Botulinum toxin assessment, intervention and follow‐up for paediatric upper limb hypertonicity: international consensus statement
Bibliographic record
Abstract
The primary objective of this paper was to evaluate the published evidence of efficacy and safety of botulinum neurotoxin (BoNT) injections in paediatric upper limb hypertonia (PULH). Secondary objectives included the provision of clinical context, based on evidence and expert opinion, in the areas of assessment, child and muscle selection, dosing, and adjunctive treatment. A multidisciplinary panel of authors systematically reviewed, abstracted, and classified relevant literature. Recommendations were based on the American Academy of Neurology (AAN) evidence classification. Following a literature search, 186 potential articles were screened for inclusion, and 15 of these met the criteria and were reviewed. Grade A evidence was found to support the use of BoNT to reach individualized therapeutic goals for PULH. There is grade B evidence (probably effective) for tone reduction following BoNT injections and grade U evidence (inconclusive) for improvement in upper limb (UL) activity and function. BoNT injections were generally found to be safe and well tolerated with the most common side effect identified as a transient decrease in grip strength.
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 | 0.034 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".