Clinical factors associated with trunk control after stroke: A prospective study.

INTRODUCTION: Poor trunk control after stroke can impact recovery of global functional abilities. Therefore, the aim of this study was to evaluate whether clinical and functional data from stroke participants can be used to predict trunk control at 90 days. METHODS: This is a prospective study of 37 participants with stroke. The variables evaluated at hospital discharge were stroke severity (National Institute of Health Stroke Scale - NIHSS); functional capacity (modified Rankin scale - mRS); handgrip; and cognitive function. At 90 days, the variables evaluated were autonomy (Functional Independence Measure - FIM, Barthel Index); gait mobility (Tinetti mobility test -TMT); quality of life (European Quality of Life Scale - EuroQol-5D) and trunk control (trunk impairment scale - TIS). The participants were considered to have satisfactory (TIS³14) or non-satisfactory trunk control (TIS≤13), and the differences between them were assessed by chi-square test (categorical variables) and Mann-Whitney/unpaired t-test (continuous variables). A ROC curve was used to show cut-off value of clinical variables to predict trunk control. RESULTS: The unsatisfactory trunk control group presented ahigher NIHSS at discharge (p=0.01), higher mRS at discharge (p=0.00), lower Barthel Index at 90 days (p=0.03), lower FIM at 90 days (p=0.01) and lower TMT at 90 days (p=0.00) than the satisfactory trunk control group. The best cut-off points for the NIHSS and mRS scores at discharge for predicting unsatisfactory trunk control are ≥6 and ≥3, respectively. CONCLUSION: Greater NIHSS and mRS scores at hospital discharge increase the chance of unsatisfactory trunk control at 90 days after stroke.

Clinical factors associated with the development of nonuse learned after stroke: a prospective study.

Background: Upper extremity impairment is present in most of people with stroke. The use of the affected upper extremity can be impacted not only by physical impairment but also by abehavioral phenomenon called learned nonuse. Objective: The aim of this study was to evaluate which clinical factors in the acute phase are associated with the development of learned nonuse in the upper extremity after stroke. Methods: This cohort study included 38 patients with ischemic stroke. Hospital discharge data were collected for clinical aspects, scales of severity, incapacity and autonomy, as well as for neuromuscular and sensory evaluations. At 90 days after hospital discharge, the score on the Motor Activity Log scale for detecting learned nonuse was obtained, and life quality was evaluated by the EuroQol. The individuals with and without learned nonuse were compared by attest for univariate analysis, and ageneralized linear model was employed to find possible predictors, which were considered significant p <0.05. Results: In the statistical model, age (p= .006), severity at discharge (p= .036), handgrip strength (p= .000), altered sensitivity (p= .011), incapacity at discharge (p= .009) and autonomy at discharge (p= .011) were found to be associated with learned nonuse. In relation to quality of life, mobility, personal care, usual activities, anxiety, depression and perception had lower mean values in the learned nonuse group. Conclusion: Age, severity of stroke, incapacity and neuromuscular and sensory compromises are associated with upper extremity learned nonuse in stroke patients.