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Record W2063350905 · doi:10.1007/s10227-001-0050-9

The Use of Diphenylcyclopropenone in the Treatment of Recalcitrant Warts

2002· article· en· W2063350905 on OpenAlexaff
Jennifer A. Upitis, Alfons Krol

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2002
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineDermatologySurgeryLocal ReactionAdverse effectInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The treatment of recalcitrant palmoplantar and periungual warts using topical immunotherapy with diphenylcyclopropenone (DPC) was reviewed retrospectively over a seven-year period. METHODS: Two hundred eleven patients were sensitized during this time. The patients consisted of 90 males and 121 females and were between 5 and 78 years old. Twenty-three patients were lost to followup. Of the remaining, 4 were undergoing treatment at the time of evaluation, 1 patient failed sensitization, and 1 patient became pregnant. Four discontinued because of side effects, 3 because of financial reasons, and 18 patients discontinued treatment prior to completing the minimum required applications (defined as 6), producing a dropout rate of 12% (25/211). Three patients had additional treatment during the course of DPC and were not included in the study. The remaining 154 patients were classified as nonresponders or responders. RESULTS: The responders consisted of 135 individuals (87.7%) that had complete clearance of warts. Reported adverse effects were local and included with pruritus (15.6%), with blistering (7.1%), and with eczematous reactions (14.2%). The majority of the patients tolerated the treatment very well. One patient developed local impetigo. Patients had an average of 5 treatments over a 6-month period. CONCLUSIONS: Topical immunotherapy using DPC is an effective treatment option for recalcitrant warts. It should be considered as first-line treatment for warts based on its high response rate, absence of scarring, and painless application.

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)0.001
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 score0.920
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.192
GPT teacher head0.335
Teacher spread0.144 · 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

Citations38
Published2002
Admission routes1
Has abstractyes

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