Summarizing disease features over time: I. Adjusted mean SLEDAI derivation and application to an index of disease activity in lupus.
Bibliographic record
Abstract
OBJECTIVE: To develop a measurement of lupus disease activity over time. METHODS: We studied patients from the University of Toronto Lupus Clinic with "regular" followup, defined as having been in the clinic for at least 3 visits and never having been away from the clinic for a period exceeding 18 consecutive months. For each visit, disease activity was evaluated with the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K). The common approach to summarize over multiple visits by calculating a mean ignores the presence of varying time intervals between visits. We used the adjusted mean SLEDAI-2K (AMS), determined by the calculation of the area under the curve of SLEDAI-2K over time by adding the area of each of the blocks of visit interval and then dividing by the length of time for the whole period. The resulting AMS has the same units as the original SLEDAI-2K. A time-dependent covariate survival analysis was done to test which of AMS, SLEDAI-2K at presentation, sex, and age at diagnosis is the best predictor of mortality. RESULTS: A total of 575 patients with regular followup were included. Only AMS and age at diagnosis were significant predictors. Odds ratio (OR) and 95% confidence intervals (CI) for AMS: OR 1.15 (CI 1.09, 1.20), p = 0.0001; age at diagnosis: OR 1.05 (CI 1.03, 1.06), p = 0.0001. CONCLUSION: AMS represents an average disease activity measure over time and is strongly associated with mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".