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Revista médica de Chile · Aug 2010
[Predictive value of clinical features and nocturnal oximetry for the detection of obstructive sleep apnea syndrome].
- Fernando Saldías P, Jorge Jorquera A, and Orlando Díaz P.
- Departamento de Enfermedades respiratorias, Pontifica Universidad de Chile, Santiago, Chile. fsaldias@med.puc.cl
- Rev Med Chil. 2010 Aug 1; 138 (8): 941-50.
BackgroundObstructive sleep apnea syndrome (OSA) is an important cause of morbidity and mortality in adults.AimTo evaluate the diagnostic value of clinical features and oximetric data to screen for obstructive sleep apnea before performing polysomnograpy or respiratory polygraphy.Material And MethodsWe studied 328 consecutive adult patients referred for snoring or excessive daytime sleepiness to a sleep clinic in whom a standardized questionnaire and the Sleepiness Epworth Scale were performed and body mass index (BMI), cervical circumference (CC), and nocturnal oximetry were measured.ResultsFifty three percent (n = 173) had evidence of clinically significant OSA (apnea/hypopnea index (AHI) > 15 events/h). Patients with OSA were more likely to be male, obese (BMI ≥ 26 kg/m²), smokers, to have a thick neck (CC > 41 cm), and to have a significant greater prevalence of relative reported apneas and excessive daytime sleepiness, as determined by Epworth scale. Male gender (Odds ratio (OR): 4.00; 95% confidence intervals (CI): 1.59-10.0, p = 0.003), BMI ≥ 26 kg/m² (OR: 3.68; 95%CI: 1.59-8.49, p = 0.002), smoking (OR: 2.29; 95% CI: 1.17-4.47, p = 0.015), Epworth index > 13 (OR: 2.65; 95% CI: 1.35-5.23, p = 0.005) and duration of symptoms over 2 years (OR: 2.35; 95% CI: 1.20-4.58, p = 0.012) were significant independent predictors of OSA. In nocturnal oximetry, the lowest SpO2 (SpO2 min) and the length of registries below 90% (CT-90) were independent predictors of OSA and both correlated significantly with AHI (r = -0.49 and r = 0.46 respectively, p < 0.001).ConclusionsNo single factor was usefully predictive of obstructive sleep apnea. However, combining clinical features and oximetry data may be appropriate to detect clinically significant OSA patients.
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