact that these complex models are impractical and not prospectively validated in heterogeneous groups of foals reduces their validity and clinical use.

Boosting is a statistical tool that combines the prediction power of several models to improve the predictive performance of a final model

Due to the potential clinical and financial benefits of having a survival scoring system that could be implemented in hospitalized foals within hours of admission, the goals of this study were 1) to develop a foal survival score (FSS) by means of GBM using readily available historical, clinical, and laboratory information from foals with a wide range of clinical conditions (retrospective study), and 2) to validate this scoring system in a large population of hospitalized foals (prospective study).

Two populations of hospitalized foals (n = 624) of less than four days of age, from three equine veterinary hospitals (The Ohio State University, Columbus, Ohio; Hagyard Equine Medical Institute, Lexington, Kentucky; Rood and Riddle Equine Hospital, Lexington, Kentucky) were included in the study. A retrospective population of foals (n = 339) from three foaling seasons was used to select variables and develop the FSS and a prospective population of foals (n = 285) from the three following foaling seasons was used to validate the performance of the FSS. This study was approved by the OSU Institutional Animal Care and Use Committee and adhered to the principles of humane treatment of animals in veterinary clinical research, as stated by the American College of Veterinary Internal Medicine and National Institutes of Health guidelines.

Prognostic variables and weights (scores) for each variable to be included in the FSS were identified by GBM and generalized linear models (GLM) in the retrospective study. Foals of less than four days of age of any breed or sex admitted to the equine hospitals were included. Foals were categorized into three groups: septic, sick non-septic (SNS) and healthy. Foals in the septic group had a sepsis score (SS) of ≥12, a positive blood culture, or both

