Objective: To develop a clinical assessment model for predicting moderate to severe obstructive sleep apnea (OSA).

Materials and Methods: All patients suspected of having OSA and undergoing the laboratory polysomnography (PSG) were enrolled. The clinical data, associated factors and PSG finding were reviewed. Significant risk factors for the model were chosen using multivariate logistic regression analysis. The predictive parameters of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated.

Results: Of the 929 patients, 580 (62.4%) had moderate to severe OSA. Patient ages ranged between 18 and 85 years, with the majority between 30 and 60 years (71.5%). Males were significantly prominent in the moderate to severe OSA group (76.4%). Forty-three percent had a body mass index (BMI) greater than 30 and 52% had a neck circumference (NC) greater than 40. Multivariate analysis showed the male gender, a BMI of 30 or greater, a NC of 40 or greater, a waist to height ratio (WHtR) of 0.5 or greater, the presence of hypertension (HT), and observed apnea were significant factors correlated with moderate to severe OSA. The clinical assessment model was created by using their estimated coefficients. The optimal cutoff points for predicting apnea-hypopnea index (AHI) of 15 or greater was 2, with sensitivity of 85.5% and specificity of 49.6%.

Conclusion: The present clinical risk assessment model appears to be a useful practical tool for identifying patients at risk for moderate to severe OSA, with acceptable predictive performance.

Keywords: Obstructive sleep apnea, Clinical assessment model, Predicting, Sleep apnea

DOI: doi.org/10.35755/jmedassocthai.2020.07.10236

Received 4 Jun 2019 | Revised 20 Apr 2020 | Accepted 27 Apr 2020