Published in:
01-12-2017 | Sleep Breathing Physiology and Disorders • Original Article
Discriminating between positional and non-positional obstructive sleep apnea using some clinical characteristics
Published in: Sleep and Breathing | Issue 4/2017
Login to get accessAbstract
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.