LIKELIHOOD RATIOS FOR A SLEEP-APNEA CLINICAL-PREDICTION RULE

Nocturnal polysomnography, the standard diagnostic test for sleep apne a, is an expensive and limited resource. In order to help identify the urgency of need for treatment, we determined which clinical features were most useful for establishing an accurate estimate of the probabil ity that a patient had sleep apnea. Of 263 physician-referred patients , 200 were eligible for the study and 180 (90%) completed it. All pati ents had their histories recorded with a standard questionnaire, and u nderwent anthropomorphic measurements and nocturnal polysomnography. S leep apnea was defined as more than 10 episodes of apnea or hypopnea p er hour of sleep. Multiple linear and logistic regression models predi ctive of sleep apnea were compared with physicians' subjective impress ions and previously reported models. Likelihood ratios were calculated for several levels of a sleep apnea clinical score produced by one of the linear models. Predictors of sleep apnea in the final model (R(2) = 0.34) included neck circumference, hypertension, habitual snoring, and bed partner reports of nocturnal gasping/choking respirations This model was superior to physician impression, slightly inferior to more detailed linear and logistic models, and comparable to previously rep orted models. A sleep apnea clinical score of less than 5 had a likeli hood ratio of 0.25 (95% CI: 0.15 to 0.42) and a corresponding posttest probability of 17%, while a score of greater than 15 had a likelihood ratio of 5.17 (95% CI: 2.54 to 10.51) and posttest probability of 81% . These likelihood ratios can simply and accurately determine the prob ability of whether a patient has sleep apnea.