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Word Counts: Abstract: 244 Text: 3542 Title: The use of a fully automated automatic adaptive servo ventilation algorithm in the acute and chronic treatment of central sleep apnea Running Head: Functionality of an automated, advanced algorithm Shahrokh Javaheri1, M.D., David Winslow2, Pamela McCullough2, Paul Wylie3, Meir H. Kryger4 1
Sleepcare Diagnostics, Cincinnati, Ohio,
2
Kentucky Research Group, Louisville, Kentucky,
3
Arkansas Center of Sleep Medicine, Little Rock, AR,
4
Yale University and the VA Healthcare System, New Haven CT,
Corresponding author: Shahrokh Javaheri, M.D, Professor Emeritus, University of Cincinnati, College of Medicine, 6461 Pepperell Ln., Cincinnati, OH 4526 USA Email: [email protected] This study was sponsored by Philips Respironics. Dr. Javaheri is on the speakers Bureau for Philips-Respironics, Res-Med, and Respicardia and received research support from Philips-Respironics and is a consultant for Respicardia Dr. Kryger is a consultant for Medtronic, Merck, and Inspire and has received research support from ResMed and Philips Respironics. Dr. Winslow has received research support from Philips Respironics Dr. McCullough has no disclosures Dr. Wylie has received research support and is a consultant for Philips Respironics
KEYWORDS: Central sleep apnea, servo ventilation, adherence
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ABSTRACT Background Central sleep apnea (CSA), in association with obstructive disordered breathing, occurs in patients using opioids chronically and those with congestive heart failure. In these patients treatment with continuous positive airway pressure (CPAP) frequently fails. The current Adaptive Servo-Ventilation (ASV) devices are promising for the treatment of complex sleep disordered breathing. These devices use algorithms to automatically titrate expiratory and inspiratory pressures. We hypothesized that an ASV device operating automatically would significantly reduce the frequency of breathing events in patients with mixed sleep apnea during polysomnography and with 3 months of treatment. Design Prospective, multicenter, observational trial. Methods Patients completed 3 nights of attended polysomnography, scored at an independent center. Twenty-seven patients with an apnea hypopnea index (AHI) ≥ 15 and a central apnea index (CAI) ≥ 5 per hour underwent automated ASV titration without technician intervention. 26 patients (96%) used ASV at home for 3 months. Results Patients had an AHI of (mean ± SD) 55 ± 24 and CAI of 23 ± 18 at baseline. Overnight, ASV titration improved AHI, CAI, obstructive apnea and arousal index significantly. Patients reported better sleep quality on ASV than CPAP. Over 3 months, ASV remained effective (Median AHI 11 versus 4 during PSG). Mean adherence was 4.2 hours per night. Epworth Sleepiness Scale decreased from 12.8 to 7.8 (p=0.001). Conclusions The ASV device treated complex breathing disorders using automated algorithms. Compared to CPAP, patients reported improved sleep quality. Home use of ASV remained effective with acceptable adherence and improvements in daytime sleepiness.
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This trial was registered with Clinical-Trials.gov (NCT01199042)
ABBREVIATIONS: AHI apnea hypopnea index AI Arousal index CAI central apnea index CSA central sleep apnea CSB Cheyne-Stokes breathing CPAP continuous positive airway pressure ESS Epworth Sleepiness Scale EPAP expiratory positive airway pressure IPAP inspiratory positive airway pressure OAI obstructive apnea index OSA obstructive sleep apnea PSG polysomnogram or polysomnography PAP positive airway pressure SDB sleep disordered breathing
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INTRODUCTION Central Sleep Apnea (CSA) in association with obstructive sleep disordered breathing is commonly found in a variety of conditions which could be classified as hyocapnic or hypercapneic 1 . Respective examples include congestive heart failure 1,2,3 and use of opioids 1,4,5
In addition, patients with obstructive sleep apnea (OSA), upon commencement of continuous
positive airway pressure (CPAP) titration, may develop CSA. This is referred to as complex sleep apnea or treatment-emergent central sleep apnea 6,7 CSA is commonly defined as a central apnea index (CAI) of 5 or more central apnea events per hour of sleep. In almost 50% of heart failure patients, CSA is not suppressed by CPAP either acutely 8 or over longer periods 9,10, and these patients have poor survival compared to those whose CSA is suppressed by therapy with CPAP 10. Similarly, studies have showed that patients who use opioids chronically often suffer from CSA and this has been found to be uniformly resistant to CPAP, acutely and chronically 11-16. However, in patients on opioids presenting with CSA 17, or OSA 18 with CPAP-emergent CSA, bilevel positive airway pressure with a back-up rate was reported to be effective. Meanwhile, two randomized trials showed that patients on opioids respond best to adaptive Servo ventilation (ASV) rather than CPAP 19, or bi-level with backup rate 20, though, ASV is not uniformly effective 12, 15. In one study ASV failed to lower AHI below ≤ 10/hr. in approximately 40% of patients on chronic opioid therapy 15 and a systematic review of the literature of PAP therapy for SDB in the chronic opioid population could not conclude that ASV offered advantages over other forms of PAP therapy 21. However, one important caveat is the level of various air pressures which, if not appropriately titrated and set correctly, failure ensues 22, 23
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ASV devices have undergone a number of innovative modifications to address these difficult to treat sleep related breathing disorders
22-24
. The most recent generation of ASV devices are
equipped with automatically titrating expiratory positive airway pressure (EPAP) algorithms, automatic adjustment of inspiratory pressure support and automatic adjustment of backup rate. With these features, the devices are capable of treating complex sleep-related breathing disorders with central and obstructive components
22,23,25,26
. Furthermore, if the phenotype of sleep apnea
changes with time 27, ASV devices adapt to variable respiratory pathology 22,23. With this in mind, the primary aim of the present study was to determine if the AHI from a full night attended BiPAP AutoSV Advanced™ (Philips Respironics, Murrysville, PA) titration PSG will be significantly lower than the AHI from the full night, attended diagnostic PSG. Secondary aims included a comparison of the obstructive and central apnea index on ASV to CPAP, and a comparison of the Epworth Sleepiness Scale values at baseline and after 90 days of treatment with the ASV device operating automatically. METHODS This was a prospective, controlled, multicenter trial recruiting a consecutive series of eligible patients. The study was approved and overseen by an independent ethics committee (Western Institutional Review Board, Study Number 1117606). This trial was registered with ClinicalTrials.gov (NCT01199042). To be eligible, participants were required to have an apnea hypopnea index (AHI) ≥ 15 and a CAI of ≥ 5/ hour of sleep either during the diagnostic polysomnography (PSG) or with the application of positive airway pressure therapy (i.e. CPAP emergent central sleep apnea, complex sleep apnea). The CAI of ≥ 5/ hour of sleep represents the full night threshold, for both diagnostic and CPAP-emergent PSG’s. In regard to the latter, we
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note that in our experience 13 occurrence of CPAP emergent CSA is largely independent of the air pressure until very high levels are achieved. Additional inclusion and exclusion criteria are listed in Table 1. All PSG’s were carried out using a nasal-oral thermocouple, nasal pressure measurement of nasal air-flow, two inductance plethysmography belts secured around the chest and abdomen to measure breathing effort, and a sensor to measure body position. Lead II ECG was recorded. Electrodes were attached to the scalp and face to measure sleep stages, electro-oculgram and submental EMG. A microphone was attached to the skin at the base of the neck to record snoring sounds. Surface electrodes were attached to the skin bilaterally over the anterior tibialis muscle, to measure leg movements. A flexible finger sensor placed on the finger to measure oxygen saturation with the pulse oximeter set to the highest sampling rate available on the PSG device. All participants first underwent a full night, attended diagnostic PSG. Eligible participants then had an attended, full night manual CPAP titration. CPAP pressure was initially set at 4 cm H2O and was progressively increased to eliminate obstructive events. Once all obstructive events were eliminated and central apneas were present, CPAP pressure was increased gradually up to an additional 5 cm H2O in an attempt to determine if central apneas could be eliminated. If central apneas persisted, the pressure was lowered to the level that CPAP was most effective. The CPAP titration PSG was followed by a full night, attended, but automated titration with the BiPAP autoSV Advanced device. The ASV device adjusts expiratory pressure to maintain airway patency and inspiratory pressure to maintain a target peak flow. The device operated automatically without interference from technicians.
