Baseline clusters and the response to positive airway pressure treatment in obstructive sleep apnoea patients: longitudinal data from the European Sleep Apnea Database cohort

INTRODUCTION: The European Sleep Apnea Database was used to identify distinguishable obstructive sleep apnoea (OSA) phenotypes and to investigate the clinical outcome during positive airway pressure (PAP) treatment. METHOD: Prospective OSA patient data were recruited from 35 sleep clinics in 21 European countries. Unsupervised cluster analysis (anthropometrics, clinical variables) was performed in a random sample (n=5000). Subsequently, all patients were assigned to the clusters using a conditional inference tree classifier. Responses to PAP treatment change in apnoea severity and Epworth sleepiness scale (ESS) were assessed in relation to baseline patient clusters and at short- and long-term follow-up. RESULTS: At baseline, 20 164 patients were assigned (mean age 54.1±12.2 years, 73% male, median apnoea–hypopnoea index (AHI) 27.3 (interquartile range (IQR) 14.1–49.3) events·h(−1), and ESS 9.8±5.3) to seven distinct clusters based on anthropometrics, comorbidities and symptoms. At PAP follow-up (median 210 [IQR 134–465] days), the observed AHI reduction (n=1075) was similar, whereas the ESS response (n=3938) varied: largest reduction in cluster 3 (young healthy symptomatic males) and 6 (symptomatic males with psychiatric disorders, −5.0 and −5.1 units, respectively (all p<0.01), limited reduction in clusters 2 (obese males with systemic hypertension) and 5 (elderly multimorbid obese males, −4.2 (p<0.05) and −3.7 (p<0.001), respectively). Residual sleepiness in cluster 5 was particularly evident at long-term follow-up (p<0.05). CONCLUSION: OSA patients can be classified into clusters based on clinically identifiable features. Importantly, these clusters may be useful for prediction of both short- and long-term responses to PAP intervention.