Inter-Rater Reliability and Downstream Financial Implications of Electrocardiography Screening in Young Athletes
Bibliographic record
Abstract
BACKGROUND: Preparticipation screening for cardiovascular disease in young athletes with electrocardiography is endorsed by the European Society of Cardiology and several major sporting organizations. One of the concerns of the ECG as a screening test in young athletes relates to the potential for variation in interpretation. We investigated the degree of variation in ECG interpretation in athletes and its financial impact among cardiologists of differing experience. METHODS AND RESULTS: Eight cardiologists (4 with experience in screening athletes) each reported 400 ECGs of consecutively screened young athletes according to the 2010 European Society of Cardiology recommendations, Seattle criteria, and refined criteria. Cohen κ coefficient was used to calculate interobserver reliability. Cardiologists proposed secondary investigations after ECG interpretation, the costs of which were based on the UK National Health Service tariffs. Inexperienced cardiologists were more likely to classify an ECG as abnormal compared with experienced cardiologists (odds ratio, 1.44; 95% confidence interval, 1.03-2.02). Modification of ECG interpretation criteria improved interobserver reliability for categorizing an ECG as abnormal from poor (2010 European Society of Cardiology recommendations; κ=0.15) to moderate (refined criteria; κ=0.41) among inexperienced cardiologists; however, interobserver reliability was moderate for all 3 criteria among experienced cardiologists (κ=0.40-0.53). Inexperienced cardiologists were more likely to refer athletes for further evaluation compared with experienced cardiologists (odds ratio, 4.74; 95% confidence interval, 3.50-6.43) with poorer interobserver reliability (κ=0.22 versus κ=0.47). Interobserver reliability for secondary investigations after ECG interpretation ranged from poor to fair among inexperienced cardiologists (κ=0.15-0.30) and fair to moderate among experienced cardiologists (κ=0.21-0.46). The cost of cardiovascular evaluation per athlete was $175 (95% confidence interval, $142-$228) and $101 (95% confidence interval, $83-$131) for inexperienced and experienced cardiologists, respectively. CONCLUSIONS: Interpretation of the ECG in athletes and the resultant cascade of investigations are highly physician dependent even in experienced hands with important downstream financial implications, emphasizing the need for formal training and standardized diagnostic pathways.
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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 | 0.119 | 0.324 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".