ArticleEuropean journal of medical research2025
Association between cardiometabolic index and gallstones: a cross-sectional study based on NHANES 2017-2020.
Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundGallstone formation is strongly influenced by obesity, and timely detection is generally associated with improved clinical outcomes. This study aimed to investigate the relationship between cardiometabolic index (CMI) levels and gallstone occurrence.
methodsThis cross-sectional study included 3743 adults. To comprehensively assess the association between the CMI and gallstone prevalence, we employed multivariable logistic regression, smoothed curve fitting, threshold effect analysis, and subgroup stratification. Key predictors of gallstones were identified using the least absolute shrinkage and selection operator (LASSO) method. A predictive nomogram incorporating the selected variables was developed, and its diagnostic performance was evaluated using the area under the receiver operating characteristic (AUROC) curve.
resultsA significant association was observed between the CMI and the likelihood of gallstone occurrence. Smoothed curve fitting indicated a saturation effect in this relationship, with a threshold identified at a CMI value of 1.83. Subgroup analyses revealed consistent associations across most strata, except for gender-based stratification. The nomogram, developed using variables selected by LASSO and multivariable logistic regression, demonstrated good discriminative performance, with an area under the curve (AUC) of 0.720 (95% CI 0.695-0.746).
conclusionElevated CMI levels are positively associated with gallstone occurrence. The nomogram, developed using gender, age, race, hypertension, diabetes, and CMI, shows a strong association with gallstone risk and may serve as a practical tool for risk prediction.
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