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Table 2: Comparison of the ability of imaging paradigms in discriminating clinical outcomes using logistic regression modeling^{^a}
Comparison
Imaging Paradigm/Criteria No. Odds Ratio (95% CI) P Value C-Statistic AIC/BIC AIC/BIC (o)
90-day mRS 
 mCTA (>3 vs ≤3) 82 9.6 (1.9–48.8) .001 0.86 95.7/114.9 300.6/331.9
 DEFUSE-3 criteria 82 5.5 (1.2–25.3) .028 0.84 99.0/118.3 
 DAWN criteria 82 9.3 (0.9–98.8) .065 0.83 99.3/118.6 303.1/334.4
Early neurologic improvement (≥50% drop in 24-hr NIHSS score from baseline)
 mCTA (>3 vs ≤3) 82 13.3 (2.9–61) .001 0.80 98.2 117.5
 DEFUSE-3 criteria 82 8.5 (1.9–37.5) .005 0.74 105.9 125.1
 DAWN criteria 82 5.6 (0.6–56.1) .141 0.71 109.6 
↵a Variables age, sex, baseline NIHSS score, baseline NCCT ASPECTS, onset/last known well to imaging time, EVT, and the interaction term imaging paradigm × EVT (yes versus no) were included in all models. C-statistic represents the area under a receiver operating characteristic curve. AIC and BIC are Bayesian information criteria methods to assess model fit in which the model with the lowest AIC or BIC is preferred. AIC/BIC (o) denotes the AIC and BIC for the ordinal regression models.