Prevalence of congenital heart disease and its related risk indicators among 90 796 Chinese infants aged less than 6 months in Tianjin
Bibliographic record
Abstract
BACKGROUND: Congenital heart disease (CHD) represents one of the most prevalent congenital malformations. However, few studies use whole-population screening by colour Doppler ultrasonic diagnostic system to identify CHD among live infants. We estimate the prevalence of CHD and its major risk indicators among infants aged less than 6 months in urban Tianjin, China. METHODS: A colour Doppler ultrasonic diagnostic system was used as the screening tool for the diagnosis of CHD. A total of 90,796 infants aged less than 6 months, living in the nine urban districts of Tianjin, China, participated in the CHD screening programme between July 2009 and June 2011. RESULTS: A total of 1817 children were identified as having CHD. The overall prevalence of congenital heart disease was 16.4 per 1000 live births among 47,697 boys, 24.1 per 1000 live births among 43,099 girls, and 20.0 per 1,000 live births among 90,796 boys and girls combined. Atrial septal defect was the most common heart lesion of CHD, with the prevalence of 10.6 per 1000 live births. Several maternal antenatal factors, such as older age, pregnant infections, pregnancy-induced hypertension, gestational diabetes, family history of CHD, and lower education level, and several child factors, such as early screening age, lower birthweight and short gestational age, were associated with an increased risk of CHD. CONCLUSIONS: The prevalence of CHD of live infants in Tianjin was found to be relatively high by using a colour Doppler ultrasonic diagnostic system to screen CHD. Several maternal factors were associated with CHD risk.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".