Clinical measures for tone assessment in adults with central nervous system disorders—A scoping review in a rehabilitation context
Bibliographic record
Abstract
Assessment of muscle tone in a clinical setting is important for the physiotherapist to better analyse and establish appropriate treatments for CNS disorders. This study aims to review and summarise how to assess changes in tone in the context of adult rehabilitation. Secondarily, this study aimed to identify the central nervous system disorders, the respective variable/concept under study, and the testing procedures employed. PRISMA-ScR guidelines were followed using the “population”, “concept”, and “context” to define the eligibility criteria and to delineate the research question. PubMed®, Science Direct®, Web of Science™, and Google Scholar® databases were used to search the literature. The search included studies published between 2011 and March 2023 in Portuguese, English, French, and Spanish that assessed an adult population (>19 years) with CNS injury. Review articles, qualitative studies, conference proceedings, letters to the editor, and editorials were excluded. Initially, 1519 references were identified, of which eight met the eligibility criteria. The measurement instruments included the Modified Ashworth Scale (n = 5), the Modified Modified Ashworth Scale (n = 3), the BioTone™ system (n = 2), the Montreal Spasticity Measurement (n = 1), and the Tone Evaluation Scale (n = 1). The health conditions considered included stroke sequelae (n = 7), multiple sclerosis (n = 4), spinal cord injuries (n = 4), cerebral palsy (n = 2), brain tumour (n = 2), and traumatic brain injuries (n = 3). The concepts of spasticity (n = 7) and muscle tone (n = 2) were explored. Considering the variables spasticity and muscle tone in different CNS disorders, mainly stroke, subjective instruments were preferred compared to objective ones, with the Modified Ashworth Scale being highlighted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".