Oh for fucks sake, this is totally useless, not one survivor gives a damn about your assessments. I'd have your asses fired in no time. The only goal in stroke is 100% recovery, this does nothing for that.
Give us EXACT STROKE PROTOCOLS PRODUCING EXACT RESULTS.
European evidence-based recommendations for clinical assessment of upper limb in neurorehabilitation (CAULIN): data synthesis from systematic reviews, clinical practice guidelines and expert consensus
Journal of NeuroEngineering and Rehabilitation volume 18, Article number: 162 (2021)
Abstract
Background
Technology-supported rehabilitation can help alleviate the increasing need for cost-effective rehabilitation of neurological conditions, but use in clinical practice remains limited. Agreement on a core set of reliable, valid and accessible outcome measures to assess rehabilitation outcomes is needed to generate strong evidence about effectiveness of rehabilitation approaches, including technologies. This paper collates and synthesizes a core set from multiple sources; combining existing evidence, clinical practice guidelines and expert consensus into European recommendations for Clinical Assessment of Upper Limb In Neurorehabilitation (CAULIN).
Methods
Data from systematic reviews, clinical practice guidelines and expert consensus (Delphi methodology) were systematically extracted and synthesized using strength of evidence rating criteria, in addition to recommendations on assessment procedures. Three sets were defined: a core set: strong evidence for validity, reliability, responsiveness and clinical utility AND recommended by at least two sources; an extended set: strong evidence OR recommended by at least two sources and a supplementary set: some evidence OR recommended by at least one of the sources.
Results
In total, 12 measures (with primary focus on stroke) were included, encompassing body function and activity level of the International Classification of Functioning and Health. The core set recommended for clinical practice and research: Fugl-Meyer Assessment of Upper Extremity (FMA-UE) and Action Research Arm Test (ARAT); the extended set recommended for clinical practice and/or clinical research: kinematic measures, Box and Block Test (BBT), Chedoke Arm Hand Activity Inventory (CAHAI), Wolf Motor Function Test (WMFT), Nine Hole Peg Test (NHPT) and ABILHAND; the supplementary set recommended for research or specific occasions: Motricity Index (MI); Chedoke-McMaster Stroke Assessment (CMSA), Stroke Rehabilitation Assessment Movement (STREAM), Frenchay Arm Test (FAT), Motor Assessment Scale (MAS) and body-worn movement sensors. Assessments should be conducted at pre-defined regular intervals by trained personnel. Global measures should be applied within 24 h of hospital admission and upper limb specific measures within 1 week.
Conclusions
The CAULIN recommendations for outcome measures and assessment procedures provide a clear, simple, evidence-based three-level structure for upper limb assessment in neurological rehabilitation. Widespread adoption and sustained use will improve quality of clinical practice and facilitate meta-analysis, critical for the advancement of technology-supported neurorehabilitation.
Background
Neurological conditions are a leading cause of disability world-wide. Incidence is rising due to an ageing world population and prevalence is increasing due to growth of the world population, better survival rates and improved long-term care [1]. The result is increasing pressure on the healthcare system globally and frames the need for effective and efficient approaches to enable and maintain access to care.
Recent advances in neurorehabilitation research have resulted in a better understanding of recovery, giving rise to new promising approaches such as increased intensity of practice, early intervention and use of technology. Of those, the use of technology in rehabilitation may help alleviate the pressure on the healthcare system. Moreover, technologies could enable access to rehabilitation throughout the lifespan and has been advocated by the World Health Organisation (WHO) as an investment in human capital that contributes to health, economic and social development [2].
For a successful transfer of therapeutic interventions using rehabilitation technology into clinical practice, evidence of their effectiveness is essential. This is reflected in national strategies and frameworks emphasising the need for informed decision making in healthcare that is research-led and evidence-based. Yet, several national guidelines cite limited research evidence to justify the use of rehabilitation technologies [3,4,5]. Indeed, data on clinical evaluations of interventions in neurological rehabilitation, either conventional or technological, are not easily comparable due to inconsistency in what is actually measured [2], and the measurement tools used. Consequently, there is a paucity of high-quality evidence from systematic reviews and meta-analyses [6].
Agreement on outcome measures (OM) and corresponding procedures for assessment are critical to advancing the field. For new approaches to be used effectively in clinical practice (the right therapy approach with the right patients, at the right time and delivered via the most effective protocols), clinicians need clear assessment guidelines to enable them to make informed decisions. The use of agreed, uniform OM is not only useful in order to compare the effectiveness of different training approaches, but also to identify which patients benefit most from which training approach and dose.
For example, the use of different technologies for task-oriented training of the upper limb was investigated in highly functional chronic stroke patients in two separate clinical trials using a sensor system [7] or a robot system [8]. As both studies used the same OM, results could be combined, showing that training with the inertial sensor system providing feedback on exercise performance was more beneficial for highly functional patients than the robot-guided system [9].
In addition, practical and accurate tools are emerging that can predict recovery, with the potential to significantly improve patient management and reduce costs of health services [10]. Establishing and elaborating clinical prediction models for the upper limb, such as SAFE [11] and PREP2 [12], to facilitate personalisation of patient rehabilitation and discharge planning, can only occur if sufficient good quality objective assessment data is available.
The European Network on Robotics for Neurorehabilitation (European Co-operation in Science and Technology, COST Action TD1006) has developed a set of recommendations for upper limb assessment in neurological conditions, to evaluate both conventional and technology-supported therapy. These European recommendations aim to improve the quality of upper limb neurorehabilitation in clinical practice globally, through the adoption of standardised, agreed protocols for assessment in clinical practice and research. The recommendations will directly support clinical research and facilitate larger scale multi-centre studies, allowing meta-analyses, essential for informing and stimulating investigation of prediction for patient-specific training approaches and more generally advancing understanding of recovery. It will also inform and influence the development of new upper limb neurorehabilitation technologies both as therapies and assessment tools, and assist in the translation of useful technologies into clinical practice.
The present paper collates and synthesizes the recommendations from multiple sources, combining existing evidence, current clinical practice guidelines and expert consensus, into the recommendations for Clinical Assessment of Upper Limb In Neurorehabilitation (CAULIN). The CAULIN recommendations provide evidence-based recommendations for upper limb assessment of patients with neurological conditions before, during and after therapy (either conventional or technology-assisted treatment), including the recommended time frame of applying structured assessment where available.
More at link.
No comments:
Post a Comment