Discriminating between positional and non-positional obstructive sleep apnea using some clinical characteristics.

Autor: Oulhaj A; Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates., Al Dhaheri S; Internal medicine, Tawam hospital, Al Ain, United Arab Emirates., Su BB; Internal Medicine, Respirology and Sleep Medicine, College of Medicine and Health Sciences, United Arab Emirates University, P.O. Box 17666, Al Ain, United Arab Emirates., Al-Houqani M; Internal Medicine, Respirology and Sleep Medicine, College of Medicine and Health Sciences, United Arab Emirates University, P.O. Box 17666, Al Ain, United Arab Emirates. alhouqani@uaeu.ac.ae.
Jazyk: angličtina
Zdroj: Sleep & breathing = Schlaf & Atmung [Sleep Breath] 2017 Dec; Vol. 21 (4), pp. 877-884. Date of Electronic Publication: 2017 Apr 19.
DOI: 10.1007/s11325-017-1499-0
Abstrakt: Purpose: The primary objective of this paper was to identify significant factors associated with positional Obstructive Sleep Apnea (POSA) and to provide a clinical tool for discriminating non positional from POSA. Secondary objectives were about estimating the prevalence of POSA, comparing the polysomnographic variables across POSA and non-POSA patients.
Methods: This was a cross sectional study on 278 patients who completed an overnight sleep study for OSA assessment. Patients were aged over 18 years, without central sleep apnea or narcolepsy and slept no less than 20 min in a non-supine position. POSA was defined as a total apnea/hypopnea index (AHI) ≥5 and a ratio supine AHI/non-supine AHI ≥2. The binary logistic regression was used for modeling the likelihood for OSA patient to be positional, and the LASSO method was used for selecting the optimal set of clinical characteristics associated with POSA.
Results: Overall, 53% of patients had POSA. These patients were younger (p = 0.005), had lower BMI (p < 0.0001), lower prevalence of hypertension (p = 0.006), lower Berlin (p = 0.01), and lower STOP (p = 0.001) scores compared to non-POSA patients. Neck and waist circumference were higher in non-POSA (p = 0.005, p = 0.009, respectively) patients. Age, BMI, DBP, Mallampati, and Berlin scores were found to be the best clinical characteristics associated with POSA with an area under the ROC curve (AUC) of 0.71 (95% CI [0.63, 0.78]).
Conclusions: Half of patients referred for the sleep study had POSA. Age, BMI, DBP, Mallampati, and Berlin scores, put together, were shown to act as good clinical characteristics to discriminate between POSA and non-POSA patients.
Databáze: MEDLINE
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