Global Disparities in Outcomes of Pregnant Individuals With Rheumatic Heart Disease
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".