Propranolol versus Prednisone in the Treatment of Infantile Hemangiomas: A Retrospective Comparative Study
Bibliographic record
Abstract
The goal of the current study was to compare the clinical effectiveness of oral propranolol with that of oral prednisone in the treatment of infantile hemangiomas (IH). Patients treated for IH with oral propranolol were retrospectively matched with patients treated with oral prednisone according to type, location, and size of the IH and age at start of treatment. Response to treatment was evaluated by rating serial medical photographs taken 1, 2, and 6 months after initiation of treatment. Degree of clinical improvement in overall appearance (including color and size) was rated as follows: worse or stable (0), slight (<25%), moderate (25-50%), good (50-75%), or excellent (>75%). A second assessment was done using a 100-mm visual analog scale to rate improvement at 6 months. Pre and post-treatment imaging was available for several patients. Twelve pairs of infants with IH were analyzed. At 1 month, clinical improvement in the propranolol group was moderate to good in all patients. In the prednisone group, only one patient had moderate improvement, with others showing slight (7/12) or no improvement or stabilization (3/12) from baseline and one case worsening. At 6 months, the propranolol group showed good to excellent response in all cases, whereas nine in the prednisone group showed slight to moderate response. Doppler ultrasound and magnetic resonance imaging correlated with the clinical improvement in the cases in which it was performed. No major side effects were observed in either group. Propranolol appears superior to oral prednisone in inducing more-rapid and greater clinical improvement in this study. A larger prospective study comparing these two treatment modalities is warranted.
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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 | 0.000 |
| 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".