Frontiers in medicine · 2025
Risk prediction model of early vascular aging based on nomogram in patients with type 2 diabetes mellitus: a cross-sectional study in a Chinese population.
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Zhao Xin, Sun Jianbin, Xin Sixu, Zhang Xiaomei
Аннотация
BACKGROUND: Early Vascular Aging (EVA) is a significant risk factor for cardiovascular disease in patients with type 2 diabetes mellitus (T2DM). This study aimed to explore the risk factors for EVA in patients with T2DM in China and develop nomograms for EVA in patients with T2DM.
METHODS: We retrospectively analyzed data from 1,543 patients with T2DM. The patients were divided into non-EVA and EVA groups based on ankle-brachial pulse wave velocity (PWV).
RESULTS: (1) The risk factors for EVA in male included longer diabetic duration (OR = 1.09 95 CI% 1.06-1.11), high blood pressure (OR = 2.06, 95 CI% 1.51-2.81), smoking (OR = 1.96 95 CI% 1.17-3.27), diabetic nephropathy (DN; OR = 1.60 95 CI% 1.10-2.32), and diabetic retinopathy (DR; OR = 2.93 95 CI% 2.00-4.29). The risk factors for EVA in females included longer duration of diabetes (OR = 1.04 95 CI% 1.01-1.07), smoking (OR = 2.02, 95 CI% 1.13, 3.59), high blood pressure (OR = 1.91, 95 CI% 1.22-2.79), diabetic nephropathy (OR = 1.61 95 CI% 1.02-2.52), and diabetic retinopathy (OR = 3.61 95 CI% 2.24-5.74). (2) The results showed that the nomogram-based risk prediction model achieved an area under the curve of 0.73 for men and 0.74 for women. The overall predictive accuracy of the nomogram for EVA in men was 67.85%, and its specificity and sensitivity were 73.74 and 62.33%, respectively. The overall predictive accuracy of the nomogram for EVA in females was 69.29%, and its specificity and sensitivity were 66.55 and 71.93%, respectively.
CONCLUSIONS: The nomogram-based risk prediction model for EVA in T2DM patients showed good discriminative ability and predictive accuracy. It provides clinicians with a reliable tool to estimate the risk of EVA in T2DM patients, allowing for early interventions and reduction of cardiovascular diseases in high-risk populations.
METHODS: We retrospectively analyzed data from 1,543 patients with T2DM. The patients were divided into non-EVA and EVA groups based on ankle-brachial pulse wave velocity (PWV).
RESULTS: (1) The risk factors for EVA in male included longer diabetic duration (OR = 1.09 95 CI% 1.06-1.11), high blood pressure (OR = 2.06, 95 CI% 1.51-2.81), smoking (OR = 1.96 95 CI% 1.17-3.27), diabetic nephropathy (DN; OR = 1.60 95 CI% 1.10-2.32), and diabetic retinopathy (DR; OR = 2.93 95 CI% 2.00-4.29). The risk factors for EVA in females included longer duration of diabetes (OR = 1.04 95 CI% 1.01-1.07), smoking (OR = 2.02, 95 CI% 1.13, 3.59), high blood pressure (OR = 1.91, 95 CI% 1.22-2.79), diabetic nephropathy (OR = 1.61 95 CI% 1.02-2.52), and diabetic retinopathy (OR = 3.61 95 CI% 2.24-5.74). (2) The results showed that the nomogram-based risk prediction model achieved an area under the curve of 0.73 for men and 0.74 for women. The overall predictive accuracy of the nomogram for EVA in men was 67.85%, and its specificity and sensitivity were 73.74 and 62.33%, respectively. The overall predictive accuracy of the nomogram for EVA in females was 69.29%, and its specificity and sensitivity were 66.55 and 71.93%, respectively.
CONCLUSIONS: The nomogram-based risk prediction model for EVA in T2DM patients showed good discriminative ability and predictive accuracy. It provides clinicians with a reliable tool to estimate the risk of EVA in T2DM patients, allowing for early interventions and reduction of cardiovascular diseases in high-risk populations.