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Record W4229026528 · doi:10.1177/24755303221099292

Practice Patterns of Palmoplantar Pustulosis: Patient Demographics and Treatment Options

2022· article· en· W4229026528 on OpenAlexaffabout
Antoinette Chandler, Hannah Wood, Novin Nezamololama, Melinda Gooderham

Bibliographic record

VenueJournal of Psoriasis and Psoriatic Arthritis · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsProbity Medical ResearchQueen's UniversityTrent UniversitySKiN Health
Fundersnot available
KeywordsPalmoplantar pustulosisDemographicsMedicineDermatologyPsoriasis

Abstract

fetched live from OpenAlex

Background: Palmoplantar pustulosis (PPP) is a chronic skin condition characterized by sterile pustules on the palms and soles. This condition is more commonly reported among women and smokers causing considerable discomfort and interference with daily activities. Although there are various off-label treatment options available for PPP, there remains a demand to identify more effective and safer treatments. Objective: To review the patient demographics and treatment patterns of our PPP patient population. Methods: A retrospective chart review was performed at a dermatology office with two locations in Ontario, Canada. Results: We identified 71 adult PPP patients. A third of patients did not return for follow up after diagnosis. Among those who returned for follow-up, 20% were managed with topical therapy alone. Of our patients who took systemic treatment for PPP, apremilast, followed by ustekinumab and guselkumab, had the greatest retention of therapy. Conclusion: Targeting PDE4, IL-12/23 and IL-23 provided some benefit for our patients with PPP leading to greatest retention of therapy over time. Further investigation is required into the cause for high no-show rates and the search for effective and safe treatment options.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.944
Threshold uncertainty score0.744

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.013
GPT teacher head0.230
Teacher spread0.217 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations0
Published2022
Admission routes2
Has abstractyes

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