Objectives/Introduction: Obstructive Sleep Apnoea (OSA) is a heterogeneous condition with different clinical presentation between genders. This study aimed to identify specific OSA phenotypes in women in the ESADA database.
Methods: Latent class analysis was applied to data from 9,710 females among 32,700 ESADA participants. Clusters were built using: age, Body Mass Index (BMI), Epworth Sleepiness Scale (ESS), co-morbidities (cardiovascular, pulmonary, psychiatric, metabolic, other) and Apnea Hypopnea Index (AHI).
Results: Four different clusters were revealed: Cluster 1 ?Women with ischemic heart disease? (38.3%):middle aged women, overweight with moderate OSA[ AHI: 22.9/h [17.4; 30]],non-sleepy(ESS: 9 [5; 12])characterized by ischemic heart disease (56%). Cluster 2 ?Elderly women with co-morbidities? (23%): elderly (66 years[60-71]), obese (36 kg/m2, [31.6-40.4]) patients with severe OSA (AHI: 46 events/h, [30 -60.1]) but no sleepiness (ESS 9, [6-13] )and the highest degree of co-morbidities. Cluster 3: ?Sleepy obese women? (16.2 %):the youngest (49 years [42- 55]), sleepiest (ESS 12, [8-16])patients with the highest BMI (43kg/m2[37.6 ; 48.9]), severe OSA (AHI 53.3 events /h, [32- 80.5]), psychiatric disease (22.7%) and asthma (13.9%).Cluster 4: ?Women with mild OSA and low co-morbidities" (22.5 %): middle aged, overweight non-sleepy (ESS: 9 [5; 13]) women with mild OSA(AHI 8.6events/h [6.9 ; 10.4])with low co-morbidities. PAP adherence was higher in Clusters 2 and 3 but low in Cluster 4. Conclusion: Four distinct women phenotypes with different clinical presentation and co-morbidities were identified. Gender-based phenotypes may be relevant for patient?s risk stratification and personalized treatment.