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Record W2126057417 · doi:10.2310/7750.2009.00027

Psoriatic Nail Disease: Quality of Life and Treatment

2009· review· en· W2126057417 on OpenAlexaff
Aditya K. Gupta, Elizabeth A. Cooper

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2009
Typereview
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsHealth Sciences CentreUniversity of TorontoMediprobe Research (Canada)Sunnybrook Health Science Centre
FundersAbbott Laboratories
KeywordsMedicinePsoriasisEtanerceptPsoriatic arthritisDermatologyInfliximabOnycholysisAdalimumabNail diseaseNail (fastener)EfalizumabClinical trialDiseasePlaque psoriasisInternal medicineRheumatoid arthritis

Abstract

fetched live from OpenAlex

Nail psoriasis is common among patients with plaque psoriasis or psoriatic arthritis and has a detrimental effect on quality of life. However, there are currently no standardized therapeutic regimens for nail psoriasis. Traditional treatments for nail psoriasis, which include topical, intralesional, and oral therapies, may be time-consuming, painful, or unsafe when administered long term. Biologic therapies have demonstrated efficacy for plaque psoriasis and psoriatic arthritis; these therapies may be particularly promising for the treatment of nail psoriasis as both groups of patients have an elevated incidence of nail dystrophy. The biologic therapies adalimumab, alefacept, efalizumab, etanercept, and infliximab have demonstrated clinically important nail psoriasis improvements using the Nail Psoriasis Severity Index, a helpful tool that, upon validation, will allow comparison across treatments and trials. Large-scale, long-term trials using standardized outcome measures are needed to further evaluate biologic therapies for the treatment of nail psoriasis.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.084
GPT teacher head0.330
Teacher spread0.246 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations32
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cutaneous Medicine and SurgerySame topicPsoriasis: Treatment and PathogenesisFrench-language works237,207