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Record W4410055779 · doi:10.1016/j.jbspin.2025.105919

Diagnostic accuracy and trajectories of referrals for gout to rheumatology

2025· article· en· W4410055779 on OpenAlex
Timothy S.H. Kwok, Tripti Papneja, Vandana Ahluwalia, Gregory Choy, Raman Joshi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJoint Bone Spine · 2025
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsWilliam Osler Health SystemSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineGoutRheumatologyJoint boneInternal medicineMedical physicsPhysical therapy

Abstract

fetched live from OpenAlex

• Non-rheumatologists, especially those in acute care specialties, are accurate in diagnosing gout, suggesting care gaps stem from suboptimal treatment, rather than inaccurate diagnosis • Gout mimickers include conditions with mono/oligoarticular involvement and/or intermittent periods of disease flares • Male sex, serum urate ≥500 µmol/L, lower extremity monoarthritis and symptom duration ≤2 weeks may be useful at point of referral triage to ascertain a final gout diagnosis Objectives: To evaluate diagnostic accuracy and trajectories of gout referrals to rheumatology including factors associated with an accurate diagnosis. Methods: We performed a retrospective cohort study of referrals at 4 rheumatology clinics in Brampton, Canada from December 2019 to January 2023. We assessed gout diagnostic accuracy referenced to the rheumatologist’s “gold standard” diagnosis, describing alternative final diagnoses. Using multivariable logistic regression, we identified factors associated with an accurate gout diagnosis. Results: Among 4,315 patients, 216 were diagnosed with gout. Of 191 gout referrals (mean (SD) age 58.4 (15.4) years; 77.0% male), the diagnosis was unchanged in 159 (83.2%) patients with alternative diagnoses comprising osteoarthritis, autoimmune inflammatory arthritis and calcium pyrophosphate deposition disease. Referring physicians had moderate-to-high sensitivity (73.6%, 95% CI: 67.2–79.4), specificity (99.2%, 95% CI: 98.9–99.5), positive predictive value (83.2%, 95% CI: 77.2–88.2), negative predictive value (98.6%, 95% CI: 98.2–99.0) and inter-rater reliability (Cohen’s kappa: 0.77, 95% CI: 0.72–0.82). Accuracy was highest amongst internists and emergency room physicians. Male sex (OR 14.32, 95% CI: 4.44–46.17), serum urate ≥500 µmol/L (OR 9.10, 95% CI: 2.19–7.78), lower extremity monoarthritis (OR 5.08, 95% CI: 1.59–16.27) and symptom duration ≤2 weeks (OR 3.87, 95% CI 1.23–12.21) were predictive of a final gout diagnosis. Conclusions: Referring providers had reasonably high accuracy in diagnosing gout. Traditional risk factors were associated with concordance with the consultant rheumatologist. Suboptimal gout care likely does not stem at point-of-diagnosis and quality improvement efforts should be focused on mitigating treatment-associated care gaps.

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.

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.009
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)0.0000.000

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 head0.025
GPT teacher head0.318
Teacher spread0.292 · 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