Integrating Exercise Into Personalized Ventricular Arrhythmia Risk Prediction in Arrhythmogenic Right Ventricular Cardiomyopathy
Bibliographic record
Abstract
BACKGROUND: Exercise is associated with sustained ventricular arrhythmias (VA) in Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) but is not included in the ARVC risk calculator (arvcrisk.com). The objective of this study is to quantify the influence of exercise at diagnosis on incident VA risk and evaluate whether the risk calculator needs adjustment for exercise. METHODS: We interviewed ARVC patients without sustained VA at diagnosis about their exercise history. The relationship between exercise dose 3 years preceding diagnosis (average METh/wk) and incident VA during follow-up was analyzed with time-to-event analysis. The incremental prognostic value of exercise to the risk calculator was evaluated by Cox models. RESULTS: We included 176 patients (male, 43.2%; age, 37.6±16.1 years) from 3 ARVC centers, of whom 53 (30.1%) developed sustained VA during 5.4 (2.7-9.7) years of follow-up. Exercise at diagnosis showed a dose-dependent nonlinear relationship with VA, with no significant risk increase <15 to 30 METh/wk. Athlete status, using 3 definitions from literature (>18, >24, and >36 METh/wk), was significantly associated with VA (hazard ratios, 2.53-2.91) but was also correlated with risk factors currently in the risk calculator model. Thus, adding athlete status to the model did not change the C index of 0.77 (0.71-0.84) and showed no significant improvement (Akaike information criterion change, <2). CONCLUSIONS: Exercise at diagnosis was dose dependently associated with risk of sustained VA in ARVC patients but only above 15 to 30 METh/wk. Exercise does not appear to have incremental prognostic value over the risk calculator. The ARVC risk calculator can be used accurately in athletic patients without modification.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".