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During the ASV PSG, scoring of sleep stages and breathing events was done with the device operating in an extreme range of pressure settings. However, being a real world trial and along the lines of sound clinical practice, the investigators could alter the range for minimum and maximum inspiratory and expiratory pressures for use at home over 3 months (Table 2). In this regard, an important change was in the maximum EPAP level which was allowed to be lowered from that of the night of initial automatic titration when it was set at maximum of 25 cm H2O. Other changes were limited. The change in maximum EPAP was allowed in order to prevent excessive rise in the air pressure in the unlikely situation of the ASV device responding to potential artifacts 22, 23 Participants answered a 5-point Likert question rating their quality of sleep following the CPAP and ASV nights. Although initial eligibility was determined on the interpretation of the diagnostic PSG at each site, all PSG’s were scored by an independent, centralized scoring center following 2007 AASM recommended scoring criteria
28
. Hypopneas were defined when airflow deceased by 30% ≥
from baseline and associated with either ≥4% decrease in saturation or an arousal. Individuals scoring the PSG’s were blinded to other patient information. Only PSG data from the centralized scoring center were used in the analysis. All participants used the ASV device for 90 days at home. Therapy data were recorded on a data card and uploaded into a standard software program (Encore Pro, Philips Respironics, Murrysville, PA) to generate adherence, pressure, and breathing event (ASV At-Home) data. Participants received phone calls weekly from study staff for the first four weeks of treatment to
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troubleshoot any therapy issues. Sleep clinic visits took place at 30 and 90 days to obtain adherence data and complete the Epworth Sleepiness Scale (ESS). STATISTICAL METHODS Due to the asymmetric distributions of the endpoints, the non-parametric Friedman’s analysis of variance was used to compare the related values in the three PSGs of the study, including the diagnostic, CPAP, and BiPAP autoSV nights. Post-hoc pair-wise comparisons were done with the Wilcoxon Signed Ranks test, with Bonferroni correction for multiple comparisons. The Likert sleep quality scores were compared between the CPAP and ASV nights using the Wilcoxon Signed Ranks test. Nightly data obtained from Encore Pro were averaged within each participant. To calculate an unbiased participant-average of therapy pressures and respiratory indices, the daily values were weighted relative to each day’s device usage. Any missing adherence data had 0 imputed for each day. The Epworth Sleepiness Scale at 90 days was compared to baseline using the paired t-test, as the distribution of scores for this measure was normal. P values < 0.05 were considered significant. Descriptive statistics include the median, mean and standard deviation. All analyses were completed in the Statistical Package for Social Sciences software (SPSS 20.0, Chicago, IL). RESULTS Twenty nine patients were enrolled between September 2010 and February 2013. Two participants did not meet the AHI or CAI criteria after centralized scoring of diagnostic and CPAP PSGs and were excluded from analysis. Twenty seven participants (5 females) completed 3 nights in-laboratory attended polysomnography, and 26 completed 3 months of follow up. One participant was lost to follow-up. The mean values for age (years) and body mass index (Kg/m2) 8
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were 59 ± 12 and 33 ± 5, respectively. Participants presented with a variety of medical conditions. Twenty four participants had central sleep apnea at baseline PSG and three participants originally diagnosed with OSA developed treatment emergent CSA with CPAP treatment. Among 24 participants with CSA at baseline PSG, 13 had the typical erratic Biot’s breathing pattern associated with opioids 11 and six had Hunter-Cheyne-Stokes breathing pattern. Two patients had atrial fibrillation without history of CHF, two patients suffered from multiple sclerosis, and one had a previous stroke. At the time of enrollment, the mean ESS value for all participants was 12.8± 5. Participants presented with severe sleep apnea with a mean AHI of 55±24 per hour of sleep at baseline PSG. During the third PSG, the ASV effectively treated breathing disorders regardless of the etiology of CSA. When operated with the settings described in Table 2, the device automatically adjusted expiratory and inspiratory pressures and breathing rate and provided effective treatment. Median AHI decreased from 33 per hour on CPAP to 4 per hour with ASV and the median CAI decreased from 10 to 0 events per hour of sleep (Table 3). In all participants, 78 %, and, in those using opioids, 81%, achieved an AHI ≤ 10. Over the 90 day home treatment period, the ASV device consistently treated obstructive and central sleep disordered breathing events. The mean value for home AHI was 11 (median 10), for CAI 1 (median 1), OAI 1 (median 1) and hypopnea index 9 (median 8) per hour. These values compare well with those obtained acutely during the in-laboratory titration (Table 3). We note that the home device settings were mostly similar to the device settings used in the laboratory, except that maximum EPAP was lower than that in the laboratory (Table 2).