Variables (n = 37) | Survivors (n = 263) | Non-survivors (n = 76) | P |

PCV (%) | 39 (12–56) | 40 (21–59) | 0.39 |

WBC × (10^{3}/µL) |
8.6 (0.6–32.5) | 4.3 (0.1–23) | 0.01 |

Segmented Neutrophils × (10^{3}/µL) |
6 (1.9–26.5) | 3.74 (0.014–30.1) | 0.04 |

Band Neutrophils × (10^{3}/µL) |
0.1 (0.01–4.8) | 0.28 (0.01–6.5) | 0.12 |

Lymphocytes × (10^{3}/µL) |
1.2 (0.01–17) | 1.0 (0.01–22) | 0.21 |

Monocytes × (10^{3}/µL) |
0 (0–9.1) | 0.1 (0–6.7) | 0.23 |

Platelets × (10^{3}/µL) |
270 (59–552) | 265 (101–618) | 0.97 |

Fibrinogen (mg/dL) | 263 (60–800) | 261 (100–800) | 0.72 |

Total protein (g/dL) | 4.8 (2.8–7.7) | 4.5 (3.1–6.4) | 0.01 |

Albumin (g/dL) | 2.9 (1.9–3.8) | 3.1 (1.7–3.9) | 0.01 |

L-lactate (mmol/L) | 4.7 (0.8–17.9) | 7 (1.17–18.9) | 0.01 |

IgG (mg/dL) | 844 (100–4000) | 429 (100–1399) | 0.01 |

Sodium (mEq/L) | 138 (107–149) | 137 (128–155) | 0.5 |

Potassium (mEq/L) | 3.8 (2.1–6.9) | 4.1 (2–7) | 0.04 |

Chloride (mEq/L) | 99 (76–109) | 95 (78–108) | 0.05 |

Anion gap (mEq/L) | 13 (4–40) | 16 (7–44) | 0.01 |

Glucose (mg/dL) | 125 (10–336) | 84 (5–224) | 0.01 |

BUN (mg/dL) | 20 (4–40) | 24.4 (12–67) | 0.01 |

Creatinine (mg/dL) | 2.3 (0.5–22.3) | 4.3 (1–17.6) | 0.01 |

Total calcium (mg/dL) | 11.4 (3.4–18.5) | 11.6 (4.73–17.4) | 0.34 |

Phosphorus (mg/dL) | 5.7 (3–14.8) | 6.5 (2.5–22.8) | 0.01 |

Total bilirubin (mg/dL) | 3.4 (0.8–13.3) | 4.2 (1.1–14.6) | 0.01 |

Temperature (°C) | 37.7 (32.3–41.4) | 37.1 (32.4–40) | 0.01 |

Heart Rate (bpm) | 100 (30–170) | 100 (40–170) | 0.21 |

Respiratory rate (bpm) | 34 (12–124) | 36 (18–90) | 0.26 |

Sepsis score | 7 (0–21) | 13 (5–22) | 0.01 |

Abnormal mucous membrane color | 76y, 187n | 44y, 32n | 0.01 |

Prolonged CRT | 83y, 180n | 30y, 46n | 0.19 |

Cold extremities | 14y, 249n | 36y, 40n | 0.01 |

Hypoxic ischemic encephalopathy | 36y, 227n | 16y, 60n | 0.11 |

Abnormal mentation | 85y, 178n | 41y, 35n | 0.01 |

Weak peripheral pulse | 6y, 257n | 4y, 72n | 0.17 |

≥2 infection/inflammation sites | 28y, 235n | 20y, 56n | 0.01 |

Diarrhea | 32y, 231n | 8y, 68n | 0.15 |

Prematurity/prolonged gestation | 18y, 245n | 20y, 56n | 0.01 |

Abnormal foaling | 72y, 191n | 33y, 43n | 0.01 |

Age (h) | 24 (1–96) | 11 (1–96) | 0.04 |

Survival was defined as discharged alive from the hospital. Foals that died or were euthanized due to a grave medical prognosis were defined as non-survivors and included in the study. Foals euthanized for other reasons such as financial constraints were not included in the study.

The same inclusion criteria used in the retrospective study were used for the prospective study. A probability of survival>50% was considered predictive of survival (positive test) and <50% of non-survival (negative test). Contingency tables were used to calculate sensitivity, specificity, positive and negative predictive values of the FSS for each season individually and for the entire population of foals included in the prospective study. Sensitivity was the number of foals accurately predicted by the FSS to survive divided by the total number of foals that survived (true-positive results). Specificity was the number of foals predicted by the FSS to die divided by the total number of foals that died (true-negative results). Positive predictive value was calculated as the number of foals that were accurately predicted to survive divided by the total number of foals that the FSS predicted to survive (true-positive plus false-positive). Negative predictive value was the number of foals accurately predicted to die divided by the total number of foals that the FSS predicted to die (true-negative plus false-negative results).

Data sets were tested for normality by the Shapiro-Wilk statistic and most variables were found to be not normally distributed. Medians and ranges were calculated for continuous variables. The Mann-Whitney-U test was used to compare survivor and non-survivor groups in the retrospective study. Relationships between survival and categorical variables were analyzed using contingency tables and chi-square analysis in the retrospective study. The Kruskal-Wallis statistics was used to compare SS and FSS between foaling seasons in the prospective study. Significance was set at P<0.05.

A GBM was used to determine which of the 37 variables analyzed were the best predictors of survival and to establish the cutoff values for each predictor.

GBM is a method for fitting regression models to data where certain model variables can be modify to find the best-fitting model

Based on these cutoff values, variables retained in the final model were considered to be factors in the FSS: a factor was assigned a final value of 1 in the FSS if the value of the original variable was above the established cutoff value, and assigned a final value of 0 in the FSS if the value of the variable was below the cutoff value (for example: a glucose concentration of ≥80 mg/dL was assigned a value of 1 and <80 mg/dL a value of 0).

Scores (weights) for each retained variable were defined based on a GLM with a logit link run that used these factors to determine the influence of each individual variable on survival. Although the regression coefficients in the GLM were not equal we decided to use equal factors (0, 1 or 2) for the FSS to make it simple and easy to calculate.

Probability of survival was calculated for each possible total FSS. The Pearson chi-squared Goodness-of-Fit test indicated that the GLM fitted the data set well (P = 0.99). Data were analyzed with SPSS Statistics (IBM Corporation, New York, USA) and R project (

Survival score (FSS) was categorized by two cutoff values divided into tertiles based on the distribution within the prospective population. This was then analyzed using logistic regression for binomial distribution. Crude odds ratios and 95% confidence intervals were calculated for each category.

