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Record W1501767356 · doi:10.1002/art.37939

Brief Report: Reduced Joint Counts Misclassify Patients With Oligoarticular Psoriatic Arthritis and Miss Significant Numbers of Patients With Active Disease

2013· article· en· W1501767356 on OpenAlexaff
Laura C. Coates, Oliver FitzGerald, Dafna D. Gladman, Neil McHugh, Philip J. Mease, Vibeke Strand, Philip Helliwell

Bibliographic record

VenueArthritis & Rheumatism · 2013
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsToronto Western HospitalUniversity of Toronto
FundersNational Institute for Health and Care Research
KeywordsMedicinePsoriatic arthritisOligoarthritisReceiver operating characteristicRheumatoid arthritisArthritisPsoriasisInternal medicineCohortSurgeryJoint (building)DermatologyPolyarthritis

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate joint counts in patients with oligoarticular psoriatic arthritis (PsA) for their correlation with treatment decisions and to determine the proportion of patients in whom active disease was missed using reduced joint counts. METHODS: The international Group for Research and Assessment of Psoriasis and Psoriatic Arthritis Composite Exercise cohort was used for this study. Oligoarthritis was defined as <5 tender and/or swollen joints. At baseline, a tender joint count (TJC) using 68 joints and a swollen joint count (SJC) using 66 joints (66/68-joint counts) were assessed. Reduced joint counts designed for use in rheumatoid arthritis (RA), including 28- and 44-joint counts, were analyzed. In addition, the following proposed joint counts for PsA were tested: the PsA-44 (which includes elbows, wrists, metacarpophalangeal joints, finger proximal interphalangeal [PIP] joints, distal interphalangeal joints, knees, and metatarsophalangeal joints) and the PsA-56 (which includes the same joints as those assessed for the PsA-44 plus ankles and toe PIP joints). Receiver operating characteristic (ROC) curve analysis was used to assess whether joint counts predict treatment changes. The proportion of patients in whom active disease was missed using reduced joint counts designed for RA was also assessed. RESULTS: Among 503 patients recruited to the study, 266 (53%) had oligoarthritis. ROC curve analysis revealed that no TJC or active joint count (AJC), even a 66/68-joint count, predicted treatment change (for the TJC, area under the curve [AUC] 0.57, P = 0.125; for the AJC, AUC 0.56, P = 0.159). Use of the SJC in 66 joints did predict treatment change (AUC 0.62, P = 0.006), as did the SJC using the PsA-44 and the PsA-56 (P < 0.03). Neither of the reduced joint counts designed for RA predicted treatment change. A 28-joint count designed for RA missed 21% of patients with tender joints (n = 29) and 27% of patients with swollen joints (n = 23). The PsA-44 and PsA-56 joint counts missed tender joints in 25 patients and 13 patients, respectively, and missed swollen joints in 11 patients and 2 patients, respectively. CONCLUSION: Patients with oligoarticular PsA cannot be accurately assessed for active disease using reduced joint counts designed for RA. Full 66/68-joint counts should be performed to assess patients with PsA.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.005
GPT teacher head0.195
Teacher spread0.190 · 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.

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

Citations74
Published2013
Admission routes1
Has abstractyes

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