Task: Intent Identification
Input (English): (1) Compare ideal cut-off points for DS and %FEV1 at 1 and 3\xa0h\xa0to predict hospitalization/relapse in subjects with moderate to severe asthma exacerbation (2) Develop a multivariate regression model using DS, %FEV1, demographic, and clinical variables to predict hospitalization/relapse.', 'Subjects with acute exacerbation of asthma (FEV1 <50% predicted following 30\xa0min\xa0of standardized treatment: 5\xa0mg nebulized albuterol; 0.5-1.5\xa0mg nebulized ipratropium; and 50\xa0mg oral prednisone) were eligible. All subjects had %FEV1 and DS obtained at baseline and hourly for 3\xa0h. Using hospitalization/relapse as the outcome of interest; we compared the area under the receiveroperator curves (AUC) between the 1 and 3\xa0h\xa0DS and %FEV1 measurements, and the AUC for the change in DS and %FEV1 between baseline and hour-3. We determined ideal cut-points for %FEV1 and DS to maximize sensitivity and specificity. Sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios (LR) were compared between %FEV1 and DS. We developed a multivariate regression model examining the association of specific demographic and clinical variables to hospitalization/relapse.', '142 patients were included for analysis. The AUC was greatest for the 3-h\xa0DS (0.721), followed by the 3-h\xa0%FEV1 (0.669). Optimum cut-off values were a DS of 2, and an FEV1 of 42%. These were associated with a +LR for the composite outcome of 3.06 and 2.48 respectively. Logistic regression showed baseline DS, 3-h\xa0DS, change in DS, and oxygen use at hour 3 were all associated with the composite outcome.
Output (English): 1