Original article doi:10.1093/rheumatology/kes231 Early consultation with a rheumatologist for RA: does it reduce subsequent use of orthopaedic surgery?
Bibliographic record
Abstract
Objective. Optimal care in RA includes early use of DMARDs to prevent joint damage and hopefully decrease the need for costly surgical interventions. Our objective was to determine whether a reduced rate of orthopaedic surgery was evident for persons with RA who saw a rheumatologist early in the disease course. Methods. We studied persons who had a diagnosis of RA based on billing code data in the province of Quebec in 1995, and for whom the initial date of RA diagnosis by a non-rheumatologist could be estab-lished before the confirmatory diagnosis by the rheumatologist. We followed these patients until 2007. Patients were classified as early consulters or late consulters depending on whether they were seen by a rheumatologist within or beyond 3 months of being diagnosed with RA by their referring physician. The outcome, orthopaedic surgery, was defined using International Classification of Diseases (ICD) pro-cedure codes ICD9 and ICD10. Multivariate Cox regression with time-dependent covariates estimated the effect of early consultation on the time to orthopaedic surgery. Results. Our cohort consisted of 1051 persons; mean age at diagnosis was 55.7 years, 68.2 % were female and 50.7 % were early consulters. Among all patients, 20.5 % (215) had an orthopaedic surgery
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.487 | 0.152 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".