Evidence map›Paper›PMID 41427050›Full record

ArticleFrontiers in endocrinology2025

The predictive value of the metabolic score for insulin resistance for metabolism-related disorders and fertility outcomes in Chinese women with polycystic ovary syndrome.

Fengjuan Lu, Hong Yu, Baichao Shi, Jiaxing Feng, Yang Liu, Muxin Guan, Jiannan Yu, Zhuwei Gao, Jingshu Gao, Hongli Ma and 3 more

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Fengjuan LuGraduate School, Heilongjiang University of Chinese Medicine, Harbin, China.
Hong YuDepartment of Obstetrics and Gynecology, First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China.
Baichao ShiGraduate School, Heilongjiang University of Chinese Medicine, Harbin, China.
Jiaxing FengThe First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China.
Yang LiuDepartment of Obstetrics and Gynecology, First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China.
Muxin GuanGraduate School, Heilongjiang University of Chinese Medicine, Harbin, China.
Jiannan YuGraduate School, Heilongjiang University of Chinese Medicine, Harbin, China.
Zhuwei GaoGraduate School, Heilongjiang University of Chinese Medicine, Harbin, China.
Jingshu GaoDepartment of Obstetrics and Gynecology, First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China.
Hongli MaThe First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China.
Yu WangThe First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China.
Jing CongThe First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China.
Xiaoke WuDepartment of Obstetrics and Gynecology, First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to evaluate the predictive value of the Metabolic Score for Insulin Resistance (Mets-IR) for metabolism-related disorders and its association with hormonal status and fertility outcomes in Chinese women with Polycystic Ovary Syndrome (PCOS). Methods: This secondary analysis included 957 women from the PCOSAct trial. Participants were stratified by Mets-IR quartiles. Linear regression analyzed correlations between Mets-IR and metabolic/hormonal parameters. ROC curves assessed Mets-IR's predictive performance for metabolic disorders. Multivariable logistic regression evaluated associations with fertility outcomes. Results: Significant linear correlations were observed between Mets-IR and key metabolic parameters (e.g., HOMA-IR, TG, WHR) and hormonal parameters (PG, E2, FT, LH, FSH, LH/FSH ratio, SHBG, FAI, AMH) (all Conclusion: In women with PCOS, Mets-IR demonstrates significant associations with both metabolic and hormonal parameters and exhibits superior predictive ability over BMI for key hormonal markers (SHBG, FAI, AMH). This index serves as an effective non-invasive predictor for IR, MetS, and NAFLD. For the assessment of ovulatory dysfunction, its predictive performance is comparable to that of BMI, yet it demonstrates no significant association with other fertility outcomes.

Indexed as

FertilityInfertility, FemaleInsulin ResistanceMetabolic DiseasesPolycystic Ovary SyndromeAdultBiomarkersChinaEast Asian PeopleFemaleHumansPredictive Value of TestsPregnancyYoung AdultBiomarkersinsulin resistancemetabolic score for insulin resistance (METS-IR)metabolism-related disordersovulatory dysfunctionpolycystic ovary syndrome

Identifiers

PMID41427050
PMCPMC12714639

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Registered trials

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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.