Impact of Positive Airway Pressure Therapy Adherence on Outcomes in Patients with Obstructive Sleep Apnea and Chronic Obstructive Pulmonary Disease.

Rationale: The co-occurrence of obstructive sleep apnea and chronic obstructive pulmonary disease, termed overlap syndrome, has a poor prognosis. However, data on positive airway pressure (PAP) treatments and their impact on outcomes and costs are lacking. Objectives: This retrospective observational study investigated the effects of PAP on health outcomes, resource usage, and costs in patients with overlap syndrome. Methods: Deidentified adjudicated claims data for patients with overlap syndrome in the United States were linked to objectively measured PAP user data. Patients were considered adherent to PAP therapy if they met Centers for Medicare and Medicaid Services criteria for eight 90-day timeframes from device setup through 2-year follow-up. Propensity score matching was used to create comparable groups of adherent and nonadherent patients. Healthcare resource usage was based on the number of doctor visits, all-cause emergency room visits, all-cause hospitalizations, and PAP equipment and supplies, and proxy costs were obtained. Measurements and Main Results: A total of 6,810 patients were included (mean age, 60.8 yr; 56% female); 2,328 were nonadherent. Compared with the year before therapy, there were significant reductions in the number of emergency room visits, hospitalizations, and severe acute exacerbations during 2 years of PAP therapy in patients who were versus were not adherent (all P < 0.001). This improvement in health status was paralleled by a significant reduction in the associated healthcare costs. Conclusions: PAP usage by patients with overlap syndrome was associated with reduced all-cause hospitalizations and emergency room visits, severe acute exacerbations, and healthcare costs.

Association of serious adverse events with Cheyne-Stokes respiration characteristics in patients with systolic heart failure and central sleep apnoea: A SERVE-Heart Failure substudy analysis.

BACKGROUND AND OBJECTIVE: Increases in Cheyne-Stokes respiration (CSR) cycle length (CL), lung-to-periphery circulation time (LPCT) and time to peak flow (TTPF) may reflect impaired cardiac function. This retrospective analysis used an automatic algorithm to evaluate baseline CSR-related features and then determined whether these could be used to identify patients with systolic heart failure (HF) who experienced serious adverse events in the Treatment of Sleep-Disordered Breathing with Predominant Central Sleep Apnea by Adaptive Servo Ventilation in Patients with Heart Failure (SERVE-HF) substudy. METHODS: A total of 280 patients had overnight diagnostic polysomnography data available; an automated algorithm was applied to quantify CSR-related features. RESULTS: Median baseline CL, LPCT and TTPF were similar in the control (n = 152) and adaptive servo-ventilation (ASV, n = 156) groups. In both groups, CSR-related features were significantly longer in patients who did (n = 129) versus did not (n = 140) experience a primary endpoint event (all-cause death, life-saving cardiovascular intervention or unplanned hospitalization for worsening HF): CL, 61.1 versus 55.1 s (P = 0.002); LPCT, 36.5 versus 31.5 s (P < 0.001); TTPF, 15.20 versus 13.35 s (P < 0.001), respectively. This finding was independent of treatment allocation. CONCLUSION: Patients with systolic HF and central sleep apnoea who experienced serious adverse events had longer CSR CL, LPCT and TTPF. Future studies should examine an independent role for CSR-related features to enable risk stratification in systolic HF.

Association between positive airway pressure therapy adherence and health care resource utilization in patients with obstructive sleep apnea and type 2 diabetes in the United States.

