Obstructive Sleep Apnea (OSA) is defined by the presence of repetitive episodes of upper airways collapse during sleep, leading to nocturnal hypoxemia, sleep fragmentation and daytime sleepiness. When untreated, OSA is a risk factor for arterial hypertension , cardiovascular and cerebrovascular diseases, road accidents and a worse quality of life. The application of a continuous positive airways pressure (CPAP) represents the first line therapy in patients with moderate to severe OSA. CPAP treatment improves daytime sleepiness and oxygen saturation, reduces cardiovascular risk, ameliorates neurobehavioral performance, improves quality of life and reduces road accidents. Despite its demonstrated efficacy, CPAP effectiveness is significantly limited by poor adherence. A closer follow up could improve CPAP adherence but it would take up more work and additional costs for sleep units.
So, on that account, the investigators propose a study to evaluate the effect of adding a telemedicine approach to traditional follow up on CPAP treatment compliance, patients' satisfaction and follow-up costs.
Telemedicine will be provided by an integrated platform composed by a web site (https://www.myosa.net/menu/login.aspx) and a smartphone application.
Methods:
Design: Prospective randomised clinical study. Follow up: 6 months. Participants: 60 patients diagnosed as OSA at St. Maria's Hospital (Sleep Unit) and requiring CPAP treatment.
Randomization: Patients will be randomized into two groups differing in CPAP treatment management (standard care vs. telemedicine). Patients of both groups will be visited in Sleep Unit at 3st and 6th month after starting CPAP treatment. The CPAP machine of both groups will be provided with a modem sending daily information about CPAP treatment compliance and adherence to MyOSA web site (this kind of information will only be actively used during the follow-up in the telemedicine group).
Intervention:
Group 1- Telemedicine Patients will be fitted with a mask , given a CPAP, and instructed on how to use the device. An intelligent software specifically developed for this project will be integrated in the web site. Using patients' baseline data (sociodemographic characteristics, presence of comorbidities, quality of life, sleepiness, pharmacologic treatment, toxic habits), the software will be capable to provide an initial prediction of the expected CPAP compliance at 6 months. Then, the real data about patients' treatment compliance sent on daily base by the CPAP machine will train the software improving the level of confidence of the prediction. Based on the prediction of compliance at six months, the software will provide specific and personalized interventions to modify or maintain this prediction. Interventions will be administered to the patients through a smartphone application connected to the web site and specifically developed for this study (MyOSA-App). Using the mobile-app patients will receive information about their own CPAP compliance and advice on how to improve compliance. All patients will be visited at 3 and 6 months at sleep unit. Patients will be checked about progress and adherence to therapy and any problems with their machine.
Group 2- Standard care Patients will be fitted with a mask and given a CPAP and instructed on how to use the device. Each CPAP machine will be provided with a modem sending daily compliance and adherence information to MyOSA web site but no intervention based on these data is planned in this group. All patients will be visited at 1, 3 and 6 months at sleep unit. Patients will be checked about progress and adherence to therapy and any problems with their machine. Information will be downloaded from their machines (CPAP adherence, applied CPAP pressure, mask leak, and residual respiratory events…).
