A precise description of the natural history of motor recovery after stroke provides a framework for understanding the mechanisms underlying this improvement and for tracking the efficacy of rehabilitation treatments. To characterize the time course of this change in motor impairment, we examined voluntary elbow movements in hemiparetic stroke survivors over a period of 1 year after stroke. Based on the possibility that both central nervous system and muscle factors could contribute to the observed clinical state, we hypothesized that we should observe at least two major recovery patterns of motor impairment. To explore these predictions, we assessed elbow movement range, movement speed, and isometric force generation. Subjects were examined five times over the 12-month period. We used the "growth mixture" model to characterize recovery of these measures, and the Fugl-Meyer scale (FMS) of upper-extremity function at 1 month to predict the recovery. We observed two distinct recovery classes. Class 1 started with low values for the physiological measures, and these increased over time, whereas class 2 tended to start with higher values and showed widely divergent recovery patterns. Using the logistic regression model, the impact of FMS on class membership was estimated for each parameter. Based on these data, we were able to accurately predict arm impairment recovery at different time-points in the first year, information of great potential value for planning targeted therapeutic interventions.
- Motor impairment
ASJC Scopus subject areas
- Clinical Neurology
- Cellular and Molecular Neuroscience
- Physiology (medical)