Impact of Socioeconomic Status, Race and Ethnicity, and Geography on Prenatal Detection of Hypoplastic Left Heart Syndrome and Transposition of the Great Arteries
Bibliographic record
Abstract
BACKGROUND: Prenatal detection (PND) has benefits for infants with hypoplastic left heart syndrome (HLHS) and transposition of the great arteries (TGA), but associations between sociodemographic and geographic factors with PND have not been sufficiently explored. This study evaluated whether socioeconomic quartile (SEQ), public insurance, race and ethnicity, rural residence, and distance of residence (distance and driving time from a cardiac surgical center) are associated with the PND or timing of PND, with a secondary aim to analyze differences between the United States and Canada. METHODS: score using the neighborhood summary score or Canadian Chan index and separated into quartiles. Insurance type and self-reported race and ethnicity were obtained from medical charts. We evaluated associations among SEQ, insurance type, race and ethnicity, rural residence, and distance of residence with PND of HLHS and TGA (aggregate and individually) using bivariate analysis with adjusted associations for confounding variables and cluster analysis for centers. RESULTS: Data on 1862 subjects (HLHS: n=1171, 92% PND; TGA: n=691, 58% PND) were submitted by 21 centers (19 in the United States). In the United States, lower SEQ was associated with lower PND in HLHS and TGA, with the strongest association in the lower SEQ of pregnancies with fetal TGA (quartile 1, 0.78 [95% CI, 0.64-0.85], quartile 2, 0.77 [95% CI, 0.64-0.93], quartile 3, 0.83 [95% CI, 0.69-1.00], quartile 4, reference). Hispanic ethnicity (relative risk, 0.85 [95% CI, 0.72-0.99]) and rural residence (relative risk, 0.78 [95% CI, 0.64-0.95]) were also associated with lower PND in TGA. Lower SEQ was associated with later PND overall; in the United States, rural residence and public insurance were also associated with later PND. CONCLUSIONS: We demonstrate that lower SEQ, Hispanic ethnicity, and rural residence are associated with decreased PND for TGA, with lower SEQ also being associated with decreased PND for HLHS. Future work to increase PND should be considered in these specific populations.
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 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".