12-1: SIMULTANEOUS ISLET-KIDNEY TRANSPLANTATION AS AN ALTERNATIVE FOR PATIENTS INELIGIBLE FOR PANCREAS TRANSPLANT: INITIAL EXPERIENCE AT A NORTH AMERICAN TRANSPLANT CENTER
Bibliographic record
Abstract
Introduction: Simultaneous pancreas-kidney (SPK) transplantation is the standard for patients with type 1 diabetes mellitus (T1DM) and end-stage renal disease (ESRD). However, its high surgical morbidity makes some patients ineligible. Simultaneous islet-kidney (SIK) transplantation offers a less invasive alternative with promising outcomes for glycemic control and kidney function. This study evaluates the safety and efficacy of SIK transplantation in a high-risk cohort. Methods: Between July 2022 and November 2024, 12 patients with T1DM and ESRD ineligible for SPK (90% due to significant peripheral vascular disease; 10% due to high cardiovascular risk) underwent SIK transplantation at Toronto General Hospital. Donor pancreases were processed using standardized islet isolation protocols. Monitored outcomes included kidney graft function, glycemic control, insulin independence, and complications. Graft function was assessed using the Beta-2 score at 1 month after the last infusion and the Igls criteria for ß-cell replacement therapy at 6 months after the last infusion. Results: At a median follow-up of 14 months (range: 2-27), all patients maintained stable kidney function (mean eGFR: 86.41 ± 23.01 ml/min/1.73m²). Four patients (33%) achieved complete insulin independence, with two resuming basal insulin due to immunosuppression-related complications. Among non-insulin-independent patients, 90% achieved HbA1c targets <7%, with a 70% reduction in insulin requirements. No severe hypoglycemic episodes were reported. Islet graft function was classified as optimal/good in 75% of cases at six months. Complications included antibody-mediated rejection (1), recurrent infections (1), immunosuppression-related issues (2), and bleeding requiring laparotomy (3). (Table 1 and Figure 1)Conclusions: SIK transplantation is a viable alternative for patients ineligible for SPK, offering improved metabolic control and stable kidney function with reduced surgical risk. While insulin independence rates are lower than SPK, SIK effectively enhances glycemic outcomes and reduces complications, demonstrating its potential in high-risk populations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".