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Published on: December 6, 2016
Sleep breathing impairment index predicts incident atrial fibrillation in obstructive sleep apnea: A prospective
Lixia Wang1, Xinjie Hui1, Wenhao Cao1
1Department of Pulmonary and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Objectives:
Respiratory-event-associated hypoxia is crucial in cardiovascular comorbidities of obstructive sleep apnea (OSA). Intermittent hypoxia is an independent risk factor for atrial fibrillation (AF). The sleep breathing impairment index (SBII) is a novel metric that quantifies respiratory events and hypoxia, showing exceptional efficacy in predicting cardiovascular diseases. This study aims to evaluate the association between SBII and AF in OSA patients and compare the predictive performance of various OSA severity indices in predicting incident AF.
Methods:
This study included 1660 OSA patients without pre-existing AF from the Sleep Heart Health Study. Baseline SBII values were stratified into quartiles. Multivariate logistic regression analysis and restricted cubic spline analysis were conducted to explore the association between SBII and incident AF. Harrell's concordance statistic (C-statistic) was performed to compare the predictive value of SBII against other OSA severity indices.
Results:
During a mean follow-up of 5.3 years, 190 (11.5 %) OSA patients developed AF. SBII and hypoxic burden (HB) were associated with an increased risk of incident AF, with adjusted odds ratios of 1.87 (95 %CI: 1.14, 3.11; P = 0.015) and 2.01 (95 %CI: 1.20, 3.41; P = 0.009) for the third and fourth quartiles of SBII, respectively, and 1.70 (95 %CI: 1.04, 2.81; P = 0.038) for the fourth quartile of HB. Moreover, SBII had the largest C-statistic (0.75, 95 % CI: 0.709, 0.782) compared with HB, AHI, and ODI.
Conclusion:
This study demonstrated that elevated SBII and HB levels increased the risk of incident AF in OSA patients, with SBII outperforming other OSA severity indices in predicting AF.
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