Short- and long-term outcomes from endovascular thrombectomy (EVT) for large vessel
occlusion stroke remain variable. Numerous relevant predictors have been identified,
including severity of neurological deficits, age, and imaging features. The latter
is typically defined as acute changes (most commonly Alberta Stroke Programme Early
CT Score, ASPECTS, at presentation), but there is little information on the impact
of imaging assessment of premorbid brain health as a determinant of outcome.To examine
the impact of automated measures of stroke severity and underlying brain frailty on
short- and long-term outcomes in acute stroke treated with EVT.In 215 patients with
anterior circulation stroke, who subsequently underwent EVT, automated analysis of
presenting non-contrast CT scans was used to determine acute ischemic volume (AIV)
and e-ASPECTS as markers of stroke severity, and cerebral atrophy as a marker of brain
frailty. Univariate and multivariate logistic regression were used to identify significant
predictors of NIHSS improvement, modified Rankin scale (mRS) at 90 and 30 days, mortality
at 90 days and symptomatic intracranial hemorrhage (sICH) following successful EVT.For
long-term outcome, atrophy and presenting NIHSS were significant predictors of mRS
0-2 and death at 90 days, whereas age did not reach significance in multivariate analysis.
Conversely, for short-term NIHSS improvement, AIV and age were significant predictors,
unlike presenting NIHSS. The interaction between age and NIHSS was similar to the
interaction of AIV and atrophy for mRS 0-2 at 90 days.Combinations of automated software-based
imaging analysis and clinical data can be useful for predicting short-term neurological
outcome and may improve long-term prognostication in EVT. These results provide a
basis for future development of predictive tools built into decision-aiding software
in stroke.