STUDY OBJECTIVES: There is a complex interplay between obstructive sleep apnea (OSA) and type 2 diabetes. There are minimal data regarding the effects of treating OSA with positive airway pressure (PAP) therapy on outcomes and health care resource utilization (HCRU) in patients with OSA and type 2 diabetes. We investigated the impact of PAP adherence on HCRU and costs in this population. METHODS: A retrospective analysis was conducted with a cohort of OSA patient from a US administrative claims dataset linked to objective device data (AirView, ResMed Corp., San Diego, California). Propensity score matching was used to control for potential imbalance in baseline covariates between PAP-adherent and -nonadherent patients. Newly diagnosed patients with OSA aged ≥ 18 years with type 2 diabetes were included. PAP adherence was defined as meeting Centers for Medicare and Medicaid Services compliance criteria in all 8 90-day periods over 2 years. HCRU was based on the number of all-cause doctor visits, emergency room visits, inpatient hospitalizations, and PAP equipment and supplies. RESULTS: In years 1 and 2 of PAP therapy, HCRU was significantly lower in adherent vs nonadherent patients (number/patient for emergency room visits 0.68 ± 1.47 vs 0.99 ± 1.91 [year 1], 0.69 ± 1.43 vs 0.95 ± 1.89 [year 2]; for hospitalizations 0.16 ± 0.58 vs 0.22 ± 0.62 [year 1], 0.15 ± 0.51 vs 0.21 ± 0.74 [year 2]; all P < .001). Changes in estimated total 24-month payments were higher for nonadherent patients ($2,282, 95% confidence interval: $1,368, $3,205). CONCLUSIONS: Consistent use of PAP therapy over 2 years was associated with decreased HCRU in patients with OSA and type 2 diabetes, strongly suggesting a role for screening and treating OSA in type 2 diabetes. CITATION: Sterling KL, Cistulli PA, Linde-Zwirble W, et al. Association between positive airway pressure therapy adherence and health care resource utilization in patients with obstructive sleep apnea and type 2 diabetes in the United States. J Clin Sleep Med. 2023;19(3):563-571.

Relationship between Self-reported Sleepiness and Positive Airway Pressure Treatment Adherence in Obstructive Sleep Apnea.

Rationale: Positive airway pressure (PAP) is the first-choice treatment for obstructive sleep apnea (OSA). However, its real-world effectiveness is often questioned because of usage issues. The relationship between patient sleepiness and PAP usage has been assessed in relatively small and selected populations within the research context. Objectives: To assess the impact of patient-reported sleep outcomes, particularly self-reported sleepiness and its change during therapy, on PAP usage in the real-world setting. Methods: Deidentified data for U.S.-based patients receiving PAP therapy were examined. Eligible patients were registered in the myAir app and provided self-reported sleepiness at baseline and after 7, 14, 21, and 28 days of PAP between November 2019 and April 2020. Results: A total of 95,397 registered patients met all eligibility criteria and were included in the analysis (mean age, 49.6 ± 13.0 yr; 61.6% male). Daytime sleepiness was the most common reason for PAP therapy initiation (57.1% of patients), and 42.2% of all patients had self-reported moderate to severe OSA. Self-reported sleepiness improved with PAP therapy in most patients over the assessment period, with 62.1% of patients reporting "no" or "slight" sleepiness at Day 28. There was a dose-dependent association between improvement in self-reported sleepiness at Day 28 and PAP usage, and this finding was maintained at Day 360. Self-reported sleepiness at Day 28 was associated with achieving U.S. Centers for Medicare & Medicaid Services compliance at 90 days (approximately 90% for those with no or slight sleepiness vs. <70% for those with residual very or extreme sleepiness); average daily PAP usage over 360 days was ⩾5.0 and ⩽3.7 hours, respectively, for those with no or slight versus very or extreme sleepiness. Conclusions: This study demonstrates the feasibility of capturing patient-reported outcomes via a digital platform. Patient-reported outcomes appear to be associated with PAP usage, especially self-reported sleepiness and its response to therapy. Capturing patient-reported outcomes using digital solutions during the course of treatment has the potential to enhance patient outcomes by providing actionable insights.

Usability evaluation of a novel compact pneumatic compression device for the treatment of lymphoedema: Pilot study.

OBJECTIVE: To perform a preliminary usability evaluation of a novel, compact pneumatic compression device in patients with lymphoedema. METHODS: This open-label, single-arm trial had two phases: the first focused on the fitting of the pneumatic compression device (Aria FreeTM, Aria Health, San Diego CA, USA) and the second focused on evaluating the comfort of the entire system during a 45-min usage period. Both phases were conducted in a monitored clinical environment. Patients aged ≥18 years with a diagnosis of lower limb lymphoedema who had used a pneumatic compression device for ≥3 months were eligible. Patients rated subjective fit, comfort and usability on an 11-point Likert scale (where higher scores indicate better fit/comfort/usability). The truncated cone method was used to infer limb volume before and after therapy in phase 2. RESULTS: Twenty-four patients were screened, and 15 were enrolled (80% female; mean age 62 years); all completed both study phases. Patients rated the garment as easy to set up and fit (median score 6.5), and all reported that the therapy was comfortable (median score 10; p < 0.001 vs. reference score of 6). There was a 1.85% reduction in limb volume after device use for 45 min (p = 0.018 vs. before therapy). No safety issues were identified. CONCLUSIONS: The new pneumatic compression device fitted well, was easy to use and reduced leg oedema.

