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Sleep Apnea Syndromes: HELP
Articles by Daniel J. Gottlieb
Based on 43 articles published since 2008
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Between 2008 and 2019, Dan J. Gottlieb wrote the following 43 articles about Sleep Apnea Syndromes.
 
+ Citations + Abstracts
Pages: 1 · 2
1 Guideline Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. 2012

Berry, Richard B / Budhiraja, Rohit / Gottlieb, Daniel J / Gozal, David / Iber, Conrad / Kapur, Vishesh K / Marcus, Carole L / Mehra, Reena / Parthasarathy, Sairam / Quan, Stuart F / Redline, Susan / Strohl, Kingman P / Davidson Ward, Sally L / Tangredi, Michelle M / Anonymous3090739. ·University of Florida Health Science Center, Gainesville, FL 32610, USA. richard.berry@medicine.ufl.edu ·J Clin Sleep Med · Pubmed #23066376.

ABSTRACT: The American Academy of Sleep Medicine (AASM) Sleep Apnea Definitions Task Force reviewed the current rules for scoring respiratory events in the 2007 AASM Manual for the Scoring and Sleep and Associated Events to determine if revision was indicated. The goals of the task force were (1) to clarify and simplify the current scoring rules, (2) to review evidence for new monitoring technologies relevant to the scoring rules, and (3) to strive for greater concordance between adult and pediatric rules. The task force reviewed the evidence cited by the AASM systematic review of the reliability and validity of scoring respiratory events published in 2007 and relevant studies that have appeared in the literature since that publication. Given the limitations of the published evidence, a consensus process was used to formulate the majority of the task force recommendations concerning revisions.The task force made recommendations concerning recommended and alternative sensors for the detection of apnea and hypopnea to be used during diagnostic and positive airway pressure (PAP) titration polysomnography. An alternative sensor is used if the recommended sensor fails or the signal is inaccurate. The PAP device flow signal is the recommended sensor for the detection of apnea, hypopnea, and respiratory effort related arousals (RERAs) during PAP titration studies. Appropriate filter settings for recording (display) of the nasal pressure signal to facilitate visualization of inspiratory flattening are also specified. The respiratory inductance plethysmography (RIP) signals to be used as alternative sensors for apnea and hypopnea detection are specified. The task force reached consensus on use of the same sensors for adult and pediatric patients except for the following: (1) the end-tidal PCO(2) signal can be used as an alternative sensor for apnea detection in children only, and (2) polyvinylidene fluoride (PVDF) belts can be used to monitor respiratory effort (thoracoabdominal belts) and as an alternative sensor for detection of apnea and hypopnea (PVDFsum) only in adults.The task force recommends the following changes to the 2007 respiratory scoring rules. Apnea in adults is scored when there is a drop in the peak signal excursion by ≥ 90% of pre-event baseline using an oronasal thermal sensor (diagnostic study), PAP device flow (titration study), or an alternative apnea sensor, for ≥ 10 seconds. Hypopnea in adults is scored when the peak signal excursions drop by ≥ 30% of pre-event baseline using nasal pressure (diagnostic study), PAP device flow (titration study), or an alternative sensor, for ≥ 10 seconds in association with either ≥ 3% arterial oxygen desaturation or an arousal. Scoring a hypopnea as either obstructive or central is now listed as optional, and the recommended scoring rules are presented. In children an apnea is scored when peak signal excursions drop by ≥ 90% of pre-event baseline using an oronasal thermal sensor (diagnostic study), PAP device flow (titration study), or an alternative sensor; and the event meets duration and respiratory effort criteria for an obstructive, mixed, or central apnea. A central apnea is scored in children when the event meets criteria for an apnea, there is an absence of inspiratory effort throughout the event, and at least one of the following is met: (1) the event is ≥ 20 seconds in duration, (2) the event is associated with an arousal or ≥ 3% oxygen desaturation, (3) (infants under 1 year of age only) the event is associated with a decrease in heart rate to less than 50 beats per minute for at least 5 seconds or less than 60 beats per minute for 15 seconds. A hypopnea is scored in children when the peak signal excursions drop is ≥ 30% of pre-event baseline using nasal pressure (diagnostic study), PAP device flow (titration study), or an alternative sensor, for ≥ the duration of 2 breaths in association with either ≥ 3% oxygen desaturation or an arousal. In children and adults, surrogates of the arterial PCO(2) are the end-tidal PCO(2) or transcutaneous PCO(2) (diagnostic study) or transcutaneous PCO(2) (titration study). For adults, sleep hypoventilation is scored when the arterial PCO(2) (or surrogate) is > 55 mm Hg for ≥ 10 minutes or there is an increase in the arterial PCO(2) (or surrogate) ≥ 10 mm Hg (in comparison to an awake supine value) to a value exceeding 50 mm Hg for ≥ 10 minutes. For pediatric patients hypoventilation is scored when the arterial PCO(2) (or surrogate) is > 50 mm Hg for > 25% of total sleep time. In adults Cheyne-Stokes breathing is scored when both of the following are met: (1) there are episodes of ≥ 3 consecutive central apneas and/or central hypopneas separated by a crescendo and decrescendo change in breathing amplitude with a cycle length of at least 40 seconds (typically 45 to 90 seconds), and (2) there are five or more central apneas and/or central hypopneas per hour associated with the crescendo/decrescendo breathing pattern recorded over a minimum of 2 hours of monitoring.

2 Editorial Does Obstructive Sleep Apnea Treatment Reduce Cardiovascular Risk?: It Is Far Too Soon to Say. 2017

Gottlieb, Daniel J. ·Medical Service, VA Boston Healthcare System, Boston, Massachusetts2Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts. ·JAMA · Pubmed #28697240.

ABSTRACT: -- No abstract --

3 Editorial Does Treatment of Sleep Apnea Prevent Perioperative Complications? Wish We Knew! 2015

Gottlieb, Daniel J. ·VA Boston Healthcare System, Brigham and Women's Hospital, and Harvard Medical School, Boston MA. ·Sleep · Pubmed #26194573.

ABSTRACT: -- No abstract --

4 Editorial Obstructive sleep apnea: how much is too much? 2015

Gottlieb, Daniel J. ·VA Boston Healthcare System, Brigham & Women's Hospital, and Harvard Medical School, Boston, MA. ·Sleep · Pubmed #25845683.

ABSTRACT: -- No abstract --

5 Editorial Sleep apnea and the risk of atrial fibrillation recurrence: structural or functional effects? 2014

Gottlieb, Daniel J. ·VA Boston Healthcare System, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA. ·J Am Heart Assoc · Pubmed #24390147.

ABSTRACT: -- No abstract --

6 Review The Sleep Heart Health Study: a progress report. 2008

Gottlieb, Daniel J. ·VA Boston Healthcare System and Boston University School of Medicine, Boston, Massachusetts 02118-2394, USA. gottlieb@bu.edu ·Curr Opin Pulm Med · Pubmed #18812830.

ABSTRACT: PURPOSE OF REVIEW: The Sleep Heart Health Study began in 1994 as a prospective cohort study of cardiovascular disease. The results of longitudinal analysis are not yet available, but numerous analyses of cross-sectional data have been published. This review provides an overview of study results so far. RECENT FINDINGS: Recent findings covered in this review include a methodological study supporting the choice of a 4% oxyhemoglobin desaturation criterion for identification of hypopneas; evidence that sleepiness may modify the association of sleep apnea with hypertension; the association of sleep apnea with increased left ventricular mass in a pattern suggesting predominantly eccentric left ventricular hypertrophy; the association of restless legs syndrome with an increase in prevalent cardiovascular disease; and the results of a genome-wide association study of sleep and circadian phenotypes. SUMMARY: Although designed as a prospective cohort study, analysis of cross-sectional data from the Sleep Heart Health Study has contributed numerous insights to the field of sleep medicine.