In order to determine the area under the curve (AUC) and a cutoff value above which survival could be most reliably predicted by the FSS, receiver operating characteristic (ROC) curve, sensitivity, and specificity were calculated.

A total of 339 (283 hospitalized; 56 healthy) and 285 (239 hospitalized; 46 healthy) neonatal foals were included in the retrospective and prospective studies, respectively. The median age of all hospitalized foals on admission was 12 h in the retrospective and 14 h in the prospective studies (P = 0.21). In the retrospective study, 40% (114/283) of hospitalized foals were septic and 60% (169/283) were SNS, whereas in the prospective study 38% (90/239) were septic and 62% (149/239) were SNS (P = 0.58). In the retrospective study, 59% (167/283) of hospitalized foals were colts and 41% (116/283) were fillies, while in the prospective study 52% (124/239) were colts and 48% (115/239) were fillies (P = 0.11). Breeds of hospitalized foals from both studies predominantly consisted of Thoroughbreds, Standardbreds, Quarter Horse, Warmbloods, and Arabian horses. All healthy foals from both studies were Thoroughbreds.

In both studies, foals were presented for a variety of medical conditions including sepsis/septicemia, septic arthritis, omphalophlebitis, umbilical/inguinal hernia, peritonitis, meningoencephalitis, pneumonia, enteritis, enterocolitis, colic, meconium impaction, hypoxic ischemic encephalopathy, failure of transfer of passive immunity, flexural and angular limb deformities, ruptured bladder, patent urachus, neonatal isoerythrolysis, and trauma.

Positive blood cultures were obtained in 33% (38/114) of septic foals in the retrospective study and 31% (28/90) in the prospective study (P = 0.76). The median SS was eight for the retrospective and nine for the prospective study (P = 0.21). The survival rate in neonatal foals was 78% (264/339) for the retrospective and 76% (216/285) for the prospective study (P = 0.56).

Final regression coefficients are presented in

Variables | Estimate | Standard Error | Z value | P value |

Intercept | −0.3072 | 0.55 | −0.56 | 0.57 |

Cold extremities | −2.0115 | 0.42 | −4.77 | 0.0001 |

Prematurity (<320 days) | −0.8166 | 0.46 | −1.75 | 0.07 |

≥2 infection/inflammation sites | −0.7685 | 0.42 | −1.8 | 0.07 |

IgG (mg/dL) | 0.9877 | 0.35 | 2.8 | 0.005 |

Glucose (mg/dL) | 1.1331 | 0.4 | 2.77 | 0.005 |

WBC × (10^{3}/µL) |
0.9043 | 0.4 | 2.22 | 0.02 |

Variables | Score | ||

Cold extremities | no | yes | |

2 | 0 | ||

Prematurity (<320 days) | no | yes | |

1 | 0 | ||

≥2 infection/inflammation sites | no | yes | |

1 | 0 | ||

IgG (mg/dL) | <400 | ≥400 | |

0 | 1 | ||

Glucose (mg/dL) | <80 | ≥80 | |

0 | 1 | ||

WBC × (10^{3}/µL) |
≤4 | >4 | |

0 | 1 | ||

Total Foal Survival Score | Probability of Survival |

0 | 3% |

1 | 8% |

2 | 18% |

3 | 38% |

4 | 62% |

5 | 82% |

6 | 92% |

7 | 97% |

In the prospective study, the ability of the survival score to predict survival was determined by the association of the final and predicted outcome using a contingency table. Foals from the prospective study were classified as predicted to survive (a total survival score ≥4) or to die (survival score <4). This classification was compared to the actual outcome, of which the sensitivity, specificity, positive and negative predictive values of the FSS were 96%, 71%, 91% and 86%, respectively. There were no differences in the median SS and FSS, as well as in the survival rate between each season within the prospective study.

