Background: Continuous positive airway pressure (CPAP) is an effective treatment for obstructive sleep apnea (OSA), but treatment compliance is often unsatisfactory. Objective: The aim of this study was to assess the effectiveness and cost-effectiveness of an intelligent monitoring system for improving CPAP compliance. Methods: This is a prospective, open label, parallel, randomized controlled trial including 60 newly diagnosed patients with OSA requiring CPAP (Apnea–Hypopnea Index [AHI] >15) from Lleida, Spain. Participants were randomized (1:1) to standard management or the MiSAOS intelligent monitoring system, involving (1) early compliance detection, thus providing measures of patient’s CPAP compliance from the very first days of usage; (2) machine learning–based prediction of midterm future CPAP compliance; and (3) rule-based recommendations for the patient (app) and care team. Clinical and anthropometric variables, daytime sleepiness, and quality of life were recorded at baseline and after 6 months, together with patient’s compliance, satisfaction, and health care costs. Results: Randomized patients had a mean age of 57 (SD 11) years, mean AHI of 50 (SD 27), and 13% (8/60) were women. Patients in the intervention arm had a mean (95% CI) of 1.14 (0.04-2.23) hours/day higher adjusted CPAP compliance than controls (P=.047). Patients’ satisfaction was excellent in both arms, and up to 88% (15/17) of intervention patients reported willingness to keep using the MiSAOS app in the future. No significant differences were found in costs (control: mean €90.2 (SD 53.14) (US $105.76 [SD 62.31]); intervention: mean €96.2 (SD 62.13) (US $112.70 [SD 72.85]); P=.70; €1=US $1.17 was considered throughout). Overall costs combined with results on compliance demonstrated cost-effectiveness in a bootstrap-based simulation analysis. Conclusions: A machine learning–based intelligent monitoring system increased daily compliance, reported excellent patient satisfaction similar to that reported in usual care, and did not incur in a substantial increase in costs, thus proving cost-effectiveness. This study supports the implementation of intelligent eHealth frameworks for the management of patients with CPAP-treated OSA and confirms the value of patients’ empowerment in the management of chronic diseases. Trial Registration: ClinicalTrials.gov NCT03116958; https://clinicaltrials.gov/ct2/show/NCT03116958

Continuous positive airway pressure (CPAP) has a heterogeneous effect on blood pressure (BP) in hypertensive patients. However, the effect of CPAP on BP in hypertensive subjects regarding circadian BP pattern has never been explored. This study aimed to assess the effect of CPAP on BP, taking into consideration the circadian BP pattern in untreated hypertensive patients.This study is apost hocanalysis of the Spanish Cohort for the Study of the Effect of CPAP in Hypertension (CEPECTA), a multicentre, randomised trial of CPAPversussham-CPAP in patients with new-onset systemic hypertension and an apnoea–hypopnoea index >15 events·h⁻¹. We included patients for whom 24-h ambulatory BP monitoring (ABPM) data were available at baseline and 12 weeks after the intervention. Subjects were classified based on the dipping ratio (dipper/non-dipper). We evaluated the effect of CPAP on ABPM parameters after 12 weeks of treatment.Overall, 272 hypertensive subjects were included in the analysis (113 dippers and 159 non-dippers). Baseline clinical and polysomnographic variables were similar between the groups. CPAP treatment in non-dipper patients was associated with reductions in 24-h ambulatory BP variables and night-time ambulatory BP measurements. However, a nonsignificant effect was reported in the dipper group. The differential effects of CPAP between the groups were −2.99 mmHg (95% CI −5.92­– −0.06 mmHg) for the mean 24-h ambulatory BP and −5.35 mmHg (95% CI −9.01– −1.69 mmHg) for the mean night-time ambulatory BP.Our results show a differential effect of CPAP treatment on BP in hypertensive patients depending on the circadian pattern. Only non-dipper patients benefited from CPAP treatment in terms of BP reduction.

