Immunosuppressant Medication Use in Patients with Kidney Allograft Failure: A Prospective Multicenter Canadian Cohort Study
Bibliographic record
Abstract
Significance Statement Current recommendations suggest discontinuation of immunosuppressants 1 year after kidney transplant failure. In this first prospective multicenter study of 269 patients with kidney transplant failure in 16 Canadian centers, most patients were prescribed immunosuppressants for longer than 2 years. Continued use of immunosuppressants was not associated with an increased risk of death or hospitalized infection. However, the continued use of immunosuppressants did not prevent rejection of the failed allograft or an increase in anti-HLA antibodies, possibly due to inadequate drug exposure. The findings challenge current recommendations and highlight the need for a controlled trial of immunosuppressant use in patients with transplant failure. Background Patients with kidney transplant failure have a high risk of hospitalization and death due to infection. The optimal use of immunosuppressants after transplant failure remains uncertain and clinical practice varies widely. Methods This prospective cohort study enrolled patients within 21 days of starting dialysis after transplant failure in 16 Canadian centers. Immunosuppressant medication use, death, hospitalized infection, rejection of the failed allograft, and anti-HLA panel reactive antibodies were determined at 1, 3, 6, and 12 months and and then twice yearly until death, repeat transplantation, or loss to follow-up. Results The 269 study patients were followed for a median of 558 days. There were 33 deaths, 143 patients hospitalized for infection, and 21 rejections. Most patients (65%) continued immunosuppressants, 20% continued prednisone only, and 15% discontinued all immunosuppressants. In multivariable models, patients who continued immunosuppressants had a lower risk of death (hazard ratio [HR], 0.40; 95% confidence interval [CI], 0.17 to 0.93) and were not at increased risk of hospitalized infection (HR, 1.81; 95% CI, 0.82 to 4.0) compared with patients who discontinued all immunosuppressants or continued prednisone only. The mean class I and class II panel reactive antibodies increased from 11% to 27% and from 25% to 47%, respectively, but did not differ by immunosuppressant use. Continuation of immunosuppressants was not protective of rejection of the failed allograft (HR, 0.81; 95% CI, 0.22 to 2.94). Conclusions Prolonged use of immunosuppressants >1 year after transplant failure was not associated with a higher risk of death or hospitalized infection but was insufficient to prevent higher anti-HLA antibodies or rejection of the failed allograft.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".