Systematic Review of the Effectiveness of Pharmacological Interventions in the Treatment of Spasticity of the Hemiparetic Lower Extremity More Than Six Months Post Stroke
Bibliographic record
Abstract
BACKGROUND: The long-term management of lower limb spasticity after stroke is an important aspect of an individual's physical recovery and quality of life. OBJECTIVE: To examine the effectiveness of pharmacological interventions in reducing spasticity of the lower limb in chronic stroke survivors. METHODS: PubMed, CINAHL, and EMBASE were searched for studies in which (1) ≥50% of the sample size had sustained a stroke; (2) the research design was a randomized controlled trial (RCT); (3) the mean time since stroke was ≥6 months for both the treatment and control groups, at the time treatment was initiated; (4) the treatment group received a pharmacological intervention aimed at treating lower limb spasticity; and (5) spasticity was assessed pre and post treatment. Methodological quality of each study was assessed using the PEDro tool. RESULTS: Nine RCTs (PEDro scores, 4-9) met inclusion criteria and included a pooled sample size of 605 individuals with a mean age of 54.8 years (range, 14-86). Four RCTs provided evidence that botulinum toxin type A was effective in reducing spasticity compared to persons receiving placebo or a phenol neurolytic. One study provided evidence that both alcohol and phenol neurolytics were effective in reducing spasticity. Finally, 4 studies provided evidence that oral and intrathecal medications were effective in reducing lower limb spasticity compared to placebo. CONCLUSIONS: Pharmacological treatment initiated 6 months post stroke reduced lower limb spasticity. Relevant areas of exploration for future research could include the period of effectiveness, long-term complications, and a cost-benefit analysis of such treatments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.008 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".