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Record W1964867500 · doi:10.3899/jrheum.130163

Dactylitis in Psoriatic Arthritis: Prevalence and Response to Therapy in the Biologic Era

2013· article· en· W1964867500 on OpenAlexafffundvenue
Dafna D. Gladman, Olga Ziouzina, Arane Thavaneswaran, Vinod Chandran

Bibliographic record

VenueThe Journal of Rheumatology · 2013
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity of CalgaryUniversity Health Network
FundersCanadian Institutes of Health ResearchJanssen CanadaKrembil Foundation
KeywordsDactylitisMedicinePsoriatic arthritisInternal medicineMultivariate analysisMethotrexateDiseaseSurgeryEnthesitis

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the prevalence of acute dactylitis in patients with psoriatic arthritis (PsA) and to compare the response of new acute dactylitis to treatment with traditional disease-modifying antirheumatic drug (DMARD) and anti-tumor necrosis factor-α (anti-TNF) agents in a longitudinal PsA cohort. METHODS: Patients with PsA followed at 6 months according to a standard protocol from January 2000 to January 2010 were included in our study. Acute dactylitis was defined as the presence of painful swelling of an entire digit. Response was defined as either complete resolution of dactylitis or > 50% improvement in the number of dactylitic digits. A multivariate generalized estimating equations analysis using a negative binomial model to account for repeated measures was conducted to determine predictors for response to treatment of dactylitis. RESULTS: Of the 752 patients seen in the clinic during this period, 294 had dactylitis in at least 1 visit, giving a prevalence of 39%. Patients with acute dactylitis and data available for response at 6 and 12 months (n = 252; 34% women, mean age 47 yrs, PsA duration 11 yrs) were included in the study on predictors of response to treatment. Multivariate analysis showed that treatment with anti-TNF agents was a significant predictor of improvement in dactylitis at 12 months (relative risk 0.528, 95% CI 0.283-0.985, p = 0.045). CONCLUSION: The prevalence of dactylitis on at least 1 visit was 39%. Treatment was associated with improvement of dactylitis. Patients treated with biologics had better response to treatment compared with those treated with nonbiologic DMARD alone.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.191

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.015
GPT teacher head0.273
Teacher spread0.258 · 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 designObservational
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

Citations103
Published2013
Admission routes3
Has abstractyes

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