We evaluated the influence of untreated obstructive sleep apnoea (OSA) on the magnitude of cognitive decline and on several cognitive subdomains in patients with mild-to-moderate Alzheimer's disease.In this single-centre study, 144 patients were recruited prospectively from a cognitive impairment unit and underwent overnight polysomnography.The mean±sdchange in the Alzheimer's Disease Assessment Scale cognitive subscale (ADAS-cog) score at 12 months was 3.19±5.61 in the non-OSA group and 0.08±5.62 in the OSA group, with an intergroup difference of −3.36 (95% CI 0.19–0.16; p=0.002). We did not observe a significant difference in any cognitive subdomains at 12 months. Regarding Mini-Mental State Examination scores at 36 months, the mean change was 1.69 (95% CI −1.26–4.64; p=0.445). No significant differences were found among different OSA severity groups.We observed that ADAS-cog scores were better in the OSA group than in the non-OSA group by a statistically but not clinically significant margin. We did not find differences in the different cognitive subdomains after 1 year or in global cognition after 3 years of follow-up.

Background: Continuous positive airway pressure (CPAP) treatment reduces blood pressure (BP) in obstructive sleep apnoea (OSA) and hypertensive patients, but there is a lack of data about the effects of CPAP on the BP in normotensive patients. Objective: The aim of the study was to evaluate BP changes in normotensive OSA individuals receiving CPAP treatment. Methods: We selected 131 normotensive outpatients with an apnoea/hypopnoea index (AHI) greater than 15 events/hour who required CPAP treatment. All patients underwent a sleep study and 24-h ambulatory BP monitoring (ABPM) at baseline and after 6 months. In addition, the patients were assessed for the presence of baseline masked hypertension, defined as office BP less than 140/90 mmHg and increased BP on 24-h ABPM (mean 24-h BP ≥130/80 mmHg). Results: After 6 months of CPAP treatment, a mild reduction in all 24-h ABPM variables was observed, but only the mean 24-h DBP [−1.39 mmHg, 95% confidence interval (95% CI), −2.50 to −0.27], mean daytime DBP (−1.39 mmHg, 95% CI −2.56 to −0.22) and the mean 24-h ambulatory BP (−1.80 mmHg, 95% CI, −3.16 to −0.44) reached statistical significance. The reduction was primarily due to BP changes in individuals with masked hypertension who displayed a mean BP reduction of −4.78 mmHg (−7.25 to −2.30 mmHg). Consistent with a circadian BP pattern, a reduction in mean nocturnal BP of −4.73 mmHg (−7.39 to −2.06 mmHg) was observed at 6 months in nondippers; in contrast, the mean nocturnal BP in dippers increased by 2.61 mmHg (0.60–4.62 mmHg). Conclusion: Our findings suggest that the CPAP effects may be different in normotensive outpatients depending on the presence of undiagnosed masked hypertension and the dipping pattern. Therefore, it is important to consider measuring ABPM in this type of patient.

Background: Continuous positive airway pressure (CPAP) is an effective treatment for obstructive sleep apnoea (OSA), but an evaluation of CPAP adherence is rarely carried out among patients with acute coronary syndrome (ACS). The goals of the study are to analyse long-term adherence and identify the predictors of non-compliance with CPAP treatment for patients with non-sleepy OSA and ACS. Methods: This is an ancillary study of the ISAACC study, which is a multicentre, prospective, open-label, parallel, randomized, and controlled trial (NCT01335087) in patients with hospital admission for ACS. For the purpose of this study, only non-sleepy patients with moderate or severe OSA and randomized to receive CPAP treatment were analysed (n=357). Non-compliance was defined as CPAP dropout or average cumulative CPAP use of <4 hours/night. Multivariable logistic regression analysis was performed to identify predictors of CPAP adherence. Results: Adherence to treatment was 35.3% at 12 months. According to the unadjusted analysis, higher apnoea-hypopnea index (AHI) (P<0.001) and oxygen desaturation index (ODI) (P=0.001) were associated with a lower risk of non-compliance. Multivariable logistic regression analysis showed that high AHI (P=0.0051), high amounts of smoking pack-year (P=0.0170), and long intensive care unit (ICU) stays (P=0.0263) were associated with lower odds of non-compliance. It also showed a significant interaction between ACS history and age (P=0.0131), such that young patients with their first ACS showed significantly lower odds of CPAP non-compliance than patients with recurrent ACS and significantly lower odds of CPAP non-compliance were associated with ageing only in patients with recurrent ACS. Conclusions: Protective factors against non-compliance with CPAP treatment in non-sleepy patients with ACS were illness severity (high values of AHI or ICU stay length) or smoking amount. Patients with no previous history of ACS showed lower odds of CPAP non-compliance than patients with a recurrent ACS with younger age.