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High-profile failures in stroke clinical trials have discouraged clinical translation of neuroprotectants. While there are several plausible explanations for these failures, we believe that the fundamental problem is the way clinical and pre-clinical studies are designed and analyzed for heterogeneous disorders such as stroke due to innate biological and methodological variability that current methods cannot capture. Recent efforts to address pre-clinical rigor and design, while important, are unable to account for variability present even in genetically homogenous rodents. Indeed, efforts to minimize variability may lessen the clinical relevance of pre-clinical models. We propose a new approach that recognizes the important role of baseline stroke severity and other factors in influencing outcome. Analogous to clinical trials, we propose reporting baseline factors that influence outcome and then adapting for the pre-clinical setting a method developed for clinical trial analysis where the influence of baseline factors is mathematically modeled and the variance quantified. A new therapy's effectiveness is then evaluated relative to the pooled outcome variance at its own baseline conditions. In this way, an objective threshold for robustness can be established that must be overcome to suggest its effectiveness when expanded to broader populations outside of the controlled environment of the PI's laboratory. The method is model neutral and subsumes sources of variance as reflected in baseline factors such as initial stroke severity. We propose that this new approach deserves consideration for providing an objective method to select agents worthy of the commitment of time and resources in translation to clinical trials.

Hyperglycemia at the time of ischemic stroke has been associated with poorer outcomes. Preclinical literature suggests that hyperglycemia is an independent prognostic factor and the vasculature is more vulnerable to reperfusion injury. We applied a method to match subjects on important baseline factors to test whether, independent of stroke severity, stroke subtype influences the effect of hyperglycemia on outcome after recombinant tissue plasminogen activator (rt-PA). We reanalyzed the NINDS rt-PA dataset with respect to matching variables baseline NIHSS, age, and investigator-determined stroke subtypes small-vessel occlusive stroke (SVS), large-vessel occlusive stroke (LVS), and cardioembolic stroke (CES), above and below a glucose threshold of 150 mg/dl. Ninety-day outcomes were compared. Post hoc baseline matching was excellent in most cases. Hyperglycemia was associated with worsened functional outcome mostly in the LVS subtype with increased mortality in the placebo arm (15.3 % mortality normoglycemia vs. 30.6 % hyperglycemia; p = .046), worse functional outcome in the rt-PA arm (modified Rankin Score (mRS) 0–1; 46.3 vs. 22.0 %; p = .034), and no improvement in functional outcome with rt-PA compared to placebo (mRS 0–1; 25 % in both groups). Among hyperglycemic subjects, CES subjects showed significant improvement following rt-PA (p = .027). After matching for baseline severity, the influence of hyperglycemia on outcome was primarily in the LVS subtype, especially after rt-PA. This finding is consistent with a deleterious effect of hyperglycemia on ischemia/reperfusion of symptomatic large arteries. If confirmed, the particular vulnerability of the LVS subtype is important in understanding the role of stroke subtype in the mechanism of worsening and potential treatment of hyperglycemic stroke patients.