7 Clinical Conference Knowledge Gaps in the Perioperative Management of Adults with Obstructive Sleep Apnea and Obesity Hypoventilation Syndrome. An Official American Thoracic Society Workshop Report. 2018

Ayas, Najib T / Laratta, Cheryl R / Coleman, John M / Doufas, Anthony G / Eikermann, Matthias / Gay, Peter C / Gottlieb, Daniel J / Gurubhagavatula, Indira / Hillman, David R / Kaw, Roop / Malhotra, Atul / Mokhlesi, Babak / Morgenthaler, Timothy I / Parthasarathy, Sairam / Ramachandran, Satya Krishna / Strohl, Kingman P / Strollo, Patrick J / Twery, Michael J / Zee, Phyllis C / Chung, Frances F / Anonymous631114. · ·Ann Am Thorac Soc · Pubmed #29388810.

ABSTRACT: The purpose of this workshop was to identify knowledge gaps in the perioperative management of obstructive sleep apnea (OSA) and obesity hypoventilation syndrome (OHS). A single-day meeting was held at the American Thoracic Society Conference in May, 2016, with representation from many specialties, including anesthesiology, perioperative medicine, sleep, and respiratory medicine. Further research is urgently needed as we look to improve health outcomes for these patients and reduce health care costs. There is currently insufficient evidence to guide screening and optimization of OSA and OHS in the perioperative setting to achieve these objectives. Patients who are at greatest risk of respiratory or cardiac complications related to OSA and OHS are not well defined, and the effectiveness of monitoring and other interventions remains to be determined. Centers involved in sleep research need to develop collaborative networks to allow multicenter studies to address the knowledge gaps identified below.

8 Article Multiethnic Meta-Analysis Identifies RAI1 as a Possible Obstructive Sleep Apnea-related Quantitative Trait Locus in Men. 2018

Chen, Han / Cade, Brian E / Gleason, Kevin J / Bjonnes, Andrew C / Stilp, Adrienne M / Sofer, Tamar / Conomos, Matthew P / Ancoli-Israel, Sonia / Arens, Raanan / Azarbarzin, Ali / Bell, Graeme I / Below, Jennifer E / Chun, Sung / Evans, Daniel S / Ewert, Ralf / Frazier-Wood, Alexis C / Gharib, Sina A / Haba-Rubio, José / Hagen, Erika W / Heinzer, Raphael / Hillman, David R / Johnson, W Craig / Kutalik, Zoltan / Lane, Jacqueline M / Larkin, Emma K / Lee, Seung Ku / Liang, Jingjing / Loredo, Jose S / Mukherjee, Sutapa / Palmer, Lyle J / Papanicolaou, George J / Penzel, Thomas / Peppard, Paul E / Post, Wendy S / Ramos, Alberto R / Rice, Ken / Rotter, Jerome I / Sands, Scott A / Shah, Neomi A / Shin, Chol / Stone, Katie L / Stubbe, Beate / Sul, Jae Hoon / Tafti, Mehdi / Taylor, Kent D / Teumer, Alexander / Thornton, Timothy A / Tranah, Gregory J / Wang, Chaolong / Wang, Heming / Warby, Simon C / Wellman, D Andrew / Zee, Phyllis C / Hanis, Craig L / Laurie, Cathy C / Gottlieb, Daniel J / Patel, Sanjay R / Zhu, Xiaofeng / Sunyaev, Shamil R / Saxena, Richa / Lin, Xihong / Redline, Susan. ·1 Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts. · 2 Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health and. · 3 Center for Precision Health, School of Public Health & School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas. · 4 Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, Massachusetts. · 5 Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts. · 6 Department of Public Health Sciences, University of Chicago, Chicago, Illinois. · 7 Division of Genetics, Brigham and Women's Hospital, Boston, Massachusetts. · 8 Center for Genomic Medicine and Department of Anesthesia, Pain, and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts. · 9 Department of Biostatistics, University of Washington, Seattle, Washington. · 10 Departments of Medicine and Psychiatry, University of California, San Diego, California. · 11 the Children's Hospital at Montefiore, Division of Respiratory and Sleep Medicine, Albert Einstein College of Medicine, Bronx, New York. · 12 Section of Adult and Pediatric Endocrinology, Diabetes, and Metabolism, the University of Chicago, Chicago, Illinois. · 13 Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee. · 14 Division of Medical Sciences, Harvard Medical School, Boston, Massachusetts. · 15 California Pacific Medical Center Research Institute, San Francisco, California. · 16 Internal Medicine B, University Medicine Greifswald, Greifswald, Germany. · 17 Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas. · 18 Computational Medicine Core, Center for Lung Biology, University of Washington Medicine Sleep Center, Division of Pulmonary, Critical Care, and Sleep Medicine, University of Washington, Seattle, Washington. · 19 Center of Investigation and Research on Sleep, Lausanne University Hospital, Lausanne, Switzerland. · 20 Department of Population Health Sciences, University of Wisconsin, Madison, Wisconsin. · 21 Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia. · 22 Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne, Switzerland. · 23 Swiss Institute of Bioinformatics, Lausanne, Switzerland. · 24 Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts. · 25 Department of Medicine, Division of Allergy, Pulmonary, and Critical Care, Vanderbilt University Medical Center, Nashville, Tennessee. · 26 Institute of Human Genomic Study, College of Medicine, Korea University Ansan Hospital, Jeokgum-ro, Danwon-gu, Ansan-si, Gyeonggi-Do, Republic of Korea. · 27 Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, Ohio. · 28 Division of Pulmonary Critical Care and Sleep Medicine, Department of Medicine, University of California San Diego School of Medicine, La Jolla, California. · 29 Adelaide Institute for Sleep Health, Flinders Centre of Research Excellence, Flinders University, Adelaide, South Australia, Australia. · 30 School of Public Health, University of Adelaide, Adelaide, South Australia, Australia. · 31 Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, Maryland. · 32 University Hospital Charité Berlin, Sleep Center, Berlin, Germany. · 33 Division of Cardiology, Johns Hopkins University, Baltimore, Maryland. · 34 Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida. · 35 Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute and Department of Pediatrics at Harbor-University of California Los Angeles Medical Center, Torrance, California. · 36 Division of Pulmonary, Critical Care, and Sleep, Icahn School of Medicine at Mount Sinai, New York, New York. · 37 Department of Pulmonary, Sleep, and Critical Care Medicine, College of Medicine, Korea University Ansan Hospital, Jeokgum-ro, Danwon-gu, Ansan-si, Gyeonggi-do, Republic of Korea. · 38 Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California. · 39 Department of Physiology, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland. · 40 Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. · 41 Computational and Systems Biology, Genome Institute of Singapore, Singapore. · 42 Department of Psychiatry, University of Montreal, Montreal, Quebec, Canada. · 43 Department of Neurology and Sleep Medicine Center, Northwestern University, Chicago, Illinois. · 44 Veterans Affairs Boston Healthcare System, Boston, Massachusetts. · 45 Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania. · 46 Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts; and. · 47 Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts. ·Am J Respir Cell Mol Biol · Pubmed #29077507.

