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Updated: May 5, 2026

Modeling Ascending Vaginal Infection, Preterm Birth, and Neonatal Morbidity in Mice
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Rethinking navel size thresholds for omphalitis diagnosis in newborn dairy calves using machine learning.

A Rico1,2, A F A Pires1, N Silva-Del-Rio1,2

  • 1Department of Population Health and Reproduction, UC Davis School of Veterinary Medicine, Davis, CA 95616.

JDS Communications
|May 4, 2026
PubMed
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Umbilical stump diameter measurement is a reliable method for diagnosing omphalitis in newborn calves, though thresholds require cautious interpretation due to variable sensitivity and specificity.

Area of Science:

  • Veterinary Medicine
  • Neonatal Calf Health
  • Diagnostic Imaging

Background:

  • Omphalitis is an underreported neonatal calf disease lacking a gold standard diagnostic test.
  • Current diagnostic methods, often impractical on farms, rely on limited evidence for umbilical stump diameter thresholds.

Purpose of the Study:

  • To assess the reliability of umbilical stump diameter measurement.
  • To develop statistical models for diameter based on disease status in Holstein and Jersey heifers.
  • To propose thresholds for farm-level prevalence estimation and high-probability omphalitis identification.

Main Methods:

  • Evaluated intra- and interobserver agreement for umbilical stump diameter measurements.
  • Employed unsupervised machine learning (Gaussian mixture models) to infer healthy and diseased subpopulations.

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  • Utilized Receiver Operating Characteristic (ROC) analysis to estimate diagnostic performance.

    • Main Results:

    • Measurement reliability was good for intraobserver (CV=5.94%) and fair-to-good for interobserver agreement (ICC=0.76).
    • Breed-specific models showed diagnostic utility (HO AUC=0.56, JE AUC=0.65).
    • Thresholds optimizing sensitivity/specificity had high specificity but low sensitivity; higher thresholds prioritized specificity.

    Conclusions:

    • Umbilical stump diameter measurement is reliable but requires cautious interpretation due to modest diagnostic accuracy.
    • Proposed thresholds offer options for farm-level prevalence or high-probability case identification.
    • Further validation and association with clinical findings are essential for clinical application.