Characterizing respiratory parameters, settings, and adherence in real-world patients using adaptive servo ventilation therapy: big data analysis.

STUDY OBJECTIVES: There is minimal guidance around how to optimize inspiratory positive airway pressure (IPAP) levels during use of adaptive servo ventilation (ASV) in clinical practice. This real-world data analysis investigated the effects of IPAP and minimum pressure support settings on respiratory parameters and adherence in ASV-treated patients. METHODS: A United States-based telemonitoring database was queried for patients starting ASV between August 1, 2014 and November 30, 2019. Patients meeting the following criteria were included: United States-based patients aged ≥ 18 years; AirCurve 10 device (ResMed); and ≥ 1 session with usage of ≥ 1 hour in the first 90 days. Key outcomes were mask leak and residual apnea-hypopnea index at different IPAP settings, adherence and therapy termination rates, and respiratory parameters at different minimum pressure support settings. RESULTS: There were 63,996 patients included. Higher IPAP was associated with increased residual apnea-hypopnea index and mask leak but did not impact device usage per session (average > 6 h/day at all IPAP settings; 6.7 h/day at 95th percentile IPAP 25 cm H2O). There were no clinically relevant differences in respiratory rate, minute ventilation, leak, and residual apnea-hypopnea index across all possible minimum pressure support settings. Patients with a higher 95th percentile IPAP or with minimum pressure support of 3 cm H2O were most likely to remain on ASV therapy at 1 year. CONCLUSIONS: Our findings showed robust levels of longer-term adherence to ASV therapy in a large group of real-world patients. There were no clinically important differences in respiratory parameters across a range of pressure and pressure support settings. Future work should focus on the different phenotypes of patients using ASV therapy. CITATION: Malhotra A, Benjafield AV, Cistulli PA, et al. Characterizing respiratory parameters, settings, and adherence in real-world patients using adaptive servo ventilation therapy: big data analysis. J Clin Sleep Med. 2021;17(12):2355-2362.

Adherence with positive airway pressure therapy for obstructive sleep apnea in developing vs. developed countries: a big data study.

STUDY OBJECTIVES: Minimal focus has been placed on variations in health care delivery for obstructive sleep apnea (OSA). This study compared positive airway pressure usage in developing countries (Brazil and Mexico) vs. a developed country (United States) and investigated the impact of a patient engagement tool (myAir; ResMed, San Diego, CA) on adherence. METHODS: Deidentified data from the AirView database (ResMed) for patients receiving positive airway pressure therapy with wirelessly connected Air10 (AirSense and AirCurve) devices in Brazil, Mexico, and the United States were analyzed. Adherence was defined using US Center for Medicare and Medicaid Services (CMS) criteria (usage ≥ 4 h/night on ≥ 70% of nights in the first 90 days). RESULTS: The analysis included 4,181,490 patients (Brazil: 31,672; Mexico 16,934; United States: 4,132,884). CMS adherence over 90 days was slightly lower in Latin America vs. the United States (Brazil: 71.7%; Mexico: 66.4%; United States: 74.0%). Significantly fewer patients were using the patient engagement tool in Brazil (8.1%) and Mexico (2.8%) vs. the United States (26%; both P < .001). Patients registered to use an engagement tool had a higher rate of CMS adherence and were twice as likely to achieve CMS adherence. Average daily usage and days with usage > 4 hours in the first week were the strongest predictors of CMS adherence. Across all countries, > 80% of patients meeting CMS criteria at 3 months were still using positive airway pressure therapy at 1 year, with 1-year adherences rates of > 75%. CONCLUSIONS: Short-term and long-term positive airway pressure adherence rates in Brazil and Mexico were similar to those achieved in the United States. Patients who registered to use an engagement tool consistently had better adherence than those who did not.

Adherence in children using positive airway pressure therapy: a big-data analysis.

