Expectations and Strategies Regarding Islet Transplantation: Metabolic Data From the GRAGIL 2 Trial
Bibliographic record
Abstract
BACKGROUND: Whether islet transplantation should be aimed at restoring insulin independence or providing adequate metabolic control is still debated. The GRAGIL2 trial was designed as a phase 1-2 study where primary outcome was the rate of insulin independence, and secondary outcome was the success rate defined by a composite score based upon basal C-peptide, HbA1c, hypoglycemic events, and exogenous insulin needs. METHODS: C-peptide negative type 1 brittle diabetic patients experiencing severe hypoglycemia were eligible to receive a maximum of two islet preparations totalizing 10,000 IE/kg or more, with a threshold of 5,000 IE/kg for the first infusion, according to the Edmonton protocol, within the Swiss-French GRAGIL multicentric network. A sequential analysis with a triangular test was performed in every five patients after 6- and 12-month follow-up. Maximal inefficiency was set at 40% and minimal efficiency at 66%. RESULTS: From September 2003 to October 2005, 10 patients were included. Median waiting time was 6.7 months (first injection) and 9 weeks (second injection). All but one patient received 11,089+/-505 IE/kg: one received a single graft of 5398 IE/kg. At 6 months, insulin independence and composite success rates were 6 of 10 and 6 of 10, respectively. At 12 months, insulin independence was observed in 3 of 10 patients and success in 5 of 10 patients. CONCLUSION: Based upon our sequential analysis settings, islet transplantation failed to achieve the primary goal, insulin independence, but tended to succeed in reaching the secondary goal, successful metabolic control. Currently it appears to be a successful biological closed-loop glucose control method for brittle diabetes.
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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 | 0.018 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".