MétaCan
Menu
Back to cohort
Record W4403960006 · doi:10.1016/j.jacadv.2024.101368

Global Disparities in Outcomes of Pregnant Individuals With Rheumatic Heart Disease

2024· article· en· W4403960006 on OpenAlexaff
Jenny Yang, Natalie Tchakerian, Candice K. Silversides, Samuel C. Siu, Rachel F. Spitzer, Wycliffe Kosgei, Nanette Okun, Rebecca Lumsden, Rohan D’Souza, Anish Keepanasseril

Bibliographic record

VenueJACC Advances · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Issues in Pregnancy
Canadian institutionsHospital for Sick ChildrenMcMaster UniversityUniversity of TorontoWestern UniversitySunnybrook HospitalMount Sinai Hospital
Fundersnot available
KeywordsMedicineHeart diseaseRheumatic diseasePregnancyInternal medicineHealth equityCardiologyObstetricsIntensive care medicineDiseasePublic healthBiologyPathology

Abstract

fetched live from OpenAlex

Background: Rheumatic heart disease (RHD) remains as 1 of the major contributors to indirect pregnancy-related mortality and morbidity worldwide and disproportionately affects marginalized populations. Objectives: In this scoping review, the authors sought to explore the socioeconomic, cultural, and health care access-related causes of global disparities in outcomes of pregnancy among individuals with RHD. Methods: We performed a literature search of all studies published between January 1, 1990, and January 1, 2022, that investigated causes for disparate outcomes in pregnant individuals with RHD. Results: Of the 3,544 articles identified, 16 were included in the final analysis. The key reasons for disparate outcomes included lack of secondary antibiotic RHD prophylaxis; late and more severe RHD diagnosis, differences in management and antenatal care access; lack of expert and coordinated multidisciplinary care; suboptimal patient health education; inadequate access to RHD medication, intervention and surgery in pregnancy; and limited financial and economic resources. Conclusions: These findings illustrated using a life-course approach demonstrate opportunities for clinical and public health interventions to improve outcomes in this population.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.338
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.010
GPT teacher head0.302
Teacher spread0.292 · 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 teacher head, 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

Citations6
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJACC AdvancesSame topicCardiovascular Issues in PregnancyFrench-language works237,207