A comparison of islet autotransplantation with allotransplantation and factors elevating acute portal pressure in clinical islet transplantation
Bibliographic record
Abstract
BACKGROUND: Acute portal pressure rise is occasionally observed during intraportal islet infusion, especially in islet autotransplantation (IAT) where tissue purification is rarely applied. In this paper we investigate factors associated with acute portal pressure rise, a known risk factor for portal vein thrombosis. METHODS: Retrospective data was collected on 15 islet autotransplant and 122 allogeneic islet transplant subjects. Non-purified pancreatic cells were transplanted in islet autotransplants, and purified islet cells were transplanted in allogeneic transplants. Portal pressure was documented throughout the islet infusion. RESULTS: The total numbers of transplanted islets were significantly smaller in autotransplants than allografts, although the packed cell volume in autotransplants was larger. Autoislet infusion, with a larger packed cell volume, caused higher transient portal venous pressures than allogeneic islet transplant. Univariate analysis and multivariate linear regression revealed that packed cell volume and the number of transplanted cells were significant risk factors for acute portal pressure rise in both autotransplants and allogeneic transplants. CONCLUSIONS: Non-purified IAT has a higher risk for acute portal pressure rise than allogeneic islet transplantation, and the rise is associated with the packed cell volume and the number of transplanted cells. Minimization of packed cell volume and cautious monitoring of portal pressure are important to avoid potential complications of portal hypertension.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".