Safety of Sports for Young Patients With Implantable Cardioverter-Defibrillators
Bibliographic record
Abstract
BACKGROUND: Despite safety concerns, many young patients with implantable cardioverter-defibrillators (ICDs) participate in sports. We undertook a prospective, multinational registry to determine the incidence of serious adverse events because of sports participation. The primary end points were death or resuscitated arrest during sports or injury during sports because of arrhythmia or shock. Secondary end points included system malfunction and incidence of ventricular arrhythmias requiring multiple shocks for termination. METHODS: Athletes with ICDs aged ≤21 years were included in this post hoc subanalysis of the ICD Sports Registry. Data on sports and clinical outcomes were obtained by phone interview and medical records review. ICD shocks and clinical details of lead malfunction were classified by 2 electrophysiologists. RESULTS: A total of 129 young athletes participating in competitive (n=117) or dangerous (n=12) sports were enrolled. The mean age was 16 years (range, 10-21; 40% female; 92% white). The most common diagnoses were long QT syndrome (n=49), hypertrophic cardiomyopathy (n=30), and congenital heart disease (n=16). The most common sports were basketball and soccer, including 79 varsity/junior varsity high school and college athletes. During a median follow-up of 42 months, 35 athletes (27%) received 38 shocks. There were no occurrences of death, arrest, or injury related to arrhythmia, during sports. There was 1 ventricular tachycardia/ventricular fibrillation storm during competition. Freedom from lead malfunction was 92.3% at 5 years and 79.6% at 10 years. CONCLUSIONS: Although shocks related to competition/practice are not uncommon, there were no serious adverse sequelae. Lead malfunction rates were similar to previously reported in unselected pediatric ICD populations. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT00637754.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".