BACKGROUND: Positive airway pressure (PAP) has become a prominent treatment for children with sleep-disordered breathing. However, there are no large-scale studies to clarify whether PAP is well tolerated in children, and which factors are associated with better adherence to PAP therapy. In this study, we aimed to clarify adherence patterns of PAP therapy in a large paediatric population. METHODS: We did a cross-sectional big-data analysis in children from Oct 1, 2014, to Aug 1, 2018, using existing data derived from PAP devices uploaded nightly in the AirView cloud database. The AirView database is a usage tracking system available to all patients who are assigned PAP therapy, which requires consent from the patient or parent or guardian. All patients older than 4 years and younger than 18 years who used continuous or automated PAP devices were evaluated. Only patients living in the USA and enrolled with a single insurance company were included. If patients were participating in an engagement programme, programme onset must have been within 7 days of therapy onset. Our primary outcome was the proportion of patients who used PAP continuously over 90 days. The primary outcome was assessed in all patients who met the age inclusion criterion and had reliable age data available. Data on missing PAP use were imputed as zero, but data on other metrics were not imputed and excluded from analysis. FINDINGS: We used data recorded from Oct 1, 2014, to Aug 1, 2018. Of 40 140 children screened, 36 058 (89·8%) were US residents and 20 553 (90·1%) of them met the eligibility criteria and had accessible data (mean age 13·0 years [SD 3·7]). On the basis of 90 days of monitoring data, 12 699 (61·8%) patients continuously used PAP. Factors significantly associated with adherence included age group, residual apnoea-hypopnoea index, use and onset of patient engagement programmes, PAP pressure, and nightly median PAP mask leak, all over the 90-day study period. INTERPRETATION: To our knowledge, our study represents the largest analysis of children using PAP therapy to date. The findings suggest that adherence to PAP therapy is lower than in previous reports from adults. However, numerous actionable factors were associated with improvements in adherence and should be used strategically in clinical decision making to improve PAP adherence in children. FUNDING: ResMed.

Validation of ApneaLink as screening device for Cheyne-Stokes respiration.

STUDY OBJECTIVES: Polysomnography (PSG) is the gold standard in diagnosing sleep disordered breathing (SDB). Diagnostic analysis of SDB is time-consuming and labor-intensive and entails long waiting lists for patients. The aim of this study was to assess the validity of a flow-based screening classifier as an automated diagnostic test for Cheyne-Stokes respiration (CSR). SETTING: Sleep laboratory. PARTICIPANTS: 70 study subjects (28 with obstructive sleep apnea [OSA], 20 with CSR, 11 with CSR+OSA and 11 without SDB). MEASUREMENTS: The nasal cannula flow signal was analyzed by ApneaLink (ResMed, Sydney, Australia), based on a classifier algorithm using pattern recognition. In a simultaneous PSG, results were compared with manual scoring of respiratory events by certified sleep experts. RESULTS: For detecting CSR we obtained a sensitivity of 87.1% (95% confidence interval 75.3% to 98.9%), a specificity of 94.9% (95% confidence interval 87.9% to 100%), a positive likelihood ratio of 17.0, and a negative likelihood ratio of 0.14. The area under the curve (AUC) of the according receiver operating characteristic (ROC) curve was 93.4%. This resulted in an accuracy of 91.4% for identifying CSR. CONCLUSION: In this study we demonstrated that the screening classifier was able to detect CSR with high diagnostic accuracy. Hence, ApneaLink equipped with CSR classifier is an appropriate screening tool which may help to prioritize patients with CSR for PSG.

Compliance after switching from CPAP to bilevel for patients with non-compliant OSA: big data analysis.

Introduction: For patients with obstructive sleep apnoea (OSA) who are initially non-compliant with continuous (automatic) positive airway pressure (CPAP/APAP) therapy, a bilevel PAP (Spont/VAuto) therapy transition pathway is available to improve therapy adherence. The aim of this retrospective study was to compare PAP therapy usage data of patients with non-compliant OSA (ncOSA) on CPAP/APAP who were switched to bilevel PAP. Methods: A PAP telemonitoring database was queried between 1 January 2015 and 31 July 2016 for eligible patients started on CPAP/APAP and non-CMS (United States Center for Medicare and Medicaid Services) compliant and switched to bilevel PAP within 90 days of starting CPAP/APAP therapy. PAP therapy data on all patients were compared before switch (CPAP/APAP) and after switch (VAuto/Spont). Results: Of the 1496 patients with ncOSA identified, 30.3% used CPAP, 62.3% APAP, and 7.4% both APAP and CPAP before switching to a bilevel mode. 47.8% patients switched to Spont mode and 52.2% to VAuto mode. PAP usage significantly improved by 0.9 h/day (p<0.001) and all other device metrics (residual apnoea-hypopnoea index and unintentional mask leak) also improved after the switch. No patients had achieved US CMS criteria for compliance before the switch, and 56.8% did after. Conclusion: This shows for the first time that there may be potential benefit from switching from CPAP/APAP to bilevel PAP for patients struggling with PAP adherence.

