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
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,019 | 0,035 |
| Bibliométrie | 0,006 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».