OBJECTIVE: To analyze the predictive value of clinical data for identifying @entity1 suspected of @entity27 with an @entity27 index (AHI)> or = 30. MATERIAL AND METHODS: @entity1 characteristics, cardiorespiratory medical history, and clinical signs and symptoms were recorded for all @entity1 . Exclusion criteria were daytime @entity1576 or @entity712 . All @entity1 underwent polysomnographic testing (AutoSet Portable Plus II, ResMed Corp, Sydney, Australia) for @entity27 and manual determination of central and obstructive @entity386 . A logistic regression model was constructed to calculate the likelihood of an individual's presenting an AHI> or = 30 as well as the predictive value of each variable and of the final model. RESULTS: Three hundred twenty-nine @entity1 with a mean +/- SD age of 58 +/- 13.45 years were studied; 76.4% were @entity1 . Data for 207 @entity1 were used to construct the logistic regression model: logit (P) = 2.5 blood pressure + 1.5 Epworth test + body mass index + 0.6 repeated observed episodes of @entity386 2.1. Logit(P) was loge (1-P)/P and variables were dichotomized with cut points of 11 for the Epworth test and of 30 kg/m2 for body mass index. The diagnostic sensitivity of the model was 80.2% (75%-86%), specificity was 93.4% (89%-95%), positive predictive value was 89.6% (84%-93%) and negative predictive value was 86.9% (81%-90%), such that 89.6% of the @entity1 were correctly classified. The variable with the greatest predictive value was @entity101 . The model was validated prospectively in the remaining 102 @entity1 . CONCLUSIONS: Prior to diagnostic tests for SAHS, clinical data can be useful for identifying @entity1 suspected to have a AHI> or = 30.

[Clinical predictors of XXXX susceptible to treatment with continuous positive airway pressure].

@entity1 :: ('9606', 'Species') :: ['patients', 'Patient', 'men'] @entity712 :: ('MESH:D006333', 'Disease') :: ['heart failure'] @entity101 :: ('MESH:D006973', 'Disease') :: ['high blood pressure'] @entity27 :: ('MESH:D020181', 'Disease') :: ['sleep apnea-hypopnea syndrome', 'apnea-hypopnea', 'automatic AHI calculation'] @entity1576 :: ('MESH:D012131', 'Disease') :: ['respiratory insufficiency'] @entity386 :: ('MESH:D001049', 'Disease') :: ['apnea', 'apneas']
@entity27 :: (MESH:D020181,Disease) :: ['sleep apnea-hypopnea syndrome']