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Treatment with ASV resulted in improved sleep architecture with reduction in N1 sleep and arousal index (Table 4). Based on the Likert scale, the median subjective sleep quality score was significantly higher following the ASV night [4 (3.3 ± 0.9)], compared to the CPAP night [3 (2.9 ± 0.8)] (p=0.034). In 26 participants, adherence averaged 4.8 ± 2.0 (median 5.4), 4.2 ± 2.0 (median 4.4) hours per day for 30 and 90 nights respectively. The device was used on 84.3 ± 19.9 and 76.1 ± 29.2 percent of nights for 30 and 90 nights respectively (Table 5). Participants reported improvement in excessive daytime sleepiness. ESS decreased significantly at 3 months of ASV use to 7.8 ± 4 (vs. baseline of 12.8 ± 5, p = 0.001). DISCUSSION From the results of this study we conclude that the fully automated ASV device operating with manufacturer default algorithms is effective in suppressing complex sleep related breathing disorders acutely and chronically with adherence that resulted in improvements in subjective (ESS) daytime sleepiness.
Acutely, the ASV device, operating automatically according to its algorithm, was quite effective in suppressing sleep related breathing disorders. When compared to CPAP, sleep architecture and disordered breathing improved significantly with ASV and this was reflected in patients subjective (Likert scale) improved sleep quality.
Efficacy of ASV was maintained over the course of the next 3 months. Data obtained from the device download indicated suppression of sleep related breathing disorders when averaged for the 90 nights and Epworth sleepiness scale improved significantly (12.8 to 7.8). 10
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The mean, in-lab AHI with the ASV was 12; the mean AHI after 90 nights at home was 11. Although these indices compare well, we note that the latter AHI is based solely on airflow, unlike the AHI calculated from the PSG. For this device, an obstructive apnea is detected when airflow decreases below 80% of the baseline for ten seconds (versus 90% for in-lab titration). Hypopnea is identified when airflow decreases 40% to 80% from baseline (versus 30% to 90% for in-lab titration). Furthermore, the denominator of in-lab AHI is total sleep time, versus the “mask on” time for the device AHI. Appreciating these differences, the downloaded AHI of various positive airway pressure devices is used for long-term follow up both by care givers and insurance companies, though there are no systematic validation studies. We concur with the recent American Thoracic Society publication 29 and the study by Berry et al 30, that when the AHI reported by the device is low, particularly when comparable to in-lab AHI as in the present study, and importantly, the improvement in AHI is matched with improvement in patient’s symptomatology, one becomes most confident in the efficacy of the positive airway pressure device.
In the present study, participants used the device 4.2 ±2 hours per night, averaged for 90 nights, while at home. As noted above, at the time of enrollment, participants suffered from excessive daytime sleepiness, which improved significantly following home use of the ASV device. Central sleep apnea was seen in a number of conditions including use of opioids, treatment emergent central apnea, Hunter-Cheyne–Stokes breathing, atrial fibrillation, stroke and neuromuscular disease. Studies indicate that these patients suffer from mixed disordered breathing events as noted in our participants and that the central apnea component of the disorder 11
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is often not suppressed by CPAP 8-16, 18, 19. In addition, Guilleminault and associates have shown CPAP emergent central sleep apnea in patients using opioids who initially were diagnosed only with OSA 18. The fully automated ASV devices 22 24 provide a variable degree of inspiratory pressure support, automatically determine end expiratory positive airway pressure requirements to eliminate obstructive breathing events, and initiate mandatory breaths on a timely basis aborting the course of an impending apnea. Having these innovative capabilities such devices are adaptive to address varying degrees of obstructive and central sleep disordered breathing events. As the phenotype of sleep apnea changes acutely (changing position or sleep stage) and chronically (changes in medication, weight, or worsening of cardiovascular function and fluid status), ASV devices adapt to the needs of the patient. The results of the present study demonstrate that an ASV device can be effective long-term in suppressing sleep-related breathing disorders of various causes. As noted above, most participants in this study were on opioids for chronic pain management. Sleep apnea is highly prevalent in this population and frequently both obstructive and central apneas are observed within the background of unique patterns of breathing referred to as Biot’s and ataxic breathing 4,31
. CPAP is generally ineffective and 2 randomized trials indicate that ASV therapy is superior
to both CPAP 18 and bilevel 19. Similar to sleep-related breathing disorders seen with opioids, patients with atrial fibrillation, recipients of cardiac pacemakers/defibrillators 5, and those with congestive heart failure may have a combination of central and obstructive apneas and hypopneas 32. Therefore, ASV devices with automatic algorithms should be effective in successfully treating the respiratory events in these populations as demonstrated in the present study. 12
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Overall, adherence with CPAP therapy is disappointing even in the selective environment of a controlled trial. In the multi-center Canadian trial of patients with congestive heart failure and central sleep apnea, the average nightly use of CPAP was 3.6 hours when determined at 12 months 10. Similarly, in the Sleep Apnea cardio Vascular Endpoints (SAVE) trial 33 of 275 patients with known cardiovascular disease, the average nightly use of CPAP at 12 months was 3.3 hour/night. Furthermore, percent of patients using CPAP ≥ 4 hr. was 62% at one month, 53% at 6 months, and 39% at 12 months 31. Thus, ASV devices with improved algorithms may promote adherence, though this remains to be proven in long-term ASV trials. One limitation of the study is that there was not a PSG conducted at the end of the trial to compare the effectiveness of treatment to what the device was reporting. The device reported AHI is based on airflow only and may differ from what would be seen during PSG 20. However, the device’s breathing event detection algorithm was shown to be generally consistent with the AHI from PSG 21. A control group was not included due to the lack of effectiveness of CPAP in this population 8, 9, 12, 16, 17. The lack of a control group could have resulted in a placebo effect for both the Likert scale values and the ESS values. Although the ASV device reduced the frequency of breathing events, we did not monitor cardiac parameters or changes in pain medications and BMI over the course of the study to show how the improvement in AHI impacted the underlying participants’ conditions.
