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

Jun Chen, Shuang-Bin Yang, Juanmei Liu, Zi-Hui Tang, Jun Chen, Shuang-Bin Yang, Juanmei Liu, Zi-Hui Tang

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.

Keywords: Bayesian estimation; Diabetic cardiovascular autonomic neuropathy; Heart rate variability; Without a gold standard.

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