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HUMAN PANCREATIC ISLET TRANSPLANTATION IN INTERNATIONAL COLLABORATION WITH A DISTANT ISLET ISOLATION CENTER: PRELIMINARY RESULTS FROM THE BUDAPEST-GENEVA EXPERIENCE

2004· article· en· W2319102520 on OpenAlexaboutno aff
Z. Máthé, R.M. Langer, J. Járay, Aneta Filo, Attila Doros, V. Weszelits, Ádám Remport, Mária Zsófia Varga, Ferenc Perner, Axel Andrès, Domenico Bosco, P. Morel, Thierry Berney

Bibliographic record

VenueTransplantation · 2004
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTransplantationIsletImmunosuppressionPancreasPancreas transplantationIslet cell transplantationDiabetes mellitusSurgeryUrologyInternal medicineKidney transplantationEndocrinology

Abstract

fetched live from OpenAlex

P448 Aims: Although, recent developments in clinical islet transplantation led to insulin independence in several patients with type 1 diabetes mellitus, isolation of a large number of high-quality human islets for transplantation still remains a great challenge. To overcome the critical islet processing and to ensure patient safety and quality care, we have established an international collaboration between two geographically distant transplant centers. Methods: All pancreata were harvested from multiorgan cadaveric donors in Hungary and were procured by the same team. Careful attention was paid to pancreas harvesting, using no-touch technique and rapid preparation. The pancreata were immediately preserved by the two-layer method (oxigenated perfluorocarbon+UW) and subsequently transported by scheduled regular flight for isolation to Cell Isolation and Transplantation Center, Geneva University Hospitals which is situated at a distance of 1400 km from Budapest. Islets were isolated after enzymatic ductal perfusion of the pancreas using the automated method. After purification, the islets were cultured overnight, then transported back to Budapest also with a scheduled flight. Upon arrival the islets were assessed for viability. Two consecutive kidney transplant patients with type 1 diabetes mellitus, from our IAK waiting list, underwent islet transplantation via percutaneous transhepatic portal embolization using the “bag-method”. The immunosuppression followed the Edmonton-protocol and consisted of daclizumab, sirolimus and low-dose tacrolimus. Results: Median donor age was 44 years (35-54), mean BMI: 25.6. The average time from donor aortic cross-clamp to pancreas procurement was 23 minutes. The islet isolation process began within 8 hours from the donor aorta cross-clamp in all cases. The isolation success rate was 75% (3/4). After overnight culture, the islets were transported back to Budapest and assessed for viability which was >80% in all cases. No complications have occurred during the transplantation, the portal pressure remained within the normal range. The first patient has received 12 000IE/BW from two donors and insulin requirement decreased from 40U/day to 10U/day. The second patient has received 7200IE/BW from single donor and became immediately insulin free. Posttransplantation follow-up for these two patients are 3 and 1 months, respectively. Both patients achieved metabolic stability, the mean glycosylated hemoglobin values have been reduced, none of them have had a hyper- or hypoglycemic episode since islet transplantation. Conclusions: The experience of a traditional islet transplant center, possessing the advanced pancreatic islet isolation techniques, combined with strict donor and recipient selection criteria, suitable organ harvesting and recipient management could overcome national borders and could result in an excellent international collaboration. These preliminary results demonstrate the feasibility of an international collaborative islet transplantation program at a distance over 1000 km.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.013
GPT teacher head0.262
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2004
Admission routes1
Has abstractyes

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