The association between of placenta previa and congenital abnormalities: a systematic review and network meta-analysis
Bibliographic record
Abstract
Abstract Background Congenital abnormalities, as one of the fetal complications of placenta previa, may cause health problems or disability of the child throughout life. This study aimed to determine the relationship between placenta previa and congenital abnormalities. Methods Potential articles were retrieved from three electronic databases (PubMed/Medline, Scopus, and Web of Sciences) up to 21 May 2023 without limit of time and language. A random effect model was applied for meta-analysis. The heterogeneity was calculated based on I2 statistic and Cochrane Q-test. All analyses were conducted at the significance level of 0.05 using STATA software, version 14. The quality assessment of the included studies was performed using the improved Newcastle-Ottawa Scale. Results In the initial search, 829 articles were retrieved. Finally, according to the inclusion criteria, eight studies were analyzed in the meta-analysis. A significant association was reported between placenta previa and risk of congenital abnormalities based on crude form (OR = 1.81, 95% CI = 1.34 to 2.28) and adjusted studies (OR = 6.38, 95% CI = 1.47 to 11.30). The high heterogeneity was observed among the studies reported based on adjusted and crude form, respectively (I2 = 97.9%, P = 0.000) (I2 = 80.6%, P = 0.000). Therefore, publication bias was not observed among studies. Seven studies of the included studies were of high quality. Conclusion Our study provides evidence that there is a positive and significant association between placenta previa and congenital malformations, including all structural anomalies, chromosomal defects, and congenital hypothyroidisms. Therefore, monitoring congenital abnormalities in the fetus of a mother with placenta previa is necessary.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.041 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| 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".