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Record W2323826900 · doi:10.1097/prs.0b013e318245eb11

Pharmacologic Therapies for Infantile Hemangioma

2012· letter· en· W2323826900 on OpenAlexaffabout
Jugpal S. Arneja

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2012
Typeletter
Languageen
FieldMedicine
TopicVascular Malformations and Hemangiomas
Canadian institutionsUniversity of British ColumbiaBC Children's Hospital
Fundersnot available
KeywordsMedicineHemangiomaModalitiesPropranololPathologyInternal medicine

Abstract

fetched live from OpenAlex

Sir:FigureI read with great interest the special report by Drs. Itinteang et al. entitled “Pharmacologic Therapies for Infantile Hemangioma: Is There a Rational Basis?”1 The authors are to be congratulated for achieving a true advance toward understanding the pathogenesis of hemangioma and its response to pharmacologic therapy; recently, practitioners treating hemangioma have been intrigued by the favorable clinical response to propranolol (including our group2). However, until now, a model to describe a basis for its efficacy has been elusive. Their translational explanations as to how the basic science correlates with the pharmacology and physiology are most insightful. Furthermore, I had the pleasure of listening to Dr. Tan's presentation this past May at the 16th Congress of the International Confederation for Plastic, Reconstructive and Aesthetic Surgery, in 2011 in Vancouver, British Columbia, and without hesitation, this dissertation can be considered a highlight of the confederation's proceedings. Some questions are certain to stem from one's analysis of this article, specifically, pertaining to the response of hemangiomas to the different pharmacologic modalities. Why do certain tumors respond to corticosteroid and/or β-blocker therapy whereas others do not? Why does congenital hemangioma (i.e., rapidly involuting congenital hemangioma/noninvoluting congenital hemangioma) seldom respond to pharmacologic intervention? Should there be a similar response using angiotensin-converting enzyme inhibitors or even combined therapies that target the renin-angiotensin system? An illustration indicating the purported mechanism of action of the various pharmacologic modalities would be valuable. Clearly, scientific advances are often met by more questions than answers; however, these authors are to be congratulated on their strong body of work on this subject. I welcome their future contributions to the study of this most interesting tumor. Jugpal S. Arneja, M.D. Division of Plastic Surgery, University of British Columbia, and, British Columbia Children's Hospital, Vancouver, British Columbia, Canada, [email protected]

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.263
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.272
Teacher spread0.238 · 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
GenreEmpirical

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
Published2012
Admission routes2
Has abstractyes

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