Medical, Surgical, and Wound Care Management of Ulcerated Infantile Hemangiomas: A Systematic Review
Bibliographic record
Abstract
Ulcerated infantile hemangiomas may present a therapeutic challenge, especially if there is concurrent hemorrhage or infection. The aim of this study was to systematically review the published evidence on the treatment of ulcerated hemangiomas, focusing on wound healing as the outcome of interest. We searched MEDLINE, Embase, SCOPUS, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Web of Science from inception to July 2016. Seventy-seven studies met our inclusion criteria. One study was a randomized controlled trial, 30 were observational studies, and 46 were case reports or case series. There is significant heterogeneity among the methods used. We reviewed 1239 patients in total. Of the 197 treated with oral propranolol, 191 (97.0%) achieved complete ulcer healing. Thirty-one patients failed corticosteroid therapy (oral, intralesional, or topical) and were subsequently successfully treated with other therapies. Surgical resections were typically performed for larger hemangiomas and those causing complications. None of the therapies discussed appear to offer significant advantages over others. Therefore, treatment decisions should be individualized based on location of disease, extent, symptoms, feasibility, cost, and parental preference.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".