Pattern recognition of obstructive sleep apnoea and Cheyne-Stokes respiration.

The aim of this study was to assess the validity of an artificial neural network based on flow-related spectral entropy as a diagnostic test for obstructive sleep apnoea and Cheyne-Stokes respiration. A data set of 37 subjects was used for spectral analysis of the airflow by performing a fast Fourier transform. The examined intervals were divided into epochs of 3 min. Spectral entropy S was applied as a measure for the spread of the related power spectrum. The spectrum was divided into several frequency areas with various subsets of spectral entropy. We studied 11 subjects with obstructive apnoeas (n = 267 epochs), 10 subjects with obstructive hypopnoeas (n = 80 epochs), 11 subjects with Cheyne-Stokes respiration (n = 253 epochs) and 5 subjects with normal breathing in non-REM sleep (n = 174 epochs). Based on spectral entropy an artificial neural network was built, and we obtained a sensitivity of 90.2% and a specificity of 90.9% for distinguishing between obstructive apnoeas and Cheyne-Stokes respiration, and a sensitivity of 91.3% and a specificity of 94.6% for discriminating between obstructive hypopnoeas and normal breathing in non-REM sleep. This resulted in an accuracy of 91.5% for identifying flow patterns of obstructive sleep apnoea, Cheyne-Stokes respiration and normal breathing in non-REM sleep. It is concluded that the use of an artificial neural network relying on spectral analysis of the airflow could be a useful method as a diagnostic test for obstructive sleep apnoea and Cheyne-Stokes respiration.

Adherence to Positive Airway Therapy After Switching From CPAP to ASV: A Big Data Analysis.

STUDY OBJECTIVES: There is a lack of data regarding adherence trajectories when switching from continuous positive airway pressure (CPAP) to adaptive servoventilation (ASV) in the context of persistent or treatment-emergent central sleep apnea (CSA). This study investigated 90-day adherence rates in patients with sleep apnea based on the type of positive airway pressure (PAP) device used and any switching of PAP modality over time. METHODS: Telemonitoring data were obtained from a United States PAP database. Eligible patients were a 30% random sample who started PAP, plus all who started ASV, from January 1, 2015 to October 2, 2015. All received PAP and had at least one session with usage of 1 hour or more. Adherence and device usage were determined in three groups: started on CPAP and stayed on CPAP (CPAP only); started on ASV and stayed on ASV (ASV only); started on CPAP, switched to ASV (Switch). The United States Medicare definition of adherence was used. RESULTS: The study included 198,890 patients; 189,724 (CPAP only), 8,957 (ASV only) and 209 (Switch). In the Switch group, average apnea-hypopnea index decreased significantly on ASV versus CPAP. At 90 days, adherence rates were 73.8% and 73.2% in the CPAP only and ASV only groups. In the Switch group, CPAP adherence was 62.7%, improving to 76.6% after the switch to ASV. Mean device usage at 90 days was 5.27, 5.31, and 5.73 h/d in the CPAP only, ASV only, and Switch groups, respectively. CONCLUSIONS: Treatment-emergent or persistent CSA during CPAP reduced therapy adherence, but adherence improved early after switching from CPAP to ASV.

Monitoring of nocturnal central sleep apnea in Heart failure patients using noncontact respiratory differences.

