128 The lupus severity index is a predictor of damage and death in lupus patients
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Bibliographic record
Abstract
<h3>Background</h3> Predictors of poor outcome in systemic lupus erythematosus (SLE) may lead to the identification of high-risk patients at the onset of disease (incident cases) and/or when we first assess them in our clinics (prevalent cases). We tested whether the Lupus Severity Index (LSI) can help characterize high versus low risk lupus patients. <h3>Methods</h3> Population: Patients from six lupus centers were recruited according to a standard data collection protocol. We characterized incident cases and prevalent cases as those with a diagnosis made within or after the previous 15 months. Data collected: Demographic, socioeconomic, disease specific and medication data were collected at baseline and annually. We collected: the American College of Rheumatology (ACR) and the Systemic Lupus International Collaborating Clinics (SLICC) classification criteria, the SLE Disease Activity Index (SLEDAI), the Systemic Lupus Activity Questionnaire (SLAQ), and the SLICC Damage Index (SDI). The LSI was derived from the ACR classification criteria and used as a predictor variable. Statistical analyses: Kruskal-Wallis test and Spearman correlations were used to see the association of LSI with categorical and continuous variables respectively. The baseline LSI was used to predict outcomes at follow-ups using logistic regressions and Spearman correlations for dichotomous and continuous variables respectively. <h3>Results</h3> We enrolled 639 lupus patients and 440, 324 and 168 were re-evaluated at 1, 2 and 3 years. Baseline characteristics (table 1) [median (IQR)] were: age=49.0 (36.8–58.5) years, female=92%, Caucasian=74%, disease duration=10.1 (2.7–20.6) years. We had 129 (20%) incident cases and 471 (74%) prevalent cases with missing information in 39 (6%). Twelve patients died during follow-up. Table 1 summarizes baseline associations between LSI and several characteristics for the incident and prevalent cases. We found that age, sex, ethnicity (Asian worse LSI), SLICC classification criteria, SLEDAI, prednisone use and daily dose were associated with LSI in both incident and prevalent groups while the SDI and the use of immunosuppressors drugs was associated with LSI only in the prevalent cases. In follow-up, baseline LSI predicted SDI in prevalent cases (p=0.02) with a trend in incident cases (p=0.07). LSI predicted death in the prevalent group. <h3>Conclusions</h3> The LSI is easy to derive from the ACR classification criteria and a useful measure of severity in lupus. The LSI is associated with baseline characteristics, some of them - like disease activity and prednisone dose - modifiable. LSI can predict adverse outcome such as damage or death over time. <h3>Funding Source(s):</h3> Lupus Canada.
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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 | 0.000 | 0.000 |
| 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 it