Costs Associated With Severe and Nonsevere Systemic Lupus Erythematosus in Canada
Bibliographic record
Abstract
OBJECTIVE: To evaluate the annual direct medical cost of systemic lupus erythematosus (SLE) in Canada by disease severity and to estimate the incremental cost associated with disease severity and flares. METHODS: Medical charts of consecutive patients seen in 3 SLE-specialized treatment centers between July 2007 and June 2008 were retrospectively assessed for disease severity at baseline and for disease activity and health care resource utilization over the following 2 years (±6 months). Annual cost was stratified by disease severity at baseline. Two-year cost was compared for patients with and without flares over 2 years. Multiple linear regression was used to determine the associations between annual cost and SLE severity, and between 2-year cost and the number and type of flare (mild/moderate versus severe). RESULTS: A total of 109 active SLE patients (94% women, mean age 41.4 years, mean disease duration 11.3 years, 56 patients with severe disease) were studied. The average annual direct medical cost was $10,608 Canadian (2010 dollars) and was higher for patients with severe disease, $15,048 versus $5,917 (P < 0.001). The 2-year direct cost for patients with at least 1 flare was $22,633 versus $11,113 (P = 0.028) for patients without flares. The mean incremental annual cost was $7,007 (95% confidence interval [95% CI] $3,487, $13,048) for an SLE patient with severe disease, and the 2-year mean incremental cost was $5,848 (95% CI $2,919, $8,777) for each additional severe flare. CONCLUSION: The direct health care cost of SLE patients in Canada is influenced by disease severity and the type and frequency of flares.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".