Portal Venous Versus Systemic Venous Drainage of Pancreas Grafts: Impact on Long-Term Results
Bibliographic record
Abstract
Portal venous (PV) and systemic venous (SV) drainage methods are used in pancreas transplantation. The impact of the reconstruction technique on long-term outcome remains unclear. We compared the efficacy and side effects of both methods in 192 recipients who received synchronous pancreas kidney transplants between November 1995 and November 2007. SV and PV drainage were used in 147 and 45 cases, respectively. Pancreas function was determined by hemoglobin A1c levels and annual oral glucose tolerance test. Serum creatinine assessed kidney function. Serum lipid (low-density lipoprotein, high-density lipoprotein and cholesterol) levels and body mass index were measured annually. Patient and graft survival were calculated by log-rank analysis. Pancreas survival for SV versus PV patients was similar after 5 years (81.8% vs. 75.5%) and 10 years (65.1% vs. 60%; p = NS). Similarly, no difference was detected between the groups regarding kidney survival after 5 years (92.9% vs. 84.4%) and 10 years (81.6% vs. 75.5%; p = NS). Patient survival did not differ at 5 years (94.3% vs. 88.8%) and 10 years (85.1% vs. 84.4%; p = NS). Pancreas and kidney function and the lipid profiles were similar in both groups. SV and PV drainage of pancreas grafts offer similar long-term graft survival and function and choice of method should remain the preference of the surgeon.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".