Towards an algorithm guiding clinical decision-making for transition of locomotor therapy between Lokomat® and body-weight supported treadmill training in subacute stroke – an exploratory study

Ms Nicole Prideaux1, Associate Professor Christopher Barr2, Associate Professor Claire  Drummond2, Associate Professor Maayken van den Berg2

1SA Health, Adelaide, Australia, 2Flinders University of South Australia, Adelaide, Australia

Background: Contemporary post-stroke subacute locomotor rehabilitation typically includes robotics or Body-Weight Supported Treadmill Training (BWSTT). Advantages and disadvantages, as well as conflicting evidence of efficacy, exist between these two modalities(1). Questions therefore remain regarding the choice of modality throughout the subacute rehabilitation journey.

Aim: To develop an algorithm guiding transition from the Lokomat® to BWSTT in adults with subacute stroke.

Method: Ten participants with subacute stroke were clinically judged as either being capable, or not capable, of completing BWSTT. This judgement was contrasted with: participants’ Functional Ambulation Category (FAC) score; clinical evaluation of sit to stand and standing; Lokomat® settings; maximal active hip and knee flexion in standing; and gait kinematics in BWSTT. Based on the findings, a clinical decision-making algorithm was proposed.

Results: Clinical judgement deemed four of ten participants capable of BWSTT. Unlike  participants judged not-capable of BWSTT these participants: a) had a FAC of 1; b) performed sit to stand and standing with minimal support and even weight bearing; c) trained with Lokomat®: BWS <30%, GF <30-35%, speed >2.0kph; d) had >45 degrees standing active hip and knee flexion; e) had no significant issues with their physiological stepping pattern in BWSTT that could not be controlled with verbal or physical facilitation by only one person.

Conclusion: Participants clinically judged ready for BWSTT presented with a FAC of 1, more independence with function, more challenging Lokomat® settings, and greater active volitional lower-limb control. We have translated these findings into an algorithm guiding the transition from Lokomat® to BWSTT.

References

  1. Hornby, T.G., D.J. Reinkensmeyer, and D. Chen, Manually-assisted versus robotic-assisted body weight-supported treadmill training in spinal cord injury: what is the role of each. PM R, 2010. 2(3): p. 214-221.

Biography:

Nicole Prideaux is a Senior Physiotherapist in SA Health with over 20 years of clinical experience. Recently, Nicole completed her Master in Clinical Rehabilitation through undertaking research into cardiovascular exercise on the Lokomat robotic and transition to body-weight supported treadmill training in patients with subacute stroke.

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