ABSTRACT: Obstructive sleep apnea (OSA) is a common heritable disorder displaying marked sexual dimorphism in disease prevalence and progression. Previous genetic association studies have identified a few genetic loci associated with OSA and related quantitative traits, but they have only focused on single ethnic groups, and a large proportion of the heritability remains unexplained. The apnea-hypopnea index (AHI) is a commonly used quantitative measure characterizing OSA severity. Because OSA differs by sex, and the pathophysiology of obstructive events differ in rapid eye movement (REM) and non-REM (NREM) sleep, we hypothesized that additional genetic association signals would be identified by analyzing the NREM/REM-specific AHI and by conducting sex-specific analyses in multiethnic samples. We performed genome-wide association tests for up to 19,733 participants of African, Asian, European, and Hispanic/Latino American ancestry in 7 studies. We identified rs12936587 on chromosome 17 as a possible quantitative trait locus for NREM AHI in men (N = 6,737; P = 1.7 × 10

9 Article Predictors of sleepiness in obstructive sleep apnoea at baseline and after 6 months of continuous positive airway pressure therapy. 2017

Budhiraja, Rohit / Kushida, Clete A / Nichols, Deborah A / Walsh, James K / Simon, Richard D / Gottlieb, Daniel J / Quan, Stuart F. ·Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA rbudhiraja@partners.org. · Division of Pulmonary and Critical Care Medicine, Dept of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. · Stanford University Sleep Clinic and Center for Human Sleep Research, Redwood City, CA, USA. · Sleep Medicine and Research Center, St Luke's Hospital, Chesterfield, MO, USA. · Providence St Mary Medical Center, Walla Walla, WA, USA. · Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. · VA Boston Healthcare System, Boston, MA, USA. · Arizona Respiratory Center, University of Arizona, Tucson, AZ, USA. ·Eur Respir J · Pubmed #29191951.

ABSTRACT: We evaluated factors associated with subjective and objective sleepiness at baseline and after 6 months of continuous positive airway pressure (CPAP) therapy in patients with obstructive sleep apnoea (OSA).We analysed data from the Apnoea Positive Pressure Long-term Efficacy Study (APPLES), a prospective 6-month multicentre randomised controlled trial with 1105 subjects with OSA, 558 of who were randomised to active CPAP. Epworth sleepiness scale (ESS) scores and the mean sleep latency (MSL) on the maintenance of wakefulness test at baseline and after 6 months of CPAP therapy were recorded.Excessive sleepiness (ESS score >10) was present in 543 (49.1%) participants. Younger age, presence of depression and higher apnoea-hypopnoea index were all associated with higher ESS scores and lower MSL. Randomisation to the CPAP group was associated with lower odds of sleepiness at 6 months. The prevalence of sleepiness was significantly lower in those using CPAP >4 h·night

10 Article Obstructive and Central Sleep Apnea and the Risk of Incident Atrial Fibrillation in a Community Cohort of Men and Women. 2017

Tung, Patricia / Levitzky, Yamini S / Wang, Rui / Weng, Jia / Quan, Stuart F / Gottlieb, Daniel J / Rueschman, Michael / Punjabi, Naresh M / Mehra, Reena / Bertisch, Suzie / Benjamin, Emelia J / Redline, Susan. ·Division of Cardiology, Atrius Health, Boston, MA patricia_tung1@atriushealth.org. · Division of Cardiology, Newton-Wellesley Hospital, Newton, MA. · Division of Sleep and Circadian Disorders, Brigham & Women's Hospital, Harvard Medical School, Boston, MA. · Arizona Respiratory Center, University of Arizona, Tucson, AZ. · VA Boston Healthcare System, Boston, MA. · Johns Hopkins University School of Medicine, Baltimore, MD. · Sleep Center, Neurologic Institute, Cleveland Clinic, Cleveland, OH. · Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH. · Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA. · Boston University School of Medicine, Boston, MA. · Boston University School of Public Health, Boston, MA. · NHLBI's and Boston University's Framingham Heart Study, Framingham, MA. ·J Am Heart Assoc · Pubmed #28668820.

ABSTRACT: BACKGROUND: Previous studies have documented a high prevalence of atrial fibrillation (AF) in individuals with obstructive sleep apnea (OSA). Central sleep apnea (CSA) has been associated with AF in patients with heart failure. However, data from prospective cohorts are sparse and few studies have distinguished the associations of obstructive sleep apnea from CSA with AF in population studies. METHODS AND RESULTS: We assessed the association of obstructive sleep apnea and CSA with incident AF among 2912 individuals without a history of AF in the SHHS (Sleep Heart Health Study), a prospective, community-based study of existing ("parent") cohort studies designed to evaluate the cardiovascular consequences of sleep disordered breathing. Incident AF was documented by 12-lead ECG or assessed by the parent cohort. obstructive sleep apnea was defined by the obstructive apnea-hypopnea index (OAHI). CSA was defined by a central apnea index ≥5 or the presence of Cheyne Stokes Respiration. Logistic regression was used to assess the association between sleep disordered breathing and incident AF. Over a mean of 5.3 years of follow-up, 338 cases of incident AF were observed. CSA was a predictor of incident AF in all adjusted models and was associated with 2- to 3-fold increased odds of developing AF (central apnea index ≥5 odds ratio [OR], 3.00, 1.40-6.44; Cheyne-Stokes respiration OR, 1.83, 0.95-3.54; CSA or Cheyne-Stokes respiration OR, 2.00, 1.16-3.44). In contrast, OAHI was not associated with incident AF (OAHI per 5 unit increase OR, 0.97, 0.91-1.03; OAHI 5 to <15 OR, 0.84, 0.59-1.17; OAHI 15 to <30 OR, 0.93, 0.60-1.45; OAHI ≥30 OR, 0.76, 0.42-1.36). CONCLUSIONS: In a prospective, community-based cohort, CSA was associated with incident AF, even after adjustment for cardiovascular risk factors.

11 Article Impact of continuous positive airway pressure and oxygen on health status in patients with coronary heart disease, cardiovascular risk factors, and obstructive sleep apnea: A Heart Biomarker Evaluation in Apnea Treatment (HEARTBEAT) analysis. 2017

Lewis, Eldrin F / Wang, Rui / Punjabi, Naresh / Gottlieb, Daniel J / Quan, Stuart F / Bhatt, Deepak L / Patel, Sanjay R / Mehra, Reena / Blumenthal, Roger S / Weng, Jia / Rueschman, Michael / Redline, Susan. ·Brigham and Women's Hospital, Boston, MA; Harvard Medical School, Boston, MA. Electronic address: eflewis@partners.org. · Brigham and Women's Hospital, Boston, MA. · Johns Hopkins University, Baltimore, MD. · Brigham and Women's Hospital, Boston, MA; Harvard Medical School, Boston, MA; Veterans Affairs Boston Healthcare System, Boston, MA. · Brigham and Women's Hospital, Boston, MA; Harvard Medical School, Boston, MA. · University of Pittsburgh, Pittsburgh, PA. · Cleveland Clinic, Cleveland, OH. ·Am Heart J · Pubmed #28625382.

