Evidence map›Paper›PMID 40468362›Full record

ArticleBMC women's health2025

Serum creatinine as a risk factor for endometriosis: insights from cross-sectional study, mendelian randomization analysis, and diagnostic model study.

Yanan Duan, Yiqing Peng, Aiping Chen

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Article in BMC women's health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yanan DuanDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, 266000, Shandong Province, China.
Yiqing PengDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Jining Medical University, Jining, 270000, Shandong Province, China.
Aiping ChenDepartment of Obstetrics and Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, 266000, Shandong Province, China. chenaiping516@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEndometriosis (EM) is a prevalent gynecological condition impacting roughly 10% of women of reproductive age worldwide, causing chronic pain, infertility, and menstrual irregularities. Traditional diagnosis typically relies on invasive surgical methods, and non-invasive diagnostic techniques remain underdeveloped. This study seeks to investigate the association between creatinine levels and endometriosis through cross-sectional analysis and mendelian randomization (MR) analysis, while also developing and assessing diagnostic models.

methodThis research integrates data from the NHANES database (1999-2006) and the affiliated hospital of Jining Medical College in China. The study cohort consists of women aged 20-60, with data collection covering age, race, education level, marital status, family income, weight, height, body mass index(BMI), and serum creatinine levels. Logistic regression models were used for univariate and multivariate analyses. Bidirectional MR analysis, utilizing genetic variation data from Large Genome Association Studies (GWAS), was performed to evaluate causal relationships using the inverse variance weighted (IVW) method, complemented by sensitivity analysis. A diagnostic model based on data from top-tier hospitals in China was constructed and its performance assessed through receiver operating characteristic(ROC) curves, area under the curve(AUC) values, and calibration curves.

resultIn the NHANES dataset, univariate analysis indicated a significant correlation between creatinine levels and endometriosis (OR = 1.01, 95% CI: 1.00-1.01, P = 0.0048), while multivariate analysis maintained significant results after adjustment (OR = 1.00, 95% CI: 1.00-1.01, P = 0.0431). Bidirectional MR analysis demonstrated a causal relationship between creatinine levels and endometriosis, with a positive IVW result of 1.001 (95% CI: 1.00-1.002, P = 0.0350). In the chinese tertiary hospital dataset, the AUC for the diagnostic model on both training and validation sets were 0.721 and 0.730, respectively. An increase of 10 μmol/L in creatinine levels raised the risk of endometriosis by approximately 8% (OR = 1.08, 95% CI: 1.07-1.09, P < 0.001).

conclusionThis study establishes a significant link between creatinine levels and endometriosis, confirming creatinine as an independent risk factor. Elevated creatinine levels could be used as non-invasive biomarkers for the early detection and diagnosis of endometriosis. Future research should aim to validate these findings in larger, multicenter studies and delve into the specific biological mechanisms, paving the way for novel therapeutic strategies.

Indexed as

CreatinineEndometriosisAdultBiomarkersChinaCross-Sectional StudiesFemaleHumansMendelian Randomization AnalysisMiddle AgedNutrition SurveysRisk FactorsYoung AdultBiomarkersCreatinineDiagnostic modelEndometriosisMendelian randomizationSerum creatinine

Identifiers

PMID40468362
PMCPMC12135542

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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.