Incidence, Risk Factors, Clinical Management, and Outcomes of Posttransplant Lymphoproliferative Disorder in Kidney Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: Posttransplant lymphoproliferative disorder (PTLD) is a severe complication after kidney transplantation. This study examined the incidence, risk factors, clinical management, and outcomes of PTLD in a cohort of kidney transplant recipients. DESIGN: This single-center cohort study included 1642 patients transplanted from January 1, 2000, to December 31, 2012, with follow-up until December 31, 2013. The incidence and risk factors for PTLD were examined using a Cox proportional hazards model. A Cox model was also used to assess the association of PTLD and graft outcomes. RESULTS: Sixteen recipients developed PTLD over follow-up. The incidence rate was 0.18 (95% confidence interval [CI]: 0.11-0.29) cases per 100 person-years. Four were from Epstein-Barr virus (EBV) mismatched (D+/R-) transplants and 12 from EBV-positive recipients (R+). Recipients with D+/R- matches were at a significantly higher risk of developing PTLD than R+ (hazard ratio [HR]: 7.52 [95% CI: 2.42-23.32]). Fifteen cases had immunosuppression reduced, 11 cases were supplemented with rituximab or ganciclovir, 6 cases required chemotherapy or radiation, and 6 cases had tumors excised. By the end of follow-up, 6 patients went into remission, 5 returned to chronic dialysis, and 5 patients died. Patients with PTLD were significantly more likely to have total graft failure (return to chronic dialysis, preemptive retransplant, or death with graft function) than patients without PTLD (HR: 3.41 [95% CI: 1.72-6.78). DISCUSSION: Epstein-Barr virus mismatch continues to be a strong risk factor for developing PTLD after kidney transplantation. Recipients with PTLD have a poor prognosis, as the optimal management remains to be elucidated.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".