Sleep apnoea phenotypes in women: A cluster analysis from the ESADA cohort

• Published in: Sleep medicine Vol. 124; pp. 494 - 501
• Main Authors: Pataka, A., Pepin, J.L., Bonsignore, M.R., Schiza, S., Saaresranta, T., Bouloukaki, I., Steiropoulos, P., Trakada, G., Riha, R., Dogas, Z., Testelmans, D., Basoglu, O.K., Mihaicuta, S., Fanfulla, F., Grote, L., Bailly, S., Verbraecken, J., Petiet, E., Fietze, I., Penzel, T., Ludka, O., McNicholas, W.T., Ryan, S., Riha, R.L., Kvamme, J.A., Hedner, J., Zou, D., Hertegonne, K., Pevernagie, D., Pépin, J.L., Tamisier, R., Hein, H., Tasbakan, M.S., Buskova, J., Joppa, P., Staats, R., Kalkanis, A., Gouveris, H., Ludwig, K., Lombardi, C., Parati, G., Francesco, Fanfulla, Drummond, M., van Zeller, M., Randerath, W., Treml, M., Pecotic, R., Anttalainen, U., Sliwinski, P.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01-12-2024; Elsevier
• Subjects: Cluster analysis; Co-morbidities; Female; Gender; Life Sciences; Obstructive sleep apnoea; OSA; PAP; Phenotypes; Sex; Treatment; Women; Women; Cluster analysis; Phenotypes; Obstructive sleep apnoea; Treatment; Co-morbidities; Sex; Female; Gender; OSA; PAP
• ISSN: 1389-9457; 1878-5506; 1878-5506
• DOI: 10.1016/j.sleep.2024.10.015

and Objectives: The clinical presentation of Obstructive Sleep Apnoea (OSA) differs between genders. This study aimed to identify the specific OSA phenotypes of women in the European Sleep Apnoea Database (ESADA) cohort.
Latent class cluster analysis was applied to data from 9710 female OSA patients. Variables used included age, Body Mass Index (BMI), Epworth Sleepiness Scale (ESS), comorbidities (cardiovascular, pulmonary, psychiatric, metabolic, other) and the Apnoea Hypopnea Index (AHI).
Four different clusters were found: Cluster 1“Women with ischemic heart disease” (38.3 %):middle aged (59 years [53–65]),overweight to obese (BMI 30.1 kg/m2 [26.9–33.5]), AHI 22.9 events/h[17.4–30], ESS 9 [5,12] with the highest prevalence of ischemic heart disease (56 %). Cluster 2“Elderly women with comorbidities” (23 %): oldest (66 years[60–71]), obese (BMI 36 kg/m2 [31.6–40.4]),AHI 46 events/h [30–60.1]),ESS 9 [6-13] with the highest prevalence of comorbidities. Cluster 3“Sleepy obese women” (16.2 %): the youngest (49 years [42–55]), sleepiest (ESS 12 [8-16]), most obese(BMI 43 kg/m2[37.6–48.9]) females with severe OSA (AHI 53.3 events/h [32–80.5]). Cluster 4 “Women with mild OSA and low comorbidities" (22.5 %): middle aged (53.5 years [46–60]) with BMI 29 kg/m2[25–34.1],ESS9 [5,13]),AHI 8.6events/h[6.9–10.4])and low prevalence of comorbidities. The distribution of the clusters differed across Europe. PAP administration was higher in Clusters 2 and 3 but low in Cluster 4.
Four distinct female phenotypes were identified with different clinical presentation and comorbidities. Sex-based phenotyping may provide improved risk stratification and personalized treatment.
•OSA in females has different clinical presentation and sleep study findings.•Latent class cluster analysis was applied to 9710 female patients of the ESADA.•Four clusters with different clinical presentation and comorbidities were found.•Gender-based phenotyping is warranted to better identify and treat OSA in women.