Patient-Identified Factors That Influence Spasticity in People with Stroke and Multiple Sclerosis Receiving Botulinum Toxin Injection Treatments
Bibliographic record
Abstract
PURPOSE: To describe the nature, extent, and impact of spasticity; determine factors that are perceived to influence its severity; and examine the relationship between time since diagnosis and impact of spasticity on daily activities in people with stroke and multiple sclerosis (MS) who are receiving botulinum toxin injection treatments. METHODS: After a cross-sectional telephone survey, descriptive statistics and correlations were analyzed separately for the stroke and MS groups. RESULTS: A total of 29 people with stroke and 10 with MS were surveyed. Both groups perceived increased spasticity with outdoor cold (69% stroke, 60% MS), muscle fatigue (59% stroke, 80% MS), and mental stress (59% stroke, 90% MS). No statistically significant correlations were found between time since diagnosis and perceived impact of spasticity on function in the stroke (r=0.07, p=0.37) or MS (r=0.16, p=0.33) groups. The MS group experienced bilateral and more severe perception of spasticity in the legs than the stroke group and identified more factors as worsening their spasticity (p<0.05). Severity of leg (but not arm) spasticity was significantly correlated with severity of impact of the following factors in the MS group only: lying on the back (r=0.70, p<0.05), outdoor heat (r=0.61, p<0.05), and morning (r=0.59, p<0.05). CONCLUSION: Intrinsic and extrinsic triggers can influence the perception of spasticity differently depending on individual factors, severity, location (arm vs. leg), and distribution of spasticity (unilateral vs. bilateral). Clinicians can use the findings to better understand, educate, and treat people with stroke and MS.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".