Abobotulinumtoxin A injections for the chronic sialorrhea correction in children: Russian retrospective multicenter study
Bibliographic record
Abstract
OBJECTIVE: Multicenter retrospective analysis of the Russian experience in the use of AbobotulinumtoxinA injections for the correction of chronic sialorrhea of various etiologies in children. MATERIAL AND METHODS: 608 injections (from 1 to 5 repeated injections) of the AbobotulinumtoxinA into the salivary glands for 226 patients aged 2.0 to 17.8 years (Me - 5.1 years) with various neurological diseases and neurodevelopmental disorders in 12 Russian centers. RESULTS: In 180 patients (79.6%), AbobotulinumtoxinA was the first drug used to correct drooling. 177 (78.3%) children received combined injections into the salivary glands and body muscles to correct spasticity. The total doses of AbobotulinumtoxinA administered into the salivary glands during the first injection were (Med; min-max; 25-75%):150 U (7.7 U/kg); 30-400 U (1.9-27.3); 100-200 units (4.8-15.3). Doses to both parotid glands - 80 units (4.1 units/kg); 18-250 U (0.8-15.4 U/kg); 60-120 U (2.7-8.5 U/kg); in both submandibular - 70 U (3.3 U/kg); 12-160 U (0.5-13.6 U/kg); 40-80 U (2.1-6.1 U/kg). After the first injection of AbobotulinumtoxinA, a significant decrease in salivation was observed in 212 cases (93.8%). The effect lasted for an average of 4.9 months (0.5 to 24 months). Changes in the Drooling Impact Scale and subjective duration of effect were not significantly different after repeated injections. Adverse events were noted in 30 (13.3%) cases and persisted up to 2-3 weeks after injection. CONCLUSION: AbobotulinumtoxinA injections have shown effectiveness and safety in the correction of chronic sialorrhea in children, also in combination with concomitant spasticity treatment. Further research is needed to determine the optimal dose and treatment protocols.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".