Hepatokine levels during the first or early second trimester of pregnancy and the subsequent risk of gestational diabetes mellitus: a systematic review and meta-analysis
Bibliographic record
Abstract
The relationship between hepatokine levels during the first or early second trimester of pregnancy and the subsequent risk of gestational diabetes mellitus (GDM) have been studied extensively. However, conclusions remain debateable whether hepatokines are potential markers of GDM. We conducted a meta-analysis of published articles to understand the association between circulating levels of selected hepatokines (including FGF21, fetuin-A, afamin, adropin, ficolin-3, selenoprotein P, ANGPTL4 and AGF) and the risk of GDM. We searched the PubMed, Embase, Cochrane Library and Web of Science databases for studies published before January 2021 that examined the association between hepatokines and GDM (Prospero Registration# CRD42020191408). The quality was assessed by the Newcastle–Ottawa Scale (NOS). Pooled standard mean differences (SMDs) and weighted mean differences (WMDs) with 95% confidence intervals (CIs) were used to compare the levels of hepatokines in different groups using fixed effects or random effects models. Meta-regression analysis and publication bias were conducted in accordance with standard methods. The trim-fill adjustment method was used to further assess the possible effect of publication bias. Sensitivity analysis was performed by omitting each study one at a time. The meta-analysis included 31 observational studies relating hepatokine levels to GDM in 4729 participants (1908 GDM, 2821 non-GDM). Serum FGF21 levels in patients with GDM were higher than those in healthy pregnant women during the second trimester and after delivery (SMD 0.89, [95% CI] 0.01–1.78 for the second trimester; SMD 1.42, [95% CI] 0.86–1.98 for after delivery). The serum levels of afamin in patients with GDM were significantly higher than those in healthy pregnant women during the first trimester and before pregnancy (SMD 0.51, [95% CI] 0.15–0.86 for first trimester; SMD 0.97, [95% CI] 0.45–1.50 for before pregnancy). Serum adropin levels in patients with GDM were higher than those in healthy pregnant women during the first and third trimesters of pregnancy (SMD 4.26, [95% CI] 3.30–5.23 for the first trimester; SMD 4.02, [95% CI] 3.09–4.94 for the third trimester). The serum levels of ficolin-3 in GDM patients were higher than those in healthy pregnant women during the second and third trimesters of pregnancy (WMD 1.43, [95% CI] 0.91–1.96 for the second trimester; SMD 1.28, [95% CI] 0.72–1.84 for the third trimester). The serum AGF level of patients with GDM was higher than that of healthy pregnant women in the control group in the third trimester (WMD 61 [95% CI] 37.04–81.96). The serum levels of selenoprotein P in patients with GDM were higher than those in healthy pregnant women in the control group during the first trimester (WMD 7.09 [95% CI] 4.6–9.57). Measurement of circulating hepatokines in the first or second trimester of pregnancy may improve the identification of women at risk of developing GDM later. Prospective evaluation of the combination of hepatokines and maternal characteristics for early identification of those who do and do not require OGTT is warranted. Additional well-designed prospective studies with longitudinal assessment of hepatokines during pregnancy are needed to understand the trajectories and dynamic associations of hepatokines with GDM risk.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.035 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".