ABSTRACT: INTRODUCTION: Obstructive sleep apnea (OSA) is associated with impaired health-related quality of life (HRQL). Treatment with continuous positive airway pressure (CPAP) has variable impacts on HRQL, and this may be influenced by patient's tolerance of therapy. The objective is to determine the impact of nocturnal supplemental oxygen (NSO) and CPAP on HRQL compared with healthy lifestyle education (HLSE) in individuals with OSA. METHODS: Patients with coronary heart disease (CHD) or at least 3 major CHD risk factors with apnea-hypopnea index of 15 to 50 events/h were randomized to CPAP, NSO, or HLSE. Health-related quality of life was assessed using the Short-Form 36, and depression was assessed with Patient Health Questionnaire-9 at baseline and 12 weeks. The treatment effect on HRQL change scores through 12 weeks was assessed using multivariable models adjusting for study site, presence of CHD at baseline, race, and baseline HRQL. RESULTS: A total of 318 patients were randomized to 1 of 3 treatment arms with 1:1:1 ratio and 94% completed baseline and follow-up HRQL instruments. Mean Short-Form 36 scores were similar at baseline in all 3 groups ranging from 41.8±12 to 51.6±12 in various domains. In multivariable models, the CPAP group noted a significantly greater improvement than NSO in mental health (+2.33, 95% CI 0.34-4.31, P=.02) and mental composite score (+2.40, 95% CI 0.40-4.41, P=.02). Conversely, the CPAP group noted less improvement than NSO in physical function (-2.68, 95% CI -4.66 to -0.70, P=.008) and physical composite score (-2.17, 95% CI -3.82 to -0.51, P=.01). Compared with HLSE, vitality and Patient Health Questionnaire-9 improved with CPAP but not with NSO. Significant interactions were noted between treatment effects with larger differences in black and sleepy patients. CONCLUSION: These data support the use of CPAP for improving vitality, sleepiness, mental health, social functioning, and depressive symptoms in patients with OSA and established CHD or risk factors. Nocturnal supplemental oxygen may have beneficial effects on perceived physical functioning.

12 Article Obstructive Sleep Apnea and Subclinical Interstitial Lung Disease in the Multi-Ethnic Study of Atherosclerosis (MESA). 2017

Kim, John S / Podolanczuk, Anna J / Borker, Priya / Kawut, Steven M / Raghu, Ganesh / Kaufman, Joel D / Stukovsky, Karen D Hinckley / Hoffman, Eric A / Barr, R Graham / Gottlieb, Daniel J / Redline, Susan S / Lederer, David J. ·1 Department of Medicine, Columbia University Medical Center, New York, New York. · 2 Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts. · 3 Department of Medicine and the Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania. · 4 Department of Medicine. · 5 Department of Environmental and Occupational Health Sciences and Department of Epidemiology, and. · 6 Department of Biostatistics, University of Washington, Seattle, Washington. · 7 Departments of Radiology, Medicine, and Biomedical Engineering, University of Iowa Carver College of Medicine, Iowa City, Iowa. · 8 Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, New York. · 9 Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts; and. · 10 Department of Medicine, VA Boston Healthcare System, Boston, Massachusetts. ·Ann Am Thorac Soc · Pubmed #28613935.

ABSTRACT: RATIONALE: Obstructive sleep apnea (OSA) has been postulated to contribute to idiopathic pulmonary fibrosis by promoting alveolar epithelial injury via tractional forces and intermittent hypoxia. OBJECTIVES: To determine whether OSA is associated with subclinical interstitial lung disease (ILD) and with biomarkers of alveolar epithelial injury and remodeling. METHODS: We performed cross-sectional analyses of 1,690 community-dwelling adults who underwent 15-channel in-home polysomnography and thoracic computed tomographic imaging in the Multi-Ethnic Study of Atherosclerosis. We measured the obstructive apnea-hypopnea index (oAHI) by polysomnography and high-attenuation areas (HAAs) and interstitial lung abnormalities (ILAs) by computed tomography. Serum matrix metalloproteinase-7 (MMP-7) and surfactant protein-A (SP-A) were measured by ELISA in 99 participants. We used generalized linear models to adjust for potential confounders. RESULTS: The mean age was 68 years, and the mean forced vital capacity was 97% predicted. The median oAHI was 8.4 events/h, and 32% had an oAHI greater than 15. After adjusting for demographics, smoking, and center, an oAHI greater than 15 was associated with a 4.0% HAA increment (95% confidence interval [CI], 1.4-6.8%; P = 0.003) and 35% increased odds of ILA (95% CI, 13-61%; P = 0.001). However, there was evidence that these associations varied by body mass index (BMI) (P for interaction = 0.08 and 0.04, respectively). Among those with a BMI less than 25 kg/m CONCLUSIONS: Moderate to severe OSA is associated with subclinical ILD and with evidence of alveolar epithelial injury and extracellular matrix remodeling in community-dwelling adults, an association that is strongest among normal-weight individuals. These findings support the hypothesis that OSA might contribute to early ILD.

13 Article Variants in angiopoietin-2 (ANGPT2) contribute to variation in nocturnal oxyhaemoglobin saturation level. 2016

Wang, Heming / Cade, Brian E / Chen, Han / Gleason, Kevin J / Saxena, Richa / Feng, Tao / Larkin, Emma K / Vasan, Ramachandran S / Lin, Honghuang / Patel, Sanjay R / Tracy, Russell P / Liu, Yongmei / Gottlieb, Daniel J / Below, Jennifer E / Hanis, Craig L / Petty, Lauren E / Sunyaev, Shamil R / Frazier-Wood, Alexis C / Rotter, Jerome I / Post, Wendy / Lin, Xihong / Redline, Susan / Zhu, Xiaofeng. ·Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA. · Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA. · Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA. · Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. · Department of Public Health Sciences, University of Chicago, Chicago, IL, USA. · Center for Human Genetic Research and Department of Anesthesia, Pain, and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA. · Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA. · Department of Medicine, Division of Allergy, Pulmonary and Critical Care, Vanderbilt University Medical Center, Nashville, TN, USA. · Preventive Medicine & Epidemiology, Boston University School of Medicine, Boston, MA, USA. · Framingham Heart Study, Framingham, MA. · Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA. · Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA. · Department of Pathology & Laboratory Medicine, University of Vermont, Burlington, VT, USA. · Epidemiology and Prevention Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA. · Sleep Disorders Center, VA Boston Healthcare System, Boston, MA, USA. · Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA. · Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. · Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA. · Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA. · Division of Cardiology, Johns Hopkins University, Baltimore, MD, USA. ·Hum Mol Genet · Pubmed #27798093.

ABSTRACT: Genetic determinants of sleep-disordered breathing (SDB), a common set of disorders that contribute to significant cardiovascular and neuropsychiatric morbidity, are not clear. Overnight nocturnal oxygen saturation (SaO2) is a clinically relevant and easily measured indicator of SDB severity but its genetic contribution has never been studied. Our recent study suggests nocturnal SaO2 is heritable. We performed linkage analysis, association analysis and haplotype analysis of average nocturnal oxyhaemoglobin saturation in participants in the Cleveland Family Study (CFS), followed by gene-based association and additional tests in four independent samples. Linkage analysis identified a peak (LOD = 4.29) on chromosome 8p23. Follow-up association analysis identified two haplotypes in angiopoietin-2 (ANGPT2) that significantly contributed to the variation of SaO2 (P = 8 × 10-5) and accounted for a portion of the linkage evidence. Gene-based association analysis replicated the association of ANGPT2 and nocturnal SaO2. A rare missense SNP rs200291021 in ANGPT2 was associated with serum angiopoietin-2 level (P = 1.29 × 10-4), which was associated with SaO2 (P = 0.002). Our study provides the first evidence for the association of ANGPT2, a gene previously implicated in acute lung injury syndromes, with nocturnal SaO2, suggesting that this gene has a broad range of effects on gas exchange, including influencing oxygenation during sleep.

