Late Rebound of Infantile Hemangioma after Cessation of Oral Propranolol
Bibliographic record
Abstract
Propranolol has become the first line of treatment for infantile hemangiomas (IHs), with a high response rate, but rebound growth after cessation of propranolol has been reported, primarily in the first year of life. We sought to determine the frequency and associated factors leading to late regrowth after successful treatment at an age when the proliferative phase has usually ceased. We retrospectively reviewed the clinical charts, serial photographs, and radiologic images of children with rebound IH occurring after the age of 15 months after a successful course of oral propranolol averaging 2.6 mg/kg/day (range 2-3 mg/kg/day). Thirteen (10 female, 3 male) of 212 patients (6%) treated with oral propranolol since 2008 were evaluated. The mean age at the start of treatment was 5.3 months (range 1.8-13 months), and an average of 10.3 months (range 4.5-16 months) of treatment was given. It took an average of 5.3 months (range 1-13.8 months) for a significant rebound to appear. Late rebound after successful propranolol indicates a prolonged proliferation phase of IH even after 15 months of age. This is compared with previous reports of rebound, which occurred primarily in infants younger than 1 year old. Late proliferation can occur in localized, small, mixed, and deep IH, even after several months of a positive response to propranolol. A second course of propranolol readily controlled the recurrence.
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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 | 0.001 | 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 | 0.001 |
| 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".