Thresholds for the 28-joint disease activity score (DAS28) using C-reactive protein are lower compared to DAS28 using erythrocyte sedimentation rate in early rheumatoid arthritis.
Bibliographic record
Abstract
OBJECTIVES: The 28-Joint Disease Activity Score (DAS28) using C-reactive protein (CRP) and DAS28 using erythrocyte sedimentation rate (DAS28-ESR) may not be interchangeable. We sought to compare and estimate optimal thresholds for the DA28-CRP for use in early rheumatoid arthritis (ERA). METHODS: Patients from the Canadian Early Arthritis Cohort with baseline and 12 months' data for both DAS28-ESR and DAS28-CRP were examined for correlations and differences between DAS28-CRP and DAS28-ESR across their range of values. Receiver operating characteristic analysis identified thresholds for DAS28-CRP that best corresponded to established thresholds for the DAS28-ESR using the total sample, then stratified by age and sex. Agreement between DAS28-CRP and DAS28-ESR thresholds was assessed with the kappa statistic. RESULTS: The sample included 995 patients with mean (SD) age of 53.7 (14.5) years, 5.8 (2.9) months of symptom duration and 74% were female. DAS28-CRP and DAS28-ESR scores were highly correlated (r= 0.92, p<0.0001), however DAS28-CRP values were consistently lower than DAS28-ESR values. Calculated thresholds for DAS28-CRP were lower with 2.5 for remission, 2.9 for low disease activity, and 4.6 for high disease activity but showed moderate agreement with the DAS28-ESR thresholds (kappa=0.70). CONCLUSIONS: In this large sample of ERA patients, newly estimated thresholds for DAS28-CRP were consistently lower than DAS28-ESR thresholds across the spectrum of disease activity. This may have important clinical implications if inflammatory markers are used interchangeably. Additional external validation of our findings is needed.
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".