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PloS one2015; 10(8); e0137013; doi: 10.1371/journal.pone.0137013

Speed and Cardiac Recovery Variables Predict the Probability of Elimination in Equine Endurance Events.

Abstract: Nearly 50% of the horses participating in endurance events are eliminated at a veterinary examination (a vet gate). Detecting unfit horses before a health problem occurs and treatment is required is a challenge for veterinarians but is essential for improving equine welfare. We hypothesized that it would be possible to detect unfit horses earlier in the event by measuring heart rate recovery variables. Hence, the objective of the present study was to compute logistic regressions of heart rate, cardiac recovery time and average speed data recorded at the previous vet gate (n-1) and thus predict the probability of elimination during successive phases (n and following) in endurance events. Speed and heart rate data were extracted from an electronic database of endurance events (80-160 km in length) organized in four countries. Overall, 39% of the horses that started an event were eliminated--mostly due to lameness (64%) or metabolic disorders (15%). For each vet gate, logistic regressions of explanatory variables (average speed, cardiac recovery time and heart rate measured at the previous vet gate) and categorical variables (age and/or event distance) were computed to estimate the probability of elimination. The predictive logistic regressions for vet gates 2 to 5 correctly classified between 62% and 86% of the eliminated horses. The robustness of these results was confirmed by high areas under the receiving operating characteristic curves (0.68-0.84). Overall, a horse has a 70% chance of being eliminated at the next gate if its cardiac recovery time is longer than 11 min at vet gate 1 or 2, or longer than 13 min at vet gates 3 or 4. Heart rate recovery and average speed variables measured at the previous vet gate(s) enabled us to predict elimination at the following vet gate. These variables should be checked at each veterinary examination, in order to detect unfit horses as early as possible. Our predictive method may help to improve equine welfare and ethical considerations in endurance events.
Publication Date: 2015-08-31 PubMed ID: 26322506PubMed Central: PMC4556447DOI: 10.1371/journal.pone.0137013Google Scholar: Lookup
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  • Journal Article
  • Research Support
  • Non-U.S. Gov't

Summary

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This research aimed to predict the probability of a horse being eliminated in endurance events based on heart rate recovery variables and speed. The results from examining these factors indicate that an unfit horse, that may suffer from issues such as lameness or metabolic disorders, could be detected earlier in competitions, potentially enhancing equine welfare and ethical considerations.

Study Methodology

  • The researchers utilized an electronic database of endurance events ranging from 80 to 160 km in length and organized in four different countries.
  • The heart rate, cardiac recovery time, and average speed data of each horse at the previous vet gate (n-1) was observed, with the aim to predict the probability of a horse being eliminated in subsequent phases of the event.
  • The researchers hypothesized that horses experiencing difficulties or symptoms of poor health would take longer to recover heart rates, hinting at potential physical unfitness.
  • For each vet gate, they performed logistic regressions of these explanatory variables, along with categorical variables like the age of the horse and the event distance, to calculate the likelihood of elimination in successive stages.

Study Findings

  • The study found that nearly 39% of the horses starting an event were eliminated, primarily due to lameness (64%) or metabolic disorders (15%).
  • The researchers discovered that heart rate recovery and average speed variables recorded at the previous vet gate facilitated the prediction of elimination at the next vet gate.
  • The logistic regressions for vet gates 2-5 correctly categorized between 62% and 86% of the eliminated horses.
  • The robustness of these results was confirmed by the high areas under the receiving operating characteristic curves (between 0.68 and 0.84).
  • One important finding was that a horse has a 70% chance of being disqualified at the next gate if its cardiac recovery time is longer than 11 min at vet gate 1 or 2, or more than 13 min at vet gates 3 or 4.

Conclusions and Recommendations

  • Utilizing predictive measures based on heart rate recovery time and average speed data effectively aids in the early detection of unfit horses, potentially preventing the unnecessary strain and health issues they may encounter in endurance events.
  • This means that monitoring these variables should be embedded in the evaluation process at each vet gate.
  • The predictive method developed in this study has the potential to greatly enhance the welfare of horses in endurance events and strengthen ethical considerations buoying the sport.

Cite This Article

APA
Younes M, Robert C, Cottin F, Barrey E. (2015). Speed and Cardiac Recovery Variables Predict the Probability of Elimination in Equine Endurance Events. PLoS One, 10(8), e0137013. https://doi.org/10.1371/journal.pone.0137013

Publication

ISSN: 1932-6203
NlmUniqueID: 101285081
Country: United States
Language: English
Volume: 10
Issue: 8
Pages: e0137013
PII: e0137013

Researcher Affiliations

Younes, Mohamed
  • UBIAE, Université d'Evry Val d'Essonne, Evry, France.
Robert, Céline
  • INRA, GABI, UMR1313, Jouy-en-Josas, France; Université Paris-Est, Ecole Nationale Vétérinaire d'Alfort, Maison Alfort, France.
Cottin, François
  • EA4532 CIAMS, Université Paris Sud, Orsay, France; Département STAPS, Université d'Evry Val d'Essonne, Evry, France.
Barrey, Eric
  • UBIAE, Université d'Evry Val d'Essonne, Evry, France; INRA, GABI, UMR1313, Jouy-en-Josas, France.

MeSH Terms

  • Animals
  • Gait / physiology
  • Heart / physiology
  • Heart Rate / physiology
  • Horses / physiology
  • Lameness, Animal / physiopathology
  • Logistic Models
  • Metabolic Diseases / physiopathology
  • Physical Conditioning, Animal / physiology
  • Physical Endurance / physiology
  • Probability
  • Veterinarians

Conflict of Interest Statement

The author's declare that the ACA provided a research grant of €2000 per year for research expenses as part of the 4-year GenEndurance project. This contribution was compliant with PLOS ONE’s policies on sharing data and materials. All data are available online and as supplementary data. Furthermore, the ACA did not contribute directly to the present retrospective, statistical study.

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Citations

This article has been cited 9 times.
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