Combined liver and islet transplantation using steroid-free immunosuppression.
Bibliographic record
Abstract
Due to a vicious circle in which HCV favors insulin resistance and, alternatively, insulin resistance facilitates the persistence of HCV, HCV patients have often diabetes associated with liver cirrhosis. We present the case of combined liver and pancreatic islets transplantation performed in a patient with HCV liver cirrhosis associated with insulin-dependent diabetes. This is also the first case of islet allotransplantation in Romania. A 40-year-old male diagnosed with liver cirrhosis due to HCV infection and insulin dependent diabetes underwent combined liver and islet transplantation. Our therapeutic design was based on data provided by both the use of Edmonton immunosuppressive steroid-free protocol in islets cell transplantation and the findings of international studies on the effects of this protocol in liver transplantation for patients with HCV infection. Good metabolic control of the diabetes was obtained. The absence of anti beta cell autoimmunity could explain also the good tolerance for the transplanted islets, proved by the rapid and durable decrease of the insulin need, from 64 U/day to 20 U/day at one month post-transplantation, dose that was maintained for 16 months when the patient died due to recurrent HCV hepatitis. Islet transplantation can be associated to liver transplantation in order to improve the associated diabetes in cirrhotic patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".