Practice Variations in the Diagnosis, Monitoring, and Treatment of Systemic Lupus Erythematosus in Canada
Bibliographic record
Abstract
OBJECTIVE: To evaluate the diagnosis, monitoring, and treatment of systemic lupus erythematosus (SLE) in Canada. METHODS: A 63-question electronic survey was developed with the Canadian Rheumatology Association and others. Descriptive analyses of responses were performed. RESULTS: Survey respondents (n = 175) reported varying practices in the diagnosis, monitoring, and treatment of SLE. Performance of laboratory investigations for diagnosis and monitoring varied, with 78% of responders performing them at least every 6 months. Validated measures of SLE disease activity and damage were not commonly used. Most common first-line agents besides steroids for induction therapy for class III or IV lupus nephritis included intravenous cyclophosphamide and mycophenolate mofetil. Antimalarial use was common, with 96% of respondents using these in active skin disease. Over 60% of respondents indicated that 80-100% of their patients were taking antimalarials, while another 25% indicated they used these drugs in up to 80% of their patients. There were 71% of responders who reported completing frequent (6-12 mos) ophthalmology screening in patients taking antimalarials. Biologics were infrequently used. Responders were more likely to stop azathioprine and chloroquine than hydroxychloroquine in pregnant patients with SLE. Other aspects of routine care including vaccination and cardiovascular risk management varied considerably. The majority (80%) agreed that a dedicated multidisciplinary care team would improve SLE care. CONCLUSION: Considerable practice variation in SLE management was noted. This may help inform future recommendations for the diagnosis, monitoring, and treatment of SLE in Canada.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".