Core concepts in congenital melanocytic nevi and infantile hemangiomas
Bibliographic record
Abstract
PURPOSE OF REVIEW: Congenital melanocytic nevi (CMN) and infantile hemangiomas are commonly encountered in newborns and may present diagnostic and therapeutic dilemmas for medical practitioners. Herein, we review and discuss these two important clinical entities and focus on core issues and recent advances. RECENT FINDINGS: Melanoma risk for patients with CMN is greatest in infants with large CMN located on the trunk, CMN greater than 40 cm, and multiple satellite nevi. Recent histological and molecular findings have been described to assist in differentiating benign proliferative nodules arising in CMN from melanoma. Multiple CMN and associated neurological lesions have recently been shown to be due to a single postzygotic mutation in NRAS [neuroblastoma RAS viral (v-ras) oncogene homolog]. Over the last several years, numerous advancements have occurred in redefining the clinical course of infantile hemangiomas, describing clinical syndromes associated with infantile hemangiomas and treating complicated infantile hemangiomas. The nonselective β-blocker propranolol has become first-line therapy for the treatment of complicated infantile hemangiomas. Topical timolol shows promise for the treatment of certain types of infantile hemangiomas. SUMMARY: Although most CMN and infantile hemangiomas do not require active intervention, understanding which lesions may impact the overall health of the infant assists in early intervention. This article touches on core concepts in the clinical evaluation and treatment of CMN and infantile hemangioma.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".