Are Immunosuppression Treatments for Glomerular Disease Associated With Increased Cardiovascular Risk?
Bibliographic record
Abstract
Background: The risk of cardiovascular disease (CVD) associated with immunosuppression (IS) treatments for glomerular disease is currently unknown. This was investigated in a population-level cohort of patients with glomerular diseases from British Columbia, Canada after adjusting for eGFR and proteinuria over time as measures of disease activity. Methods: All adults with IgA nephropathy, FSGS, membranous nephropathy or minimal change disease on a kidney biopsy between January 2000 & December 2012 were identified from a provincial registry, excluding those with ESKD prior to the biopsy date or no available follow-up. IS medications were categorized as antimetabolites, calcineurin inhibitors, corticosteroids or cyclophosphamide, and quantified using defined daily doses (DDD) or grams, as appropriate. The primary outcome was acute cardiovascular events and urgent revascularization after biopsy date, evaluated using extended Cox regression models to determine the association with time-varying IS exposure after adjusting for eGFR & proteinuria over time, type of glomerular disease & CV risk factors. Results: Amongst 1,912 patients with median follow-up 6.8 years, 212 (11.1%) patients developed a CV outcome event. In multivariable models, prednisone and antimetabolite exposures were not associated with CV risk. However, modest (150-300 DDD) & high (≥300 DDD) cumulative doses of calcineurin inhibitors were both associated with >2-fold higher risk of CV events, and each 10g of cumulative cyclophosphamide exposure was associated with a 1.5-fold higher risk of CV events (Table). Conclusions: Calcineurin inhibitors and cyclophosphamide used for the treatment of glomerular diseases are both associated with increased risk of CV events independent of treatment effects on disease activity. These results can inform the selection of therapies in clinical practice with less CVD morbidity.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".