The Impact of Achieving Low Disease Activity in the First Year of Disease on Future Disability and Damage in Early Rheumatoid Arthritis
Bibliographic record
Abstract
Aim: To describe the predictive validity of reaching low disease activity (LDA) at 1 year on future disability and joint damage in patients with early rheumatoid arthritis (ERA). \n\nMethods: First a systematic literature review of prognostic studies assessing the association between disease activity and functional or radiographic outcomes in ERA was performed. Then data from the Study Of New-Onset RA (SONORA) were used to evaluate the impact of year-one LDA on 3-year disability and 2-year radiographic progression using multivariate regression analyses. \n\nResults: Our review demonstrated evidence for relationship between baseline disease activity and future disability and join damage. However evidence for the impact of early treatment response on long-term outcomes in ERA is sparse. Analysis of 984 patients showed year one LDA predicts lower HAQ (p<.0001) and less damage (p=0.04) in future. \n\nConclusion: Reaching LDA early is associated with better long-term functional and radiographic outcomes in patients with early RA.
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.
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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".