CLINICAL IMPLICATIONS
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This study was conducted in a real world setting and the results demonstrate that while operating with automatic titration of EPAP and inspiratory pressure support with automatic back up rate, the device is effective both acutely and chronically for treatment of complex sleep-related breathing disorders. Studies have shown efficacy of auto CPAP for home titration of patients with OSA 27. Given pressures to reduce health care costs, studies need to be performed to determine if patients suffering from complex sleep-related breathing disorders such as those seen in this study can be treated with ASV at home without in-lab titration. Given the present circumstances of widespread use of home sleep testing as well as auto-titrating CPAP for treatment of obstructive sleep apnea, home titration with ASV devices may also prove to be both effective and cost saving. However, practitioners should confirm that efficacy and adherence are acceptable in patients prescribed ASV, since not all devices use the same algorithms. SUMMARY From the results of the present study we conclude that this automated ASV effectively treats sleep disordered breathing including Hunter-Cheyne Stokes breathing, CPAP emergent central apnea and central apnea associated with opioids acutely and chronically. Suppression of these sleep disordered breathing events over the course of 3 months use at home resulted in improvement in AHI and subjective assessment of excessive day time sleepiness in the study participants.
ACKNOWLEDGMENTS This study was sponsored by Philips Respironics. 14
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Author contributions: Dr. Javaheri: contributed to study design, data collection and analysis, and writing of the manuscript. He takes responsibility for the integrity of this work from study inception to publication. Dr. Winslow: Study design, Data collection, Manuscript review. Ms. McCollough: Data collection, Manuscript review. Dr. Wylie: Study design, Data collection, Manuscript review Dr. Kryger: Study design, data collection and analysis, and manuscript review
The authors thank the following individuals from Philips Respironics for their support in this study: Jeff Jasko, Donna O’Malley, Bill Hardy, and Gary Lotz, for their valuable and constructive insights on this manuscript.
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Legends Table 1 Legend: Inclusion and exclusion criteria
Table 2 Legend: There were no variations of device settings during the in laboratory ASV PSG and the device titrated therapy automatically. Mean ± SD presented for home settings.
Table 3 Legend Values are median (mean ± SD). CPAP = continuous positive airway pressure; ASV= adaptive servoventilation; AHI= apnea hypopnea index; C= central; O = obstructive; SpO2= saturation measured by pulse oximetry; Min= minimum. *Friedman Test comparing all 3 nights. aSignificant vs. Diagnostic; bSignificant vs. CPAP; Bonferroni-adjusted P-values for significant pairwise comparisons were P ≤ 0.006. † 26 Participants completed the 3 month home follow-up Table 4 Legend CPAP, continuous positive airway pressure; PLMI, Periodic leg movements index during sleep. *Friedman Test comparing all 3 nights. aSignificant vs. Diagnostic; bSignificant vs. CPAP; Bonferroni-adjusted P-values for significant pairwise comparisons were P ≤ 0.009. Values are median (mean ± SD). ‡For PLMI, pair wise comparisons were not significant after Bonferroni adjustment. Table 5 Legend *N=24 for Average Hours of Device Usage (All Days), due to incomplete adherence data from two participants. Daily adherence imputed as 0 for these two participants. N=26 for all other endpoints. In the analysis of days 1-90, N=24 for Average Hours of Device Usage (All Days), due to incomplete adherence data from two participants; N=26 for the other endpoints. In the analysis segmenting days 1-30 and days 31-90, two additional participants were excluded because their daily adherence data were not available to calculate their adherence for the two intervals. A paired t-test compared the adherence between days 1-30 and days 31-90.
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Table 1: Inclusion Criteria
Exclusion Criteria
Males and females, ages 21-75.
Active participation in another interventional research study Diagnosis of acute decompensated heart failure. Surgery of the upper airway, nose, sinus or middle ear within the last 90 days
Able and willing to provide written informed consent Diagnosis of Central Sleep Apnea such as Cheyne Stokes Breathing, Complex Sleep Apnea, or Central Apnea with current daily Opioid use or any other predominant central sleep apnea. Systolic blood pressure > 80 mm Hg at screening visit
Major medical or psychiatric condition that would interfere with the demands of the study or the ability of
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Agreement to undergo a full-night, attended Diagnostic PSG or the availability of a recent clinical diagnostic PSG (within four weeks of signing consent with at least four hours of sleep). Agreement to undergo a full-night, attended CPAP titration PSG. Agreement to undergo a full-night, attended BiPAP autoSV Advanced™ titration PSG
the participant to complete the study. For example, severe unstable chronic lung disease, neuromuscular disease, cancer, or end stage renal failure. Qualifying for or awaiting heart transplantation
Currently prescribed oxygen therapy (e.g. as needed, nocturnal, or continuous). Current home treatment with ASV. Unable to use PAP therapies due to physical (e.g. facial structural abnormalities) or cognitive (e.g. dementia) issues. Participants in whom PAP therapy is medically contraindicated. Uncontrolled hypertension (systolic ≥ 200 mm Hg/diastolic ≥ 120 mm Hg). Narcolepsy Untreated Restless Legs Syndrome Periodic Limb Movement arousal index > 20/hr
Table 2: Device Operating Parameters during PSG and average Operating Parameter settings during home-use ASV Device Parameter Setting During PSG EPAPmin (cm H2O) EPAPmax (cm H2O) PSmin (cm H2O) Psmax (cm H2O) Max Pressure (cm H2O)
4 25 0 21 21
ASV Device Parameter Setting During Home Use (Mean ± SD) 4.3 ± 0.8 20.9 ± 4.7 0.2 ± 0.7 18.3 ± 3.1 23.9 ± 2.7 22
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# of Participants with at Least 1 Variation in Device Parameter Setting 5 15 3 16 28
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Flex Setting
2
2.0 ± 0.4
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Table 3. Respiratory indices from the three polysomnography nights (N=27†) Variable
Diagnostic
CPAP
ASV
p-value*
AHI , n/hr
53 (55 ± 24)
33 (37 ± 22)a
4 (12 ± 20)a,b
ONLINE FIRST This is an Online First, unedited version of this article. The final, edited version will appear in a numbered issue of CHEST and may contain substantive changes. We encourage readers to check back for the final article. Online First papers are indexed in PubMed and by search engines, but the information, including the final title and author list, may be updated on final publication. http://journal.publications.chestnet.org/
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Word Counts: Abstract: 244 Text: 3542 Title: The use of a fully automated automatic adaptive servo ventilation algorithm in the acute and chronic treatment of central sleep apnea Running Head: Functionality of an automated, advanced algorithm Shahrokh Javaheri1, M.D., David Winslow2, Pamela McCullough2, Paul Wylie3, Meir H. Kryger4 1
Sleepcare Diagnostics, Cincinnati, Ohio,
2
Kentucky Research Group, Louisville, Kentucky,
3
Arkansas Center of Sleep Medicine, Little Rock, AR,
4
Yale University and the VA Healthcare System, New Haven CT,
Corresponding author: Shahrokh Javaheri, M.D, Professor Emeritus, University of Cincinnati, College of Medicine, 6461 Pepperell Ln., Cincinnati, OH 4526 USA Email: [email protected] This study was sponsored by Philips Respironics. Dr. Javaheri is on the speakers Bureau for Philips-Respironics, Res-Med, and Respicardia and received research support from Philips-Respironics and is a consultant for Respicardia Dr. Kryger is a consultant for Medtronic, Merck, and Inspire and has received research support from ResMed and Philips Respironics. Dr. Winslow has received research support from Philips Respironics Dr. McCullough has no disclosures Dr. Wylie has received research support and is a consultant for Philips Respironics
