Disease impact of rheumatoid arthritis in patients not treated with advanced therapies; survey findings from the National Rheumatoid Arthritis Society
Bibliographic record
Abstract
Abstract Objective The aim was to reveal the everyday impact of living with RA in people not treated with advanced therapies (i.e. biologic or targeted synthetic DMARDs). Methods People with RA, with disease duration >2 years, not currently treated with advanced therapies, completed an online survey promoted by the National Rheumatoid Arthritis Society. Items covered demographics, current treatment, RA flare frequency, the Rheumatoid Arthritis Impact of Disease (RAID) tool and questions reflecting work status and ability. Descriptive and multivariable regression analyses were performed. Results There were 612 responses from patients having a mean age of 59 years, 88% female, 37.7% with disease duration 2–5 years and 27.9% with disease duration 5–10 years. In the last year, 90% reported an RA flare, with more than six flares in 23%. A RAID patient acceptable state was recorded in 12.4%. Each of the seven domains was scored in the high range by >50% respondents; 74.3% scored sleep problems and 72% fatigue in the high range. A need to change working hours was reported by 70%. Multivariable analyses revealed that increasing difficulties with daily physical activities, reduced emotional and physical well-being in the past week were all significantly associated with pain, number of flares and ability to cope (P < 0.005). The RAID score was significantly predictive of the number of flares. Conclusion Patients not currently treated with advanced therapies experience profound difficulties in everyday living with RA, across a broad range of measures. We advocate that patient-reported measures be used to facilitate holistic care, addressing inflammation and other consequences of RA on everyday life.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".