Objectives: To develop and validate a new clinical prediction model for screening patients at risk for obstructive sleep apnea–hypopnea syndrome (OSAHS). Methods: This study used 2 data sets to develop and validate the model. To build the model, the first data set comprised 892 patients who had diagnostic polysomnography (PSG); data were assessed by multivariate logistic regression analysis. To validate the new model, the second data set comprised 374 patients who were enrolled to undergo overnight PSG. Receiver operating characteristic analysis and all predictive parameters were validated. Results: In the model development phase, univariate analysis showed 6 parameters were significant for prediction apnea–hypopnea index ≥15 events/hour: male sex, choking or apnea, high blood pressure, neck circumference >16 inches (female) or 17 inches (male), waist circumference ≥80 (female) or 90 cm (male), and body mass index >25 kg/m2. Estimated coefficients showed an area under the curve of 0.753. In the model validation phase, the sensitivity and specificity were approximately 93% and 26%, respectively, for identifying OSAHS. Comparison with the Epworth Sleepiness Scale score of ≥10 and STOP-Bang score ≥3 showed sensitivity of 42.26% and 56.23%, respectively, for detecting patients at risk. Conclusions: This new prediction model gives a better result on identifying patients at risk for OSAHS than Epworth Sleepiness Scale and STOP-Bang in terms of sensitivity. Moreover, this model may play a role in clinical decision-making for a comprehensive sleep evaluation to prioritize patients for PSG.

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Objective: To identify the prevalence and to determine both risk factors and clinical manifestation of obstructive sleep apnea (OSA).Material and Methods: A retrospective study was conducted to review the medical records and polysomnographic data of patients from March 2006 to December 2017.Results: A total of 929 patients was enrolled, however, only 124 patients had habitual snoring (13.4%). The prevalence of OSA and OSAS was 85.6% and 52.7% respectively. OSA was more prevalent in men than women (60.5% vs 25.1%). The presence of HT or symptoms of choking, gasping and neurocognitive impairment were significantly greater in OSA patients compared with the non-OSA group. In multivariate analysis, it was revealed that male gender, age ≥50 years, body-mass index (BMI) >25 kg/m2, neck circumference (NC) >40 cm and waist to height ratio (WHtR) >0.6 were the significant predictors for OSA.Conclusion: This study demonstrated that; OSA is a major health concern within the Thai population. Male gender, elderly age and those higher in BMI, NC or WHtR can be predicted as having the presence of OSA.