The association between cardiometabolic index (CMI) and metabolic dysfunction-associated steatotic liver disease (MASLD): a systematic review and meta-analysis.

[BACKGROUND] Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health challenge, with cardiovascular mortality. The cardiometabolic index (CMI), a biomarker derived by multiplying the waist-to-height ratio (WHtR) with the triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDL-C), shows promise as a predictive tool for MASLD. This study aims to systematically evaluate the association between CMI and MASLD.

[METHODS] A comprehensive search of PubMed, Scopus, Embase, and Web of Science was conducted up to January 2025. Studies reporting the association between CMI and MASLD in adults were included. For meta-analysis, odds ratios (OR) and standardized mean differences (SMD) were computed. Heterogeneity was assessed using I², and publication bias was evaluated via Egger’s test. Subgroup analyses and meta-regressions explored sources of heterogeneity.

[RESULTS] Ten studies with 51,037 participants were included. Individuals with MASLD had significantly higher CMI (SMD = 1.22, 95%CI: 0.99, 1.45; I = 98.5%) compared to those without MASLD. Studies with higher smoking prevalence and elevated systolic and diastolic blood pressure showed a lower SMD of CMI in MASLD compared to non-MASLD patients, while meta-regression indicated that factors such as age, gender, body mass index, fasting blood glucose, lipid profile, and liver function tests were not significant sources of heterogeneity. Each 1-SD increase in CMI was associated with roughly 2-fold higher odds of MASLD (OR = 2.26, 95%CI: 1.75, 2.91; I² = 96.6%). Patients in the highest CMI quartile had substantially greater odds of MASLD compared to the lowest quartile (OR = 7.66, 95%CI: 4.84, 12.10; I² = 90.2%). The pooled area under the curve (AUC) for CMI in predicting MASLD was 0.81, 95%CI: 0.79–0.84.

[CONCLUSIONS] CMI correlates strongly with MASLD, suggesting its potential as a non-invasive tool for early detection and risk stratification. Future research should investigate whether interventions that reduce CMI can slow disease progression and prevent complications such as cirrhosis or hepatocellular carcinoma. Future research should focus on refining CMI cut-off values and validating its applicability across diverse populations.

[SUPPLEMENTARY INFORMATION] The online version contains supplementary material available at 10.1186/s13098-025-01912-4.