Hypoxic indices for obstructive sleep apnoea severity and cardiovascular disease risk prediction: A comparison and application in a community population

Author:

Hui Xinjie1ORCID,Cao Wenhao1,Xu Zeyu2ORCID,Guo Junwei1,Luo Jinmei1,Xiao Yi1ORCID

Affiliation:

1. Department of Respiratory and Critical Care Medicine Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College Beijing China

2. State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing China

Abstract

AbstractBackground and ObjectiveThe apnoea‐hypopnoea index (AHI) and oxygen desaturation index (ODI) encounter challenges in capturing the intricate relationship between obstructive sleep apnoea (OSA) and cardiovascular disease (CVD) risks. Although novel hypoxic indices have been proposed to tackle these limitations, there remains a gap in comprehensive validation and comparisons across a unified dataset.MethodsSamples were derived from the Sleep Heart Health Study (SHHS), involving 4485 participants aged over 40 years after data quality screening. The study compared several key indices, including AHI, ODI, the reconstructed hypoxic burden (rHB), the percentage of sleep time with the duration of respiratory events causing desaturation (pRED_3p) and the sleep breathing impairment index (SBII), in relation to CVD mortality and morbidity risks. Adjusted Cox proportional models were employed to calculate hazard ratios (HRs) for each index, and comparisons were performed.ResultsSBII and pRED_3p exhibited significant correlations with both CVD mortality and morbidity, with SBII showing the highest adjusted HR (95% confidence interval) for mortality (2.04 [1.25, 3.34]) and pRED_3p for morbidity (1.43 [1.09‐1.88]). In contrast, rHB was only significant in predicting CVD mortality (1.63 [1.05–2.53]), while AHI and ODI did not show significant correlations with CVD outcomes. The adjusted models based on SBII and pRED_3p exhibited optimal performance in the CVD mortality and morbidity datasets, respectively.ConclusionThis study identified the optimal indices for OSA‐related CVD risks prediction, SBII for mortality and pRED_3p for morbidity. The open‐source online platform provides the computation of the indices.

Funder

National Key Research and Development Program of China

National Heart, Lung, and Blood Institute

Publisher

Wiley

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