Early Gastric Post-Transplant Lymphoproliferative Disorder and<i>H pylori</i>Detection after Kidney Transplantation: A Case Report and Review of the Literature
Bibliographic record
Abstract
The incidence of post-transplantation lymphoproliferative disorder (PTLD) in the adult renal transplant population ranges from 0.7% to 4%. The majority of cases involve a single site and arise, on average, seven months after transplantation. Histopathology usually reveals B-cell proliferative disease and has been standardized into its own classification. Treatment modalities consist of decreased immunosuppression, eradication of Epstein-Barr virus, surgical resection, systemic chemotherapy and monoclonal antibody therapy; however, mortality remains high, typically with a short survival time. In patients who have undergone renal transplantation, approximately 10% of those with PTLDs present with gastrointestinal symptomatology and disease. Reported sites include the stomach, and small and large bowel. Very few cases of Helicobacter pylori or mucosal-associated lymphoid tissue have been described in association with PTLD. In the era of cyclosporine immunosuppression, the incidence of PTLD affecting the gastrointestinal tract may be increasing in comparison with the incidence seen with the use of older immunosuppression regimens. A case of antral PTLD and H pylori infection occurring three months after renal transplantation is presented, and the natural history and management of gastric PTLD are reviewed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".