QT Interval and Cardiac Restitution Ratio Complexity in Standardbred Racehorses From Rest to Maximal Effort: Insights Into Arrhythmia Risk
Bibliographic record
Abstract
BACKGROUND: Sudden cardiac death is common in racehorses. Factors associated with the QT interval that could predispose to fatal cardiac arrhythmias are unknown. Cardiac restitution, expressed as a ratio of QT/TQ, has been used in humans to assess arrhythmia risk but has not been described in horses during maximal intensity exercise. HYPOTHESIS/OBJECTIVE: Describe factors associated with the QT interval and cardiac restitution ratio (CRR) in clinically normal Standardbred racehorses under race-day conditions. ANIMALS: Archival electrocardiograms from 42 Standardbred horses during live racing in Ontario. METHODS: Observational study performing an automated cardiac restitution analysis. Cardiac cycles were obtained from rest, non-race exercise, non-race recovery, live racing, and post-race recovery periods. Multivariable linear regression analysis was performed with both QT interval and CRR as outcomes of interest. RESULTS: Analysis of 3827 sequential pairs of cardiac cycles was performed. Exercise period and RR interval were highly associated with both QT interval and CRR. Other significant associations varied by exercise period and included: racing gait, sex, age, whether the horse received furosemide, and whether the horse experienced complex ventricular arrhythmias after racing. Interactions between gait and furosemide, and sex and gait were also significant. CONCLUSIONS AND CLINICAL IMPORTANCE: An automated cardiac restitution analysis is feasible in exercising racehorses. The QT-RR interval relationship is multifactorial, and there are numerous significant associations that must be considered to interpret changes in QT interval and CRR in horses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".