Objective <p>This study aimed to evaluate the prognostic value of the Chinese Visceral Adiposity Index (CVAI) for all-cause mortality in the high-risk population with coexisting type 2 diabetes mellitus (T2DM), heart failure (HF), and chronic kidney disease (CKD).</p> Results <p>Over a median 26-month follow-up among 442 patients, 194 deaths occurred. The highest CVAI tertile (T3) exhibited a significantly elevated mortality risk (adjusted hazard ratio [HR] = 2.806, 95% confidence interval [CI] 1.848–4.261, <i>P</i> &lt; 0.001), demonstrating a linear dose-response relationship. CVAI provided significant incremental predictive value beyond left ventricular ejection fraction (LVEF) and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Subgroup analysis revealed a significant association in patients with LVEF &lt; 40% but not in those with LVEF ≥ 40% (P for interaction = 0.049).</p>

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Chinese visceral adiposity index predicts all-cause mortality in patients with type 2 diabetes, heart failure, and chronic kidney disease: a retrospective cohort study

  • Xiang Zhao,
  • Dan Zhang,
  • Bing Zhu,
  • Yuanhao Yao,
  • Lingxiao Geng,
  • Xiang Ma,
  • Zhenyan Fu,
  • Yitong Ma

摘要

Objective

This study aimed to evaluate the prognostic value of the Chinese Visceral Adiposity Index (CVAI) for all-cause mortality in the high-risk population with coexisting type 2 diabetes mellitus (T2DM), heart failure (HF), and chronic kidney disease (CKD).

Results

Over a median 26-month follow-up among 442 patients, 194 deaths occurred. The highest CVAI tertile (T3) exhibited a significantly elevated mortality risk (adjusted hazard ratio [HR] = 2.806, 95% confidence interval [CI] 1.848–4.261, P < 0.001), demonstrating a linear dose-response relationship. CVAI provided significant incremental predictive value beyond left ventricular ejection fraction (LVEF) and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Subgroup analysis revealed a significant association in patients with LVEF < 40% but not in those with LVEF ≥ 40% (P for interaction = 0.049).