BoNT-A for Post-Stroke Spasticity: Guidance on Unmet Clinical Needs from a Delphi Panel Approach
Bibliographic record
Abstract
There is extensive literature supporting the efficacy of botulinum toxin (BoNT-A) for the treatment of post-stroke spasticity, however, there remain gaps in the routine management of patients with post-stroke spasticity. A panel of 21 Italian experts was selected to participate in this web-based survey Delphi process to provide guidance that can support clinicians in the decision-making process. There was a broad consensus among physicians that BoNT-A intervention should be administered as soon as the spasticity interferes with the patients' clinical condition. Patients monitoring is needed over time, a follow-up of 4-6 weeks is considered necessary. Furthermore, physicians agreed that treatment should be offered irrespective of the duration of the spasticity. The Delphi consensus also stressed the importance of patient-centered goals in order to satisfy the clinical needs of the patient regardless of time of onset or duration of spasticity. The findings arising from this Delphi process provide insights into the unmet needs in managing post-stroke spasticity from the clinician's perspective and provides guidance for physicians for the utilization of BoNT-A for the treatment of post-stroke spasticity in daily practice.
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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 | 0.159 | 0.137 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".