Polysomnographic Phenotypes of Obstructive Sleep Apnea in a Real-Life Cohort: A Pathophysiological Approach.

INTRODUCTION: Obstructive sleep apnea (OSA) is heterogeneous and complex, but its severity is still based on the apnea-hypoapnea index (AHI). The present study explores using cluster analysis (CA), the additional information provided from routine polysomnography (PSG) to optimize OSA categorization. METHODS: Cross-sectional study of OSA subjects diagnosed by PSG in a tertiary hospital sleep unit during 2016-2020. PSG, demographical, clinical variables, and comorbidities were recorded. Phenotypes were constructed from PSG variables using CA. Results are shown as median (interquartile range). RESULTS: 981 subjects were studied: 41% females, age 56 years (45-66), overall AHI 23events/h (13-42) and body mass index (BMI) 30kg/m2 (27-34). Three PSG clusters were identified: Cluster 1: "Supine and obstructive apnea predominance" (433 patients, 44%). Cluster 2: "Central, REM and shorter-hypopnea predominance" (374 patients, 38%). Cluster 3: "Severe hypoxemic burden and higher wake after sleep onset" (174 patients, 18%). Based on classical OSA severity classification, subjects are distributed among the PSG clusters as severe OSA patients (AHI≥30events/h): 46% in cluster 1, 17% in cluster 2 and 36% in cluster 3; moderate OSA (15≤AHI<30events/h): 57% in cluster 1, 34% in cluster 2 and 9% in cluster 3; mild OSA (5≤AHI<15events/h): 28% in cluster 1, 68% in cluster 2 and 4% in cluster 3. CONCLUSIONS: The CA identifies three specific PSG phenotypes that do not completely agree with classical OSA severity classification. This emphasized that using a simplistic AHI approach, the OSA severity is assessed by an incorrect or incomplete analysis of the heterogeneity of the disorder.

Telemedicine home CPAP titration and follow-up in the COVID-19 scenario.

Introduction: Continuous positive airway pressure (CPAP) titration was dramatically affected by the coronavirus disease 2019 (COVID-19) pandemic due to increased biological risk. This study aimed to compare successful CPAP adaptation and compliance with home telemedicine CPAP titration with the usual method based on face-to-face visits. Methodology: A prospective cohort using telemedicine home CPAP titration and follow-up during the COVID-19 pandemic (TC) was compared with a retrospective cohort receiving face-to-face pre-pandemic home titration (RC). The TC included a subgroup with a smartphone application (TC-APP). Successful CPAP adaptation and compliance at 1 month of follow-up were the main endpoints, while patient satisfaction and costs were secondary endpoints. Results: 210 consecutive patients were evaluated (80 RC and 130 TC). 36 patients were in the TC-APP subgroup. CPAP titration was successful in 90% in RC versus 95% in TC and 100% in TC-APP. No compliance differences between groups were found at 1  month (4.79 h·night-1 RC, 4.33  h·night-1 TC and 4.59 h·night-1 TC-APP). Mean±sd patient satisfaction out of 10 was 7.69±2.05 in RC versus 9.02±0.64 in TC (p<0.001). 64% of the TC-APP subgroup reported that their telemedicine strategy influenced an increase in CPAP use (p=0.011). CPAP adaptation with follow-up had an estimated direct staff cost per patient of EUR 19.61±8.61 in TC with no smartphone application used versus EUR 23.79±9.94 in TC-APP (p=0.048). Conclusions: Telemedicine in CPAP titration and early follow-up is equivalent to the usual care in terms of successful adaptation and compliance, while achieving greater patient satisfaction.