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Impact of Socioeconomic Status, Race and Ethnicity, and Geography on Prenatal Detection of Hypoplastic Left Heart Syndrome and Transposition of the Great Arteries

2021· article· en· W3161904723 on OpenAlexaffabout
Anita Krishnan, Marni Jacobs, Shaine A. Morris, Shabnam Peyvandi, Aarti Bhat, Anjali Chelliah, Joanne S. Chiu, Bettina F. Cuneo, Grace Freire, Lisa K. Hornberger, Lisa Howley, Nazia Husain, Catherine Ikemba, Ann Kavanaugh‐McHugh, Shelby Kutty, Caroline Lee, Keila N. Lopez, Angela McBrien, Erik Michelfelder, Nelangi M. Pinto, Rachel M. Schwartz, Kenan W.D. Stern, Carolyn L. Taylor, Varsha Thakur, Wayne Tworetzky, Carol Wittlieb‐Weber, Kris Woldu, Mary T. Donofrio, Mary Craft, Heather Gramse, Anita J. Moon‐Grady, Wesley Lee, Dawn Park, Alysia Wiener

Bibliographic record

VenueCirculation · 2021
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsUniversity of TorontoUniversity of Alberta HospitalUniversity of Alberta
FundersNational Institute on Minority Health and Health Disparities
KeywordsMedicineHypoplastic left heart syndromeQuartileDemographySocioeconomic statusResidenceEthnic groupGreat arteriesRetrospective cohort studyConfoundingPediatricsGerontologyHeart diseaseInternal medicinePopulationEnvironmental healthConfidence interval

Abstract

fetched live from OpenAlex

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.009
GPT teacher head0.253
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations110
Published2021
Admission routes2
Has abstractyes

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