Purpose: Mixed events in obstructive sleep apnea (OSA) patients (mixed-OSA) indicate respiratory regulation instability and are essential for OSA pathogenesis and prognosis. It also shows a decreased compliance with continuous positive airway pressure (CPAP). Using predictors to identify mixed-OSA has significant clinical guidance for OSA precise diagnosis and treatment. This study aimed to establish a simple and accessible method for rapid screening of mixed-OSA, thus promoting OSA precise diagnosis.
Patients and Methods: A total of 907 patients with suspected OSA were screened, of which 513 OSA patients, including 344 with pure-OSA and 169 with mixed-OSA, were finally included in the study. The clinical characteristics and polysomnography (PSG) parameters of the two OSA groups were compared. Multivariate logistic regression analysis was used to investigate the factors affecting the morbidity of mixed-OSA. The receiver operating characteristic (ROC) curve was used to explore if some convenient PSG parameters can be used to predict mixed-OSA.
Results: About 33% of OSA patients were identified as mixed-OSA. Multivariate logistic regression analysis showed that apnea hypopnea index (AHI) and lowest oxygen saturation (LSO₂) were independently associated with mixed-OSA after adjusting for age, sex, body mass index (BMI), smoking, drinking, hypertension, and Epworth Sleepiness Score (ESS) (AHI: OR=1.046, 95% CI 1.032– 1.060, P < 0.001; LSO₂: OR=0.958, 95% CI 0.936– 0.981, P < 0.001). ROC curve analysis showed that AHI > 47 or LSO₂ < 77% indicated mixed-OSA. The sensitivity and specificity of AHI> 47 was 0.952 and 0.652, respectively, and 0.822 and 0.675 for LSO₂ < 77%, respectively.
Conclusion: Our research found that AHI > 47 or LSO₂ < 77% are independently associated with mixed-OSA and can be used to quickly identify the occurrence of mixed-OSA. Therefore, this study can help detect mixed-OSA and precise individual diagnosis of OSA patients.
Keywords: mixed events, apnea hypopnea index, lowest saturation, precise individual diagnosis