Abstract
OBJECTIVES: To investigate the predictors influencing the advancement of 10-year cardiovascular disease (CVD) risk after infection with Corona Virus Disease 2019 (COVID-19) in type 2 diabetes patients, and to provide a theoretical basis for an early intervention program for the cardiovascular dimension of the cardiovascular-kidney-metabolic syndrome (CKM syndrome). METHODS: A cohort of 378 individuals diagnosed with type 2 diabetes was analyzed retrospectively. The progression of 10-year CVD risk was characterized by an elevation in the 10-year CVD risk category, as determined by the SCORE2-Diabetes scoring system, in type 2 diabetic infected with COVID-19. Factors influencing 10-year CVD risk progression were evaluated through univariate and multivariate stepwise logistic regression. Nonlinear relationships between predictors and 10-year CVD progression were assessed using restricted cubic spline (RCS) analysis, subsequently followed by an analysis of threshold effects. Finally, the predictive performance of various factor combinations for 10-year CVD risk progression during the post-acute COVID-19 phase in type 2 diabetes mellitus cohorts was measured by area under roc curve (AUC). RESULTS: After infection with COVID-19, 12.2% (n=46) experienced progression in their 10-year CVD risk category. In multifactorial stepwise logistic regression, alcohol consumption [odds ratio (OR) 2.10, 95% confidence interval (CI) 1.02-4.34], estimated glomerular filtration rate (eGFR) (OR 0.96, 95% CI 0.94-0.99) and high-sensitivity C-reactive protein (hs-CRP) (OR 1.33, 95% CI 1.13-1.57), were found to be significantly linked to the progression of 10-year CVD risk. Restricted cubic spline analysis (RCS) demonstrated a nonlinear correlation between hs-CRP and 10-year CVD risk progression with a threshold of 3.0 mg/L. 10-year CVD risk was significantly higher with increasing hs-CRP levels at hs-CRP < 3.0 mg/L (OR 2.28, 95% CI 1.48-3.55), and the two-stage model significantly superior to a single linear model (P = 0.028 for log-likelihood ratio). Among the different combinations of models for alcohol consumption, hs-CRP, and eGFR, the full model combination of all three had the best predictive effect (AUC = 0.749). CONCLUSION: Alcohol consumption and elevated hs-CRP were associated with increased cardiovascular risk progression, while higher eGFR levels were inversely associated with risk progression.