title: Predicting sleep apnea and excessive day sleepiness in the severely obese: indicators for polysomnography.
abstract: BACKGROUND
  Obstructive sleep apnea (OSA) is common in severely obese subjects (body mass index [BMI] > 35). Overnight polysomnography (OPS) is the "gold standard" method of evaluating this condition; however, it is time-consuming, inconvenient, and expensive. Selection of patients for OPS would be enhanced if we could better predict those likely to have clinically significant OSA.
  
  
  OBJECTIVE
  To look for clinical and biochemical predictors of OSA in symptomatic patients presenting for obesity surgery.
  
  
  METHODS
  Symptoms suggestive of OSA were sought in a structured interview. We report OPS results of 99 consecutive subjects in whom OSA was clinically suspected. Predictors of apnea-hypopnea index (AHI) were sought from an extensive preoperative data collection. Multivariate linear and logistic analysis was used to identify independent predictors of AHI.
  
  
  RESULTS
  Symptoms were poor predictors of AHI, with observed sleep apnea the only positive predictor. Four clinical and two biochemical factors independently predicted AHI: observed sleep apnea, male sex, higher BMI, age, fasting insulin, and glycosylated hemoglobin A(Ic) (r(2) = 0.42). Neck circumference (the best single measure) could replace BMI and sex in the analysis (r(2) = 0.43). With cutoffs selected, a simple scoring system using these six factors provides a method of predicting those with moderate or severe OSA. A score > or = 3 provides a sensitivity and specificity of 89% and 81%, and 96% and 71% for AHIs of > or = 15 and > or = 30, respectively. None of the 31 subjects with scores of 0 or 1 were found to have an AHI > or = 15.
  
  
  CONCLUSIONS
  We explore sleep disturbance and report a simple method of predicting OSA in severely obese symptomatic subjects. This should assist in limiting the use of OPS to those with greater risk and provide a method of assessing risk in those not presenting primarily with a sleep problem.
authors.affiliation: Monash University Department of Surgery, Alfred Hospital, Melbourne, Australia. john.dixon@med.monash.edu.au
authors.forename: John B
authors.initials: JB
authors.lastname: Dixon
authors.forename: Linda M
authors.initials: LM
authors.lastname: Schachter
authors.forename: Paul E
authors.initials: PE
authors.lastname: O'Brien
mesh_terms: D000328:Adult; D005260:Female; D006801:Humans; D016014:Linear Models; D016015:Logistic Models; D008297:Male; D009765:Obesity / Q000150:complications* / Q000453:epidemiology; D018579:Patient Selection; D017286:Polysomnography; D018570:Risk Assessment; D012307:Risk Factors; D012680:Sensitivity and Specificity; D012891:Sleep Apnea Syndromes / Q000175:diagnosis* / Q000453:epidemiology / Q000209:etiology; D020181:Sleep Apnea, Obstructive / Q000175:diagnosis* / Q000453:epidemiology / Q000209:etiology