Factors affecting the discrepancy between patient and physician global assessment in early rheumatoid arthritis: The Ontario Best Practices Research Initiative
Bibliographic record
Abstract
OBJECTIVES: We aimed to assess the prevalence and factors affecting the discrepancy between patient global assessment (PtGA) and physician global assessment of disease activity (PhGA) in patients with early rheumatoid arthritis (RA) at enrolment and after one year. METHODS: Patients from the Ontario Best Practices Research Initiative (OBRI) were included. The discrepancy between PtGA and PhGA was calculated by simple subtraction (PtGA-PhGA). An absolute value ≥30 was considered discordant. Linear regression analysis was used to assess factors affecting PtGA, PhGA, and PtGA-PhGA discrepancy at enrolment and 1-year follow-up. RESULTS: A total of 531 patients with mean disease duration of 0.3 years were analysed. The discordance prevalence was 22.4% at enrolment and 20.3% after one year. PtGA was higher in the majority of the discordant cases. Multivariable regression analysis showed higher PtGA was significantly associated with higher pain score, tender joint counts (TJC28), ESR, and fatigue at enrolment and 1-year follow-up while PtGA was associated with higher swollen joint counts (SJC28) only at enrolment. Similar associations were found for PhGA, with the exception of fatigue, which was not a significant factor at one year. Multivariable analysis showed that higher discrepancy between PtGA-PhGA was associated with lower SJC28 and higher pain score at enrolment and lower SJC28 and higher pain and fatigue score at 1-year follow-up. CONCLUSIONS: Significant PtGA-PhGA discrepancy was found in approximately one-quarter of early RA patients. In the majority of these patients, PtGA was higher than PhGA. The main predictors of PtGA and PhGA remained the same after one year.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".