Development, Validation, and Assessment of an Ischemic Stroke or Transient Ischemic Attack-Specific Prediction Tool for Obstructive Sleep Apnea

Jason J. Sico, H. Klar Yaggi, Susan Ofner, John Concato, Charles Austin, Jared Ferguson, Li Qin, Lauren Tobias, Stanley Taylor, Carlos A. Vaz Fragoso, Vincent McLain, Linda Williams, Dawn Bravata

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Background: Screening instruments for obstructive sleep apnea (OSA), as used routinely to guide clinicians regarding patient referral for polysomnography (PSG), rely heavily on symptomatology. We sought to develop and validate a cerebrovascular disease-specific OSA prediction model less reliant on symptomatology, and to compare its performance with commonly used screening instruments within a population with ischemic stroke or transient ischemic attack (TIA). Methods: Using data on demographic factors, anthropometric measurements, medical history, stroke severity, sleep questionnaires, and PSG from 2 independently derived, multisite, randomized trials that enrolled patients with stroke or TIA, we developed and validated a model to predict the presence of OSA (i.e., Apnea-Hypopnea Index ≥5 events per hour). Model performance was compared with that of the Berlin Questionnaire, Epworth Sleepiness Scale (ESS), the Snoring, Tiredness, Observed apnea, high blood Pressure, Body mass index, Age, Neck circumference, and Gender instrument, and the Sleep Apnea Clinical Score. Results: The new SLEEP Inventory (Sex, Left heart failure, ESS, Enlarged neck, weight [in Pounds], Insulin resistance/diabetes, and National Institutes of Health Stroke Scale) performed modestly better than other instruments in identifying patients with OSA, showing reasonable discrimination in the development (c-statistic .732) and validation (c-statistic .731) study populations, and having the highest negative predictive value of all in struments. Conclusions: Clinicians should be aware of these limitations in OSA screening instruments when making decisions about referral for PSG. The high negative predictive value of the SLEEP INventory may be useful in determining and prioritizing patients with stroke or TIA least in need of overnight PSG.

Original languageEnglish (US)
JournalJournal of Stroke and Cerebrovascular Diseases
DOIs
StateAccepted/In press - Feb 7 2017

Fingerprint

Transient Ischemic Attack
Obstructive Sleep Apnea
Polysomnography
Stroke
Apnea
Neck
Referral and Consultation
Cerebrovascular Disorders
Equipment and Supplies
Snoring
Sleep Apnea Syndromes
National Institutes of Health (U.S.)
Berlin
Population
Insulin Resistance
Decision Making
Sleep
Body Mass Index
Heart Failure
Demography

Keywords

  • Ischemic stroke
  • Obstructive sleep apnea
  • Screening
  • TIA

ASJC Scopus subject areas

  • Surgery
  • Rehabilitation
  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine

Cite this

Development, Validation, and Assessment of an Ischemic Stroke or Transient Ischemic Attack-Specific Prediction Tool for Obstructive Sleep Apnea. / Sico, Jason J.; Yaggi, H. Klar; Ofner, Susan; Concato, John; Austin, Charles; Ferguson, Jared; Qin, Li; Tobias, Lauren; Taylor, Stanley; Vaz Fragoso, Carlos A.; McLain, Vincent; Williams, Linda; Bravata, Dawn.

In: Journal of Stroke and Cerebrovascular Diseases, 07.02.2017.

Research output: Contribution to journalArticle

Sico, Jason J. ; Yaggi, H. Klar ; Ofner, Susan ; Concato, John ; Austin, Charles ; Ferguson, Jared ; Qin, Li ; Tobias, Lauren ; Taylor, Stanley ; Vaz Fragoso, Carlos A. ; McLain, Vincent ; Williams, Linda ; Bravata, Dawn. / Development, Validation, and Assessment of an Ischemic Stroke or Transient Ischemic Attack-Specific Prediction Tool for Obstructive Sleep Apnea. In: Journal of Stroke and Cerebrovascular Diseases. 2017.
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abstract = "Background: Screening instruments for obstructive sleep apnea (OSA), as used routinely to guide clinicians regarding patient referral for polysomnography (PSG), rely heavily on symptomatology. We sought to develop and validate a cerebrovascular disease-specific OSA prediction model less reliant on symptomatology, and to compare its performance with commonly used screening instruments within a population with ischemic stroke or transient ischemic attack (TIA). Methods: Using data on demographic factors, anthropometric measurements, medical history, stroke severity, sleep questionnaires, and PSG from 2 independently derived, multisite, randomized trials that enrolled patients with stroke or TIA, we developed and validated a model to predict the presence of OSA (i.e., Apnea-Hypopnea Index ≥5 events per hour). Model performance was compared with that of the Berlin Questionnaire, Epworth Sleepiness Scale (ESS), the Snoring, Tiredness, Observed apnea, high blood Pressure, Body mass index, Age, Neck circumference, and Gender instrument, and the Sleep Apnea Clinical Score. Results: The new SLEEP Inventory (Sex, Left heart failure, ESS, Enlarged neck, weight [in Pounds], Insulin resistance/diabetes, and National Institutes of Health Stroke Scale) performed modestly better than other instruments in identifying patients with OSA, showing reasonable discrimination in the development (c-statistic .732) and validation (c-statistic .731) study populations, and having the highest negative predictive value of all in struments. Conclusions: Clinicians should be aware of these limitations in OSA screening instruments when making decisions about referral for PSG. The high negative predictive value of the SLEEP INventory may be useful in determining and prioritizing patients with stroke or TIA least in need of overnight PSG.",
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T1 - Development, Validation, and Assessment of an Ischemic Stroke or Transient Ischemic Attack-Specific Prediction Tool for Obstructive Sleep Apnea

