Diagnostic performance analysis for diabetic cardiovascular autonomic neuropathy based on short-term heart rate variability using Bayesian methods: preliminary analysis

基于贝叶斯方法的短期心率变异性糖尿病心血管自主神经病变诊断性能分析:初步分析

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Abstract

OBJECTIVES: This study aimed to estimate the performance of diabetic cardiovascular autonomic neuropathy (DCAN) diagnostic tests in the absence of a gold standard. BACKGROUND: The DCAN prevalence is rapidly growing in all populations worldwide. No document has been reported about diagnostic performance for DCAN based on short-term HRV without a gold standard. METHODS: We conducted a cross-sectional study to perform diagnostic test in Chinese diabetic patients. A dataset contained 56 subjects who completed both the short-term HRV test and Ewing's test. Simultaneous inferences about the population prevalence and the performance of each diagnostic test were possible using the Bayesian approach. RESULTS: The HRV test had a high sensitivity (0.837 and 0.821 for independence model) and specificity (0.838 and 0.797 for dependence model) to DCAN. In addition, the non-inferiority test rejected the hypothesis that the performance of the HRV test was inferior to that of Ewing's test (P < 0.05). The estimated DCAN prevalence in our study sample was more than 0.400. CONCLUSION: Our findings provided evidence that short-term HRV were used for the DCAN diagnostic test with a high sensitivity and specificity. ClinicalTrial.org ID: NCT02461381.

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