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Table 2 Infarct Evolution Classifier predictive accuracy analysis in the training set

From: Brain metabolic pattern analysis using a magnetic resonance spectra classification software in experimental stroke

Training set Sensitivity Specificity PPV NPV AUC value
Non-infarcted parenchyma 100% (32/32) 100% (22/22) 100% (32/32) 100% (22/22) 1.00 ± 0.00
Acute phase of infarct 100% (13/13) 95% (39/41) 87% (13/15) 100% (39/39) 0.98 ± 0.00
Subacute phase of infarct 78% (7/9) 100% (45/45) 100% (7/7) 96% (45/47) 0.98 ± 0.04
  1. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and the mean ± standard error area under curve (AUC) value of the receiver operating curve (ROC) of the dichotomization of each class compared to the other two classes combined. Results are given in percentage with the number of spectra within parentheses. Total number of spectra in the training set (n = 54) corresponded to non-infarcted parenchyma (n = 32), acute phase of infarct (n = 13) and subacute phase of infarct (n = 9).