Exercising electrocardiograms from Thoroughbred racehorses with exercise associated sudden death
Year: 2026
Type: article
Abstract: BACKGROUND: Exercise associated sudden death (EASD), defined as a fatal collapse in a closely monitored and previously presumed clinically healthy horse that occurs during exercise or within approximately 1 h after exercise, is disproportionately more common in equine than in human athletes. OBJECTIVES: To describe ECGs from EASD cases in Thoroughbred racehorses. STUDY DESIGN: Retrospective case series. METHODS: An international call for potential cases was made through direct contact with relevant racing authorities requesting that trainers of horses which had experienced EASD consent to researchers gaining access to any available ECG data recorded with a wearable device prior to or during EASD events. ECGs were evaluated by a single observer and the findings were described and summarised. RESULTS: Eleven horses, with a total of 24 readable ECGs (median [range] 2 [1-4]/horse) were identified. Four horses were wearing an ECG at the time of death; 3 had atrial fibrillation (AF) throughout the recording that led to malignant arrhythmias and death, and the 4th had couplets and triplets with R on T, ventricular fibrillation, and death in the late recovery period. The other seven horses had ECGs recorded 4-462 days before death. One of these horses had AF throughout the recording and died 9 days later. Late recovery arrhythmias were identified in 5 recordings from 3 additional horses. MAIN LIMITATIONS: Small number of horses with EASD were sampled, and use of a single lead ECG limited information on arrhythmia origin. CONCLUSIONS: ECG screening to detect AF before horses train or race has the potential to reduce EASD incidence. More information is needed for risk stratification of late recovery and other arrhythmias.
Source: Equine Veterinary Journal
DOI: 10.1002/evj.70166
Language: English
Subfield: Equine
Field: Veterinary
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,480
Funder: National Institutes of Health
OpenAlex ID: W7155071832
