Sleep-disordered breathing in patients with cardiovascular diseases cannot be detected by ESS, STOP-BANG, and Berlin questionnaires

Sleep-disordered breathing in patients with cardiovascular diseases cannot be detected by ESS,... Sleep-disordered breathing (SDB) is highly prevalent in patients with cardiovascular diseases (CVD) and associated with poor outcome. At least 50% of heart failure (HF) patients present with SDB, equally divided in obstructive sleep apnea (OSA) and central sleep apnea (CSA). CVD patients with SDB do not always present with typical SDB symptoms. Therefore, we asked whether established questionnaires allow for the reliable detection of SDB. In this prospective cohort study, 89 CVD patients (54 male, 59 ± 15 years, BMI 30 ± 6 kg/m2) in stable clinical state underwent an ambulatory polygraphy. SDB was defined as an apnea-hypopnea index (AHI) ≥ 15/h. We evaluated the Epworth Sleepiness Scale (ESS), STOP-BANG and Berlin questionnaires as well as anthropometric data and comorbidities regarding their ability to predict SDB. The ESS showed no correlation with SDB. The sensitivity of the Berlin Questionnaire to detect SDB was 73%, specificity was 42%. The STOP-BANG questionnaire showed a sensitivity of 97% while specificity was 13%. Coronary heart disease and/or history of myocardial infarction, hyperuricemia and age significantly contributed to a logistic regression model predicting presence of SDB. However, our regression model explains only 36% of the variance regarding the presence or absence of SDB. The approach to find variables, which would allow an early and reliable differentiation between patients with CVD and coexistence or absence of SDB, failed. Thus, as CVD patients show a high SDB prevalence and poor outcome, only a systematic screening based on measures of respiration-related parameters (i.e., respiratory flow, blood oxygen saturation, etc.) allows for a reliable SDB assessment. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Zeitschrift für Kardiologie Springer Journals

Sleep-disordered breathing in patients with cardiovascular diseases cannot be detected by ESS, STOP-BANG, and Berlin questionnaires

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Medicine & Public Health; Cardiology
ISSN
0300-5860
eISSN
1861-0692
DOI
10.1007/s00392-018-1282-7
Publisher site
See Article on Publisher Site

Abstract

Sleep-disordered breathing (SDB) is highly prevalent in patients with cardiovascular diseases (CVD) and associated with poor outcome. At least 50% of heart failure (HF) patients present with SDB, equally divided in obstructive sleep apnea (OSA) and central sleep apnea (CSA). CVD patients with SDB do not always present with typical SDB symptoms. Therefore, we asked whether established questionnaires allow for the reliable detection of SDB. In this prospective cohort study, 89 CVD patients (54 male, 59 ± 15 years, BMI 30 ± 6 kg/m2) in stable clinical state underwent an ambulatory polygraphy. SDB was defined as an apnea-hypopnea index (AHI) ≥ 15/h. We evaluated the Epworth Sleepiness Scale (ESS), STOP-BANG and Berlin questionnaires as well as anthropometric data and comorbidities regarding their ability to predict SDB. The ESS showed no correlation with SDB. The sensitivity of the Berlin Questionnaire to detect SDB was 73%, specificity was 42%. The STOP-BANG questionnaire showed a sensitivity of 97% while specificity was 13%. Coronary heart disease and/or history of myocardial infarction, hyperuricemia and age significantly contributed to a logistic regression model predicting presence of SDB. However, our regression model explains only 36% of the variance regarding the presence or absence of SDB. The approach to find variables, which would allow an early and reliable differentiation between patients with CVD and coexistence or absence of SDB, failed. Thus, as CVD patients show a high SDB prevalence and poor outcome, only a systematic screening based on measures of respiration-related parameters (i.e., respiratory flow, blood oxygen saturation, etc.) allows for a reliable SDB assessment.

Journal

Zeitschrift für Kardiologie – Springer Journals

Published: May 29, 2018

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