KEYWORDS: Central sleep apnea, servo ventilation, adherence
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ABSTRACT Background Central sleep apnea (CSA), in association with obstructive disordered breathing, occurs in patients using opioids chronically and those with congestive heart failure. In these patients treatment with continuous positive airway pressure (CPAP) frequently fails. The current Adaptive Servo-Ventilation (ASV) devices are promising for the treatment of complex sleep disordered breathing. These devices use algorithms to automatically titrate expiratory and inspiratory pressures. We hypothesized that an ASV device operating automatically would significantly reduce the frequency of breathing events in patients with mixed sleep apnea during polysomnography and with 3 months of treatment. Design Prospective, multicenter, observational trial. Methods Patients completed 3 nights of attended polysomnography, scored at an independent center. Twenty-seven patients with an apnea hypopnea index (AHI) ≥ 15 and a central apnea index (CAI) ≥ 5 per hour underwent automated ASV titration without technician intervention. 26 patients (96%) used ASV at home for 3 months. Results Patients had an AHI of (mean ± SD) 55 ± 24 and CAI of 23 ± 18 at baseline. Overnight, ASV titration improved AHI, CAI, obstructive apnea and arousal index significantly. Patients reported better sleep quality on ASV than CPAP. Over 3 months, ASV remained effective (Median AHI 11 versus 4 during PSG). Mean adherence was 4.2 hours per night. Epworth Sleepiness Scale decreased from 12.8 to 7.8 (p=0.001). Conclusions The ASV device treated complex breathing disorders using automated algorithms. Compared to CPAP, patients reported improved sleep quality. Home use of ASV remained effective with acceptable adherence and improvements in daytime sleepiness.
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This trial was registered with Clinical-Trials.gov (NCT01199042)
ABBREVIATIONS: AHI apnea hypopnea index AI Arousal index CAI central apnea index CSA central sleep apnea CSB Cheyne-Stokes breathing CPAP continuous positive airway pressure ESS Epworth Sleepiness Scale EPAP expiratory positive airway pressure IPAP inspiratory positive airway pressure OAI obstructive apnea index OSA obstructive sleep apnea PSG polysomnogram or polysomnography PAP positive airway pressure SDB sleep disordered breathing
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INTRODUCTION Central Sleep Apnea (CSA) in association with obstructive sleep disordered breathing is commonly found in a variety of conditions which could be classified as hyocapnic or hypercapneic 1 . Respective examples include congestive heart failure 1,2,3 and use of opioids 1,4,5
In addition, patients with obstructive sleep apnea (OSA), upon commencement of continuous
positive airway pressure (CPAP) titration, may develop CSA. This is referred to as complex sleep apnea or treatment-emergent central sleep apnea 6,7 CSA is commonly defined as a central apnea index (CAI) of 5 or more central apnea events per hour of sleep. In almost 50% of heart failure patients, CSA is not suppressed by CPAP either acutely 8 or over longer periods 9,10, and these patients have poor survival compared to those whose CSA is suppressed by therapy with CPAP 10. Similarly, studies have showed that patients who use opioids chronically often suffer from CSA and this has been found to be uniformly resistant to CPAP, acutely and chronically 11-16. However, in patients on opioids presenting with CSA 17, or OSA 18 with CPAP-emergent CSA, bilevel positive airway pressure with a back-up rate was reported to be effective. Meanwhile, two randomized trials showed that patients on opioids respond best to adaptive Servo ventilation (ASV) rather than CPAP 19, or bi-level with backup rate 20, though, ASV is not uniformly effective 12, 15. In one study ASV failed to lower AHI below ≤ 10/hr. in approximately 40% of patients on chronic opioid therapy 15 and a systematic review of the literature of PAP therapy for SDB in the chronic opioid population could not conclude that ASV offered advantages over other forms of PAP therapy 21. However, one important caveat is the level of various air pressures which, if not appropriately titrated and set correctly, failure ensues 22, 23
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ASV devices have undergone a number of innovative modifications to address these difficult to treat sleep related breathing disorders
22-24
. The most recent generation of ASV devices are
equipped with automatically titrating expiratory positive airway pressure (EPAP) algorithms, automatic adjustment of inspiratory pressure support and automatic adjustment of backup rate. With these features, the devices are capable of treating complex sleep-related breathing disorders with central and obstructive components
22,23,25,26
. Furthermore, if the phenotype of sleep apnea
changes with time 27, ASV devices adapt to variable respiratory pathology 22,23. With this in mind, the primary aim of the present study was to determine if the AHI from a full night attended BiPAP AutoSV Advanced™ (Philips Respironics, Murrysville, PA) titration PSG will be significantly lower than the AHI from the full night, attended diagnostic PSG. Secondary aims included a comparison of the obstructive and central apnea index on ASV to CPAP, and a comparison of the Epworth Sleepiness Scale values at baseline and after 90 days of treatment with the ASV device operating automatically. METHODS This was a prospective, controlled, multicenter trial recruiting a consecutive series of eligible patients. The study was approved and overseen by an independent ethics committee (Western Institutional Review Board, Study Number 1117606). This trial was registered with ClinicalTrials.gov (NCT01199042). To be eligible, participants were required to have an apnea hypopnea index (AHI) ≥ 15 and a CAI of ≥ 5/ hour of sleep either during the diagnostic polysomnography (PSG) or with the application of positive airway pressure therapy (i.e. CPAP emergent central sleep apnea, complex sleep apnea). The CAI of ≥ 5/ hour of sleep represents the full night threshold, for both diagnostic and CPAP-emergent PSG’s. In regard to the latter, we
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note that in our experience 13 occurrence of CPAP emergent CSA is largely independent of the air pressure until very high levels are achieved. Additional inclusion and exclusion criteria are listed in Table 1. All PSG’s were carried out using a nasal-oral thermocouple, nasal pressure measurement of nasal air-flow, two inductance plethysmography belts secured around the chest and abdomen to measure breathing effort, and a sensor to measure body position. Lead II ECG was recorded. Electrodes were attached to the scalp and face to measure sleep stages, electro-oculgram and submental EMG. A microphone was attached to the skin at the base of the neck to record snoring sounds. Surface electrodes were attached to the skin bilaterally over the anterior tibialis muscle, to measure leg movements. A flexible finger sensor placed on the finger to measure oxygen saturation with the pulse oximeter set to the highest sampling rate available on the PSG device. All participants first underwent a full night, attended diagnostic PSG. Eligible participants then had an attended, full night manual CPAP titration. CPAP pressure was initially set at 4 cm H2O and was progressively increased to eliminate obstructive events. Once all obstructive events were eliminated and central apneas were present, CPAP pressure was increased gradually up to an additional 5 cm H2O in an attempt to determine if central apneas could be eliminated. If central apneas persisted, the pressure was lowered to the level that CPAP was most effective. The CPAP titration PSG was followed by a full night, attended, but automated titration with the BiPAP autoSV Advanced device. The ASV device adjusts expiratory pressure to maintain airway patency and inspiratory pressure to maintain a target peak flow. The device operated automatically without interference from technicians.
