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Record W2007213885 · doi:10.1097/mop.0000000000000052

Core concepts in congenital melanocytic nevi and infantile hemangiomas

2013· review· en· W2007213885 on OpenAlexaff
Catherine Warner, James G. Dinulos

Bibliographic record

VenueCurrent Opinion in Pediatrics · 2013
Typereview
Languageen
FieldMedicine
TopicVascular Malformations and Hemangiomas
Canadian institutionsSKiN Health
Fundersnot available
KeywordsMedicineDermatologyMelanomaPediatrics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.159
GPT teacher head0.427
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations5
Published2013
Admission routes1
Has abstractyes

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