Monitoring of respiration patterns allows the early detection of various breathing disorders and may better identify those at risk for adverse acute outcomes in a variety of clinical settings. In this paper, we report on the use of SleepMinder (SM), a bedside non-contact Doppler-based biomotion recording sensor, to monitor remotely the nocturnal respiration patterns of 50 patients with systolic Heart failure (HF) while undergoing a lab based Polysomnography (PSG) test. A new respiration rate (RR) monitoring algorithm was developed based on the collected overnight radar signals. Two schemes of RR scoring were utilized: respiratory rate count (RRC) and instantaneous respiratory rates (IRR). Analysis of SM vs. PSG revealed that the mean/median IRR scored by SM is highly correlated with that scored on the nasal flow/effort signals from the corresponding PSG studies on all patients, with a significant correlation coefficient of 0.98 (average absolute difference of 0.31 breaths/min), and 0.97 (p<;0.01, average absolute difference of 0.38 breaths/min) for the median and mean of RR respectively. Our experimental results also show that the difference between the RR estimations from IRR and RRC schemes can be utilized to identify central sleep apnea (CSA)/Cheyne-Stokes respiration (CSR) sections without additional apnea detection modules. As a result, with a sensitivity and specificity of 71% and 88% respectively, and an accuracy of 86%, our CSA/CSR screener, plugged with our RR estimation, can play an important role in the remote management of HF patients.

Trajectories of Emergent Central Sleep Apnea During CPAP Therapy.

BACKGROUND: The emergence of central sleep apnea (CSA) during positive airway pressure (PAP) therapy has been observed clinically in approximately 10% of obstructive sleep apnea titration studies. This study assessed a PAP database to investigate trajectories of treatment-emergent CSA during continuous PAP (CPAP) therapy. METHODS: U.S. telemonitoring device data were analyzed for the presence/absence of emergent CSA at baseline (week 1) and week 13. Defined groups were as follows: obstructive sleep apnea (average central apnea index [CAI] < 5/h in week 1, < 5/h in week 13); transient CSA (CAI ≥ 5/h in week 1, < 5/h in week 13); persistent CSA (CAI ≥ 5/h in week 1, ≥ 5/h in week 13); emergent CSA (CAI < 5/h in week 1, ≥ 5/h in week 13). RESULTS: Patients (133,006) used CPAP for ≥ 90 days and had ≥ 1 day with use of ≥ 1 h in week 1 and week 13. The proportion of patients with CSA in week 1 or week 13 was 3.5%; of these, CSA was transient, persistent, or emergent in 55.1%, 25.2%, and 19.7%, respectively. Patients with vs without treatment-emergent CSA were older, had higher residual apnea-hypopnea index and CAI at week 13, and more leaks (all P < .001). Patients with any treatment-emergent CSA were at higher risk of therapy termination vs those who did not develop CSA (all P < .001). CONCLUSIONS: Our study identified a variety of CSA trajectories during CPAP therapy, identifying several different clinical phenotypes. Identification of treatment-emergent CSA by telemonitoring could facilitate early intervention to reduce the risk of therapy discontinuation and shift to more efficient ventilator modalities.

Treating Chronic Hypoventilation With Automatic Adjustable Versus Fixed EPAP Intelligent Volume-Assured Positive Airway Pressure Support (iVAPS): A Randomized Controlled Trial.

Objectives: New noninvasive ventilation (NIV) modes can automatically adjust pressure support settings to deliver effective ventilation in response to varying ventilation demands. It is recommended that fixed expiratory positive airway pressure (FixedEPAP) is determined by attended laboratory polysomnographic (PSG) titration. This study investigated whether automatically determined EPAP (AutoEPAP) was noninferior to FixedEPAP for the control of obstructive sleep apnea (OSA) during intelligent volume-assured pressure support (iVAPS) treatment of chronic hypoventilation. Methods: In this randomized, double-blind, crossover study, patients with chronic hypoventilation and OSA used iVAPS with AutoEPAP or FixedEPAP over two separate nights of attended PSG. PSG recordings were scored by an independent scorer using American Academy of Sleep Medicine 2012 criteria. Results: Twenty-five adults (14 male) with chronic hypoventilation secondary to obesity hypoventilation syndrome (n = 11), chronic obstructive pulmonary disease (n = 9), or neuromuscular disease (n = 5), all of whom were on established home NIV therapy, were included (age 57 ± 7 years, NIV for ≥3 months, apnea-hypopnea index [AHI] >5/hour). AutoEPAP was noninferior to FixedEPAP for the primary outcome measure (median [interquartile range] AHI 2.70 [1.70-6.05]/hour vs. 2.40 [0.25-5.95]/hour; p = .86). There were no significant between-mode differences in PSG sleep breathing and sleep quality, or self-reported sleep quality, device comfort, and patient preference. Mean EPAP with the Auto and Fixed modes was 10.8 ± 2.0 and 11.8 ± 3.9 cmH2O, respectively (p = .15). Conclusions: In patients with chronic hypoventilation using iVAPS, the AutoEPAP algorithm was noninferior to FixedEPAP over a single night's therapy.

