Global outcome measures that are widely used in stroke clinical trials, such as the modified Rankin Scale (mRS), lack sufficient detail to detect changes within specific domains (e.g. sensory, motor, visual, linguistic, or cognitive function). Yet such data are vital for understanding stroke recovery and its mechanisms. Post-stroke deficits in specific domains differ in their rate and degree of recovery, and in their effects on overall independence and quality of life. For example, even in a patient with complete recovery of strength, persistent deficits in the non-motor domains such as language and cognition may make a return to independent living impossible. In such cases, global measures based solely on the patient’s degree of independence would overlook a complete recovery in the motor domain. Capturing these important aspects of recovery demands a domain-specific approach. If stroke outcomes trials are to incorporate finer-grained recovery metrics -- which can require substantial time, effort, and expertise to implement -- efficiency must be a priority. In this paper we discuss how commonly collected clinical data from the NIHSS can guide the judicious selection of relevant recovery domains for more detailed testing. Our overarching goal is to make the implementation of domain-specific testing more feasible for large scale clinical trials on stroke recovery.

Numerous biological mechanisms contribute to outcome after stroke, including brain injury, inflammation, and repair mechanisms. Clinical genetic studies have the potential to discover biological mechanisms affecting stroke recovery in humans and identify intervention targets. Large sample sizes are needed to detect commonly occurring genetic variations related to stroke brain injury and recovery. However, this usually requires combining data from multiple studies where consistent terminology, methodology, and data collection timelines are essential. Our group of expert stroke and rehabilitation clinicians and researchers with knowledge in genetics of stroke recovery here present recommendations for harmonizing phenotype data with focus on measures suitable for multicenter genetic studies of ischemic stroke brain injury and recovery. Our recommendations have been endorsed by the International Stroke Genetics Consortium.

This study demonstrates that kinematic measures established in stroke research on humans are also sensitive to performance differences prestroke versus poststroke in the rat model, reinforcing the utility of this method to evaluate treatments that may ultimately translate to patient populations.

There are now a large number of technological and methodological approaches to the rehabilitation of motor function after stroke. It is important to employ these approaches in a manner that is tailored to specific patient impairments and desired functional outcomes, while avoiding the hype of overly broad or unsubstantiated claims for efficacy. Here we review the evidence for poststroke plasticity, including therapy-related plasticity and functional imaging data. Early demonstrations of remapping in somatomotor and somatosensory representations have been succeeded by findings of white matter plasticity and a focus on activity-dependent changes in neuronal properties and connections. The methods employed in neurorehabilitation have their roots in early understanding of neuronal circuitry and plasticity, and therapies involving large numbers of repetitions, such as robotic therapy and constraint-induced movement therapy (CIMT), change measurable nervous systems properties. Other methods that involve stimulation of brain and peripheral excitable structures have the potential to harness neuroplastic mechanisms, but remain experimental. Gaps in our understanding of the neural substrates targeted by neurorehabilitation technology and techniques remain, preventing their prescriptive application in individual patients as well as their general refinement. However, with ongoing research—facilitated in part by technologies that can capture quantitative information about motor performance—this gap is narrowing. These research approaches can improve efforts to attain the shared goal of better functional recovery after stroke.