Development trajectory and influencing factors of excessive daytime sleepiness in patients with obstructive sleep apnea hypopnea syndrome

LIU Yanxiu; GUAN Lijun; PENG Jing

doi:10.12102/j.issn.1009-6493.2025.23.003

Abstract：Objective:To explore the developmental trajectory of excessive daytime sleepiness(EDS)in patients with obstructive sleep apnea hypopnea syndrome(OSAHS),and to analyze the influencing factors.Methods:Using convenience sampling,a total of 216 patients with obstructive sleep apnea hypopnea syndrome who received non-invasive positive pressure ventilation therapy in our hospital from April 2022 to February 2024 were selected as the study subjects.The Epworth Sleepiness Scale(ESS)was used to evaluate patients'daytime sleepiness at baseline,7 days,1 month,and 3 months after treatment.The optimal number of trajectory categories was analyzed and named using a growth mixture model.The clinical data of patients were collected using the hospital's electronic medical record system.Univariate analysis and multivariate Logistic regression analysis were conducted to identify independent factors influencing trajectory differences.Results:The EDS development of 216 patients could be classified into four potential trajectory categories:no EDS-remission,moderate EDS-remission,mild EDS-cure,and moderate EDS-persistence.Multivariate Logistic regression analysis results showed that body mass index,alcohol consumption history,total sleep time,apnea-hypopnea index,minimum oxygen saturation,Pittsburgh Sleep Quality Index scores,comorbid hypertension,Patients' Health Questionnaire Depression Scale-9 item scores,and 7-item Generalized Anxiety Disorder scores were independent factors influencing the trajectory of EDS development(P<0.05).Conclusions:Patients with obstructive sleep apnea hypopnea syndrome exhibited certain heterogeneity in the development trajectory of EDS,which was influenced by clinical factors such as alcohol consumption history,sleep monitoring indicators,and levels of anxiety and depression.It suggests that medical staff could predict the development trajectory of EDS in patients during treatment based on various influencing factors and formulate personalized nursing measures to reduce the occurrence of EDS.