C-reactive Protein Versus Erythrocyte Sedimentation Rate in Estimating the 28-joint Disease Activity Score
Bibliographic record
Abstract
The management of rheumatoid arthritis (RA) has changed radically over the last 15 years, with the introduction of new drugs and treatment strategies and with the emergence of new concepts of disease severity, treatment targets, and means of evaluating treatment effects. In particular, the necessity to evaluate disease activity using an objective and accurate instrument has been demonstrated. In clinical practice, the 28-joint Disease Activity Score (DAS28) has gained widespread use in the monitoring of disease activity of patients with RA treated with synthetic and biological disease modifying anti-rheumatic drugs1. There is, however, no consensus on the optimal DAS version to be used. DAS28-CRP (C-reactive protein) was developed as a modification of DAS28-ESR (erythrocyte sedimentation rate), which had also previously been developed as a modification of the original DAS2. Using CRP for calculation of the DAS28 is an attractive alternative to ESR for several reasons. First, CRP is very sensitive to short-term changes in inflammation3. Second, CRP is more accurate as an indicator of inflammation than ESR, the latter being influenced by a number of unrelated factors, such as age, sex, anemia, fibrinogen levels, hypergammaglobulinemia, and rheumatoid factor3. Third, CRP measurements are routinely used in clinical practice, and measurements can be standardized in a central laboratory for … Address correspondence to Dr. Gaujoux-Viala; E-mail: cecilegaujouxviala{at}yahoo.fr
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".