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Record W2270860213

Alopecia areata: Part 2: treatment.

2015· article· en· W2270860213 on OpenAlexaff
Frank Spano, Jeff Donovan

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicHair Growth and Disorders
Canadian institutionsWomen's College HospitalUniversity of Ottawa
Fundersnot available
KeywordsHair lossMedicineAlopecia areataDermatologyMinoxidilReferralRegimenDiseaseIntensive care medicineSurgeryInternal medicineFamily medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To provide family physicians with a background understanding of the therapeutic regimens and treatment outcomes for alopecia areata (AA), as well as to help identify those patients for whom dermatologist referral might be required. SOURCES OF INFORMATION: PubMed was searched for relevant articles regarding the treatment of AA. MAIN MESSAGE: Alopecia areata is a form of autoimmune hair loss affecting both children and adults. While there is no associated mortality with the disease, morbidity from the psychological effects of hair loss can be devastating. Upon identification of AA and the disease subtype, an appropriate therapeutic regimen can be instituted to help halt hair loss or possibly initiate hair regrowth. First-line treatment involves intralesional triamcinolone with topical steroids or minoxidil or both. Primary care physicians can safely prescribe and institute these treatments. More advanced or refractory cases might require oral immunosuppressants, topical diphenylcyclopropenone, or topical anthralin. Eyelash loss can be treated with prostaglandin analogues. Those with extensive loss might choose camouflaging options or a hair prosthesis. It is important to monitor for psychiatric disorders owing to the profound psychological effects of hair loss. CONCLUSION: Family physicians will encounter many patients experiencing hair loss. Recognition of AA and an understanding of the underlying disease process will allow an appropriate therapeutic regimen to be instituted. More advanced or refractory cases need to be identified, allowing for an appropriate dermatologist referral when necessary.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.652
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.091
GPT teacher head0.254
Teacher spread0.163 · 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 designNot applicable
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

Citations29
Published2015
Admission routes1
Has abstractyes

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