Development and validation of a prediction model for cardiovascular-kidney-metabolic syndrome progression: a multicenter study

心血管-肾脏-代谢综合征进展预测模型的建立与验证:一项多中心研究

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Abstract

BACKGROUND: Dysfunction of multiple systems significantly contributes to cardiovascular-kidney-metabolic syndrome (CKM). We aimed to use routine indicators to predict progression to CKM and to examine the influence of the liver metabolic axis on CKM progression. METHODS: This study was a multicenter retrospective study. We developed a model using new lipid-metabolism indicators to predict progression to CKM. Model performance was evaluated using discrimination, calibration, and decision curve analysis (DCA). Further studies on patients with diabetes and metabolic dysfunction-associated steatotic liver disease (MASLD) explored the link to CKM progression. RESULTS: A total of 21,026 participants with CKM stages 1 or 2 at baseline. The model demonstrated robust discrimination, with AUCs of 0.718 (95% CI 0.704-0.730) in the 2016-2019 cohort, 0.727 (95% CI 0.714-0.740) in the 2020 cohort, and 0.747 (95% CI 0.711-0.777) in the 2021 validation cohort. The predicted-risk quartiles were 1.8, 7.6, 11.4, and 24.9%, respectively. Subgroup analyses confirmed stable discrimination across clinical subgroups and different centers. Exploratory analyses revealed that individuals with diabetes and MASLD had the highest risk of CKM progression (odds ratio [OR] 2.13, 95% CI 1.89-2.40). CONCLUSION: We developed a reliable model that identifies individuals at risk of progressing to CKM in the real world. Our results also suggest the liver metabolism axis may be crucial in CKM deterioration.

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