14 Article The association between sleep-disordered breathing and aortic stiffness in a community cohort. 2016

Chami, Hassan A / Vasan, Ramachandran S / Larson, Martin G / Benjamin, Emelia J / Mitchell, Gary F / Gottlieb, Daniel J. ·Department of Medicine, American University of Beirut, Beirut, Lebanon; The Pulmonary Center, Boston University School of Medicine, Boston, MA, USA. Electronic address: hchami@aub.edu.lb. · Sections of Cardiovascular and Preventive Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA; Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA. · Department of Mathematics and Statistics, Boston University, Boston, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA. · Cardiovascular Engineering, Inc., Norwood, MA, USA. · VA Boston Healthcare System, Boston, MA, USA; Departments of Medicine and Neurology, Brigham & Women's Hospital, Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA. ·Sleep Med · Pubmed #27198950.

ABSTRACT: OBJECTIVE: Sleep-disordered breathing is associated with hypertension and cardiovascular disease. Increased aortic stiffness is one possible linking mechanism. We evaluated the association between sleep-disordered breathing and aortic stiffness in a community-based sample. METHODS: Our community-based cross-sectional observational study included 381 participants from the Framingham Heart Study (55% women, mean age 58.0 S.D. = 9.4 years, 51% ethnic minorities). Polysomnographically derived apnea-hypopnea index and CT90% (cumulative % sleep time with oxyhemoglobin saturation <90%) quantified sleep-disordered breathing severity. Carotid-femoral pulse wave velocity, the gold-standard measure of aortic stiffness, was calculated using arterial applanation tonometry-derived waveforms and body surface measured transit distance. We assessed associations between sleep-disordered breathing and carotid-femoral pulse wave velocity using multivariable regression. We adjusted for age, sex, race, body mass index, diabetes, alcohol consumption, hormone replacement therapy, cholesterol/high-density lipoprotein, lipid-lowering therapy, anti-hypertensive medication, smoking, hypertension, and prevalent cardiovascular disease. RESULTS: After multivariable adjustment, carotid-femoral pulse wave velocity was associated with both apnea-hypopnea index (β = 0.03, 95% CI: 0.002-0.07, p= 0.04) and CT90% (β = 0.05, 95% CI: 0.005-0.1, p= 0.03). The adjusted mean carotid-femoral pulse wave velocity was 9.43 (95% CI: 9.12-9.74), 9.76 (95% CI: 9.25-10.26), and 10.15 (95% CI: 9.37-10.92) m/s, respectively, in subjects with apnea-hypopnea index <5, 5-14.9, and ≥15 events/h. CONCLUSIONS: In a community-based sample of middle aged and older men and women, sleep-disordered breathing was associated with increased carotid-femoral pulse wave velocity, a strong predictor of cardiovascular risk.

15 Article Influence of Lung Function and Sleep-disordered Breathing on All-Cause Mortality. A Community-based Study. 2016

Putcha, Nirupama / Crainiceanu, Ciprian / Norato, Gina / Samet, Jonathan / Quan, Stuart F / Gottlieb, Daniel J / Redline, Susan / Punjabi, Naresh M. ·1 Johns Hopkins University, Baltimore, Maryland. · 2 University of Southern California, Los Angeles, California. · 3 University of Arizona, Tucson, Arizona. · 4 Brigham and Women's Hospital and. · 5 VA Boston Healthcare System, Boston, Massachusetts. · 6 Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts; and. ·Am J Respir Crit Care Med · Pubmed #27105053.

ABSTRACT: RATIONALE: Whether sleep-disordered breathing (SDB) severity and diminished lung function act synergistically to heighten the risk of adverse health outcomes remains a topic of significant debate. OBJECTIVES: The current study sought to determine whether the association between lower lung function and mortality would be stronger in those with increasing severity of SDB in a community-based cohort of middle-aged and older adults. METHODS: Full montage home sleep testing and spirometry data were analyzed on 6,173 participants of the Sleep Heart Health Study. Proportional hazards models were used to calculate risk for all-cause mortality, with FEV MEASUREMENTS AND MAIN RESULTS: All-cause mortality rate was 26.9 per 1,000 person-years in those with SDB (AHI ≥5 events/h) and 18.2 per 1,000 person-years in those without (AHI <5 events/h). For every 200-ml decrease in FEV CONCLUSIONS: Lung function was associated with risk for all-cause mortality. The incremental contribution of lung function to mortality diminishes with increasing severity of SDB.

16 Article Impact of Randomization, Clinic Visits, and Medical and Psychiatric Cormorbidities on Continuous Positive Airway Pressure Adherence in Obstructive Sleep Apnea. 2016

Budhiraja, Rohit / Kushida, Clete A / Nichols, Deborah A / Walsh, James K / Simon, Richard D / Gottlieb, Daniel J / Quan, Stuart F. ·Division of Sleep and Circadian Disorders, Brigham and Women's Hospital and Division of Sleep Medicine, Harvard Medical School, Boston, MA. · Stanford University Sleep Clinic and Center for Human Sleep Research, Redwood City, CA. · Sleep Medicine and Research Center, St. Luke's Hospital, Chesterfield, MO. · Providence St. Mary Medical Center, Walla Walla, Washington. · VA Boston Healthcare System, Boston, MA. · Arizona Respiratory Center, University of Arizona, Tucson, AZ. ·J Clin Sleep Med · Pubmed #26518698.

ABSTRACT: STUDY OBJECTIVES: To evaluate factors associated with continuous positive airway pressure (CPAP) adherence in patients with obstructive sleep apnea (OSA) in the Apnea Positive Pressure Long-term Efficacy Study (APPLES) cohort. METHODS: The data from a prospective 6-mo multicenter randomized controlled trial with 558 subjects randomized to active CPAP and 547 to sham CPAP were analyzed to assess adherence to CPAP during first 2 mo (early period) and during months 5-6 (late period). RESULTS: Participants randomized to active CPAP had higher hours of nightly adherence compared to the sham CPAP group at both 2 (4.9 ± 2.0 h versus 4.07 ± 2.14 h, p < 0.001) and 6 mo (4.70 ± 2.08 h versus 3.41 ± 2.19 h, p < 0.001). Those assigned to sham CPAP were more likely to correctly identify their treatment group (70.0% versus 55.2%, p < 0.001). Irrespective of treatment group assignment, those who believed they were receiving active CPAP had higher hours of adherence than those who thought they were in the sham CPAP group at both 2 mo (4.91 ± 2.01 versus 4.17 ± 2.17, p < 0.001) and 6 mo (4.65 ± 2.10 versus 3.65 ± 2.22, p < 0.001). Among those randomized to active CPAP, older age was significantly related to CPAP use > 4 h per night. Presence of cardiovascular disorders was associated with higher hours of CPAP use, whereas presence of anxiety was associated with a trend toward lower hours of CPAP use. Presence of nasal congestion was associated with a decrease in mean daily CPAP use between the early and the late adherence period. The adherence during the week prior to a clinic visit was higher than the average adherence during the 2-mo period prior to the visit. CONCLUSIONS: Randomization to active therapy, belief that one is in the active treatment group, older age, and possibly presence of cardiovascular disorders are positively linked to CPAP adherence. Nasal congestion and anxiety are negatively associated with CPAP adherence. CPAP nightly usage increases as clinic visits approach.

17 Article Calibration Model for Apnea-Hypopnea Indices: Impact of Alternative Criteria for Hypopneas. 2015

Ho, Vu / Crainiceanu, Ciprian M / Punjabi, Naresh M / Redline, Susan / Gottlieb, Daniel J. ·Department of Medicine, Division of Sleep Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA. · Department of Medicine, The Pulmonary Center, Boston University School of Medicine, Boston, MA. · Veterans Affairs Boston Healthcare System, West Roxbury, MA. · Department of Biostatistics, Johns Hopkins University. · Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD. · Department of Medicine, Division of Sleep Medicine, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA. ·Sleep · Pubmed #26564122.

