Evaluating the risk of cardiovascular events associated with different immunosuppression treatments for glomerular diseases
Bibliographic record
Abstract
Patients with glomerular disease are at high risk of cardiovascular disease but the contribution of immunosuppression to this risk is unclear. In this retrospective cohort study of 1912 patients (comprised of 759 with IgA nephropathy, 540 with focal segmental glomerulosclerosis, 387 with membranous nephropathy and 226 with minimal change disease) from British Columbia, Canada, we evaluated the association between exposure to specific immunosuppressive medications and a composite outcome including coronary artery, cerebrovascular and peripheral arterial events. Survival models were adjusted for baseline cardiovascular risk factors, type of glomerular disease, estimated glomerular filtration rate (eGFR) and proteinuria over time. During a median follow-up of 6.8 years, 212 patients (11.1%) experienced the primary outcome. Corticosteroid exposure was not significantly associated with the primary outcome after adjusting for cardiovascular risk factors. In fully adjusted models, cumulative calcineurin inhibitor exposure at modest (150-300 defined daily doses [DDD]) and higher (300 or more DDD) doses were associated with a 2-fold higher risk of cardiovascular events (hazard ratio 2.98, 95% confidence interval 1.27-6.95) and (2.78, 1.32-5.84), respectively. A peak daily dose of antimetabolite (azathioprine, mycophenolate mofetil and mycophenolate sodium) of 0.5 or more DDD was associated with higher risk of cardiovascular events after adjustment for baseline risk factors and type of glomerular disease, but not after adjusting for time-varying eGFR and proteinuria (1.70, 0.91-3.20). Each 10 grams of cumulative cyclophosphamide exposure was associated with a 1.5-fold higher risk of cardiovascular events in a fully adjusted model (1.46, 1.22-1.75) Thus, our findings suggest that immunosuppressive therapies used in the treatment of glomerular disease may have different cardiovascular risk profiles, which should be considered when deciding on immunosuppression for individual patients and as a safety endpoint in future clinical trials.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".