Topical Timolol Maleate Treatment of Infantile Hemangiomas
Bibliographic record
Abstract
BACKGROUND: There has been a dramatic increase in the off-label use of ophthalmic timolol maleate, a β-blocker used for infantile hemangioma (IH) treatment as a topical counterpart to oral propranolol. Its safety and efficacy in a pediatric population with IH have not been evaluated in a large cohort. Our goal was to retrospectively assess timolol's effectiveness, discern characteristics associated with response, and document reported adverse events. METHODS: A multicenter retrospective cohort study of 731 patients treated with topical timolol was completed at 9 centers. Inclusion required an IH suitable for timolol in the treating physician's judgment and access to clinical details including photographs. Logistic regression analysis and descriptive statistics were performed. Primary outcome measures were efficacy assessed by using visual analog scales for color and for size, extent, and volume from review of digital photographs taken as standard of care. RESULTS: Most IHs were localized (80.1%) and superficial (55.3%). Risk of disfigurement was the most common indication for therapy (74.3%). Duration of therapy (P < .0001), initial thinness (P = .008), and subtype (P = .031) were significant predictors of response. Best response occurred in superficial IHs <1 mm thick. Fifty-three (7.3%) required subsequent therapy with systemic β-blocker. Adverse events were mild, occurring in 25 (3.4%) patients. No cardiovascular side effects were documented. CONCLUSIONS: Timolol seems to be a well-tolerated, safe treatment option with moderate to good effectiveness, demonstrating best response in thin, superficial IHs regardless of pretreatment size. Timolol can be recommended as an alternative to systemic β-blockers and watchful waiting for many patients.
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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 | 0.000 | 0.001 |
| 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) | 0.000 | 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".