医学
危险系数
置信区间
比例危险模型
内科学
疾病
心脏病学
人口
虚弱指数
急诊医学
环境卫生
作者
Xinjie Hui,Wenhao Cao,Zeyu Xu,Junwei Guo,Jinmei Luo,Yi Xiao
摘要
Abstract Background and Objective The 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. Methods Samples 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. Results SBII 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. Conclusion This 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.
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