Systemic lupus international collaborating clinics renal activity/response exercise: Comparison of agreement in rating renal response
Bibliographic record
Abstract
OBJECTIVE: To assess the degree to which physicians agree with each other and with ratings obtained with 3 existing responder indices, in rating the response to treatment of lupus nephritis. METHODS: Lupus nephritis patient medical records from 125 pairs of visits (6 months apart) were used to create renal response scenarios. Seven nephrologists and 22 rheumatologists rated each scenario as demonstrating complete response, partial response, same, or worsening. The plurality (most frequent) rating of renal response by the physicians was compared with the calculated score from the renal component of the British Isles Lupus Assessment Group (BILAG) index (original and updated [2004] version) and of the Responder Index for Lupus Erythematosus (RIFLE). The degree of agreement among the physicians was assessed by calculating intraclass correlation coefficients (ICCs). The degree of agreement between the plurality physician rating and ratings obtained with the established response indices was assessed using the kappa statistic. RESULTS: The ICC among all physicians was 0.64 (0.62 for nephrologists and 0.67 for rheumatologists). The chance-adjusted measure of agreement (kappa coefficient) between the plurality physician rating and the calculated score obtained using established indexes was 0.50 (95% confidence interval [95% CI] 0.38-0.61) for the RIFLE, 0.14 (95% CI 0.03-0.25) for the original BILAG, and 0.23 (95% CI 0.21-0.44) for the BILAG 2004. CONCLUSION: These findings indicate that rheumatologists as a group and nephrologists as a group have equal agreement in their rating of renal response. There was moderate agreement between plurality physician ratings and ratings obtained using the renal component of the RIFLE. Ratings of response using an index based on the original BILAG did not have good agreement with the plurality physician rating.
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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 | 0.024 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".