Electrocardiogram interpretation and management in a pediatric emergency department.
Bibliographic record
Abstract
OBJECTIVES: To determine the accuracy of electrocardiogram (ECG) interpretation by pediatric emergency physicians through comparison with a pediatric cardiologist and to determine the intrarater and interrater reliability for pediatric emergency physicians and cardiologists. METHODS: This was a prospective cohort study in which pediatric emergency physicians ordering an ECG completed a standardized questionnaire. The same emergency physician, a second emergency physician, and a pediatric cardiologist also completed the questionnaire for all ECGs at a later time. A randomly selected subset of ECGs was also interpreted by the same cardiologist and a second pediatric cardiologist. Major outcome variables were (1) whether the ECG was normal or abnormal, and if abnormal, (2) whether the abnormality represented a minor or major concern, and (3) whether the ECG warranted referral to a pediatric cardiologist. RESULTS: For pediatric emergency physicians, the intrarater and interrater kappa values were 0.56 and 0.24 for the presence of an abnormality, 0.49 and 0.36 for level of concern, and 0.63 and 0.25 for need of cardiology follow-up. For pediatric cardiologists, the intrarater and interrater kappa values were 0.82 and 0.92 for the presence of an abnormality, 0.71 and 1.00 for level of concern, and 0.82 and 0.91 for need of cardiology follow-up. A comparison of the initial emergency physician and cardiologist interpretations yielded kappa values of 0.42 for the presence of an abnormality, 0.16 for level of concern, and 0.31 for need of cardiology follow-up. CONCLUSIONS: When compared with interpretation by a pediatric cardiologist, ECG interpretation by pediatric emergency physicians was relatively inaccurate; intrarater and interrater agreement among emergency physicians was good and poor, respectively, and the intrarater and interrater agreement among pediatric cardiologists was excellent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".