Robot Assisted Gait Training in a Patient with Ataxia

Robot-assisted gait training in patients with various neurological diseases: A mixed methods feasibility study

BACKGROUND

Walking impairment represents a relevant symptom in patients with neurological diseases often compromising social participation. Currently, mixed methods studies on robot-assisted gait training (RAGT) in patients with rare neurological diseases are lacking. This study aimed to explore the feasibility, acceptability, goal attainment and preliminary effects of RAGT in patients with common and rare neurological diseases and understand the intervention context and process.

METHODS

A mixed-methods feasibility study was conducted at an Austrian rehabilitation centre. Twenty-eight inpatients after stroke in the subacute and chronic phases, with multiple sclerosis, Parkinson's disease, spinal cord injury, spinocerebellar ataxia, acute/chronic inflammatory demyelinating polyneuropathy and motor neuron disease were included. Patients received RAGT for 45 minutes, 4x/week, for 4 weeks. Baseline and post-intervention assessments included gait parameters, walking and balance, and questionnaires. Semi-structured observations were conducted twice during the intervention period and analysed using thematic analysis. Descriptive statistics within the respective disease groups and calculation of effect sizes for the total sample were performed. Triangulation was employed to develop a deeper understanding of the research topic.

RESULTS

Data from 26 patients (mean age 61.6 years [standard deviation 13.2]) were analysed. RAGT was highly accepted by patients and feasible, indicated by recruitment, retention, and adherence rates of 84.8% (95% confidence interval, CI 0.7-0.9), 92.2% (95% CI 0.7-1.0) and 94.0% (95% CI 91.4-96.2), respectively. Goal attainment was high, and only mild adverse events occurred. Improvements in walking speed (10-Metre Walk Test, effect size r = 0.876), walking distance (6-Minute Walk Test, r = 0.877), functional mobility (Timed Up and Go, r = 0.875), gait distance (r = 0.829) and number of steps (r = 0.834) were observed. Four themes were identified: familiarising with RAGT; enjoyment and acceptance through a trusting therapeutic relationship; actively interacting; and minimising dissatisfaction.

DISCUSSION

Sufficiently powered randomised controlled trials are needed to validate our results.

TRIAL REGISTRATION

German Clinical Trials Register, DRKS00027887.

Challenges in applying minimal clinically important difference: a critical review

Healthcare clinicians strive to make meaningful changes in patient function and participation. A minimal clinically important difference (MCID) is an estimate of the magnitude of change needed to be meaningful to a patient. Clinicians and investigators may assume that a cited MCID is a valid and generalizable estimate of effect. There are, however, at least two concerns about this assumption. First, multiple methods exist for calculating an MCID that can yield divergent values and raise doubt as to which one to apply. Second, MCID values may be erroneously generalized to patients with dissimilar health conditions. With this in mind, we reviewed the methods used to calculate MCID and citations of reported MCID values for outcome measures commonly used in neurologic, orthopedic, and geriatric populations. Our goal was to assess whether the calculation methods were acknowledged in the cited work and whether the enrolled patients were similar to the sample from which the MCID estimate was derived. We found a concerning variation in the methods employed to estimate MCID. We also found a lack of transparency in identifying calculation methods and applicable health conditions in the cited work. Thus, clinicians and researchers must pay close attention and exercise caution in assuming changes in patient status that exceed a specific MCID reflect meaningful improvements in health status. A common standard for the calculation and reporting of an MCID is needed to address threats to the validity of conclusions drawn from the interpretation of an MCID.