Abstract
BACKGROUND: Obstructive sleep apnea (OSA) is a modifiable risk factor for acute coronary syndrome (ACS), with high prevalence but low diagnostic rates. Therefore, it is particularly important to develop strategies for better screening for OSA in newly admitted ACS patients. METHODS: From March 2017 to October 2019, consecutive eligible patients with ACS underwent cardiorespiratory polygraphy during hospitalization. OSA was defined as an apnea-hypopnea index (AHI) ≥ 15 events/h. All anthropometric and oropharyngeal parameters are measured by specialist nurses. RESULTS: Finally, 761 ACS patients were recruited in the present study. Prevalence of moderate/severe OSA was 53.2% based on diagnostic criteria of AHI ≥ 15. Correlation analysis illustrated that AHI was positively correlated with anthropometric characteristics. In the multivariate model, only micrognathia (OR 2.02, 95% CI 1.02-4.00, P = 0.044), waist circumference (OR 1.08, 95% CI 1.04-1.11, P < 0.001), and STOP-BANG Questionnaire (SBQ) score (OR 1.45, 95% CI 1.27-1.66, P < 0.001) were independently associated with the prevalence of OSA. Receiver operating characteristic curve (ROC) analysis showed that the area under curve (AUC) of multivariable joint diagnosis (waist circumference, micrognathia combined with SBQ) was significantly better than the AUC of Epworth Sleepiness Scale (ESS) and SBQ (p < 0.0001 and p = 0.0002, respectively), and the results showed that AUC was 0.728. Under the optimal truncation value, the sensitivity was 73%, and the specificity was 61%, which was higher than the single index. Finally, we also constructed a nomogram model based on multiple logistic regression, to easily determine the probability of OSA in ACS patients. CONCLUSIONS: The new screening tool has greater power than single questionnaire or measurements in screening of OSA among ACS patients. TRIAL REGISTRATION: Clinicaltrials.gov identifier NCT03362385, registered December 5, 2017.