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Record W144398792

Short-contact clobetasol propionate shampoo 0.05% improves quality of life in patients with scalp psoriasis.

2009· article· en· W144398792 on OpenAlexaff
Jerry Tan, Richard Thomas, Béatrice Wang, David Gratton, Ronald Vender, Nabil Kerrouche, Hervé Villemagne

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsWindsor Clinical Research
Fundersnot available
KeywordsClobetasol propionateMedicineShampooPsoriasisDermatologyScalpQuality of life (healthcare)Dermatology Life Quality IndexPathology
DOInot available

Abstract

fetched live from OpenAlex

Scalp psoriasis has a considerable impact on the quality of life (QOL) of patients, and most patients are dissatisfied with available treatments. Clobetasol propionate shampoo 0.05% has been shown to be effective and safe for moderate to severe scalp psoriasis. We evaluated the effect of clobetasol propionate shampoo on QOL and the degree of participant satisfaction with the product. Participants received once-daily treatment for up to 4 weeks. Their QOL and degree of satisfaction were evaluated by questionnaires. The mean (standard deviation) Dermatology Life Quality Index (DLQI) score decreased significantly from 7.0 (4.9) at baseline to 3.2 (3.2) at week 4 (P<.001). Participants who considered the disease as having a small effect or no effect on their QOL increased from 45.6% at baseline to 81.7% at week 4. Most participants were satisfied with the cosmetic acceptability and the efficacy and safety aspects of the product, considered it better than prior treatments, and would use it again in the future. Therefore, we conclude that treatment with clobetasol propionate shampoo improved the QOL of participants and resulted in high satisfaction.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.020
GPT teacher head0.225
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations14
Published2009
Admission routes1
Has abstractyes

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