Medical Malpractice Claims for Sports Cardiology Cases Among Young Athletes
Bibliographic record
Abstract
BACKGROUND: Sudden cardiac arrest/death (SCA/D) is the leading medical cause of fatalities among young competitive athletes. Sports participation among athletes with cardiovascular disease has become more frequent, raising concerns regarding the medicolegal risk and adequacy of emergency medical response plans. OBJECTIVES: The purpose of this study was to analyze the frequency and characteristics of medical malpractice/negligence claims related to sports cardiology cases among young competitive athletes in the United States. METHODS: A comprehensive retrospective review of medical malpractice/negligence lawsuits from inception to October 2024 was performed using 4 search strategies. Cases involving young competitive athletes aged 12 to 40 years competing at the middle school, high school, competitive club, collegiate, semiprofessional/professional, or national/international level who experienced SCA/D or had a diagnosis associated with SCA/D were included. Medical malpractice/negligence case frequency, location, demographics, allegations, defendant profiles, and case outcomes/awards were identified. RESULTS: A total of 35/586 (6%) cases met inclusion criteria from 1978 to 2022. There was a favorable plaintiff outcome or settlement in 10/35 (29%) cases with known settlements or awards ranging from $600,000 to $24,000,000; a favorable defendant outcome or dismissal in 16/35 (46%) cases; and the case outcome was undisclosed/unknown in 9/35 (26%) cases. The most common primary allegation for lawsuits was a negligent emergency medical response (13/35, 37%) followed by failure to diagnose cardiovascular disease (9/35, 26%). CONCLUSIONS: Medical malpractice/negligence claims regarding cardiac cases in young competitive athletes in the United States were rare (<1 case/y), although the financial settlements were significant. This study supports ongoing efforts to improve emergency preparedness and the cardiac emergency medical response for young competitive athletes.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".