Assessment of spasticity after stroke using clinical measures: a systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To identify and appraise the literature on clinical measures of spasticity that has been investigated in people after stroke. METHODS: The literature search involved four databases (PubMed, CINAHL, Embase and The Cochrane Library) up to February 2014. The selected studies included those that aimed to measure spasticity using a clinical assessment tool among adult patients post-stroke. Two independent raters reviewed the included articles using a critical appraisal scale and a structured data extraction form. RESULTS: A total of 40 studies examining 15 spasticity assessment tools in patients post-stroke were reviewed. None of the reviewed measurement tools demonstrated satisfactory results for all psychometric properties evaluated, and the majority lacked evidence concerning validity and absolute reliability. CONCLUSION: This systematic review found limited evidence to support the use of most of clinical measures of spasticity for people post-stroke. Future research examining the application and psychometric properties of these measures is warranted. Implications for Rehabilitation There is a need for objective clinical tools for measuring spasticity that are clinically feasible and easily interpreted by clinicians. This review identified various clinical measures of spasticity that have been investigated in people after stroke. Insufficient evidence of psychometric properties precludes recommending one tool over the others. Future research should focus on investigating the psychometric properties of clinical measures of spasticity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it