Pancreas and Islet Transplantation: Comparative Outcome Analysis of a Single-centre Cohort Over 20-years
Bibliographic record
Abstract
OBJECTIVE: To provide the largest single-center analysis of islet (ITx) and pancreas (PTx) transplantation. SUMMARY BACKGROUND DATA: Studies describing long-term outcomes with ITx and PTx are scarce. METHODS: We included adults undergoing ITx (n=266) and PTx (n=146) at the University of Alberta from January 1999 to October 2019. Outcomes include patient and graft survival, insulin independence, glycemic control, procedure-related complications, and hospital readmissions. Data are presented as medians (interquartile ranges, IQR) and absolute numbers (percentages, %) and compared using Mann-Whitney and χ2 tests. Kaplan-Meier estimates, Cox proportional hazard models and mixed main effects models were implemented. RESULTS: Crude mortality was 9.4% and 14.4% after ITx and PTx, respectively ( P= 0.141). Sex-adjusted and age-adjusted hazard-ratio for mortality was 2.08 (95% CI, 1.04-4.17, P= 0.038) for PTx versus ITx. Insulin independence occurred in 78.6% and 92.5% in ITx and PTx recipients, respectively ( P= 0.0003), while the total duration of insulin independence was 2.1 (IQR 0.8-4.6) and 6.7 (IQR 2.9-12.4) year for ITx and PTx, respectively ( P= 2.2×10 -22 ). Graft failure ensued in 34.2% and 19.9% after ITx and PTx, respectively ( P =0.002). Glycemic control improved for up to 20-years post-transplant, particularly for PTx recipients (group, P= 7.4×10 -7 , time, P =4.8×10 -6 , group*time, P= 1.2×10 -7 ). Procedure-related complications and hospital readmissions were higher after PTx ( P =2.5×10 -32 and P= 6.4×10 -112 , respectively). CONCLUSIONS: PTx shows higher sex-adjusted and age-adjusted mortality, procedure-related complications and readmissions compared with ITx. Conversely, insulin independence, graft survival and glycemic control are better with PTx. This study provides data to balance risks and benefits with ITx and PTx, which could improve shared decision-making.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".