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During the ASV PSG, scoring of sleep stages and breathing events was done with the device operating in an extreme range of pressure settings. However, being a real world trial and along the lines of sound clinical practice, the investigators could alter the range for minimum and maximum inspiratory and expiratory pressures for use at home over 3 months (Table 2). In this regard, an important change was in the maximum EPAP level which was allowed to be lowered from that of the night of initial automatic titration when it was set at maximum of 25 cm H2O. Other changes were limited. The change in maximum EPAP was allowed in order to prevent excessive rise in the air pressure in the unlikely situation of the ASV device responding to potential artifacts 22, 23 Participants answered a 5-point Likert question rating their quality of sleep following the CPAP and ASV nights. Although initial eligibility was determined on the interpretation of the diagnostic PSG at each site, all PSG’s were scored by an independent, centralized scoring center following 2007 AASM recommended scoring criteria
28
. Hypopneas were defined when airflow deceased by 30% ≥
from baseline and associated with either ≥4% decrease in saturation or an arousal. Individuals scoring the PSG’s were blinded to other patient information. Only PSG data from the centralized scoring center were used in the analysis. All participants used the ASV device for 90 days at home. Therapy data were recorded on a data card and uploaded into a standard software program (Encore Pro, Philips Respironics, Murrysville, PA) to generate adherence, pressure, and breathing event (ASV At-Home) data. Participants received phone calls weekly from study staff for the first four weeks of treatment to
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troubleshoot any therapy issues. Sleep clinic visits took place at 30 and 90 days to obtain adherence data and complete the Epworth Sleepiness Scale (ESS). STATISTICAL METHODS Due to the asymmetric distributions of the endpoints, the non-parametric Friedman’s analysis of variance was used to compare the related values in the three PSGs of the study, including the diagnostic, CPAP, and BiPAP autoSV nights. Post-hoc pair-wise comparisons were done with the Wilcoxon Signed Ranks test, with Bonferroni correction for multiple comparisons. The Likert sleep quality scores were compared between the CPAP and ASV nights using the Wilcoxon Signed Ranks test. Nightly data obtained from Encore Pro were averaged within each participant. To calculate an unbiased participant-average of therapy pressures and respiratory indices, the daily values were weighted relative to each day’s device usage. Any missing adherence data had 0 imputed for each day. The Epworth Sleepiness Scale at 90 days was compared to baseline using the paired t-test, as the distribution of scores for this measure was normal. P values < 0.05 were considered significant. Descriptive statistics include the median, mean and standard deviation. All analyses were completed in the Statistical Package for Social Sciences software (SPSS 20.0, Chicago, IL). RESULTS Twenty nine patients were enrolled between September 2010 and February 2013. Two participants did not meet the AHI or CAI criteria after centralized scoring of diagnostic and CPAP PSGs and were excluded from analysis. Twenty seven participants (5 females) completed 3 nights in-laboratory attended polysomnography, and 26 completed 3 months of follow up. One participant was lost to follow-up. The mean values for age (years) and body mass index (Kg/m2) 8
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were 59 ± 12 and 33 ± 5, respectively. Participants presented with a variety of medical conditions. Twenty four participants had central sleep apnea at baseline PSG and three participants originally diagnosed with OSA developed treatment emergent CSA with CPAP treatment. Among 24 participants with CSA at baseline PSG, 13 had the typical erratic Biot’s breathing pattern associated with opioids 11 and six had Hunter-Cheyne-Stokes breathing pattern. Two patients had atrial fibrillation without history of CHF, two patients suffered from multiple sclerosis, and one had a previous stroke. At the time of enrollment, the mean ESS value for all participants was 12.8± 5. Participants presented with severe sleep apnea with a mean AHI of 55±24 per hour of sleep at baseline PSG. During the third PSG, the ASV effectively treated breathing disorders regardless of the etiology of CSA. When operated with the settings described in Table 2, the device automatically adjusted expiratory and inspiratory pressures and breathing rate and provided effective treatment. Median AHI decreased from 33 per hour on CPAP to 4 per hour with ASV and the median CAI decreased from 10 to 0 events per hour of sleep (Table 3). In all participants, 78 %, and, in those using opioids, 81%, achieved an AHI ≤ 10. Over the 90 day home treatment period, the ASV device consistently treated obstructive and central sleep disordered breathing events. The mean value for home AHI was 11 (median 10), for CAI 1 (median 1), OAI 1 (median 1) and hypopnea index 9 (median 8) per hour. These values compare well with those obtained acutely during the in-laboratory titration (Table 3). We note that the home device settings were mostly similar to the device settings used in the laboratory, except that maximum EPAP was lower than that in the laboratory (Table 2).
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Treatment with ASV resulted in improved sleep architecture with reduction in N1 sleep and arousal index (Table 4). Based on the Likert scale, the median subjective sleep quality score was significantly higher following the ASV night [4 (3.3 ± 0.9)], compared to the CPAP night [3 (2.9 ± 0.8)] (p=0.034). In 26 participants, adherence averaged 4.8 ± 2.0 (median 5.4), 4.2 ± 2.0 (median 4.4) hours per day for 30 and 90 nights respectively. The device was used on 84.3 ± 19.9 and 76.1 ± 29.2 percent of nights for 30 and 90 nights respectively (Table 5). Participants reported improvement in excessive daytime sleepiness. ESS decreased significantly at 3 months of ASV use to 7.8 ± 4 (vs. baseline of 12.8 ± 5, p = 0.001). DISCUSSION From the results of this study we conclude that the fully automated ASV device operating with manufacturer default algorithms is effective in suppressing complex sleep related breathing disorders acutely and chronically with adherence that resulted in improvements in subjective (ESS) daytime sleepiness.
