NDLI: Estimating the prevalence of sleep-disordered breathing in community-based, long-term stroke survivors using a validated predictive model.

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Estimating the prevalence of sleep-disordered breathing in community-based, long-term stroke survivors using a validated predictive model.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Pearce, Dora C. Cadilhac, Dominique A. Pierce, Robert J. Thrift, Amanda G. David, Stephen Donnan, Geoffrey A.
Description	Country affiliation: Australia Author Affiliation: Pearce DC ( National Stroke Research Institute, Bowen Centre, Austin Health, Heidelberg Heights, Victoria, Australia. dpearce@nsri.org.au)
Abstract	BACKGROUND: Assessing sleep-disordered breathing (SDB) in aged or disabled populations is difficult. AIMS: To validate a multivariable apnea risk prediction index (MAPI) in stroke survivors and estimate SDB prevalence (apnea-hypopnea index >or=10) in a community-based stroke cohort. METHODS: Self-reported sleep apnea symptoms, demographic and anthropometric data were obtained from a hospital-based (SCOPES II, n = 152) and a community-based (NEMESIS, n = 431) cohort at about 3 years after stroke. Logistic regression models for prediction of SDB using the MAPI were validated with home-based nocturnal polygraphic data recordings obtained in 74 SCOPES II participants. RESULTS: NEMESIS subjects (median age 76, females 45%) were older than SCOPES II subjects (median age 70, females 42%). SDB prevalence was 44.9% in the nocturnal polygraphy subset, and estimated as 44.1% (SCOPES II) and 50.6% (NEMESIS) using a modified MAPI. CONCLUSION: The MAPI can be reliably used in stroke cohorts and SDB affects about half of chronic stroke survivors.
File Format	HTM / HTML
ISSN	10159770
e-ISSN	14219786
Journal	Cerebrovascular Diseases
Issue Number	4
Volume Number	26
Language	English
Publisher	Karger
Publisher Date	2008-01-01
Publisher Place	Switzerland
Access Restriction	Open
Subject Keyword	Discipline Vascular Diseases Discipline Cardiology Sleep Apnea Syndromes Epidemiology Stroke Chronic Disease Logistic Models Polysomnography Predictive Value Of Tests Risk Factors Diagnosis Validation Studies
Content Type	Text
Resource Type	Article
Subject	Neurology Neurology (clinical) Cardiology and Cardiovascular Medicine

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