Long-Term Immunosuppression After Solitary Islet Transplantation Is Associated With Preserved C-Peptide Secretion for More Than a Decade
Bibliographic record
Abstract
We report on two patients with type 1 diabetes (T1D) after solitary islet transplantation in 2001. They received steroid-sparing immunosuppression (daclizumab, sirolimus, and tacrolimus according to the Edmonton protocol). Both patients became insulin independent for 2 years: Patient A, a 42-year-old female with a 12-year history of T1D, received two islet infusions; patient B, a 53-year-old female with a 40-year T1D history, received one islet infusion. Pretransplant, both had undetectable C-peptide concentrations and frequent and severe hypoglycemia. Pretransplant, hemoglobin A1c (HbA1c) was 7.8% and 8.8% and insulin requirements were 0.47 and 0.33 units/kg/day, respectively. Posttransplant, C-peptide levels remained detectable while immunosuppression was continued, but decreased over time. Insulin was re-started 2 years posttransplant in both patients. Since patient A's glycemia and insulin requirements trended toward pretransplant levels, immunosuppression was discontinued after 13 years. This resulted in a sudden cessation of C-peptide secretion. Patient B continues on immunosuppression, has better HbA1c, and half the insulin requirement compared to pretransplant. Both patients no longer experience severe hypoglycemia. Herein, we document blood glucose concentrations over time (>30 000 measurements per patient) and β cell function based on C-peptide secretion. Despite renewed insulin dependence, both patients express satisfaction with having undergone the procedure.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".