Reducing unwarranted variations in healthcare in the English NHS
Authors: N. Mays
Journal: BMJ (2011)

<h3>ABSTRACT</h3> <h3>Background</h3> Prediction of post-stroke outcome using the degree of subacute deficit or magnetic resonance imaging metrics is well studied in humans. While mice are the most commonly used animals in pre-clinical stroke research, systematic analysis of outcome predictors is lacking. <h3>Methods</h3> Data from a total of 13 studies that included 45 minutes of middle cerebral artery occlusion on 148 mice were pooled. Motor function was measured using a modified protocol for the staircase test of skilled reaching. Phases of subacute and residual deficit were defined. Magnetic resonance images of stroke lesions were co-registered on the Allen Mouse Brain Atlas to characterize stroke topology. Different random forest prediction models that either used motor-functional deficit or imaging parameters were generated for the subacute and residual deficits. <h3>Results</h3> We detected both a subacute and residual motor-functional deficit after stroke in mice. Different functional severity grades and recovery trajectories could be observed. We found that lesion volume is the best predictor of subacute deficit. The residual deficit can be predicted most accurately by the degree of the subacute deficit. When using imaging parameters for the prediction of the residual deficit, including information about the lesion topology increases prediction accuracy. A subset of anatomical regions within the ischemic lesion have an outstanding impact on the prediction of long-term outcome. Prediction accuracy depends on the degree of functional impairment. <h3>Conclusions</h3> For the first time, we identified and characterized predictors of post-stroke outcome in a large cohort of mice and found strong concordance with clinical data. In the future, using outcome prediction can improve the design of pre-clinical studies and guide intervention decisions. <h3>Novelty and Significance</h3><h3>What Is Known?</h3> Prediction of post-stoke outcome is an increasingly important tool in clinical stroke research as it could guide treatment decisions Both the subacute deficit and MRI metrics have been studied extensively in humans Despite mice being the most important model animal in pre-clinical stroke research, evidence on stroke outcome prediction in mice is scarce <h3>What New Information Does This Article Contribute?</h3> The best predictor of long-term outcome after stroke in mice is the degree of the subacute deficit Including lesion topology increases prediction accuracy and outperforms total lesion volume A small subset of grey and white matter regions within the ischemic lesion have a great impact on prediction of long-term outcome In contrast to stroke research in humans, there are no studies analyzing the prediction of functional outcome in mice, despite rodents being the most important model animal in translational stroke research. In this study we built imaging and behavior based prediction algorithms using random forest and found that the lesion volume is the best predictor of the subacute deficit. The residual deficit can be predicted most accurately by the degree of the subacute deficit and including information about the lesion topology increases prediction accuracy. Prediction error depends on the severity grade of functional impairment. In the future, using outcome prediction can improve the design of pre-clinical studies and guide intervention decisions.