Accuracy of Electrocardiography and Agreement with Echocardiography in the Diagnosis of Pediatric Left Atrial Enlargement
Bibliographic record
Abstract
Left atrial enlargement (LAE) is a marker for diastolic cardiac dysfunction. Echocardiograms are considered the gold-standard for diagnosis, but given their wider access and lower economic cost, electrocardiograms (ECGs) may be useful in identifying patients who would benefit from further investigation. This study investigates the utility of ECG criteria to diagnose LAE in pediatric patients. A retrospective chart review (n = 492) was conducted in patients whose echocardiograms demonstrated LAE by left atrial indexed diameter z-score ≥2.0 and/or increased left atrial to aortic root ratio at various cutoffs (≥1.4, ≥1.6, ≥1.8). ECG criteria studied included: (1) P wave ≥110 msec, (2) P mitrale ≥40 msec, in LII (3) terminal negative P wave deflection in lead V1 > 40 msec, and (4) P/PR segment >1.6 in lead II. Sensitivity, specificity, Cohen's Kappa coefficient (κ), and ROC curves were calculated. A combination of P mitrale ≥40 msec and terminal negative P wave deflection in lead V1 > 40 msec yielded the greatest agreement (κ = 0.221, 95%CI 0.060-0.382), but all ECG criteria used to diagnose LAE had poor diagnostic value (AUC < 0.60). The present ECG criteria should not be used to diagnose LAE in the absence of an echocardiogram and findings should be considered in the context of clinical symptoms.
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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 | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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".