Early damage as measured by the SLICC/ACR damage index is a predictor of mortality in systemic lupus erythematosus
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The aim of this study was to determine whether early damage accrued in SLE as measured by the SLICC/ACR Damage Index predicts mortality in an inception cohort of lupus patients that have been followed prospectively in a single centre. SLE patients from the University of Toronto Lupus Clinic presenting within 1 y of their diagnosis prior to 1988 were included. This enabled all patients to be potentially followed for at least 10 y. Yearly SLICC/ACR Damage Index scores were determined for each patient. Early damage was defined as a score > or = 1 and no damage as a score of 0 at the initial assessment. Log rank test was used to compare the survival experience between those with and without damage, with all patients being censored at 10 y. Two-hundred and sixty-three patients were identified in this inception cohort who were followed for 10 y. One-hundred and ninety patients (72%) had a SLICC/ACR Damage Index score of 0 (no damage) while 73 patients (28%) had at least one SLICC/ACR Damage Index item scored (early damage). Twenty-five percent of lupus patients who exhibited damage at their first SLICC/ACR Damage Index assessment died within 10 y of their illness as compared to only 7.3% who had no early damage (log rank P-value = 0.0002). SLE patients who died within 10 y were more likely to have renal damage (P = 0.013), and a trend toward more cardiovascular disease (P = 0.056), compared to patients who were alive. Early damage as reflected by the initial SLICC/ACR Damage Index is associated with a higher rate of mortality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it