Evolving Strategies in Lupus Care: Is Earlier Sustained Remission Now Within Reach?
Bibliographic record
Abstract
Systemic lupus erythematosus (SLE) is a complex autoimmune disease that remains challenging to diagnose and treat. In this interview, rheumatologist and clinical epidemiologist Zahi Touma, Associate Professor of Medicine, Clinician Scientist, University of Toronto, Canada, highlights the need for a shift from traditional symptom suppression to early and proactive treat-to-target approaches. Despite the availability of more advanced SLE-targeted therapies offering the potential to reduce glucocorticoid (GC) dependency and improve disease control, many patients continue to rely on long-term GC use, placing them at increased risk of irreversible organ damage, poor health-related quality of life, and even mortality. Touma emphasises the importance of proactive, individualised care to achieve sustained remission and improve long-term outcomes for a greater proportion of patients.
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.
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 | 0.039 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.014 | 0.021 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.016 | 0.028 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".