Outcomes of pancreas transplantation in patients with underlying inflammatory bowel disease: a retrospective case series
Bibliographic record
Abstract
Introduction: Despite having emerged as a definitive treatment for diabetes mellitus (DM), pancreas transplantation remains a formidable surgical task owing to complications like graft pancreatitis, enteric leaks, and rejection. This becomes more challenging in the setting of underlying bowel pathology, such as inflammatory bowel disease (IBD), which has a strong immune-genomic association of co-existence with DM. Risk of anastomotic leaks, dose adjustments of immunosuppressants and biologicals, and management of IBD flares constitute some of the major perioperative challenges calling for a protocol-based, systematic, multidisciplinary approach. Patients and methods: This was a retrospective case series of patients between January 1996 and July 2021, with all patients being followed up until December 2021. All consecutive patients with end-stage DM who underwent pancreas transplantation (alone, simultaneous with kidney transplantation or after kidney transplantation) and had pre-existing IBD were included in the study. A Comparison of 1-, 5-, 10-year survival was done with pancreas transplant recipients without underlying IBD using Kaplan–Meir curves. Results: Of the total 630 pancreas transplants performed between 1996 and 2021, eight patients had IBD, mostly Crohn’s disease. Following pancreas transplantation, two of the eight patients had duodenal leaks, with one a requiring graft pancreatectomy. The 5-year graft survival rate for the cohort was 75% compared to 81.6% for the overall cohort of patients undergoing pancreas transplantation (P=0.48) with a median graft survival of 48.4 months compared to 68.1 months in the latter (P=0.56). Conclusion: The findings of the series provide a snapshot of the outcome of pancreas transplantation in the background of IBD, suggesting a graft and overall patient survival rates comparable with pancreas transplantation in patients without underlying IBD, with further validation of the findings required in a larger cohort of patients in the future.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".