Significance of Serum-Plasma Leptin Profile during Pregnancy in Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Gestational diabetes mellitus (GDM) represents a stage of subclinical inflammation and a risk factor for subsequent future type 2 diabetes and cardiovascular disease development. Leptin has been related with vascular and metabolic changes in GDM with heterogeneous and contradictory results with respect to their possible involvement in maternal, perinatal, and future complications. Our objective is to evaluate current evidence on the role of leptin in maternal and perinatal complications in women with GDM. PubMed, Embase, Web of Science, and Scopus databases were searched. We evaluated the studies’ quality using the Newcastle-Ottawa scale. Meta-analyses were conducted, and heterogeneity and publication bias were examined. Thirty-nine relevant studies were finally included, recruiting 2255 GDM and 3846 control pregnant women. Leptin levels were significantly higher in GDM participants than in controls (SMD = 0.57, 95%CI = 0.19 to 0.94; p < 0.001). Subgroup meta-analysis did not evidence significant differences in leptin in the different trimesters of pregnancy. Meta-regression showed a positive significant relationship for HOMA in the GDM group (p = 0.05). According to these results, it seems that high levels of leptin can be used as predictive markers in GDM.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.026 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".