Association between body mass index in the first half of pregnancy and gestational diabetes: A systematic review
Bibliographic record
Abstract
Gestational diabetes mellitus is a more common complication in pregnancy and rising worldwide and screening for treating gestational diabetes mellitus is an opportunity for preventing its complications. Abnormal body mass index is the cause of many complications in pregnancy that is one of the major and modifiable risk factors in pregnancy too. This systematic review aimed to define the association between body mass index in the first half of pregnancy (before 20 weeks of gestation) and gestational diabetes mellitus. Web of Science, PubMed/Medline, Embase, Scopus, ProQuest, Cochrane library, and Google Scholar databases were systematically explored for articles published until April 31, 2022. Participation, exposure, comparators, outcomes, study design criteria include pregnant women (P), body mass index (E), healthy pregnant women (C), gestational diabetes mellitus (O), and study design (cohort, case-control, and cross-sectional). Newcastle-Ottawa scale checklists were used to report the quality of the studies. Eighteen quality studies were analyzed. A total of 41,017 pregnant women were in the gestational diabetes mellitus group and 285,351 pregnant women in the normal glucose tolerance group. Studies have reported an association between increased body mass index and gestational diabetes mellitus. Women who had a higher body mass index in the first half of pregnancy were at higher risk for gestational diabetes mellitus. In the first half of pregnancy, body mass index can be used as a reliable and available risk factor to assess gestational diabetes mellitus, especially in some situations where the pre-pregnancy body mass index is not available.
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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 | 0.004 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".