Development and internal validation of a model predicting four year cardiovascular kidney metabolic syndrome stage progression

Development and internal validation of a model predicting four year cardiovascular kidney metabolic syndrome stage progression. Download PDF Abstract To develop a model for predicting cardiovascular-kidney-metabolic (CKM) syndrome stage progression in middle-aged and older Chinese adults and to evaluate the incremental predictive value of routinely available clinical variables beyond baseline CKM stage. This study used data from the 2011 baseline and 2015 follow-up waves of the China Health and Retirement Longitudinal Study.

Participants were eligible if they were aged 45 years or older, had baseline CKM Stage 0–3, and had ascertainable CKM stage at baseline and follow-up. The primary outcome was any upward CKM stage transition over about 4 years. Three logistic regression models were developed: Model An included baseline CKM stage, age, and sex; Model B included clinical predictors without baseline CKM stage; and Model C added penalization-selected clinical predictors to baseline CKM stage, age, and sex.

Missing candidate predictors were handled using multiple imputation by chained equations. Model A was fitted as an unweighted logistic regression model in each imputed dataset and coefficients were pooled using Rubin’s rules. Models B and C were developed using observation-completeness-weighted stacked elastic-net logistic regression across the imputed datasets.

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