The Use of Ipratropium Bromide for the Treatment of Pediatric Sialorrhea: A Retrospective Clinical Case Series
Bibliographic record
Abstract
Objective: This retrospective review documents the experience of ipratropium bromide use among pediatric patients with sialorrhea at our multidisciplinary sialorrhea clinic at Children’s Hospital at London Health Sciences Centre (LHSC). Methods: A retrospective chart review of patients diagnosed with sialorrhea at our multidisciplinary clinic between January 2015 and June 2021 was completed. Data on patient demographics, comorbidities, clinical presentation, previous interventions, quality of life, and medication adverse side effects was collected. Drooling Frequency and Severity Scale (DFSS) scores were reviewed to compare sialorrhea management pre- and post-treatment with topical 0.03% ipratropium bromide nasal solution. A descriptive analysis and Wilcoxon signed rank tests were conducted to compare pre- versus post-treatment DFSS scores. Results: A total of 12 patients presented for follow-up and were included in the final analysis. At the pre-treatment visit, the median DFSS score was 4 for frequency and 5 for severity. Post-treatment, median DFSS score was 3 for frequency and 4.5 for severity, ( P = .020 and .129, respectively). Minimal adverse effects were encountered. Conclusions: Ipratropium bromide provided a statistically significant benefit for drooling frequency in the patients studied and may present an additional topical medical option for pediatric sialorrhea with limited adverse effects.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".