Follow-up ASPECTS improves prediction of potentially lethal malignant edema in patients with large middle cerebral artery stroke
Rebecca Stafford, Stefanos Chatzidakis, Ivy So Yeon Kim, Yihan Zhang, Rina Andriani, Benjamin Brush, Asim Mian, Mohamad Abdalkader, David M. Greer, Stelios M. Smirnakis, Steven K. Feske, Josée Dupuis, Charlene Ong
Abstract
Background Recent studies have shown that follow-up head CT is a strong predictor of functional outcomes in patients with middle cerebral artery stroke and mechanical thrombectomy. We sought to determine whether total and/or regional follow-up Alberta Stroke Program Early CT Score (ASPECTS fu ) are associated with important clinical outcomes during hospitalization and improve the performance of clinical prediction models of potentially lethal malignant edema (PLME). Methods We conducted a retrospective study of patients at three medical centers in a major North American metropolitan area with baseline and follow-up head CTs after large middle cerebral artery stroke between 2006 and 2022. We used multivariable logistic regression to test the association of total and regional ASPECTS fu with PLME (cerebral edema related death or surgery), adjusting for total baseline ASPECTS, age, sex, admission glucose, tissue plasminogen activator, and mechanical thrombectomy. We compared existing clinical risk models with and without total or regional ASPECTS fu using area under the curve. Results In our 560 patient cohort, lower total ASPECTS fu was significantly associated with higher odds of PLME when adjusting for confounders (OR 1.69, 95% CI 1.49 to 2.0), and improved model discrimination compared with existing models and models using baseline ASPECTS. Deep territory involvement (OR 2.46, 95% CI 1.53 to 4.01) and anterior territory involvement (OR 3.23, 95% CI 1.88 to 5.71) were significantly associated with PLME. Conclusions Lower ASPECTS fu and certain locations on regional ASPECTS fu , including deep and anterior areas, were significantly associated with PLME. Including ASPECTS fu information improved discrimination of established edema prediction models and could be used immediately to help facilitate clinical management decisions and prognostication.