Evidence map›Paper›PMID 40626241›Full record

ArticleFrontiers in endocrinology2025

Construct a nomogram prediction and evaluation of influencing factors of adverse pregnancy outcomes in GDM patients based on plasma miR-144-3p levels.

Sanqiang Niu, Pengwen Wu, Bing Li, Huaili Xin, Kangjun Yu, Ningning Du

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Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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6 authors.

Sanqiang NiuDepartment of Obstetrics and Gynecology, The People's Hospital of Bozhou, Bozhou, Anhui, China.
Pengwen WuGraduate School, Bengbu Medical University, Anhui, Bengbu, China.
Bing LiGraduate School, Bengbu Medical University, Anhui, Bengbu, China.
Huaili XinDepartment of Obstetrics and Gynecology, The People's Hospital of Bozhou, Bozhou, Anhui, China.
Kangjun YuDepartment of Obstetrics and Gynecology, The People's Hospital of Bozhou, Bozhou, Anhui, China.
Ningning DuDepartment of Reproductive Medicine, Bozhou People's Hospital, Bozhou, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To examine the expression levels of miR-144-3p in the plasma of patients with gestational diabetes mellitus (GDM) and to construct a nomogram for predicting and evaluating factors influencing adverse pregnancy outcomes (APO) in GDM based on plasma miR-144-3p levels. Methods: This study included 442 pregnant women, comprising 216 diagnosed with GDM (GDM group) and 226 with normal glucose tolerance (NGT group). Plasma miR-144-3p levels in both groups were measured using reverse transcription real-time polymerase chain reaction (RT-qPCR). The diagnostic performance of plasma miR-144-3p for GDM was assessed by receiver operating characteristic (ROC) curve analysis. During pregnancy, the GDM group was followed, and outcomes were categorized into two groups: 132 with favorable pregnancy outcomes (FPO) and 84 with APO. A random number table method was applied to divide the GDM group into a training set (n=151) and a validation set (n=65) using a 7:3 ratio. Differences in variables across pregnancy outcome subgroups in the training set were examined. Univariate and multivariate logistic regression analyses were performed to identify risk factors for APO in GDM. Based on these factors, a nomogram prediction model was developed to estimate the risk of APO in GDM. The model's performance was evaluated using area under the curve (AUC) analysis, calibration curve analysis, and decision curve analysis (DCA). Results: The expression of miR-144-3p was significantly higher in the GDM group than in the NGT group ( Conclusion: Elevated plasma miR-144-3p levels in pregnant women with GDM may contribute to the occurrence of APO. The number of OGTT abnormalities and glycaemic control were also identified as independent risk factors. A nomogram incorporating miR-144-3p and these clinical indicators displays strong predictive accuracy and provides a practical tool for assessing APO risk in GDM.

Indexed as

Diabetes, GestationalMicroRNAsNomogramsPregnancy OutcomeAdultBiomarkersFemaleHumansPregnancyRisk FactorsROC CurveBiomarkersMicroRNAsMIRN144 microRNA, humanadverse pregnancy outcomesgestational diabetes mellitusinfluencing factorsmiR-144-3pnomogram

Identifiers

PMID40626241
PMCPMC12229801

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.