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Cardiorenal-metabolic phenotypes and risks of mortality and cardiovascular outcomes in type 2 diabetes: a retrospective cohort study.

Jul 2026 · Diabetes Research and Clinical Practice · Vol 239, pp. 113472 · 0 citations · 44 references
Medicine

TL;DR

This transparent, rule-based classification summarized differences in recorded mortality and cardiovascular outcomes in T2D but should be interpreted as a descriptive framework rather than a validated prediction tool.

Abstract

Aims

To examine whether a transparent, rule-based cardiorenal-metabolic classification distinguished mortality and cardiovascular outcome patterns among adults with type 2 diabetes (T2D).

Methods

This retrospective cohort included 61,250 adults with T2D from Hong Kong DM2016. Three phenotypes were defined from baseline cardiorenal burden and hypertension: lower-risk metabolic, hypertensive metabolic, and cardiorenal disease. Outcomes were all-cause and cardiovascular mortality, myocardial infarction, stroke, heart failure, and atrial fibrillation. Because individual follow-up times were unavailable in the public dataset, cardiovascular event outcomes were evaluated in outcome-specific at-risk cohorts. Modified Poisson regression estimated risk ratios (RRs).

Results

The phenotypes comprised 29.4%, 20.9%, and 49.8% of participants, respectively. Compared with the lower-risk metabolic phenotype, the cardiorenal disease phenotype was associated with higher risks of all six outcomes; adjusted RRs ranged from 2.59 (95% CI, 2.36-2.84) for all-cause mortality to 9.17 (95% CI, 6.50-12.94) for myocardial infarction. The hypertensive metabolic phenotype was associated with myocardial infarction (RR, 1.56; 95% CI, 1.02-2.39), stroke (RR, 7.63; 95% CI, 5.27-11.06), and atrial fibrillation (RR, 1.76; 95% CI, 1.30-2.38), but not heart failure.

Conclusions

This transparent, rule-based classification summarized differences in recorded mortality and cardiovascular outcomes in T2D but should be interpreted as a descriptive framework rather than a validated prediction tool.

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