Obesity and risk of placenta accreta spectrum: A meta-analysis
Bibliographic record
Abstract
Abstract Background Some studies have indicated a notable association between obesity and placenta accreta spectrum (PAS), while others have not reported. Hence, we performed a meta-analysis to explore the association between obesity and the risk of PAS. Methods To explore the association between obesity and PAS through observational studies, we conducted a systematic search across PubMed, Web of Science, Google scholar, and Scopus databases up to March 30, 2024. The meta-analysis utilized a random-effect model, with the quality of included studies assessed using the Newcastle–Ottawa scale. A significance level of less than 0.05 was considered statistically significant using Stata software, version 14 (StataCorp, College Station, TX, USA). Results The association between obesity and PAS risk in crude studies showed significance (1.51 [95% CI: 1.19, 1.82; I 2 = 0.0%]). However, in adjusted studies, the association was not significant (1.25 [95% CI: 0.45, 2.05; I 2 = 52.0%]). Conclusion These findings suggest that obesity has been proposed as potentially associated with a higher risk of PAS, particularly evident in crude studies. However, it is imperative to conduct prospective cohort studies with a large sample size and meticulous control of confounding variables to further elucidate this relationship.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.031 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".