Abstract P134: Cardiac Screening in Adolescent and Young Athletes: A 3 year Cross Sectional Study Assessing the Diagnostic Accuracy of the History Questionnaire, Physical Examination, and Electrocardiogram
Bibliographic record
Abstract
Background & Aim: The accuracy of each cardiac screening tool for young athletes needs further investigation. The aim of this study is to evaluate the Preparticipation Physical Evaluation Monograph 4 th Edition (PPE-4), which is the current recommendation for cardiovascular screening in young athletes, and the 12-lead electrocardiogram (ECG). Methods: During October 2010 to June 2013 student athletes from high schools around the greater Seattle area received a one-time cardiac screen including history and physical examination as recommended in the PPE-4, and a resting 12-lead ECG. Those with abnormal findings received a focused echocardiogram. Student athletes were defined as participating in at least one high school level sport or higher per year. A true positive was defined as the identification of a cardiac disorder associated with sudden cardiac death. Sensitivity (Sn), specificity (Sp), false positive rate (FP), and positive and negative likelihood ratios (+LR, -LR), were calculated for each screening tool. Results: Screening events were held at 23 high schools; 4,743 student athletes ranged in age from 13-19 (mean 15.8), 54% male, 65% Caucasian, 13% mixed race, 10% Asian/Pacific Islander, 6% African-American. A total of 1065 (23%) students had at least one positive history response after physician review, 408 (9%) had an abnormal finding on physical exam, and 185 (4%) had an abnormal ECG. Echocardiography was performed on 1417 students who presented a positive finding on history, physical, or ECG or were a male basketball player. There were 21 cardiac disorders identified that could potentially lead to SCD (0.4%). Wolff-Parkinson-White (9) was most common, followed by 4 cases of coronary artery abnormalities, 3 cases of Long QT Syndrome, 3 dilated aortic roots or aneurysm, and 1 case each of hypertrophic cardiomyopathy and Short QT Syndrome. ECG identified 14 cases of those 21, Echo identified 9 cases of those 21. The history questionnaire had a Sn of 52%, Sp 78%, +LR 2.4, and FP 22%. Physical Exam had a Sn 19%, Sp 91%, +LR 2.2, and FP 9%. ECG had a Sn 67%, Sp 96%, +LR 18.4, and FP 4%. Conclusion: ECG had the highest Sn, Sp, and +LR of the screening tools evaluated. History and physical exam had lower Sn and +LRs and higher false positive rates. A limitation to this study is that there is no gold standard for this screening protocol. ECG may miss structural abnormalities and Echo may miss conduction disorders. A combination of the two tests was considered the gold standard, meaning sensitivity of all tests may be overestimated. More research is needed to improve the performance of cardiovascular screening methods especially through the history questionnaire and physical exam. Out of the three tools evaluated the best tool to detect underlying cardiovascular conditions associated with SCD is ECG.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".