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Record W4389139871 · doi:10.1177/2050313x231213135

Rapid hair regrowth in an alopecia universalis patient with deucravacitinib: A case report

2023· article· en· W4389139871 on OpenAlexaffabout
Sarah Oliel, Sarah Moussa, Monica Stanciu, Elena Netchiporouk

Bibliographic record

VenueSAGE Open Medical Case Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicHair Growth and Disorders
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsMedicineAlopecia areataAlopecia universalisDermatologyScalpHair lossMinoxidil

Abstract

fetched live from OpenAlex

Alopecia universalis is a severe, difficult to treat variant of alopecia areata that results in loss of hair on the scalp, eyebrows, eyelashes, and extremities. Deucravacitinib, a selective TYK2 inhibitor, has been recently approved in Canada, opening the door to novel uses of the drug. We present the case of a patient known for psoriasis who developed alopecia universalis resistant to many interventions (topical minoxidil and topical, intralesional, and systemic corticosteroids). We report the first case of successful rapid hair regrowth after starting deucravacitinib, which should prompt further inquiry into the use of TYK2 inhibitors in the management of alopecia areata.

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)0.002
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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.304
Teacher spread0.281 · 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

Citations9
Published2023
Admission routes2
Has abstractyes

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