In 514 adults with diabetes in a high-altitude population, 5 data-driven subtypes were reproducible and exhibited distinct phenotypes with differential complication burdens.
Cross-Sectional (n=514)
Data-driven diabetes subtypes are reproducible in high-altitude populations and correlate with specific complications like albuminuria and peripheral arterial disease.
Introduction and Objective: Evidence for established data-driven diabetes subtypes in high-altitude populations is limited. We examined subtype reproducibility and associations with complications in a high-altitude population. Methods: We conducted a cross-sectional analysis of 514 adults with diabetes in the Xizang Autonomous Region, China. Participants were classified into 5 subtypes (SAID, SIDD, SIRD, MOD, and MARD) using a sex-specific nearest-centroid approach. Complication associations were evaluated by logistic regression adjusted for age, sex, diabetes duration, and smoking. Results: All 5 subtypes were reproduced with distinct phenotypes. Subtype-specific associations with albuminuria and peripheral arterial disease were observed. Conclusion: Established diabetes subtypes are reproducible in a high-altitude population and exhibit distinct phenotypes with differential complication burdens. Disclosure W. Zhao: None. Z. Zeding: None. F. Zhang: None. X. Lv: None. Funding Xizang Natural Science Foundation (XZZR202402088(W))
ZHAO et al. (Fri,) conducted a cross-sectional in Diabetes (n=514). Data-driven diabetes subtypes was evaluated on Reproducibility of subtypes and associations with complications. In 514 adults with diabetes in a high-altitude population, 5 data-driven subtypes were reproducible and exhibited distinct phenotypes with differential complication burdens.
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