Towards a Clinical Decision-Making Algorithm Guiding Locomotor Therapy Modality in Subacute Stroke: An Exploratory
Nicole Prideaux1, Christopher Barr2, Claire Drummond3
1Bachelor of Applied Science Physiotherapy (honours), Master Clinical Rehabilitation, Physiotherapist, Rehabilitation, Aged Care, and Palliative Division, Southern Adelaide Local Health Network: c/o Flinders Medical Centre, Flinders Drive, Bedford Park, South Australia, 5042, Australia.
Summary
This study proposes a clinical decision-making algorithm to guide the transition from Lokomat® robotic to body-weight supported treadmill training for subacute stroke patients, improving rehabilitation choices.
Area of Science:
- Neurorehabilitation
- Robotics in Physical Therapy
- Stroke Recovery
Background:
- Limited evidence exists for transitioning stroke patients from robotic therapy to treadmill training.
- Clinical decisions regarding rehabilitation modality changes are challenging.
Purpose of the Study:
- To propose a clinical decision-making algorithm for modality transition in subacute stroke rehabilitation.
- To guide the choice between Lokomat® robotic and body-weight supported treadmill training.
Main Methods:
- Assessed 10 subacute stroke patients completing Lokomat® therapy.
- Collected physiotherapist clinical judgment and objective measures (Functional Ambulation Category, sit-to-stand, Lokomat® settings, hip/knee flexion, gait biomechanics).
- Developed a decision-making algorithm based on observed patterns.
Main Results:
- Four of 10 participants were deemed ready for transition.
- Readiness correlated with higher Functional Ambulation Category, independent sit-to-stand, specific Lokomat® settings (BWS <30%, GF <30-35%, speed >2.0kph), greater active hip/knee flexion (>45°), and fewer stepping issues.
- Key differences identified between participants ready and not ready for transition.
Conclusions:
- Patients ready for transition exhibit greater functional independence, volitional control, and fewer gait impairments.
- A proposed algorithm can guide the transition from Lokomat® to body-weight supported treadmill training.
- Further clinical trials are needed to validate the proposed algorithm.
