SLEDAI-2K 10 days versus SLEDAI-2K 30 days in a longitudinal evaluation
Bibliographic record
Abstract
The objective of the study was to evaluate SLEDAI-2K 30 days over time and to compare with the original SLEDAI-2K 10 days. Forty-one patients seen at The University of Toronto Lupus Clinic were followed at monthly intervals for 12 months. The SLEDAI-2K score was completed twice, once for a 10-day window and again for a 30-day window using the same definitions for the descriptors. Four hundred and nineteen patient-visits in 41 patients were recorded for both SLEDAI-2K for a 10-day and a 30-day window. One hundred and fifty-one patient-visits had a SLEDAI-2K activity score of 0 and 268 patient-visits had varying levels of disease activity in the range 1-15. In all but one patient-visit there was an agreement between the SLEDAI-2K 10 days and 30 days. SLEDAI-2K 30 days scores were concordant with SLEDAI-2K 10 days scores, both in patients in remission and in patients with a spectrum of disease activity levels followed monthly over 1 year. SLEDAI-2K 30 days was validated against SLEDAI-2K 10 days in a longitudinal evaluation over 1 year. We recommend the use of SLEDAI-2K 30 days in clinical studies and clinical trials.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".