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Record W4387957515 · doi:10.1002/jvc2.297

Efficacy of treatments for rosacea in the pediatric population: A systematic review

2023· review· en· W4387957515 on OpenAlexaff
Ryan S.Q. Geng, Adrienn N. Bourkas, R. Gary Sibbald, Cathryn Sibbald

Bibliographic record

VenueJEADV Clinical Practice · 2023
Typereview
Languageen
FieldMedicine
TopicAcne and Rosacea Treatments and Effects
Canadian institutionsSickKids FoundationHospital for Sick ChildrenQueen's UniversityPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsRosaceaMedicineIsotretinoinDermatologyAzithromycinMetronidazoleTacrolimusPimecrolimusPopulationRegimenMEDLINECINAHLPediatricsSurgeryAntibioticsAcne

Abstract

fetched live from OpenAlex

Abstract The prevalence of rosacea in the pediatric population is rare and treatment recommendations specific to the pediatric population are lacking. Our objective is to perform a systematic review of the published literature to identify treatments used for rosacea in the pediatric population (age <18 years) and describe their efficacy. Literature searches were performed in four electronic databases: Medline, Embase, CINAHL and EBM Reviews. Data extraction included rosacea subtype, treatment regimen and clinical outcomes. Seventy‐six studies were included, reporting on a total of 389 patients. The most commonly reported treatments included erythromycin, metronidazole, azithromycin, tacrolimus/pimecrolimus and corticosteroids in topical formulations. Isotretinoin and physical treatment modalities were reported to be effective in treating severe recalcitrant cases of rosacea. In our review, we describe the most commonly reported therapies with demonstrated efficacy in treating pediatric rosacea. The evidence supports therapy with topical anti‐inflammatory options initially, with the addition of systemic antibiotics for cases refractory to topical monotherapy.

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)0.004
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.327
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.001
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 head0.275
GPT teacher head0.577
Teacher spread0.302 · 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 designSystematic review
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

Citations2
Published2023
Admission routes1
Has abstractyes

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