Effect of recurrent onabotulinum toxin a injection into the salivary glands: An ultrasound measurement
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Onabotulinum toxin A (OBTXA) injection is a well-established therapeutic option for the management of drooling. Many of the children treated undertake repeated injections every 3 to 6 months. We aimed to assess quantitative salivary gland changes via ultrasound imaging after intraglandular injection of OBTXA for sialorrhea treatment in children, as a method that suggests permanent changes in glandular size can cause a decrease in functionality or atrophy. STUDY DESIGN: Case-control study. METHODS: The parotid and submandibular glands of 22 patients with sialorrhea with previous repetitive OBTXA treatments were measured via ultrasound. These were compared with a control group of 38 healthy children. RESULTS: A total of 60 patients were included in the study (38 boys, 22 females). Body mass index, sex, and age were defined as confounders. The mean age was 7 years (standard deviation [SD] ±2.3 years) and 9 years (SD ±3.8 years) for treatment and control groups, respectively. There were no postinjection complications. We found significant decrease in the size dimensions (surface area and depth) of both submandibular glands and one parotid gland in the treatment group (P < .05). Significant smaller anterior-posterior dimension of the submandibular glands (P < .01) was also found. CONCLUSIONS: The chronic use of intraglandular OBTXA reduced the size of the salivary glands measured ultrasonographically. Results were correlated with clinical outcomes. Pathological studies should be done to correlate whether ultrasound changes result in atrophy or apoptosis of the glands. LEVEL OF EVIDENCE: 3b
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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 | 0.002 |
| 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) | 0.001 | 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".