ABSTRACT: STUDY OBJECTIVE: To characterize the association among apnea-hypopnea indices (AHIs) determined using three common metrics for defining hypopnea, and to develop a model to calibrate between these AHIs. DESIGN: Cross-sectional analysis of Sleep Heart Health Study Data. SETTING: Community-based. PARTICIPANTS: There were 6,441 men and women age 40 y or older. MEASUREMENT AND RESULTS: Three separate AHIs have been calculated, using all apneas (defined as a decrease in airflow greater than 90% from baseline for ≥ 10 sec) plus hypopneas (defined as a decrease in airflow or chest wall or abdominal excursion greater than 30% from baseline, but not meeting apnea definitions) associated with either: (1) a 4% or greater fall in oxyhemoglobin saturation-AHI4; (2) a 3% or greater fall in oxyhemoglobin saturation-AHI3; or (3) a 3% or greater fall in oxyhemoglobin saturation or an event-related arousal-AHI3a. Median values were 5.4, 9.7, and 13.4 for AHI4, AHI3, and AHI3a, respectively (P < 0.0001). Penalized spline regression models were used to compare AHI values across the three metrics and to calculate prediction intervals. Comparison of regression models demonstrates divergence in AHI scores among the three methods at low AHI values and gradual convergence at higher levels of AHI. CONCLUSIONS: The three methods of scoring hypopneas yielded significantly different estimates of the apnea-hypopnea index (AHI), although the relative difference is reduced in severe disease. The regression models presented will enable clinicians and researchers to more appropriately compare AHI values obtained using differing metrics for hypopnea.

18 Article Association between Glucose Metabolism and Sleep-disordered Breathing during REM Sleep. 2015

Chami, Hassan A / Gottlieb, Daniel J / Redline, Susan / Punjabi, Naresh M. ·1 Department of Medicine, American University of Beirut, Beirut, Lebanon. · 2 Department of Medicine, Boston University School of Medicine, Boston, Massachusetts. · 3 VA Boston Healthcare System, Boston, Massachusetts. · 4 Department of Medicine, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts; and. · 5 Johns Hopkins University School of Medicine, Baltimore, Maryland. ·Am J Respir Crit Care Med · Pubmed #26200994.

ABSTRACT: RATIONALE: Sleep-disordered breathing (SDB) has been associated with impaired glucose metabolism. It is possible that the association between SDB and glucose metabolism is distinct for non-REM versus REM sleep because of differences in sleep-state-dependent sympathetic activation and/or degree of hypoxemia. OBJECTIVES: To characterize the association between REM-related SDB, glucose intolerance, and insulin resistance in a community-based sample. METHODS: A cross-sectional analysis that included 3,310 participants from the Sleep Heart Health Study was undertaken (53% female; mean age, 66.1 yr). Full montage home-polysomnography and fasting glucose were available on all participants. SDB severity during REM and non-REM sleep was quantified using the apnea-hypopnea index in REM (AHIREM) and non-REM sleep (AHINREM), respectively. Fasting and 2-hour post-challenge glucose levels were assessed during a glucose tolerance test (n = 2,264). The homeostatic model assessment index for insulin resistance (HOMA-IR) was calculated (n = 1,543). Linear regression was used to assess the associations of AHIREM and AHINREM with fasting and post-prandial glucose levels and HOMA-IR. MEASUREMENTS AND MAIN RESULTS: AHIREM and AHINREM were associated with fasting glycemia, post-prandial glucose levels, and HOMA-IR in models that adjusted for age, sex, race, and site. However, with additional adjustment for body mass index, waist circumference, and sleep duration, AHIREM was only associated with HOMA-IR (β = 0.04; 95% CI, 0.1-0.07; P = 0.01), whereas AHINREM was only associated with fasting (β = 0.93; 95% CI, 0.14-1.72; P = 0.02) and post-prandial glucose levels (β = 3.0; 95% CI, 0.5-5.5; P = 0.02). CONCLUSIONS: AHIREM is associated with insulin resistance but not with fasting glycemia or glucose intolerance.

19 Article Association of severe obstructive sleep apnea and elevated blood pressure despite antihypertensive medication use. 2014

Walia, Harneet K / Li, Hong / Rueschman, Michael / Bhatt, Deepak L / Patel, Sanjay R / Quan, Stuart F / Gottlieb, Daniel J / Punjabi, Naresh M / Redline, Susan / Mehra, Reena. ·Cleveland Clinic, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH; · Center for Clinical Investigation, Case Western Reserve University, Cleveland, OH; · Brigham and Women's Hospital, Boston, MA; · Brigham and Women's Hospital Heart & Vascular Center, Harvard Medical School, Boston, MA. · Brigham and Women's Hospital, Boston, MA; ; Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; · Brigham and Women's Hospital, Boston, MA; ; VA Boston Healthcare System, Harvard Medical School, Boston, MA; · Johns Hopkins University, Baltimore, MD. ·J Clin Sleep Med · Pubmed #25126027.

ABSTRACT: RATIONALE: We hypothesized that untreated severe obstructive sleep apnea (OSA) is associated with elevated ambulatory blood pressure (BP) in subjects with high cardiovascular disease (CVD) risk despite medical management. METHODS: Data from the baseline examination of the Heart Biomarker Evaluation in Apnea Treatment (HeartBEAT) study, a 4-site randomized controlled trial were analyzed. Individuals with moderate-severe OSA (apnea hypopnea index, AHI = 15-50) and cardiovascular risk were recruited from cardiology practices. Those with hypertension were included. Intensive antihypertensive regimen (IAR) was defined as ≥ 3 antihypertensives including a diuretic. Definitions were: controlled BP (BP < 130/80), uncontrolled elevated BP (BP ≥ 130/80 not on IAR) and resistant elevated BP (BP ≥ 130/80 mm Hg despite IAR). Associations of untreated severe OSA (AHI ≥ 30) and uncontrolled and resistant elevated BP were evaluated using logistic regression analyses adjusted for age, sex, race, body mass index, smoking status, diabetes, and CVD. RESULTS: Among the 284 participants (mean age 63.1 ± 7.2 years, 23.6% with severe OSA), 61.6% had controlled BP, 28.5% had uncontrolled elevated BP, and 9.9% had resistant elevated BP. Among participants prescribed IAR, resistant elevated BP was more prevalent in those with severe compared to moderate OSA (58.3% vs. 28.6%, p = 0.01). Participants with severe OSA had a 4-fold higher adjusted odds of resistant elevated BP (OR 4.1, 95% CI: 1.7-10.2), a finding not reproduced in the absence of IAR use. CONCLUSIONS: Among patients with increased cardiovascular risk and moderate to severe OSA, untreated severe compared to moderate OSA was associated with elevated BP despite IAR suggesting untreated severe OSA contributes to poor BP control despite aggressive medication use. COMMENTARY: A commentary on this article appears in this issue on page 845.

20 Article CPAP versus oxygen in obstructive sleep apnea. 2014

Gottlieb, Daniel J / Punjabi, Naresh M / Mehra, Reena / Patel, Sanjay R / Quan, Stuart F / Babineau, Denise C / Tracy, Russell P / Rueschman, Michael / Blumenthal, Roger S / Lewis, Eldrin F / Bhatt, Deepak L / Redline, Susan. ·From the Veterans Affairs Boston Healthcare System (D.J.G., D.L.B.), Brigham and Women's Hospital (D.J.G., S.R.P., S.F.Q., M.R., E.F.L., D.L.B., S.R.), Harvard Medical School (D.J.G., S.R.P., S.F.Q., E.F.L., D.L.B., S.R.), Boston University School of Medicine (D.J.G.), and Beth Israel Deaconess Medical Center (S.R.P., S.R.) - all in Boston · Johns Hopkins University, Baltimore (N.M.P., R.S.B.) · Cleveland Clinic (R.M.) and Case Western Reserve University (R.M., D.C.B.) - both in Cleveland · and the University of Vermont, Colchester (R.P.T.). ·N Engl J Med · Pubmed #24918372.

