Time to Treatment for New Patients with Rheumatoid Arthritis in a Major Metropolitan City
Bibliographic record
Abstract
OBJECTIVE: To determine the proportion of patients with rheumatoid arthritis (RA) seen by rheumatologists and treated with disease-modifying antirheumatic drugs (DMARD) within 3 months of symptom onset, to determine where treatment delays occur, and to identify contributing factors. METHODS: A retrospective cohort study in which adult patients with RA, diagnosed between January 1, 2003, and May 31, 2006, were recruited from rheumatologists' offices to participate in a telephone survey and chart review. The percentage treated with DMARD within 3 months of symptom onset was determined, along with median times for delay. Factors contributing to the delay were explored using multivariable logistic regression. RESULTS: Our study included 204 patients. Within 3 months of symptoms, 22.6% (95% CI 16.8%, 28.3%) received DMARD and within 6 months, 47.6% (95% CI 40.7%, 54.4%). The median time from symptom onset to DMARD was 6.4 months [interquartile range (IQR) 3.3, 12.0] with a median time from RA diagnosis by a rheumatologist to DMARD of 0.0 months (IQR 0.0, 1.0). Higher baseline swollen joint counts resulted in earlier treatment. Age, sex, education, comorbidity, rheumatologist practice type, and years since the physician's graduation did not affect time to treatment. CONCLUSION: Fewer than 25% of patients referred to rheumatologists were treated within 3 months of symptom onset. Identification of inflammatory arthritis and referral to rheumatologists are the key factors in timely care, because once patients are seen there is no delay to treatment. Future resources should be focused on development and evaluation of interventions to facilitate rapid triage, referral, and assessment by a rheumatologist.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".