Assessing the Utility of Targeted Neonatal Echocardiography for Congenital Heart Disease Detection: Retrospective Cohort Analysis
Bibliographic record
Abstract
PURPOSE: Targeted neonatal echocardiography (TNE) is increasingly utilized by neonatologists to assess hemodynamics, particularly when cardiology-performed echocardiography (CPE) is unavailable. It is crucial that TNE screens and identifies structural abnormalities. This study evaluated the agreement between TNE and CPE in detecting significant congenital heart disease (CHD). METHODS: This retrospective, single-center cohort study included infants who underwent TNE between 2015 and 2019 and had at least one complete CPE before discharge. Infants with a known CHD diagnosis prior to TNE were excluded. Atrial septal defects (ASD) < 3 mm, peripheral pulmonary stenosis, and patent ductus arteriosus were excluded. Agreement between TNE and CPE was assessed using correlation coefficients and kappa statistics. RESULTS: A total of 339 infants with 954 TNE scans were included. TNE identified CHD in 41 infants, with all but one (a false positive bicuspid aortic valve) confirmed by CPE. TNE missed CHD in 29 infants (31 lesions), mostly minor, with only one case (pulmonary stenosis) requiring intervention. The overall agreement was 91.15%, with a kappa of 0.68 (p < 0.0001). CONCLUSION: TNE demonstrated good agreement with CPE in detecting significant CHD in a low-risk neonatal population. Most missed lesions were minor, underscoring the importance of ongoing training and quality assurance.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".