Interatrial Communications: Prevalence and Subtypes in 12,385 Newborns–a Copenhagen Baby Heart Study
Bibliographic record
Abstract
The prevalence of interatrial communications in newborns, i.e., patent foramen ovale or atrial septal defect, was previously reported to be between 24 and 92%, but the area has been impeded by lack of a universal classification method. A recently published novel echocardiographic diagnostic algorithm for systematic classification of interatrial communications had inter-and intraobserver agreements superior to standard expert assessment. This study aimed to determine the prevalence of subtypes of interatrial communications on transthoracic echocardiography in newborns. Echocardiograms of newborns aged 0-30 days were prospectively collected in the population-based cohort study Copenhagen Baby Heart Study in 2017-2018 and analyzed according to the new diagnostic algorithm, classifying interatrial communications into three subtypes of patent foramen ovale and three subtypes of atrial septal defects. Echocardiograms from 15,801 newborns were analyzed; 3416 (21.6%) were excluded due to suboptimal image quality or severe structural heart disease (n = 3), leaving 12,385 newborns (aged 12 [interquartile range 8; 15] days, 48.2% female) included in the study. An interatrial communication was detected in 9766 (78.9%) newborns. According to the algorithm, 9029 (72.9%) had a patent foramen ovale, while 737 (6.0%) fulfilled criteria for an atrial septal defect, further divided into subtypes. An interatrial communication was seen on echocardiography in almost 80% of newborns aged 0-30 days. Patent foramen ovale was 12 times more frequent than atrial septal defects. The observed prevalence of atrial septal defects was higher than previously reported. Follow up studies could distinguish which interatrial communications require follow-up or intervention. ClinicalTrial.gov, NCT02753348, posted April 27, 2016, [ https://classic.clinicaltrials.gov/ct2/show/NCT02753348 ].
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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 | 0.000 | 0.000 |
| 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".