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Updated: May 5, 2026

Instrumentation of Near-term Fetal Sheep for Multivariate Chronic Non-anesthetized Recordings
Published on: October 25, 2015
Retrospective cohort study on diseases and risk factors associated with death in hospitalized neonatal foals
Donatienne L Castelain1, Alexander Dufourni1, Mathilde L Pas1
1Department of Internal Medicine, Reproduction and Population Medicine, Ghent University, Salisburylaan 133, Merelbeke 9820, Belgium.
Background:
The care of sick neonatal foals is labor-intensive and costly. Prediction of risk of death upon admission is often difficult but might support decision-making.
Objectives:
To determine diseases and risk factors associated with death in neonatal hospitalized foals.
Animals:
Two hundred twenty-two hospitalized foals, ≤7 days old.
Methods:
Retrospective cohort study. Clinical and laboratory variables were evaluated for their association with death by means of Cox survival analysis and by classification and regression tree (CART) analysis.
Results:
Most prevalent diseases were sepsis (43.9%), enteritis (14.0%), and omphalitis (9.0%). Case fatality rate was 33.3%. Neonatal sepsis significantly increased the risk of death (hazard ratio [HR] = 1.9; 95% confidence interval [CI] = 1.2-3.0; P = .009). Multivariable Cox regression in foals ≤7 days old revealed comatose mental state (HR = 2.9; 95% CI = 1.1-8.1; P = .04), L-lactatemia (≥373.8 mg/L [4.2 mmol/L]; HR = 4.4; 95% CI = 1.7-11.7; P = .003) and increased serum amyloid A (SAA; ≥2054 μg/mL; HR = 3.9; 95% CI = 1.2-12.7; P = .02) as risk factors for death, with a sensitivity and specificity of 7.5% and 95.7%, respectively. The CART analysis highlighted L-lactatemia, comatose mental state, and hypercapnia as risk factors for death, with a sensitivity of 38.1% and specificity of 86.1% after validation.
Conclusions And Clinical Importance:
In this study sample, sepsis was associated with the highest risk of death. Identified risk factors such as SAA, L-lactate, and comatose mental state might guide veterinarians and owners in better decision-making for economic or welfare reasons. Frequently measured laboratory variables, such as blood glucose concentration and Immunoglobulin G, were not sensitive and specific enough to provide reliable decision support for survival estimation.
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