The diagnostic yield of a structured comorbidity workup in a real-life outpatient population with obstructive sleep apnea: a cross-sectional study

Obstructive sleep apnea (OSA) is associated with multiple systemic complications. However, evidence-based recommendations for comorbidity screening remain sparse. This study aimed to evaluate whether a structured comorbidity workup could yield clinically meaningful diagnostic gains in OSA patients. In this single-center cross-sectional observational study, patients diagnosed with OSA underwent a standardized comorbidity assessment including laboratory tests, electrocardiogram, echocardiography, abdominal ultrasound, ambulatory blood pressure monitoring, spirometry, and validated questionnaires. A total of 1904 OSA patients were included. Before evaluation, patients had a median of two [IQR 1–2] known comorbidities. The structured workup identified 3,200 newly diagnosed conditions, with a median of two [IQR 1–2] new diagnoses per patient. The most frequent comorbidities were dyslipidaemia (55%), type 2 diabetes mellitus (32%), metabolic syndrome (31%), hypertension (30%), non-alcoholic fatty liver disease(29%), hyperuricemia (29%), significant coronary artery disease (15%), arrhythmia (16%), heart failure with preserved ejection fraction (13%), obesity hypoventilation syndrome (19%), chronic obstructive pulmonary disease (8%) , asthma (12%), gastro-oesophageal reflux disease (17%), anxiety or depression (17%), and thyroid dysfunction (6%). Older age, male sex and lower mean oxygen saturation were independently associated with a higher comorbidity burden. Newly identified conditions led to pharmacological treatment changes in 40%, specialist referral in 54%, and lifestyle interventions in 85% of cases. A structured comorbidity workup in OSA patients reveals a high prevalence of previously unrecognized, clinically actionable conditions, particularly cardiometabolic disorders. Integrating systematic screening into routine OSA care may improve risk stratification, treatment optimization, and prevention of adverse outcomes (See Graphic Abstract).