AUTHOR=Bivard Andrew , Spratt Neil , Miteff Ferdinand , Levi Christopher , Parsons Mark William TITLE=Tissue Is More Important than Time in Stroke Patients Being Assessed for Thrombolysis JOURNAL=Frontiers in Neurology VOLUME=9 YEAR=2018 URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2018.00041 DOI=10.3389/fneur.2018.00041 ISSN=1664-2295 ABSTRACT=Aim

The relative prognostic importance of modern imaging profiles compared with standard clinical characteristics is uncertain in acute stroke patients. In this study, we aimed to compare baseline multimodal CT imaging measures with known clinical predictors of patient outcome at 3 months [modified Rankin scale (mRS)].

Methods

We collected baseline, 24 h, and day 90 clinical and imaging data from acute ischemic stroke patients being assessed for thrombolytic therapy between 2010 and 2015 at a single center as part of a retrospective analysis.

Results

561 patients presenting within 4.5 h of ischemic stroke onset who were eligible for thrombolysis based on standard clinical criteria were assessed. Acute infarct core volume on CTP was the strongest univariate predictor of patient outcome (mRS 0–2, R2 0.497, p < 0.001), followed by collateral grade (mRS 0–2, R2 0.281, p < 0.001). The strongest baseline clinical predictor of outcome was National Institutes of Health Stroke Scale (NIHSS) (mRS 0–2, R2 = 0.203, p < 0.001). Time to treatment (mRS 0–2, R2 0.096, p = 0.01) and age (mRS 0–2, R2 0.027, p = 0.013) were relatively weak univariate baseline clinical predictors of 3-month outcome. In multivariate analysis, acute infarct core volume and collateral grade were the only significant baseline predictors of 3-month disability (both p < 0.001).

Conclusion

In patients assessed for thrombolysis by combined clinical and multimodal CT criteria within 4.5 h of onset, the size of the CTP infarct core and collateral grade on multimodal CT were highly predictive of patient outcome. Standard clinical variables, including time to treatment and NIHSS, were not as strongly predictive as multimodal CT variables.