Using the STOPBANG questionnaire and other pre-test probability tools to predict OSA in younger, thinner patients referred to a sleep medicine clinic

Abstract

The STOPBANG questionnaire is used to predict the presence of obstructive sleep apnea (OSA). We sought to assess the performance of the STOPBANG questionnaire in younger, thinner patients referred to a sleep medicine clinic. We applied the STOPBANG questionnaire to patients referred for level I polysomnography (PSG) at our sleep center. We calculated likelihood ratios and area under the receiver operator characteristic (AUROC) curve and performed sensitivity analyses. We performed our analysis on 338 patients referred for PSG. Only 17.2% (n=58) were above age 50years, and 30.5 and 6.8% had a BMI above 30 and 35years, respectively. The mean apnea-hypopnea index (AHI) was 12.9±16.4 and 63.9% had an AHI ≥5. The STOPBANG (threshold ≥3) identified 83.1% of patients as high risk for an AHI ≥5, and sensitivity, specificity, positive (PPV), and negative predictive values (NPV) were 83.8, 18.0, 64.4, and 38.0%, respectively. Positive and negative likelihood ratios were poor at 1.02-1.11 and 0.55-0.90, respectively, across AHI thresholds (AHI ≥5, AHI ≥15 and AHI ≥30), and AUROCs were 0.52 (AHI ≥5) and 0.56 (AHI ≥15). Sensitivity analyses adjusting for insomnia, combat deployment, traumatic brain injury, post-traumatic stress disorder, clinically significant OSA (ESS >10 and/or co-morbid disease), and obesity did not significantly alter STOPBANG performance. In a younger, thinner population with predominantly mild-to-moderate OSA, the STOPBANG Score does not accurately predict the presence of obstructive sleep apnea.