Atrial fibrillation and sleep-disordered breathing.

Atrial fibrillation (AF) is a common supraventricular arrhythmia that increases in prevalence with increasing age and in the presence of comorbidities such as heart failure (HF). AF increases the risk of a number of serious complications, including stroke and HF. As a result, the rate of hospitalization is high, making AF a costly disease. Treatment strategies for AF are broadly based around rate and rhythm control, either pharmacological or mechanical. There appear to be a number of links between sleep-disordered breathing (SDB) and AF, although further studies are needed to fully understand the physiological mechanisms that link these conditions. Patients with AF and SDB share a number of risk factors and comorbidities, including age, male sex, hypertension, congestive HF and coronary artery disease (CAD), and the prevalence of SDB in AF is higher than in the general population. Prevalence rates of obstructive sleep apnea (OSA) in patients with AF have been reported to range from 21% to just over 80%. The prevalence of central sleep apnea (CSA) in patients with AF is less well defined, but appears to be particularly high in patients who also have HF and a reduced left ventricular ejection fraction (LVEF). The frequency of apneas can be reduced by effective treatment of AF, while co-existing OSA reduces the effectiveness of treatments for AF and there is an increased risk of arrhythmia recurrence in the presence of SDB. Treating OSA with continuous positive airway pressure (CPAP) therapy has shown the potential to decrease the incidence of AF, improve the effectiveness of AF interventions, and decrease the risk of arrhythmia recurrence, although data from large randomized, controlled clinical trials are lacking. Based on available data, inclusion of SDB recognition and management strategies as part of AF management appears to have the potential to reduce the impact of this arrhythmia at both the individual and societal levels, and has been recognized as important in recent guidelines.

Study of a Novel APAP Algorithm for the Treatment of Obstructive Sleep Apnea in Women.

STUDY OBJECTIVES: To assess the efficacy of a novel female-specific autotitrating continuous positive airway pressure (CPAP) algorithm (AutoSet for her, AfH) in premenopausal women relative to a standard autotitrating algorithm (AutoSet, S9) (ResMed Ltd., Bella Vista, New South Wales, Australia). DESIGN: Prospective randomised crossover noninferiority trial. SETTING: Tertiary hospital sleep clinic and university research sleep laboratory. PARTICIPANTS: 20 female patients with obstructive sleep apnea (OSA) established on long-term CPAP treatment. INTERVENTIONS: Treatment with 1 night each of AfH and AutoSet while monitored with overnight laboratory-based polysomnography (PSG); order randomly allocated. MEASUREMENTS AND RESULTS: The primary outcome variables were the apnea-hypopnea index (AHI) and 3% oxygen desaturation index (ODI 3%) determined from PSG. Treatment efficacy on the AfH night was noninferior to the AutoSet night as assessed by median (IQR) AHI (1.2 [0.60-1.85]/h versus 1.15 [0.40-2.85]/h, respectively, P = 0.51) and 3% ODI (0.85 [0.25-1.5]/h versus 0.5 [0.25-2.55]/h, respectively, P = 0.83). Other PSG measures were similar, except for the percentage of the night spent in flow limitation, which was lower on the AfH (0.14%) than the AutoSet night (0.19%, P = 0.007). The device-downloaded 95th centile pressure on the AfH night was also lower than on the AutoSet night (10.6 ± 1.7 versus 11.6 ± 2.6 cmH2O, respectively; mean difference [95% confidence interval]: -1.1 [-2.13 to -0.01] cm H2O). CONCLUSION: Among premenopausal women a novel female-specific autotitrating algorithm (AfH) is as effective as the standard AutoSet algorithm in controlling obstructive sleep apnea (OSA). The new algorithm may reduce flow limitation more than the standard algorithm and achieve control of OSA at a lower (95th centile) pressure.