AU - Sico, Jason J.

AU - Yaggi, H. Klar

AU - Ofner, Susan

AU - Concato, John

AU - Austin, Charles

AU - Ferguson, Jared

AU - Qin, Li

AU - Tobias, Lauren

AU - Taylor, Stanley

AU - Vaz Fragoso, Carlos A.

AU - McLain, Vincent

AU - Williams, Linda

AU - Bravata, Dawn

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N2 - Background: Screening instruments for obstructive sleep apnea (OSA), as used routinely to guide clinicians regarding patient referral for polysomnography (PSG), rely heavily on symptomatology. We sought to develop and validate a cerebrovascular disease-specific OSA prediction model less reliant on symptomatology, and to compare its performance with commonly used screening instruments within a population with ischemic stroke or transient ischemic attack (TIA). Methods: Using data on demographic factors, anthropometric measurements, medical history, stroke severity, sleep questionnaires, and PSG from 2 independently derived, multisite, randomized trials that enrolled patients with stroke or TIA, we developed and validated a model to predict the presence of OSA (i.e., Apnea-Hypopnea Index ≥5 events per hour). Model performance was compared with that of the Berlin Questionnaire, Epworth Sleepiness Scale (ESS), the Snoring, Tiredness, Observed apnea, high blood Pressure, Body mass index, Age, Neck circumference, and Gender instrument, and the Sleep Apnea Clinical Score. Results: The new SLEEP Inventory (Sex, Left heart failure, ESS, Enlarged neck, weight [in Pounds], Insulin resistance/diabetes, and National Institutes of Health Stroke Scale) performed modestly better than other instruments in identifying patients with OSA, showing reasonable discrimination in the development (c-statistic .732) and validation (c-statistic .731) study populations, and having the highest negative predictive value of all in struments. Conclusions: Clinicians should be aware of these limitations in OSA screening instruments when making decisions about referral for PSG. The high negative predictive value of the SLEEP INventory may be useful in determining and prioritizing patients with stroke or TIA least in need of overnight PSG.

AB - Background: Screening instruments for obstructive sleep apnea (OSA), as used routinely to guide clinicians regarding patient referral for polysomnography (PSG), rely heavily on symptomatology. We sought to develop and validate a cerebrovascular disease-specific OSA prediction model less reliant on symptomatology, and to compare its performance with commonly used screening instruments within a population with ischemic stroke or transient ischemic attack (TIA). Methods: Using data on demographic factors, anthropometric measurements, medical history, stroke severity, sleep questionnaires, and PSG from 2 independently derived, multisite, randomized trials that enrolled patients with stroke or TIA, we developed and validated a model to predict the presence of OSA (i.e., Apnea-Hypopnea Index ≥5 events per hour). Model performance was compared with that of the Berlin Questionnaire, Epworth Sleepiness Scale (ESS), the Snoring, Tiredness, Observed apnea, high blood Pressure, Body mass index, Age, Neck circumference, and Gender instrument, and the Sleep Apnea Clinical Score. Results: The new SLEEP Inventory (Sex, Left heart failure, ESS, Enlarged neck, weight [in Pounds], Insulin resistance/diabetes, and National Institutes of Health Stroke Scale) performed modestly better than other instruments in identifying patients with OSA, showing reasonable discrimination in the development (c-statistic .732) and validation (c-statistic .731) study populations, and having the highest negative predictive value of all in struments. Conclusions: Clinicians should be aware of these limitations in OSA screening instruments when making decisions about referral for PSG. The high negative predictive value of the SLEEP INventory may be useful in determining and prioritizing patients with stroke or TIA least in need of overnight PSG.

KW - Ischemic stroke

KW - Obstructive sleep apnea

KW - Screening

KW - TIA

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