Addition of the Electrocardiogram to the Preparticipation Examination of College Athletes
Bibliographic record
Abstract
OBJECTIVE: Although the use of standardized cardiovascular (CV) system-focused history and physical examination is recommended for the preparticipation examination (PPE) of athletes, the addition of the electrocardiogram (ECG) has been controversial. Because the impact of ECG screening on college athletes has rarely been reported, we analyzed the findings of adding the ECG to the PPE of Stanford athletes. DESIGN: For the past 15 years, the Stanford Sports Medicine program has mandated a PPE questionnaire and physical examination by Stanford physicians for participation in intercollegiate athletics. In 2007, computerized ECGs with digital measurements were recorded on athletes and entered into a database. SETTING: Although the use of standardized CV-focused history and physical examination are recommended for the PPE of athletes, the addition of the ECG has been controversial. Because the feasibility and outcomes of ECG screening on college athletes have rarely been reported, we present findings derived from the addition of the ECG to the PPE of Stanford athletes. For the past 15 years, the Stanford Sports Medicine program has mandated a PPE questionnaire and physical examination by Stanford physicians for participation in intercollegiate athletics. In 2007, computerized ECGs with digital measurements were recorded on athletes and entered into a database. MAIN OUTCOME MEASURES: Six hundred fifty-eight recordings were obtained (54% men, 10% African-American, mean age 20 years) representing 24 sports. Although 68% of the women had normal ECGs, only 38% of the men did so. Incomplete right bundle branch block (RBBB) (13%), right axis deviation (RAD) (10%), and atrial abnormalities (3%) were the 3 most common minor abnormalities. Sokolow-Lyon criteria for left ventricular hypertrophy (LVH) were found in 49%; however, only 27% had a Romhilt-Estes score of >or=4. T-wave inversion in V2 to V3 occurred in 7%, and only 5 men had abnormal Q-waves. Sixty-three athletes (10%) were judged to have distinctly abnormal ECG findings possibly associated with conditions including hypertrophic cardiomyopathy or arrhythmogenic right ventricular dysplasia/cardiomyopathy. These athletes were offered further testing but this was not mandated according to the research protocol. RESULTS: Six hundred fifty-three recordings were obtained (54% men, 7% African American, mean age 20 years), representing 24 sports. Although 68% of the women had normal ECGs, only 38% of the men did so. Incomplete RBBB (13%), RAD (10%), and atrial abnormalities (3%) were the 3 most common minor abnormalities. Sokolow-Lyon criteria for LVH were found in 49%; however, only 27% had a Romhilt-Estes score of >or=4. T-wave inversion in V2 to V3 occurred in 7% and only 5 men had abnormal Q-waves. Sixty-five athletes (10%) were judged to have distinctly abnormal ECG findings suggestive of arrhythmogenic right ventricular dysplasia, hypertrophic cardiomyopathy, and/or biventricular hypertrophy. These athletes will be submitted to further testing. CONCLUSIONS: Mass ECG screening is achievable within the collegiate setting by using volunteers when the appropriate equipment is available. However, the rate of secondary testing suggests the need for an evaluation of cost-effectiveness for mass screening and the development of new athlete-specific ECG interpretation algorithms.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".