Bibliographic record
Abstract
Hypertrophic cardiomyopathy (HCM) is the number one cause of sudden cardiac death in elite athletes.This project used resting 12-lead electrocardiography (ECG) and ballistocardiography (BCG) to assess cardiac cycle timing events as simple screening techniques to rule out cardiac abnormalities for the safety of a group of elite ice hockey players.Clinical cardiac (ECG) and physiological (maximal aerobic power [VO 2 max], anaerobic [Wingate peak power, Watts] and musculoskeletal strength) data is presented here on an elite group of ice hockey players (n=34; age=17-18 yrs) that participated in a professional medical and fitness evaluation.Subsequently one subject was diagnosed with #1 Apical HCM and his cardiac data is compared with the group.The HCM subject performed all fitness testing and was determined to be physically fit (%BF=7.2%;VO 2 max=59.4mL•kg -1 •min -1 ; Wingate peak power output=15.1 Watt•kg -1 ; Heart Rate max=200 beats•min -1 ).However, the ECG showed extreme voltage and deeply inverted T-waves, and the BCG showed abnormal waveform complexes and cardiac timing events in comparison to the group means.Mean BCG systolic timing events for isovolumic contraction time (54.7±7.1 vs 49.5±12.4msec), acceleration time (49.1±1.8 vs 56.3±9.1 msec), diastole (470.8±25.3vs 531.4±166.7 msec), and isovolumic relaxation time (88.5±7.4 vs 100.8± 16 msec) were significantly different (p<0.05).Atrial systole amplitude was statistically higher for this subject (9.2±3.7 vs 5.3±3 mG).Subsequent follow-up assessment showed abnormal echocardiogram (Echo) dimensions (ventricular septum [12mm]; posterior wall [16 mm]), velocities (mitral valve deceleration [233 msec], LV systolic strain [14%]), and volumes (LV stroke volume [38 mL•metre -1 body surface area]), with normal E:A ratio (1.75) and LV ejection fraction (62%).Cardiac magnetic resonance imaging (MRI) showed apical septal wall thickness (24-25 mm) in the HCM player.In conclusion, BCG was able to corroborate a cardiac abnormality that was later confirmed with echocardiography and MRI, suggesting that BCG is a potential technology to detect anomalies that alter cardiac timing and amplitude.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".