Baseline and cumulative Hemoglobin Glycation Index and incident cardiovascular and cerebrovascular events in adults with early Cardiovascular-Kidney-Metabolic Syndrome: A prospective CHARLS Cohort study.
Cardiovascular-kidney-metabolic (CKM) syndrome reflects the interrelated progression of metabolic dysfunction, chronic kidney disease, and vascular risk. The hemoglobin glycation index (HGI), a marker of inter-individual glycation heterogeneity beyond fasting glycemia, has been associated with adverse cardiovascular outcomes; however, its role in early-stage CKM syndrome remains unclear. We investigated the associations of baseline HGI and cumulative HGI (CumHGI) with incident cardiovascular and cerebrovascular events in adults with CKM stages 0-3.
We analyzed 3,783 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study (2011-2018) without baseline cardiovascular or cerebrovascular disease. Baseline HGI was assessed using a residual-based approach and analyzed as quartiles and a median-based dichotomous variable. CumHGI was calculated as the arithmetic mean of HGI measured in 2011 and 2015, reflecting average long-term glycation discordance. Incident cardiovascular and cerebrovascular events were evaluated using Kaplan-Meier curves, multivariable Cox proportional hazards models, and restricted cubic spline analyses.
During follow-up, 904 participants (23.9%) developed incident cardiovascular or cerebrovascular events. Compared with the lowest quartile of baseline HGI, adjusted hazard ratios were 1.24 (95% CI 1.02-1.49) for Q2, 1.30 (1.08-1.57) for Q3, and 1.24 (1.02-1.50) for Q4. High CumHGI was also associated with increased risk (HR 1.26, 95% CI 1.10-1.44). Associations were approximately linear across exposure levels. In models including conventional risk factors, addition of HGI or CumHGI did not materially improve discrimination (AUC 0.658 vs. 0.659 and 0.660, respectively).
Higher baseline HGI and higher cumulative HGI were associated with increased risk of incident cardiovascular and cerebrovascular events in adults with early-stage CKM syndrome. These findings suggest that glycation discordance is associated with cardiovascular risk in this preclinical population; however, HGI-derived metrics provide limited incremental discrimination beyond established risk factors and may be more informative as risk-associated biomarkers than as standalone prediction tools.
We analyzed 3,783 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study (2011-2018) without baseline cardiovascular or cerebrovascular disease. Baseline HGI was assessed using a residual-based approach and analyzed as quartiles and a median-based dichotomous variable. CumHGI was calculated as the arithmetic mean of HGI measured in 2011 and 2015, reflecting average long-term glycation discordance. Incident cardiovascular and cerebrovascular events were evaluated using Kaplan-Meier curves, multivariable Cox proportional hazards models, and restricted cubic spline analyses.
During follow-up, 904 participants (23.9%) developed incident cardiovascular or cerebrovascular events. Compared with the lowest quartile of baseline HGI, adjusted hazard ratios were 1.24 (95% CI 1.02-1.49) for Q2, 1.30 (1.08-1.57) for Q3, and 1.24 (1.02-1.50) for Q4. High CumHGI was also associated with increased risk (HR 1.26, 95% CI 1.10-1.44). Associations were approximately linear across exposure levels. In models including conventional risk factors, addition of HGI or CumHGI did not materially improve discrimination (AUC 0.658 vs. 0.659 and 0.660, respectively).
Higher baseline HGI and higher cumulative HGI were associated with increased risk of incident cardiovascular and cerebrovascular events in adults with early-stage CKM syndrome. These findings suggest that glycation discordance is associated with cardiovascular risk in this preclinical population; however, HGI-derived metrics provide limited incremental discrimination beyond established risk factors and may be more informative as risk-associated biomarkers than as standalone prediction tools.