Incidence of PTLD in Pediatric Renal Transplant Recipients Receiving Basiliximab, Calcineurin Inhibitor, Sirolimus and Steroids
Bibliographic record
Abstract
Pediatric renal transplant recipients were enrolled in a multicenter, randomized, double-blind trial of steroid withdrawal. Subjects received basiliximab, calcineurin inhibitor, sirolimus and steroids. Of 274 subjects enrolled, 19 (6.9%) subjects developed posttransplant lymphoproliferative disorder (PTLD). The relative hazard (RH) for PTLD was 5.3-fold higher in children aged < or =5 versus those >12 years (p = 0.0017). EBV seronegative subjects had a 4.7-fold higher RH compared to EBV positive subjects (p = 0.02). Among EBV donor+/recipient- (D+/R-) subjects, the RH increased by 6.1-fold (p = 0.0001). In a multivariate model, risk factors included recipient age < or =5 years (RH 3.2, 95% CI: 1.1-9.6, p = 0.034) and EBV D+/R- status (RH 7.7, 95% CI: 1.6-35.9, p = 0.010). Of 19 patients with PTLD, 17 are alive with functioning grafts and 2 lost their grafts, 1 of whom subsequently died of recurrent PTLD. This 'robust' immunosuppression protocol was associated with low rejection rates but an unacceptably high incidence of PTLD. The combination of basiliximab, calcineurin inhibitor, sirolimus and steroids resulted in over-immunosuppression in a high-risk pediatric population and we do not recommend its use. Future studies must include routine viral monitoring to permit early identification of viral activity and a protocol driven reduction of immunosuppression aimed at avoiding complications.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".