Literature DB >> 26857052

Predicting CPAP Use and Treatment Outcomes Using Composite Indices of Sleep Apnea Severity.

Karthik Balakrishnan1, Kathryn T James2,3, Edward M Weaver2,3,4,5.   

Abstract

STUDY
OBJECTIVES: Measures of baseline sleep apnea disease burden (apnea-hypopnea index, Epworth Sleepiness Scale) predict continuous positive airway pressure (CPAP) adherence, but composite indices of sleep apnea severity (Sleep Apnea Severity Index, Modified Sleep Apnea Severity Index) may be more robust measures of disease burden. We tested the relative prognostic ability of each measure of sleep apnea disease burden to predict subsequent CPAP adherence and subjective sleep outcomes.
METHODS: Prospective cohort study at a tertiary academic sleep center. Patients (n = 323) underwent initial diagnostic polysomnography for suspected obstructive sleep apnea and 6 mo of subsequent CPAP therapy.
RESULTS: Baseline apnea-hypopnea index and both composite indices predicted adherence to CPAP therapy at 6 mo in multivariate analyses (all p ≤ 0.001). Baseline Epworth Sleepiness Scale did not predict CPAP adherence (p = 0.22). Both composite indices were statistically stronger predictors of CPAP adherence at 6 mo than apnea-hypopnea index (p < 0.001). In multivariate analyses, baseline apnea-hypopnea index (p < 0.05) and both composite indices (both p < 0.04) predicted change in Pittsburgh Sleep Quality Index, whereas only the composite indices predicted changes in Sleep Apnea Quality of Life Index (both p < 0.001). Adjustment for treatment adherence did not affect the relationship of the composite indices with change in Sleep Apnea Quality of Life Index (both p ≤ 0.005).
CONCLUSIONS: Composite indices of baseline sleep apnea severity better predict objective CPAP adherence and subjective treatment outcomes than baseline apnea-hypopnea index and baseline Epworth Sleepiness Scale.
© 2016 American Academy of Sleep Medicine.

Entities:  

Keywords:  cohort studies; illness burden; obstructive sleep apnea; patient adherence; prospective studies

Mesh:

Year:  2016        PMID: 26857052      PMCID: PMC4877317          DOI: 10.5664/jcsm.5884

Source DB:  PubMed          Journal:  J Clin Sleep Med        ISSN: 1550-9389            Impact factor:   4.062


  20 in total

Review 1.  Epidemiology of obstructive sleep apnea: a population health perspective.

Authors:  Terry Young; Paul E Peppard; Daniel J Gottlieb
Journal:  Am J Respir Crit Care Med       Date:  2002-05-01       Impact factor: 21.405

Review 2.  Improving CPAP use by patients with the sleep apnoea/hypopnoea syndrome (SAHS).

Authors:  Heather M Engleman; Matt R Wild
Journal:  Sleep Med Rev       Date:  2003-02       Impact factor: 11.609

3.  Polysomnography indexes are discordant with quality of life, symptoms, and reaction times in sleep apnea patients.

Authors:  Edward M Weaver; B Tucker Woodson; David L Steward
Journal:  Otolaryngol Head Neck Surg       Date:  2005-02       Impact factor: 3.497

4.  Advanced statistics: bootstrapping confidence intervals for statistics with "difficult" distributions.

Authors:  Jason S Haukoos; Roger J Lewis
Journal:  Acad Emerg Med       Date:  2005-04       Impact factor: 3.451

5.  Obstructive sleep apnea in minorities.

Authors:  Miguel A Arias; Alberto Alonso-Fernández; Francisco García-Río
Journal:  Am J Med       Date:  2007-03       Impact factor: 4.965

6.  Prevalence of symptoms and risk of sleep apnea in the US population: Results from the national sleep foundation sleep in America 2005 poll.

Authors:  David M Hiestand; Pat Britz; Molly Goldman; Barbara Phillips
Journal:  Chest       Date:  2006-09       Impact factor: 9.410

7.  Relationship between Clinical and Polysomnography Measures Corrected for CPAP Use.

Authors:  Erin M Kirkham; Susan R Heckbert; Edward M Weaver
Journal:  J Clin Sleep Med       Date:  2015-11-15       Impact factor: 4.062

8.  Factors influencing subjective sleepiness in patients with obstructive sleep apnea syndrome.

Authors:  Kenichi Hayashida; Yuichi Inoue; Shintaro Chiba; Tomoko Yagi; Mitsuyoshi Urashima; Yutaka Honda; Hiroshi Itoh
Journal:  Psychiatry Clin Neurosci       Date:  2007-10       Impact factor: 5.188

9.  Fatigue in obstructive sleep apnea: driven by depressive symptoms instead of apnea severity?

Authors:  Wayne A Bardwell; Polly Moore; Sonia Ancoli-Israel; Joel E Dimsdale
Journal:  Am J Psychiatry       Date:  2003-02       Impact factor: 18.112

10.  Relationship between hours of CPAP use and achieving normal levels of sleepiness and daily functioning.

Authors:  Terri E Weaver; Greg Maislin; David F Dinges; Thomas Bloxham; Charles F P George; Harly Greenberg; Gihan Kader; Mark Mahowald; Joel Younger; Allan I Pack
Journal:  Sleep       Date:  2007-06       Impact factor: 5.849

View more
  4 in total

1.  Symptoms During CPAP Therapy Are the Major Reason for Contacting the Sleep Unit Between Two Routine Contacts.

Authors:  Heidi Avellan-Hietanen; Pirkko Brander; Adel Bachour
Journal:  J Clin Sleep Med       Date:  2019-01-15       Impact factor: 4.062

2.  CPAP Adherence Predictors in a Randomized Trial of Moderate-to-Severe OSA Enriched With Women and Minorities.

Authors:  Anna M May; Tarek Gharibeh; Lu Wang; Amanda Hurley; Harneet Walia; Kingman P Strohl; Reena Mehra
Journal:  Chest       Date:  2018-04-21       Impact factor: 9.410

3.  Comorbidities associated with obstructive sleep apnea: a retrospective Egyptian study on 244 patients.

Authors:  Rania Ahmad Sweed; Salma Hassan; Nashwa Hassan Abd ElWahab; Soha Rashed Aref; Mahmoud Ibrahim Mahmoud
Journal:  Sleep Breath       Date:  2019-01-26       Impact factor: 2.816

4.  Factors Affecting Long-Term Compliance of CPAP Treatment-A Single Centre Experience.

Authors:  Agata Gabryelska; Marcin Sochal; Bartosz Wasik; Przemysław Szczepanowski; Piotr Białasiewicz
Journal:  J Clin Med       Date:  2021-12-27       Impact factor: 4.241

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.