Age-adjusted infarct volume threshold for good outcome after endovascular treatment

Background and purpose Infarct volume and age are strong predictors of outcome in patients with stroke. We aimed to determine the impact of infarct volume on outcome according to age. Methods Consecutive patients with acute stroke with documented internal carotid artery/middle cerebral artery occlusion who underwent endovascular procedures were studied. Patients were categorized in three age groups: <70 years (G1), 70-79 years (G2), >= 80 years (G3). The Alberta Stroke Program Early CT score (ASPECTS) was graded on initial CT. Time of successful recanalization (Thrombolysis In Cerebral Infarct (TICI) >= 2b)and good outcome at 3 months (modified Rankin Scale score <= 2) were recorded. Infarct volume was measured on the 24 h control CT. Results A total of 214 patients were studied (61: 68; G2: 74; G3: 72). For all patients the mean infarct volume was 94.7 +/- 127 mL; 35.6% had a good outcome. We observed larger infarct volumes in patients with a bad outcome in each age group (G1: 22 vs 182 mL, p<0.01/G2: 22 vs 164 mL, p<0.01/G3: 7.6 vs 132 mL, p<0.01). However, the target cut-off infarct volume that better predicted a good outcome decreased as age increased: G1: 49 mL (sensitivity 80%, specificity 92.6%); G2: 32.5 mL (sensitivity 80%, specificity 81%); G3: 15.2 mL (sensitivity 81.3%, specificity 86.7%). Overall, after adjusting for age, occlusion location, baseline NIH Stroke Scale score and infarct volume, the only predictor of a good outcome was achieving a final infarct volume less than the age-adjusted target (OR 5.5, 95% Cl 1.6 to 18.8; p<0.01). The probability of achieving an infarct volume less than the age-adjusted target decreased according to baseline ASPECTS, time and degree of recanalization. Conclusions Age-adjusted infarct size might represent a powerful surrogate marker of stroke outcome and further refine the predictive accuracy of infarct volume on prognosis in patients with stroke undergoing endovascular treatment. This information may be used in the design of new trials to individualize selection criteria for different age groups.