Circulating retinol-binding protein 4 levels in gestational diabetes mellitus: a meta-analysis of observational studies
Bibliographic record
Abstract
Retinol-binding protein 4 (RBP4) is a novel adipocyte-derived cytokine playing an important role in the regulation of energy metabolism and insulin sensitivity. Although the association between RBP4 and metabolic dysfunction is well established, studies on the relationship between circulating RBP4 levels and the risk of gestational diabetes mellitus (GDM) have yielded inconclusive results. We performed a meta-analysis to investigate whether women with GDM had higher circulating RBP4 levels than the normglycemic pregnant women. PubMed, Web of Science and EMBASE were searched up to 1 August 2014. A total of 14 studies comprised of 884 women with GDM and 1251 normglycemic pregnant women were included. The overall results suggested that maternal circulating RBP4 levels were significantly higher in GDM than their normal controls (SMD: 0.49 μg/ml, 95% CI: 0.23-0.75 μg/ml, p < 0.001, random effect model). However, stratified results indicated that this significant difference only existed in the second/third trimester and was limited to Asian populations. Furthermore, subgroup analysis according to matched maternal age and BMI still demonstrated that GDM had higher circulating RBP4 levels than the normal controls. Our findings suggested that Asian women with GDM had increased circulating RBP4 levels in their second/third trimester.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.018 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".