Endocrine · 2024
Obesity-related indices as predictors of lower extremity arterial disease in type 2 diabetes mellitus.
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Xu Xin-Yue, Wu Hong-Yan, Wei Qiong
Аннотация
PURPOSE: The aim of this study was to investigate the relationship between obesity and lower extremity arterial disease (LEAD) in patients with type 2 diabetes mellitus (T2DM).
METHODS: This retrospective study included 1821 patients with type 2 diabetes: 364 patients with LEAD and 1457 patients without LEAD. The patients were divided into training and internal test cohorts in a 7:3 ratio. LASSO regression analysis was used in the training cohort to filter relevant variables. Univariate and multivariate regression analyses were conducted to assess independent risk factors. A diagnostic nomogram was constructed and its discrimination was evaluated using the area under the ROC curve (AUC). The consistency was assessed using a calibration plot. The clinical application of the nomogram was evaluated by performing a decision curve analysis (DCA) and validated by an internal test cohort of the training cohorts.
RESULTS: The LEAD group exhibited significantly higher values in obesity-related indices compared to the non-LEAD group, including waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), conicity index (CI), body adiposity index (BAI), and abdominal volume index (AVI). Multivariate analysis identified BMI, CI, BAI, and other parameters as independent risk factors for LEAD. A nomogram was constructed, and the AUC value of the nomogram was 0.746 in the training cohort and 0.663 in the internal test cohort.
CONCLUSION: Obesity-related indices are associated with LEAD in patients with T2DM. Therefore, it is important to manage waist circumference and weight to reduce the risk of LEAD in patients with T2DM.
METHODS: This retrospective study included 1821 patients with type 2 diabetes: 364 patients with LEAD and 1457 patients without LEAD. The patients were divided into training and internal test cohorts in a 7:3 ratio. LASSO regression analysis was used in the training cohort to filter relevant variables. Univariate and multivariate regression analyses were conducted to assess independent risk factors. A diagnostic nomogram was constructed and its discrimination was evaluated using the area under the ROC curve (AUC). The consistency was assessed using a calibration plot. The clinical application of the nomogram was evaluated by performing a decision curve analysis (DCA) and validated by an internal test cohort of the training cohorts.
RESULTS: The LEAD group exhibited significantly higher values in obesity-related indices compared to the non-LEAD group, including waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), conicity index (CI), body adiposity index (BAI), and abdominal volume index (AVI). Multivariate analysis identified BMI, CI, BAI, and other parameters as independent risk factors for LEAD. A nomogram was constructed, and the AUC value of the nomogram was 0.746 in the training cohort and 0.663 in the internal test cohort.
CONCLUSION: Obesity-related indices are associated with LEAD in patients with T2DM. Therefore, it is important to manage waist circumference and weight to reduce the risk of LEAD in patients with T2DM.