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Record W2093145231 · doi:10.1517/14656566.2014.931373

Pityriasis versicolor: an update on pharmacological treatment options

2014· review· en· W2093145231 on OpenAlexaff
Aditya K. Gupta, Danika C.A. Lyons

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2014
Typereview
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsMediprobe Research (Canada)University of Toronto
Fundersnot available
KeywordsMedicinePityriasisDosingDermatologyTinea versicolorAntifungalExpert opinionMalasseziaAdverse effectIntensive care medicineClinical trialPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Pityriasis versicolor (PV) is a superficial fungal infection caused by Malassezia species; a yeast that naturally colonizes on the skins surface. High efficacy rates are generally obtained with both topical and systemic treatments. However, recurrence rates following successful treatment remain high and there are no dosage guidelines available for administration of systemic antifungal agents that carry risks of adverse events. AREAS COVERED: This review focused on providing an overview of existing treatments for PV and an introduction to new treatments. A literature search was conducted using the search strategy, pityriasis versicolor OR tinea versicolor. Over the past decade, few new treatments have been introduced, but the efficacy and the dosing regimens of existing treatments have been systematically reviewed. The results of these reviews are discussed. EXPERT OPINION: Existing topical and systemic agents are both effective treatments against PV. Previous dosage recommendations for systemic agents have been modified based on recent evidence elucidated in systematic reviews. However, the absence of standardized collection and reporting practices in clinical trials precludes any conclusions to be drawn regarding the efficacy and safety of topical and systemic agents in comparison or in concert with each other.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.162
GPT teacher head0.501
Teacher spread0.339 · 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; both teacher heads agree on what is shown here.

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

Citations44
Published2014
Admission routes1
Has abstractyes

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