A LABORATORY VALIDATION-STUDY OF THE DIAGNOSTIC MODE OF THE AUTOSET(TM) SYSTEM FOR SLEEP-RELATED RESPIRATORY DISORDERS

We performed a validation study of the diagnostic mode of the Autoset( R) system (ResMed, Australia) on a group of 44 snorers (10 women). We compared the results of the Autoset's automatic analysis of nasal airf low (using nasal prongs) to those of an in-laboratory polysomnographic study with a Fleisch facemask pneumotachograph. For the first 29 pati ents, the Autoset software was set to recognize only apneas; for the r emaining 15, the software was modified to recognize both apneas and hy popneas. Relative to polysomnography, the Autoset overestimated the nu mber of apneas. Oral breathing or displacement of the nasal prongs par tially explained these differences. A significant correlation was foun d between the apnea indices (Al) assessed by the two methods (r = 0.98 ). For an AI of 20/hour the Autoset was 100% sensitive and 88% specifi c. The Autoset significantly underestimated the number of hypopneas co mpared to the polysomnograph with pneumotachograph (62.9 +/- 4.7 vs. 8 5.5 +/- 73.1, p = 0.04), although for an apnea-hypopnea index of 20, A utoset was 100% sensitive and 88% specific. The lack of linearity of A utoset's volume evaluations at low volumes could explain most of the d ifferences.Our results indicate that the Autoset system, in its diagno stic mode, is a useful tool for identifying patients with significant obstructive sleep apnea syndrome. The system is less useful in patient s with mild to moderate sleep disordered breathing, where it may give erroneous results.