Spontaneous neurological recovery after stroke is a poorly understood process. The aim of the present article was to test the proportional recovery model for the upper extremity poststroke and to identify clinical characteristics of patients who do not fit this model.
A change in the Fugl-Meyer Assessment Upper Extremity score (FMA-UE) measured within 72 hours and at 6 months poststroke served to define motor recovery. Recovery on FMA-UE was predicted using the proportional recovery model: ΔFMA-UEpredicted = 0.7·(66 - FMA-UEinitial) + 0.4. Hierarchical cluster analysis on 211 patients was used to separate nonfitters (outliers) from fitters, and differences between these groups were studied using clinical determinants measured within 72 hours poststroke. Subsequent logistic regression analysis served to predict patients who may not fit the model.
The majority of patients (~70%; n = 146) showed a fixed proportional upper extremity motor recovery of about 78%; 65 patients had substantially less improvement than predicted. These nonfitters had more severe neurological impairments within 72 hours poststroke (P values <.01). Logistic regression analysis revealed that absence of finger extension, presence of facial palsy, more severe lower extremity paresis, and more severe type of stroke as defined by the Bamford classification were significant predictors of not fitting the proportional recovery model.
These results confirm in an independent sample that stroke patients with mild to moderate initial impairments show an almost fixed proportional upper extremity motor recovery. Patients who will most likely not achieve the predicted amount of recovery were identified using clinical determinants measured within 72 hours poststroke.