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Record W1979079562 · doi:10.1097/tp.0b013e3181b4bdbb

Islet Alone Versus Islet After Kidney Transplantation: Metabolic Outcomes and Islet Graft Survival

2009· article· en· W1979079562 on OpenAlexaboutno aff
Shaoping Deng, James F. Markmann, Heidi Yeh, James I. Kim, Moh‐Moh Lian, Yi Gu, Eileen Markmann, Maral Palanjian, Clyde F. Barker, Ali Naji

Bibliographic record

VenueTransplantation · 2009
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
FundersNational Center for Research ResourcesNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsImmunosuppressionIsletMedicineTransplantationDiabetes mellitusKidney transplantationInsulinInternal medicineKidneyEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Isolated islet transplantation with infusions from two to three donor pancreata and Edmonton immunosuppression consistently achieves insulin independence in patients with type 1 diabetes. The success of this protocol has been attributed to a novel combination of immunosuppressive agents and avoidance of steroids; however, the outcome of islet transplantation may differ in kidney transplant recipients who are already immunosuppressed. METHODS: We compared the metabolic outcomes and graft survival of islet transplantation in our program where nine patients underwent islet transplantation alone treated with Edmonton immunosuppression and eight patients received islet after kidney (IAK) transplants under standard kidney transplant immunosuppression often including steroids. RESULTS: Transplants in the IAK and islet transplantation alone setting demonstrated similar islet potency (islet equivalents/unit insulin reduction) and recipients from both groups routinely gained insulin independence, functional islet mass, and duration of graft survival, however, seemed superior in the IAK group. CONCLUSIONS: These results suggest that better islet graft function and survival may be attained using non-Edmonton rather than Edmonton immunosuppression and can include maintenance steroid therapy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.268
Teacher spread0.252 · 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 teacher head, not a consensus.

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

Citations28
Published2009
Admission routes1
Has abstractyes

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