Clinical features of patients who might benefit more from walking robotic training.
Study Goal
The researchers aimed to identify clinical features of subacute stroke patients that predict better responsiveness to robotic walking therapy compared to conventional gait training.
Results Summary
Robotic walking therapy improved the probability of achieving autonomous walking, particularly in patients with higher trunk control test scores at admission. Conventional therapy showed better outcomes for patients with higher Barthel Index scores and shorter time since stroke, while robotic therapy was more effective for those with better trunk control.
Population
Subacute stroke inpatients (n=100)
Effective Dosage
5 times per week
Duration
4 weeks
Interactions
None mentioned
| Intervention | Direction | Endpoint | Population | Dosage | Impact | Claim # |
|---|---|---|---|---|---|---|
robotic walking training | increase | probability to reach an autonomous walking | non-ambulant patients affected by subacute stroke | - | improves probability to reach an autonomous walking | #1 |
robotic therapy | increase | FAC-score at discharge | subacute inpatients | - | had a significant effect on the FAC-score at discharge | #2 |
robotic training | increase | efficacy | - | - | improved efficacy | #3 |
conventional therapy | increase | prognosis | - | - | resulted in good prognosis | #4 |
robotic walking training | no change | global ability at admission | - | - | was not associated with global ability at admission | #5 |
robotic training | increase | benefit | more severely disabled patients | - | may obtain greater benefit | #6 |
BACKGROUND: Robotic walking training improves probability to reach an autonomous walking in non-ambulant patients affected by subacute stroke. However, little information is available regarding the prognostic factors for identifying best responder patients. The purpose of the present study is therefore to investigate the clinical features of patients with subacute stroke that might benefit more from robotic walking therapy. METHODS: One hundred subacute inpatients randomized in robotic or conventional gait training were assessed at baseline and after 4 weeks of training performed 5 times per week. Forward Binary Logistic Regression was performed using functional ambulation category (FAC) as dependent variable and as independent variables: trunk function (trunk control test), global ability (Barthel Index), age, sex, time from stroke and beginning of rehabilitation, side and type of stroke, and in the first analysis also type of treatment. RESULTS: The parameters that have a significant effect on the FAC-score at discharge were a higher BI-score at admission, a higher TCT-score at admission, a short time from the ictus and a robotic therapy. The variance explained by these four factors was 78%. When the two groups were separately analysed for type of treatment, a higher BI-score and a short time from stroke resulted in good prognosis for conventional therapy, whereas only a high TCT-score improved efficacy of robotic training. CONCLUSION: Efficacy of robotic walking training was not associated with global ability at admission. Hence, more severely disabled patients may obtain greater benefit from robotic training, independently by other factors, except the need of a residual trunk control that was identified as a good prognostic factor for robotic walking training.