Complications of paediatric kidney transplantation: a paediatrician’s review
Bibliographic record
Abstract
Kidney transplantation is the preferred treatment for children with end-stage kidney disease, offering notable improvements in long-term survival and overall quality of life. Nonetheless, paediatric transplant recipients are susceptible to a spectrum of complications that compromise allograft function and overall health. This review highlights key post-transplant complications to aid general paediatricians in recognising and managing these challenges in concert with nephrologists. Early post-transplant complications include surgical issues and electrolyte abnormalities. Infectious complications are most frequent during the first year post-transplant and include viruses such as cytomegalovirus, Epstein-Barr virus and BK virus, as well as urinary tract infections and Pneumocystis jirovecii pneumonia. These infections are largely related to the degree of immunosuppression and require close monitoring. Cardiovascular and metabolic conditions, including hypertension, hyperlipidaemia and post-transplant diabetes mellitus, are also prevalent and contribute to long-term morbidity. These issues often stem from pre-existing kidney disease and ongoing immunosuppressive therapy. Allograft rejection, whether antibody-mediated or T cell-mediated, continues to be a major threat to graft survival. Early detection through donor-specific antibody screening and timely biopsy is essential for prompt intervention. Additional challenges include increased cancer risk, particularly post-transplant lymphoproliferative disorder, and recurrence of primary kidney disease. By recognising these complications early, general paediatricians play a crucial role in multidisciplinary care, improving graft survival and patient outcomes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".