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Table 3 Prediction performance of the four prediction models

From: A prediction model for good neurological outcome in successfully resuscitated out-of-hospital cardiac arrest patients

Cut-off probability Misclassification rate Sensitivity Specificity
H1 H12 H24 H48 H1 H12 H24 H48 H1 H12 H24 H48
0.45 26.2 (9.1) 22.9 (8.0) 21.8 (8.2) 75.2 (12.5) 78.4 (12.2) 79.8 (12.4) 70.8 (14.9) 76.2 (11.8) 77.4 (13.2)
0.50 25.3 (9.2) 22.5 (8.2) 21.5 (8.2) 72.9 (12.8) 76.5 (12.8) 77.6 (12.9) 77.4 (13.7) 78.9 (11.6) 79.9 (12.6)
0.55 24.8 (9.2) 22.3 (8.3) 21.5 (8.4) 23.7 (9.6) 70.5 (13.1) 74.1 (13.5) 75.3 (13.6) 78.6 (14.2) 74.3 (14.4) 81.5 (11.3) 82.2 (12.3) 74.6 (15.6)
0.60 23.4 (9.5) 76.8 (14.4) 77.2 (15.0)
0.65 23.3 (9.4) 74.6 (14.6) 77.4 (13.2)
  1. Misclassification rate is the percentage of cases misclassified. The optimal cut-off probability yielding the smallest misclassification rate is indicated in bold for each time point. Misclassification rate, sensitivity and specificity are presented in percentage (standard errors)