An Fatal Blunder Unveiled Over SWAP70 And The Ways To Prevent It

C-statistics >0.80 were considered acceptable values. Model calibration was assessed by the Hosmer-Lemeshow test and by the plots comparing predicted versus observed probability of outcome. Analyses were performed using R-project 2.11.1 (package ""rms"" version 4.11). 6) Model update. For the practical application of the model, model updating was necessary to increase its predictive power. This study used BIBW2992 order a logistic calibration method to update the calibration intercept and slope based on the external validation results.21 Results Compared with the patients included in the model development cohort, patients in the external validation cohort were older; had hypertension, hyperlipidemia, and atrial fibrillation more frequently; had previously used antiplatelets, had a history of cardioembolic stroke, and had used statins less frequently (Table 1). Subjects in the external validation cohort had lower SBP and http://www.selleckchem.com/products/BKM-120.html received thrombolytic therapy more frequently than those in the development cohort. Table 1 Baseline characteristics of the patients included in the study Prognostic model for global outcome To develop the global outcome model, the difference of -2 LL between the model with and without predictors was used to assess the effect of predictors. Among the 18 potential predictors chosen a priori, variables of age, previous mRS, initial NIHSS score, previous stroke, diabetes mellitus, history of statin use, thrombolysis, and lacune influenced a good functional outcome with high predictor effects (PSWAP70 of fast backward elimination logistic regression analysis, interaction terms with thrombolysis, and nonlinear terms for SBP and initial NIHSS score are shown in Table 3. In the model, a squared term of the initial NIHSS score, along with its linear term were added, whereas SBP was modeled with a restricted cubic spline function with 4 knots. Table 3 Independent predictors of the two prognostic models Discriminative ability of the developed model turned out to be satisfactory with a C-statistic of 0.89 (95% confidence interval [CI], 0.87-0.91; Figure 1A). The Hosmer-Lemeshow test also showed a high degree of goodness of fit (P=0.52). Internal and external validation results showed high optimism-corrected C-statistics of 0.87 (95% CI, 0.83-0.90) and 0.82 (95% CI, 0.79-0.85; Figure 1A), respectively. Figure 1 ROC curves of the global and safety outcome models in the development and external validation cohorts. Safety prognostic model Compared with the global outcome model, initial NIHSS score, thrombolysis, and lacune variables were found to influence sHT, among the 15 variables selected initially (Table 2). Using the Lasso method, age, initial NIHSS score, thrombolysis, onset to treatment time, SBP, and glucose were selected as predictors for the safety model (Table 3).