Acutely, the ASV device, operating automatically according to its algorithm, was quite effective in suppressing sleep related breathing disorders. When compared to CPAP, sleep architecture and disordered breathing improved significantly with ASV and this was reflected in patients subjective (Likert scale) improved sleep quality.
Efficacy of ASV was maintained over the course of the next 3 months. Data obtained from the device download indicated suppression of sleep related breathing disorders when averaged for the 90 nights and Epworth sleepiness scale improved significantly (12.8 to 7.8). 10
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The mean, in-lab AHI with the ASV was 12; the mean AHI after 90 nights at home was 11. Although these indices compare well, we note that the latter AHI is based solely on airflow, unlike the AHI calculated from the PSG. For this device, an obstructive apnea is detected when airflow decreases below 80% of the baseline for ten seconds (versus 90% for in-lab titration). Hypopnea is identified when airflow decreases 40% to 80% from baseline (versus 30% to 90% for in-lab titration). Furthermore, the denominator of in-lab AHI is total sleep time, versus the “mask on” time for the device AHI. Appreciating these differences, the downloaded AHI of various positive airway pressure devices is used for long-term follow up both by care givers and insurance companies, though there are no systematic validation studies. We concur with the recent American Thoracic Society publication 29 and the study by Berry et al 30, that when the AHI reported by the device is low, particularly when comparable to in-lab AHI as in the present study, and importantly, the improvement in AHI is matched with improvement in patient’s symptomatology, one becomes most confident in the efficacy of the positive airway pressure device.
In the present study, participants used the device 4.2 ±2 hours per night, averaged for 90 nights, while at home. As noted above, at the time of enrollment, participants suffered from excessive daytime sleepiness, which improved significantly following home use of the ASV device. Central sleep apnea was seen in a number of conditions including use of opioids, treatment emergent central apnea, Hunter-Cheyne–Stokes breathing, atrial fibrillation, stroke and neuromuscular disease. Studies indicate that these patients suffer from mixed disordered breathing events as noted in our participants and that the central apnea component of the disorder 11
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is often not suppressed by CPAP 8-16, 18, 19. In addition, Guilleminault and associates have shown CPAP emergent central sleep apnea in patients using opioids who initially were diagnosed only with OSA 18. The fully automated ASV devices 22 24 provide a variable degree of inspiratory pressure support, automatically determine end expiratory positive airway pressure requirements to eliminate obstructive breathing events, and initiate mandatory breaths on a timely basis aborting the course of an impending apnea. Having these innovative capabilities such devices are adaptive to address varying degrees of obstructive and central sleep disordered breathing events. As the phenotype of sleep apnea changes acutely (changing position or sleep stage) and chronically (changes in medication, weight, or worsening of cardiovascular function and fluid status), ASV devices adapt to the needs of the patient. The results of the present study demonstrate that an ASV device can be effective long-term in suppressing sleep-related breathing disorders of various causes. As noted above, most participants in this study were on opioids for chronic pain management. Sleep apnea is highly prevalent in this population and frequently both obstructive and central apneas are observed within the background of unique patterns of breathing referred to as Biot’s and ataxic breathing 4,31
. CPAP is generally ineffective and 2 randomized trials indicate that ASV therapy is superior
to both CPAP 18 and bilevel 19. Similar to sleep-related breathing disorders seen with opioids, patients with atrial fibrillation, recipients of cardiac pacemakers/defibrillators 5, and those with congestive heart failure may have a combination of central and obstructive apneas and hypopneas 32. Therefore, ASV devices with automatic algorithms should be effective in successfully treating the respiratory events in these populations as demonstrated in the present study. 12
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Overall, adherence with CPAP therapy is disappointing even in the selective environment of a controlled trial. In the multi-center Canadian trial of patients with congestive heart failure and central sleep apnea, the average nightly use of CPAP was 3.6 hours when determined at 12 months 10. Similarly, in the Sleep Apnea cardio Vascular Endpoints (SAVE) trial 33 of 275 patients with known cardiovascular disease, the average nightly use of CPAP at 12 months was 3.3 hour/night. Furthermore, percent of patients using CPAP ≥ 4 hr. was 62% at one month, 53% at 6 months, and 39% at 12 months 31. Thus, ASV devices with improved algorithms may promote adherence, though this remains to be proven in long-term ASV trials. One limitation of the study is that there was not a PSG conducted at the end of the trial to compare the effectiveness of treatment to what the device was reporting. The device reported AHI is based on airflow only and may differ from what would be seen during PSG 20. However, the device’s breathing event detection algorithm was shown to be generally consistent with the AHI from PSG 21. A control group was not included due to the lack of effectiveness of CPAP in this population 8, 9, 12, 16, 17. The lack of a control group could have resulted in a placebo effect for both the Likert scale values and the ESS values. Although the ASV device reduced the frequency of breathing events, we did not monitor cardiac parameters or changes in pain medications and BMI over the course of the study to show how the improvement in AHI impacted the underlying participants’ conditions.
CLINICAL IMPLICATIONS
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This study was conducted in a real world setting and the results demonstrate that while operating with automatic titration of EPAP and inspiratory pressure support with automatic back up rate, the device is effective both acutely and chronically for treatment of complex sleep-related breathing disorders. Studies have shown efficacy of auto CPAP for home titration of patients with OSA 27. Given pressures to reduce health care costs, studies need to be performed to determine if patients suffering from complex sleep-related breathing disorders such as those seen in this study can be treated with ASV at home without in-lab titration. Given the present circumstances of widespread use of home sleep testing as well as auto-titrating CPAP for treatment of obstructive sleep apnea, home titration with ASV devices may also prove to be both effective and cost saving. However, practitioners should confirm that efficacy and adherence are acceptable in patients prescribed ASV, since not all devices use the same algorithms. SUMMARY From the results of the present study we conclude that this automated ASV effectively treats sleep disordered breathing including Hunter-Cheyne Stokes breathing, CPAP emergent central apnea and central apnea associated with opioids acutely and chronically. Suppression of these sleep disordered breathing events over the course of 3 months use at home resulted in improvement in AHI and subjective assessment of excessive day time sleepiness in the study participants.
