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Associations Between Maternal Sociodemographics and Hospital Mortality in Newborns With Prenatally Diagnosed Hypoplastic Left Heart Syndrome

2023· article· en· W4384499390 on OpenAlexafffund
Keila N. Lopez, Shaine A. Morris, Anita Krishnan, Marni Jacobs, 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, 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, Shabnam Peyvandi, Mary Craft, Heather Gramse, Anita J. Moon‐Grady, Wes Lee, Dawn Park, Alysia Wiener

Bibliographic record

VenueCirculation · 2023
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsUniversity of TorontoUniversity of Alberta
FundersChildren's Hospital of PittsburghUniversity of California, San FranciscoNational Institutes of HealthNational Institute on Minority Health and Health DisparitiesSeattle Children's Research InstituteChildren's National HospitalChildren's Healthcare of AtlantaJohns Hopkins UniversityNationwide Children's HospitalSchool of MedicineTexas Children's HospitalChildren's Mercy HospitalCincinnati Children's Hospital Medical CenterNational Heart, Lung, and Blood InstituteHospital for Sick ChildrenCleveland ClinicVanderbilt University
KeywordsMedicineHypoplastic left heart syndromePerinatal mortalityMaternal morbidityPediatricsPregnancyFetusObstetricsCardiologyInternal medicineHeart disease

Abstract

fetched live from OpenAlex

ace and ethnicity, socioeconomic status (SES), and geography have been associated with differential outcomes in congenital heart disease death.In patients with hypoplastic left heart syndrome (HLHS), lower SES has been associated with increased complications and lower 1-year survival. 1o previous study has examined how sociodemographics affect neonatal death among prenatally diagnosed patients with HLHS.The study goal was to investigate infants with a prenatal diagnosis of HLHS to understand associations between maternal sociodemographics and patient characteristics and hospital discharge mortality.The data that support the findings of this study are available from the corresponding author on reasonable request.

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)0.004
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.280
Teacher spread0.258 · 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

Citations15
Published2023
Admission routes2
Has abstractyes

Explore more

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