Electrocardiogram interpretation by Canadian general paediatricians: Examining practice, accuracy and confidence
Bibliographic record
Abstract
BACKGROUND: Paediatric electrocardiograms (ECGs) are ordered and interpreted by general paediatricians; however, no previous studies have evaluated the accuracy of their ECG interpretations. OBJECTIVE: To determine general paediatricians' practice and opinions regarding ECG use, accuracy of their interpretation of paediatric ECGs, and the relationship between accuracy and self-perceived confidence. METHODS: In the present cross-sectional study, Canadian general paediatricians were asked to complete a questionnaire and interpret 18 paediatric ECGs. The questionnaire assessed characteristics of ECG use, self-perceived confidence and opinions regarding ECG use in general paediatric practice. For the ECGs provided, respondents were asked whether the ECG was normal or abnormal, what abnormality the ECG demonstrated and how confident they were in this interpretation. RESULTS: ECG interpretation was performed by 124 general paediatricians. General paediatricians frequently use ECGs in their practice and regard this investigation as useful in patient assessment. The mean (± SD) accuracy of identifying ECGs as normal or abnormal, and identifying the specific abnormality was 80±12% and 56±20%, respectively. The sensitivity and specificity of identifying abnormal ECGs were 80% (95% CI 78% to 82%) and 79% (95% CI 75% to 83%), respectively. Correct ECG interpretation for isolated rhythm disturbances (73%) was significantly better than for abnormalities in axis (25%), chamber hypertrophy (41%) and ECG intervals (49%) (P<0.001). Overall confidence in ECG interpretation correlated with and was the only significant predictor of interpretation accuracy (r=0.396, P<0.001). CONCLUSION: General paediatricians were adept at detecting abnormal ECGs, but were less able to identify the abnormalities. Further education in ECG interpretation may be important for this population.
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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 | 0.006 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".