ACKNOWLEDGMENTS This study was sponsored by Philips Respironics. 14
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Author contributions: Dr. Javaheri: contributed to study design, data collection and analysis, and writing of the manuscript. He takes responsibility for the integrity of this work from study inception to publication. Dr. Winslow: Study design, Data collection, Manuscript review. Ms. McCollough: Data collection, Manuscript review. Dr. Wylie: Study design, Data collection, Manuscript review Dr. Kryger: Study design, data collection and analysis, and manuscript review
The authors thank the following individuals from Philips Respironics for their support in this study: Jeff Jasko, Donna O’Malley, Bill Hardy, and Gary Lotz, for their valuable and constructive insights on this manuscript.
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27. Yumino D, Redolfi S, Ruttanaumpawan P, et al. Nocturnal rostral fluid shift: a unifying concept for the pathogenesis of obstructive and central sleep apnea in men with heart failure. Circulation. 2010;121:1598–1605. 28. Iber C, Ancoli-Israel S, Chesson A, Quan SF, American Academy of Sleep Medicine. The AASM manual for the scoring of sleep and associated events: rules, terminology and technical specifications. 2nd ed. Westchester, IL: American Academy of Sleep Medicine; 2007 29. Schwab RJ, Badr SM, Epstein LJ, et al. An official American Thoracic Society statement: continuous positive airway pressure adherence tracking systems. The optimal monitoring strategies and outcome measures in adults. ATS Subcommittee on CPAP Adherence Tracking Systems. Am J Respir Crit Care Med. 2013;188:613-20. 30. Berry RB, Kushida CA, Kryger MH, et al. Respiratory event detection by a positive airway pressure device. Sleep 2012;35:361-67. 31. Javaheri S, Harris N, Howard J, Chung E. Adaptive servoventilation for treatment of opioid-associated central sleep apnea. J Clin Sleep Med 2014;10(6):637-643. 32. Chai-Coetzer CL, Luo YM, Antic NA, et al. Predictors of long-term adherence to continuous positive airway pressure therapy in patients with obstructive sleep apnea and cardiovascular disease in the SAVE study. Sleep 2013;36:1929-37. 33. Caples S, SomersV. Sleep Disordered Breathing and Atrial Fibrillation. Prog Cardiovasc
Dis. 2009;51:411–15. 34. Garrigue S, Pépin JL, Defaye P. et al High prevalence of sleep apnea syndrome in patients with long-term pacing: the European Multicenter Polysomnographic Study. Circulation 2007;115:1703-1709.
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Legends Table 1 Legend: Inclusion and exclusion criteria
Table 2 Legend: There were no variations of device settings during the in laboratory ASV PSG and the device titrated therapy automatically. Mean ± SD presented for home settings.
Table 3 Legend Values are median (mean ± SD). CPAP = continuous positive airway pressure; ASV= adaptive servoventilation; AHI= apnea hypopnea index; C= central; O = obstructive; SpO2= saturation measured by pulse oximetry; Min= minimum. *Friedman Test comparing all 3 nights. aSignificant vs. Diagnostic; bSignificant vs. CPAP; Bonferroni-adjusted P-values for significant pairwise comparisons were P ≤ 0.006. † 26 Participants completed the 3 month home follow-up Table 4 Legend CPAP, continuous positive airway pressure; PLMI, Periodic leg movements index during sleep. *Friedman Test comparing all 3 nights. aSignificant vs. Diagnostic; bSignificant vs. CPAP; Bonferroni-adjusted P-values for significant pairwise comparisons were P ≤ 0.009. Values are median (mean ± SD). ‡For PLMI, pair wise comparisons were not significant after Bonferroni adjustment. Table 5 Legend *N=24 for Average Hours of Device Usage (All Days), due to incomplete adherence data from two participants. Daily adherence imputed as 0 for these two participants. N=26 for all other endpoints. In the analysis of days 1-90, N=24 for Average Hours of Device Usage (All Days), due to incomplete adherence data from two participants; N=26 for the other endpoints. In the analysis segmenting days 1-30 and days 31-90, two additional participants were excluded because their daily adherence data were not available to calculate their adherence for the two intervals. A paired t-test compared the adherence between days 1-30 and days 31-90.
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Table 1: Inclusion Criteria
Exclusion Criteria
Males and females, ages 21-75.
Active participation in another interventional research study Diagnosis of acute decompensated heart failure. Surgery of the upper airway, nose, sinus or middle ear within the last 90 days
Able and willing to provide written informed consent Diagnosis of Central Sleep Apnea such as Cheyne Stokes Breathing, Complex Sleep Apnea, or Central Apnea with current daily Opioid use or any other predominant central sleep apnea. Systolic blood pressure > 80 mm Hg at screening visit
Major medical or psychiatric condition that would interfere with the demands of the study or the ability of
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Agreement to undergo a full-night, attended Diagnostic PSG or the availability of a recent clinical diagnostic PSG (within four weeks of signing consent with at least four hours of sleep). Agreement to undergo a full-night, attended CPAP titration PSG. Agreement to undergo a full-night, attended BiPAP autoSV Advanced™ titration PSG
the participant to complete the study. For example, severe unstable chronic lung disease, neuromuscular disease, cancer, or end stage renal failure. Qualifying for or awaiting heart transplantation
Currently prescribed oxygen therapy (e.g. as needed, nocturnal, or continuous). Current home treatment with ASV. Unable to use PAP therapies due to physical (e.g. facial structural abnormalities) or cognitive (e.g. dementia) issues. Participants in whom PAP therapy is medically contraindicated. Uncontrolled hypertension (systolic ≥ 200 mm Hg/diastolic ≥ 120 mm Hg). Narcolepsy Untreated Restless Legs Syndrome Periodic Limb Movement arousal index > 20/hr
Table 2: Device Operating Parameters during PSG and average Operating Parameter settings during home-use ASV Device Parameter Setting During PSG EPAPmin (cm H2O) EPAPmax (cm H2O) PSmin (cm H2O) Psmax (cm H2O) Max Pressure (cm H2O)
4 25 0 21 21
ASV Device Parameter Setting During Home Use (Mean ± SD) 4.3 ± 0.8 20.9 ± 4.7 0.2 ± 0.7 18.3 ± 3.1 23.9 ± 2.7 22
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# of Participants with at Least 1 Variation in Device Parameter Setting 5 15 3 16 28
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Flex Setting
2
2.0 ± 0.4
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Table 3. Respiratory indices from the three polysomnography nights (N=27†) Variable
Diagnostic
CPAP
ASV
p-value*
AHI , n/hr
53 (55 ± 24)
33 (37 ± 22)a
4 (12 ± 20)a,b
