Recently, there has been a problem of shortage of sleep laboratories that can accommodate the patients in a timelymanner. Delayed\ndiagnosis and treatment may lead to worse outcomes particularly in patients with severe obstructive sleep apnea (OSA). For\nthis reason, the prioritization in polysomnography (PSG) queueing should be endorsed based on disease severity. To date, there\nhave been conflicting data whether clinical information can predict OSA severity. The 1,042 suspected OSA patients underwent\ndiagnostic PSG study at Siriraj Sleep Center during 2010-2011. A total of 113 variables were obtained from sleep questionnaires and\nanthropometric measurements. The 19 groups of clinical risk factors consisting of 42 variables were categorized into each OSA\nseverity. This study aimed to array these factors by employing Fuzzy Analytic Hierarchy Process approach based on normalized\nweight vector.The results revealed that the first rank of clinical risk factors in Severe, Moderate, Mild, and No OSA was nighttime\nsymptoms. The overall sensitivity/specificity of the approach to these groups was 92.32%/91.76%, 89.52%/88.18%, 91.08%/84.58%,\nand 96.49%/81.23%, respectively. We propose that the urgent PSG appointment should include clinical risk factors of Severe OSA\ngroup. In addition, the screening for Mild from No OSA patients in sleep center setting using symptoms during sleep is also\nrecommended (sensitivity = 87.12% and specificity = 72.22%).
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