| Literature DB >> 35928130 |
Leonardo Boccuni1,2,3, Lucio Marinelli4,5, Carlo Trompetto4,6, Alvaro Pascual-Leone1,7,8, José María Tormos Muñoz1,2,3.
Abstract
The problem: In the field of upper limb neurorehabilitation, the translation from research findings to clinical practice remains troublesome. Patients are not receiving treatments based on the best available evidence. There are certainly multiple reasons to account for this issue, including the power of habit over innovation, subjective beliefs over objective results. We need to take a step forward, by looking at most important results from randomized controlled trials, and then identify key active ingredients that determined the success of interventions. On the other hand, we need to recognize those specific categories of patients having the greatest benefit from each intervention, and why. The aim is to reach the ability to design a neurorehabilitation program based on motor learning principles with established clinical efficacy and tailored for specific patient's needs. Proposed solutions: The objective of the present manuscript is to facilitate the translation of research findings to clinical practice. Starting from a literature review of selected neurorehabilitation approaches, for each intervention the following elements were highlighted: definition of active ingredients; identification of underlying motor learning principles and neural mechanisms of recovery; inferences from research findings; and recommendations for clinical practice. Furthermore, we included a dedicated chapter on the importance of a comprehensive assessment (objective impairments and patient's perspective) to design personalized and effective neurorehabilitation interventions. Conclusions: It's time to reconcile research findings with clinical practice. Evidence from literature is consistently showing that neurological patients improve upper limb function, when core strategies based on motor learning principles are applied. To this end, practical take-home messages in the concluding section are provided, focusing on the importance of graded task practice, high number of repetitions, interventions tailored to patient's goals and expectations, solutions to increase and distribute therapy beyond the formal patient-therapist session, and how to integrate different interventions to maximize upper limb motor outcomes. We hope that this manuscript will serve as starting point to fill the gap between theory and practice in upper limb neurorehabilitation, and as a practical tool to leverage the positive impact of clinicians on patients' recovery.Entities:
Keywords: motor learning; neurorehabilitation; personalized medicine; stroke; upper limb
Year: 2022 PMID: 35928130 PMCID: PMC9343948 DOI: 10.3389/fneur.2022.939748
Source DB: PubMed Journal: Front Neurol ISSN: 1664-2295 Impact factor: 4.086
Summary of upper limb neurorehabilitation interventions according to key active ingredients, rationale and recommendations for clinical practice.
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| CIMT | Shaping | Explicit learning | Indicated for mild to moderately impaired patients; consider strategies for independent and distributed practice; use of a mitt is not mandatory |
| Expanded CIMT (adaptated for severely impaired patients) | Shaping | Explicit learning | Indicated for severely impaired patients; consider devices to assist movement execution; include both unilateral and bilateral arm training |
| Bobath Concept | Movement quality Afferent input to improve motor control, body schema and motor learning Facilitation techniques (handling, environmental adaptation, verbal cueing) | Explicit learning (implicit feedback/ knowledge of performance) | Suitable for any level of disability, but currently equally or less effective than other approaches. Consider repetitive practice (high number of repetitions) to increase the effectiveness of the intervention. |
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| Robotic therapy | Repetitive movement performance | Explicit learning | Particularly useful to assist shoulder and elbow movements (reaching) |
| Functional electrical stimulation | Repetitive movement performance | Explicit learning | Particularly useful to assist finger movements (grasping) |
| splint/orthotics | Repetitive movement performance | Explicit learning | Particularly useful for wrist and thumb functional positioning |
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| Virtual reality | Motivation, engagement Visual and auditory stimuli | Explicit learning | Particularly useful to increase motivation, avoid boredom and promote independent practice. Consider the provision of cues about movement quality (implicit feedback) |
| Action observation | Immediately after action observation, patients have to perform the same movements with the affected limb | Explicit learning | Indicated for severely impaired patients. Useful as additional therapy time in preparation for motor training |
| Mirror therapy | Large mirror | Explicit learning | Indicated for severely impaired patients. Useful as additional therapy time |
| Motor imagery | PRACTICE principles | Explicit learning | Indicated for severely impaired patients. Useful as additional therapy time in preparation for motor training |
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| Non-invasive brain stimulation | Stimulation parameters and localization of targets | Modulate neural activity | Consider different protocols depending on the level of impairment and underlying neural mechanisms. Consider performing motor training during (tDCS) or after (TMS) neuromodulation |
| Somatosensory electrical stimulation | More than one motor point at the same time, high frequency and intensity near motor threshold | Increased activation of sensorimotor areas | Train patients to use the stimulator independently, ideally in the 2 h preceding therapy. Consider providing stimulation concomitant with therapy |
| Aerobic training | Exercise intensity Performance immediately after motor training session | Prime motor learning consolidation | Consider short high intensity interval training protocols immediately after the motor training session |
Figure 1(A) Schematic representation of comprehensive upper limb neurorehabilitation assessment; (B) example of assessment algorithm for objective upper limb neurological deficits, developed and applied at Guttmann Institute (Barcelona, Spain). 9-HPT: 9-Hole Peg Test; Arm-A: Arm Activity Measure, section A; BBT: Box and Block Test; CIMT: Constraint Induced Movement Therapy; eCIMT: expanded CIMT; FM-UE: Fugl-Meyer Upper Extremity assessment; NIBS: Non-Invasive Brain Stimulation; SULCS: Stroke Upper Limb Capacity Scale.