ABSTRACT: BACKGROUND: Obstructive sleep apnea is associated with hypertension, inflammation, and increased cardiovascular risk. Continuous positive airway pressure (CPAP) reduces blood pressure, but adherence is often suboptimal, and the benefit beyond management of conventional risk factors is uncertain. Since intermittent hypoxemia may underlie cardiovascular sequelae of sleep apnea, we evaluated the effects of nocturnal supplemental oxygen and CPAP on markers of cardiovascular risk. METHODS: We conducted a randomized, controlled trial in which patients with cardiovascular disease or multiple cardiovascular risk factors were recruited from cardiology practices. Patients were screened for obstructive sleep apnea with the use of the Berlin questionnaire, and home sleep testing was used to establish the diagnosis. Participants with an apnea-hypopnea index of 15 to 50 events per hour were randomly assigned to receive education on sleep hygiene and healthy lifestyle alone (the control group) or, in addition to education, either CPAP or nocturnal supplemental oxygen. Cardiovascular risk was assessed at baseline and after 12 weeks of the study treatment. The primary outcome was 24-hour mean arterial pressure. RESULTS: Of 318 patients who underwent randomization, 281 (88%) could be evaluated for ambulatory blood pressure at both baseline and follow-up. On average, the 24-hour mean arterial pressure at 12 weeks was lower in the group receiving CPAP than in the control group (-2.4 mm Hg; 95% confidence interval [CI], -4.7 to -0.1; P=0.04) or the group receiving supplemental oxygen (-2.8 mm Hg; 95% CI, -5.1 to -0.5; P=0.02). There was no significant difference in the 24-hour mean arterial pressure between the control group and the group receiving oxygen. A sensitivity analysis performed with the use of multiple imputation approaches to assess the effect of missing data did not change the results of the primary analysis. CONCLUSIONS: In patients with cardiovascular disease or multiple cardiovascular risk factors, the treatment of obstructive sleep apnea with CPAP, but not nocturnal supplemental oxygen, resulted in a significant reduction in blood pressure. (Funded by the National Heart, Lung, and Blood Institute and others; HeartBEAT ClinicalTrials.gov number, NCT01086800 .).

21 Article Obstructive sleep apnea and diurnal nondipping hemodynamic indices in patients at increased cardiovascular risk. 2014

Seif, Fadi / Patel, Sanjay R / Walia, Harneet K / Rueschman, Michael / Bhatt, Deepak L / Blumenthal, Roger S / Quan, Stuart F / Gottlieb, Daniel J / Lewis, Eldrin F / Patil, Susheel P / Punjabi, Naresh M / Babineau, Denise C / Redline, Susan / Mehra, Reena. ·aDepartment of Medicine, Case School of Medicine, Cleveland, Ohio bBrigham and Women's Hospital cBeth Israel Deaconess Medical Center dVA Boston Healthcare System, Harvard Medical School, Boston, Massachusetts eJohns Hopkins University, Baltimore, Maryland fDepartment of Epidemiology and Biostatistics, Case Western Reserve University gCleveland Clinic, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, Ohio, USA. ·J Hypertens · Pubmed #24351803.

ABSTRACT: RATIONALE: We hypothesized increasing obstructive sleep apnea (OSA) severity would be associated with nondipping blood pressure (BP) in increased cardiovascular disease (CVD) risk. METHODS: Baseline data from 298 cardiology patients recruited for a multicenter randomized controlled trial were examined. Dipping was defined as a sleep-related BP or heart rate (HR) reduction of at least 10%. Logistic regression models were fit, adjusting for age, sex, race, BMI, CVD risk factors, CVD, and study site. RESULTS: There was a statistically significant 4% increase in the odds of nondipping SBP per 1-unit increase in both apnea hypopnea index (AHI) and oxygen desaturation index (ODI). There was no significant relationship between AHI and nondipping mean arterial pressure (MAP); however, a 3% increase in the odds of nondipping MAP per 1-unit increase in ODI was observed [odds ratio (OR) = 1.03; 95% confidence interval (CI) 1.00-1.05]. At severe OSA levels, a 10 and 4% increase in odds of nondipping DBP per 1-unit increase in AHI and ODI were observed, respectively. A 6% [OR = 1.06; 95% CI (1.01-1.10)] increase in nondipping HR odds was observed with each increase in ODI until the upper quartile of ODI. CONCLUSION: In patients at cardiovascular risk and moderate-to-severe OSA, increasing AHI and/or ODI were associated with increased odds of nondipping SBP and nondipping MAP. More severe levels of AHI and ODI also were associated with nondipping DBP. These results support progressive BP burden associated with increased OSA severity even in patients managed by cardiology specialty care.

22 Article Relationship between delta power and the electrocardiogram-derived cardiopulmonary spectrogram: possible implications for assessing the effectiveness of sleep. 2014

Thomas, Robert Joseph / Mietus, Joseph E / Peng, Chung-Kang / Guo, Dan / Gozal, David / Montgomery-Downs, Hawley / Gottlieb, Daniel J / Wang, Cheng-Yen / Goldberger, Ary L. ·Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA 02215, United States. Electronic address: rthomas1@bidmc.harvard.edu. · Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA 02215, United States. · Sleep Disorders Center, Meitan General Hospital, Beijing, China. · Department of Pediatrics, University of Chicago, 5721 S. Maryland Ave, MC 8000, Suite K-160, Chicago, IL 60637, United States. · Department of Psychology, West Virginia University, 53 Campus Dr., Morgantown, WV 26506, United States. · Veterans Affairs Health Care System, 1400 VFW Pkwy, West Roxbury, MA 02132, United States. · Research Center for Adaptive Data Analysis, National Central University, Chungli, Taiwan. · Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA 02215, United States; Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA 02215, United States. ·Sleep Med · Pubmed #24269134.

ABSTRACT: OBJECTIVES: The physiologic relationship between slow-wave activity (SWA) (0-4 Hz) on the electroencephalogram (EEG) and high-frequency (0.1-0.4 Hz) cardiopulmonary coupling (CPC) derived from electrocardiogram (ECG) sleep spectrograms is not known. Because high-frequency CPC appears to be a biomarker of stable sleep, we tested the hypothesis that that slow-wave EEG power would show a relatively fixed-time relationship to periods of high-frequency CPC. Furthermore, we speculated that this correlation would be independent of conventional nonrapid eye movement (NREM) sleep stages. METHODS: We analyzed selected datasets from an archived polysomnography (PSG) database, the Sleep Heart Health Study I (SHHS-I). We employed the cross-correlation technique to measure the degree of which 2 signals are correlated as a function of a time lag between them. Correlation analyses between high-frequency CPC and delta power (computed both as absolute and normalized values) from 3150 subjects with an apnea-hypopnea index (AHI) of ≤5 events per hour of sleep were performed. RESULTS: The overall correlation (r) between delta power and high-frequency coupling (HFC) power was 0.40±0.18 (P=.001). Normalized delta power provided improved correlation relative to absolute delta power. Correlations were somewhat reduced in the second half relative to the first half of the night (r=0.45±0.20 vs r=0.34±0.23). Correlations were only affected by age in the eighth decade. There were no sex differences and only small racial or ethnic differences were noted. CONCLUSIONS: These results support a tight temporal relationship between slow wave power, both within and outside conventional slow wave sleep periods, and high frequency cardiopulmonary coupling, an ECG-derived biomarker of "stable" sleep. These findings raise mechanistic questions regarding the cross-system integration of neural and cardiopulmonary control during sleep.

