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Record W4402217395 · doi:10.1097/gox.0000000000006117

Effective Treatment of an Aggressive Chest Wall Keloid in a Woman Using Deprodone Propionate Plaster without Surgery, Radiotherapy, or Injection

2024· article· en· W4402217395 on OpenAlexaff
Rei Ogawa, Whitney L. Quong

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2024
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsKeloidMedicineSurgeryScarsPresentation (obstetrics)DermatologyRadiation therapyHypertrophic scarsClobetasol propionateCorticosteroid

Abstract

fetched live from OpenAlex

Treatment with steroid tape is the standard of care for keloid and hypertrophic scars in Japan. In this article, we present a woman with an aggressive and progressive keloid of the anterior chest wall. At the time of presentation, the keloid had been present for 40 years, and was continuing to worsen and expand. Initially, it was believed that a multidisciplinary approach, including surgery and radiation, would be necessary to achieve an acceptable scar outcome. However, we successfully treated her keloid using only steroid tape (deprodone propionate plaster), and no other treatment modality. The case therefore supports the effectiveness of deprodone propionate plaster, and emphasizes its potential for wider future use. With the paucity of experience reported in the literature on steroid tape for scars, more reports are useful to inform plastic surgeons and dermatologists worldwide about this therapeutic option.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.358
Teacher spread0.305 · 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 designCase report
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

Citations3
Published2024
Admission routes1
Has abstractyes

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