The analysis of the clinical study was based on treatment completers only. The primary health outcomes used in the analysis were the number of OSA detected case, short-form 36 item health survey (SF36) and Pittsburgh Sleep Quality Index (PSQI). A respiratory distress index (RDI) (the number of events per hour) was calculated based on the number of recorded cases of apnea and hypopnea. RDI greater than 10 was defined as being the measure of OSA. Multiple stepwise logistic regression was used to construct predictive models employing 15 suspected clinical variables (the independent variables consisted of age, gender, body mass index, PSQI responses, SF-36 scores, lowest oxygen saturation recording, and number of desaturation recordings below 85%) with and without pulse oximetry data. The sensitivity and specificity of the screening methods were determined. Using the logistic function and feeding it with specific patient data, the probability of OSA could be estimated. The cut-off probability of OSA yielding maximum attainable specificity were estimated.