Large-Scale Multivariate Analysis to Interrogate an Animal Model of Stroke: Novel Insights Into Poststroke Pathology

Background and Purpose: Preclinical stroke studies endeavor to model the pathophysiology of clinical stroke, assessing a range of parameters of injury and impairment. However, poststroke pathology is complex and variable, and associations between diverse parameters may be difficult to identify within the usual small study designs that focus on infarct size. Methods: We have performed a retrospective large-scale big data analysis of records from 631 C57BL/6 mice of either sex in which the middle cerebral artery was occluded by 1 of 5 surgeons either transiently for 1 hour followed by 23-hour reperfusion (transient middle cerebral artery occlusion [MCAO]; n=435) or permanently for 24 hours without reperfusion (permanent MCAO; n=196). Analyses included a multivariate linear mixed model with random intercept for different surgeons as a random effect to reduce type I and type II errors and a generalized ordinal regression model for ordinal data when random effects are low. Results: Analyses indicated that brain edema volume was associated with infarct volume at 24 hours (β, 0.52 [95% CI, 0.45–0.59]) and was higher after permanent MCAO than after transient MCAO ( P Conclusions: Large-scale analysis of preclinical stroke data can provide researchers in our field with insight into relationships between variables not possible if individual studies are analyzed in isolation and has identified hypotheses for future study.