Patient’s assessment and prediction of recovery after stroke: a roadmap for clinicians
DOI:
https://doi.org/10.1186/s40945-023-00167-4Keywords:
Prognosis, Prediction, Clinical-guide, Motor recovery, Stroke, Neurological physiotherapy, AssessmentAbstract
Background and purpose In neurorehabilitation clinical practice, assessment is usually more oriented to evaluate patient’s present status, than to plan interventions according to predicted outcomes. Therefore, we conducted an extensive review of current prognostic models available in the literature for recovery prediction of many functions and constructs, after stroke. We reported results in the form of a practical guide for clinicians, with the aim of promoting the culture of early clinical assessment for patient stratification, according to expected outcome. Summary of key points To define a roadmap for clinicians, a stepwise sequence of five actions has been developed, from collecting information of past medical history to the adoption of validated prediction tools. Furthermore, a clinically-oriented organization of available prediction tools for recovery after stroke have been proposed for motor, language, physiological and independency functions. Finally, biomarkers and online resources with prognostic value have been reviewed, to give the most updated state of the art on prediction tools after stroke. Recommendations for clinical practice Clinical assessment should be directed both towards the objective evaluation of the present health status, and to the prediction of expected recovery. The use of specific outcome measures with predictive value is recommended to help clinicians with the definition of sound therapeutic goals.Downloads
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Published
2023-06-19
How to Cite
Salvalaggio, S., Boccuni, L., & Turolla, A. (2023). Patient’s assessment and prediction of recovery after stroke: a roadmap for clinicians. Archives of Physiotherapy, 13(1). https://doi.org/10.1186/s40945-023-00167-4
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Masterclass
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Copyright (c) 2023 The Authors
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.