23 Article Impact of treatment with continuous positive airway pressure (CPAP) on weight in obstructive sleep apnea. 2013

Quan, Stuart F / Budhiraja, Rohit / Clarke, Denise P / Goodwin, James L / Gottlieb, Daniel J / Nichols, Deborah A / Simon, Richard D / Smith, Terry W / Walsh, James K / Kushida, Clete A. ·Division of Sleep Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA ; Arizona Respiratory Center, University of Arizona, Tucson, AZ. ·J Clin Sleep Med · Pubmed #24127141.

ABSTRACT: STUDY OBJECTIVE: To determine the impact of continuous positive airway pressure (CPAP) on weight change in persons with obstructive sleep apnea (OSA). DESIGN SETTING AND PARTICIPANTS: The Apnea Positive Pressure Long-term Efficacy Study (APPLES) was a 6-month, randomized, double-blinded sham-controlled multicenter clinical trial conducted at 5 sites in the United States. Of 1,105 participants with an apnea hypopnea index ≥ 10 events/ hour initially randomized, 812 had body weight measured at baseline and after 6 months of study. INTERVENTION: CPAP or Sham CPAP. MEASUREMENTS: Body weight, height, hours of CPAP or Sham CPAP use, Epworth Sleepiness Scale score. RESULTS: Participants randomized to CPAP gained 0.35 ± 5.01 kg, whereas those on Sham CPAP lost 0.70 ± 4.03 kg (mean ± SD, p = 0.001). Amount of weight gain with CPAP was related to hours of device adherence, with each hour per night of use predicting a 0.42 kg increase in weight. This association was not noted in the Sham CPAP group. CPAP participants who used their device ≥ 4 h per night on ≥ 70% of nights gained the most weight over 6 months in comparison to non-adherent CPAP participants (1.0 ± 5.3 vs. -0.3 ± 5.0 kg, p = 0.014). CONCLUSIONS: OSA patients using CPAP may gain a modest amount of weight with the greatest weight gain found in those most compliant with CPAP. COMMENTARY: A commentary on this article appears in this issue on page 995. CITATION: Quan SF; Budhiraja R; Clarke DP; Goodwin JL; Gottlieb DJ; Nichols DA; Simon RD; Smith TW; Walsh JK; Kushida CA. Impact of treatment with continuous positive airway pressure (CPAP) on weight in obstructive sleep apnea.

24 Article Vascular inflammation and sleep disordered breathing in a community-based cohort. 2013

Chami, Hassan A / Fontes, João D / Vasan, Ramachandran S / Keaney, John F / O'Connor, George T / Larson, Martin G / Benjamin, Emelia J / Gottlieb, Daniel J. ·Department of Medicine, American University of Beirut, Beirut, Lebanon. hchami@aub.edu.lb ·Sleep · Pubmed #23633759.

ABSTRACT: STUDY OBJECTIVES: Sleep disordered breathing is associated with cardiovascular disease. The pathophysiologic mechanisms remain unclear, but enhanced vascular inflammation is implicated. We sought to evaluate the association of sleep disordered breathing with biomarkers of inflammation. DESIGN: Cross-sectional, observational. SETTING: Community-based. PARTICIPANTS: There were 900 participants from the Framingham Heart Study site of the Sleep Heart Health Study (52% females, mean age 60 y, 23% ethnic minorities). INTERVENTIONS: None. MEASUREMENTS: We assessed circulating levels of nine inflammatory biomarkers in relation to polysomnographically-derived apnea-hypopnea index and hypoxemia index (% sleep time with oxyhemoglobin saturation < 90%). Multivariable models were adjusted for demographics, smoking, cardiovascular diseases, diabetes, and other potential confounders, without and with adjustment for body mass index. RESULTS: With multivariable adjustment not including body mass index, the apnea-hypopnea index was associated with C-reactive protein, inter-leukin-6, fibrinogen, intercellular adhesion molecule-1, and P-selectin levels and hypoxemia index was associated with C-reactive protein, interleukin-6, and fibrinogen levels. After adjustment for body mass index, only the association of interleukin-6 with sleep disordered breathing remained significant: the adjusted mean serum interleukin-6 level was 2.93, 3.14, 3.34, and 4.62 pg/mL, respectively, in participants with apnea-hypopnea index < 5, 5-14.9, 15-29.9, and ≥ 30 events/h (P = 0.01 for trend) and 2.97, 3.01, 3.35, and 4.85 pg/mL, respectively, in participants with hypoxemia index < 0.5, 0.5-4.9, 5-9.9, and ≥ 10% of sleep time (P = 0.02 for trend). CONCLUSIONS: In a community-based sample, sleep disordered breathing is associated with higher levels of interleukin-6, a marker of myocardial infarction risk and mortality. Adiposity may mediate the increased levels of C-reactive protein, fibrinogen, intercellular adhesion molecule-1, and P-selectin observed in sleep disordered breathing.

25 Article Association between obstructive sleep apnea severity and endothelial dysfunction in an increased background of cardiovascular burden. 2013

Seif, Fadi / Patel, Sanjay R / Walia, Harneet / Rueschman, Michael / Bhatt, Deepak L / Gottlieb, Daniel J / Lewis, Eldrin F / Patil, Susheel P / Punjabi, Naresh M / Babineau, Denise C / Redline, Susan / Mehra, Reena. ·Department of Medicine, Case School of Medicine, Cleveland, OH, USA. ·J Sleep Res · Pubmed #23331757.

ABSTRACT: The objective of this study is to examine whether increasing obstructive sleep apnea (OSA) severity is associated with worsening endothelial function. The design is a cross-sectional examination of the baseline assessment of a multi-centre randomized controlled clinical trial examining the effects of oxygen, continuous positive airway pressure (CPAP) therapy or lifestyle modifications on cardiovascular biomarkers. Participants were recruited from cardiology clinics at four sites. Participants with an apnea-hypopnea index (AHI) of 15-50 and known cardio/cerebrovascular disease (CVD) or CVD risk factors were included. OSA severity indices [oxygen desaturation index (ODI), AHI and percentage of sleep time below 90% oxygen saturation (total sleep time <90)] and a measure of endothelium-mediated vasodilatation [Framingham reactive hyperaemia index (F-RHI) derived from peripheral arterial tonometry (PAT)] were assessed. The sample included 267 individuals with a mean AHI of 25.0 ± 8.5 SD and mean F-RHI 0.44 ± 0.38. In adjusted models, the slope of the relationship between ODI and F-RHI differed above and below an ODI of 24.6 (P = 0.04), such that above an ODI of 24.6 there was a marginally significant decline in the geometric mean of the PAT ratio by 3% [95% confidence interval (CI): 0%, 5%; P = 0.05], while below this point, there was a marginally significant incline in the geometric mean of the PAT ratio by 13% (95% CI: 0%, 27%; P = 0.05) per 5-unit increase in ODI. A similar pattern was observed between AHI and F-RHI. No relation was noted with total sleep time <90 and F-RHI. There was evidence of a graded decline in endothelial function in association with higher levels of intermittent hypoxaemia.

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