Seasons | Sensitivity | Specificity | PPV | NPV | Survival Rate | SS* | FSS* |

2011 (n = 83) | 95% | 70% | 90% | 85% | 75% | 10 (2–18) | 5 (1–7) |

2012 (n = 99) | 96% | 80% | 93% | 73% | 73% | 9 (1–26) | 6 (0–7) |

2013 (n = 103) | 94% | 72% | 93% | 75% | 79% | 9 (0–21) | 6 (1–7) |

In the hospitalized population, foals with a FSS in the range of 4–5 (95% CI: 7.04–83.32) and 6–7 (95% CI: 36.24–228.86) were 24.2 and 91 times more likely to survive than foals with a FSS of <4, respectively (P<0.001) (

Variables | Range | Crude Odds Ratio for Survival | 95% Confidence Interval |

FSS | 0–3 | referent | |

4–5 | 24.22 |
7.04–83.32 | |

6–7 | 91.07 |
36.24–228.86 |

The AUC determined by ROC was 0.91 (

A cutoff value of 4 for FSS maximized sensitivity (96%) and specificity (71%) to predict survival in hospitalized foals. AUC, area under the curve; FSS, foal survival score.

Caring for critically ill foals is often demanding and expensive, and having access to a scoring system to predict survival shortly after admission can be a valuable tool to clients and veterinarians. In our study, we used readily available clinical, historical, and laboratory information from a large and heterogeneous population of foals admitted to three equine hospitals to develop such a scoring system. Subsequently, the FSS was validated in a prospective study that included foals from three foaling seasons with similar results among seasons. A high FSS was associated with increased odds for survival.

A number of regression models to predict mortality in hospitalized neonatal foals have been developed; however, variables retained in the final model differ among studies, reflecting different study populations and experimental designs

Clinical signs of poor peripheral perfusion such as prolonged CRT, cold extremities, and injected mucous membranes are frequent and easy to assess variables in critically ill foals

In addition to cold extremities, hyperlactatemia can be used as a reliable marker of hypoperfusion in foals, horses and people

Both hypothermia and hyperthermia are frequently observed in critically ill neonatal foals and people

Based on previous studies, historical data on maternal diseases and abnormal parturition (dystocia, caesarean section, assisted delivery) were considered clinically important and possible confounders

To our knowledge this is the first study of this scale in which a large number of sick foals is used to develop a foal survival score that is subsequently validated in a prospective population of foals with a wide range of neonatal diseases, over multiple years. The ideal scoring system should be well calibrated, based on routinely recordable variables, applicable to all patient populations, and have a high level of discrimination

This study has some limitations that should be acknowledged. While the median age was different between surviving and non-surviving foals and ideally both groups should have been of similar age, age was not retained in the final model, suggesting low predictive power for the outcome. Another important point is that this survival score was developed for foals admitted to three referral centers and its effectiveness in field conditions and other institutions (in different geographic locations) needs to be evaluated. In addition, the FSS was based on data from foals of less than four days of age and its usefulness in older foals needs to be determined.

In conclusion, the survival scoring system developed here can be used as a simple and supplementary tool in helping to determine the likely prognosis for survival of hospitalized neonatal foals on or shortly after hospital admission. Variables included in this survival score can be readily obtained on admission, making it practical in the clinical setting. This score was more effective at predicting survival (positive predictive value = 91%) than at predicting death (negative predictive value = 86%) in foals admitted to the three equine referral hospitals in this study. The survival score developed in this study should not replace clinical judgment and nor should it be used in isolation to make decisions about euthanasia. This information can be used by clinicians and owners to make informed, evidence-based decisions about treatment options for individual neonatal foals based on likely survival.

The authors thank Dr. Kate Onasch and Dr. Eason Hildreth for their assistance with laboratory techniques. We are grateful to Dr. Rhonda Rathgeber at Hagyard Equine Medical Institute for collecting samples from healthy foals. Special thanks to clinicians and technicians from Rood and Riddle Equine Hospital, Hagyard Equine Medical Institute and The Ohio State University Galbreath Equine Center for samples collection. The authors also thank Mary Kinee at Rood and Riddle Equine Hospital and Justine Elam at Hagyard Equine Medical Institute for samples processing, and Di Cao and Elizabeth Petraglia from the Department of Statistics of The Ohio State University for their assistance with data analysis.