Prediction of obstructive sleep apnea syndrome in a large Greek population.

Autor: Bouloukaki I; Sleep Disorders Unit, Department of Thoracic Medicine, University General Hospital, Medical School of the University of Crete, Heraklion, Crete, Greece. izolthi@gmail.com, Kapsimalis F, Mermigkis C, Kryger M, Tzanakis N, Panagou P, Moniaki V, Vlachaki EM, Varouchakis G, Siafakas NM, Schiza SE
Jazyk: angličtina
Zdroj: Sleep & breathing = Schlaf & Atmung [Sleep Breath] 2011 Dec; Vol. 15 (4), pp. 657-64. Date of Electronic Publication: 2010 Sep 25.
DOI: 10.1007/s11325-010-0416-6
Abstrakt: Purpose: We aimed to evaluate the predictive value of anthropometric measurements and self-reported symptoms of obstructive sleep apnea syndrome (OSAS) in a large number of not yet diagnosed or treated patients. Commonly used clinical indices were used to derive a prediction formula that could identify patients at low and high risk for OSAS.
Methods: Two thousand six hundred ninety patients with suspected OSAS were enrolled. We obtained weight; height; neck, waist, and hip circumference; and a measure of subjective sleepiness (Epworth sleepiness scale--ESS) prior to diagnostic polysomnography. Excessive daytime sleepiness severity (EDS) was coded as follows: 0 for ESS ≤ 3 (normal), 1 for ESS score 4-9 (normal to mild sleepiness), 2 for score 10-16 (moderate to severe sleepiness), and 3 for score >16 (severe sleepiness). Multivariate linear and logistic regression analysis was used to identify independent predictors of apnea-hypopnea index (AHI) and derive a prediction formula.
Results: Neck circumference (NC) in centimeters, body mass index (BMI) in kilograms per square meter, sleepiness as a code indicating EDS severity, and gender as a constant were significant predictors for AHI. The derived formula was: AHIpred = NC × 0.84 + EDS × 7.78 + BMI × 0.91 - [8.2 × gender constant (1 or 2) + 37]. The probability that this equation predicts AHI greater than 15 correctly was 78%.
Conclusions: Gender, BMI, NC, and sleepiness were significant clinical predictors of OSAS in Greek subjects. Such a prediction formula can play a role in prioritizing patients for PSG evaluation, diagnosis, and initiation of treatment.
Databáze: MEDLINE
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