Translational Value of Skilled Reaching Assessment in Clinical and Preclinical Studies on Motor Recovery After Stroke.

BACKGROUND: Assessment of skilled reaching enables extensive analysis of upper limb function in clinical and preclinical studies on poststroke outcome. However, translational research if often limited by lack of correspondence between tests of human and rodent motor function. OBJECTIVES: To determine (1) the translational value of skilled reaching performance for preclinical research by comparing the behavioral recovery profiles of skilled reaching characteristics between humans and rats recovering from stroke and (2) the relationship between skilled reaching performance and commonly used clinical outcome measures after stroke. METHODS: Twelve patients with ischemic or hemorrhagic stroke and 17 rats with photothrombotic stroke underwent an equivalent skilled reaching test at different time points, representing early to late subacute stages poststroke. Success scores and a movement element rating scale were used to measure the skilled reaching performance. The Fugl-Meyer Upper Extremity (FM-UE) assessment and the Action Research Arm Test (ARAT) were used as clinical outcome measures. RESULTS: Both species had muscle flaccidity at the early subacute stage after stroke and showed motor recovery following a proximal-distal principle toward the early subacute stage, albeit for rats within a shorter time course. Human skilled reaching scores and FM-UE and ARAT scores in the first 3 months poststroke were significantly correlated (P < .05). CONCLUSIONS: Our study demonstrates that poststroke changes in skilled reaching performance are highly similar between rats and humans and correspond with standard clinical outcome measures. Skilled reaching testing therefore offers an effective and highly translational means for assessment of motor recovery in experimental and clinical stroke settings.

People's Risk Recognition Preceding Evacuation and Its Role in Demand Modeling and Planning.

Evacuation planning and management involves estimating the travel demand in the event that such action is required. This is usually done as a function of people's decision to evacuate, which we show is strongly linked to their risk awareness. We use an empirical data set, which shows tsunami evacuation behavior, to demonstrate that risk recognition is not synonymous with objective risk, but is instead determined by a combination of factors including risk education, information, and sociodemographics, and that it changes dynamically over time. Based on these findings, we formulate an ordered logit model to describe risk recognition combined with a latent class model to describe evacuation choices. Our proposed evacuation choice model along with a risk recognition class can evaluate quantitatively the influence of disaster mitigation measures, risk education, and risk information. The results obtained from the risk recognition model show that risk information has a greater impact in the sense that people recognize their high risk. The results of the evacuation choice model show that people who are unaware of their risk take a longer time to evacuate.