Factors predictive of obstructive sleep apnea in patients undergoing pre-operative evaluation for bariatric surgery and referred to a sleep laboratory for polysomnography - Ricardo Luiz de Menezes Duarte; Flavio José Magalhães-da-Silveira (Jornal Brasileiro de Pneumologia, 2015)
Objective: To identify the main predictive factors for obtaining a diagnosis of obstructive sleep apnea (OSA) in patients awaiting bariatric surgery. Methods: Retrospective study of consecutive patients undergoing pre-operative evaluation for bariatric surgery and referred for in-laboratory polysomnography. Eight variables were evaluated: sex, age, neck circumference (NC), BMI, Epworth Sleepiness Scale (ESS) score, snoring, observed apnea, and hypertension. We employed ROC curve analysis to determine the best cut-off value for each variable and multiple linear regression to identify independent predictors of OSA severity. Results: We evaluated 1,089 patients, of whom 781 (71.7%) were female. The overall prevalence of OSA-defined as an apnea/hypopnea index (AHI) ≥ 5.0 events/h-was 74.8%. The best cut-off values for NC, BMI, age, and ESS score were 42 cm, 42 kg/m2, 37 years, and 10 points, respectively. All eight variables were found to be independent predictors of a diagnosis of OSA in general, and all but one were found to be independent predictors of a diagnosis of moderate/severe OSA (AHI ≥ 15.0 events/h), the exception being hypertension. We devised a 6-item model, designated the NO-OSAS model (NC, Obesity, Observed apnea, Snoring, Age, and Sex), with a cut-off value of ≥ 3 for identifying high-risk patients. For a diagnosis of moderate/severe OSA, the model showed 70.8% accuracy, 82.8% sensitivity, and 57.9% specificity. Conclusions: In our sample of patients awaiting bariatric surgery, there was a high prevalence of OSA. At a cut-off value of ≥ 3, the proposed 6-item model showed good accuracy for a diagnosis of moderate/severe OSA.