Primary Graft Function, Metabolic Control, and Graft Survival After Islet
Bibliographic record
Abstract
OBJECTIVE — To investigate the influence of primary graft function (PGF) on graft survival and metabolic control after islet transplantation with the Edmonton protocol. RESEARCH DESIGN AND METHODS — A total of 14 consecutive patients with brittle type 1 diabetes were enrolled in this phase 2 study and received median 12,479 islet equivalents per kilogram of body weight (interquartile range 11,072–15,755) in two or three sequential infusions within 67 days (44–95). PGF was estimated 1 month after the last infusion by the �-score, a previously validated index (range 0–8) based on insulin or oral treatment requirements, plasma C-peptide, blood glucose, and A1C. Primary outcome was graft survival, defined as insulin independence with A1C �6.5%. RESULTS — All patients gained insulin independence within 12 days (6–23) after the last infusion. PGF was optimal (�-score �7) in nine patients and suboptimal (�-score �6) in five. At last follow-up, 3.3 years (2.8–4.0) after islet transplantation, eight patients (57%) remained insulin independent with A1C �6.5%, including seven patients with optimal PGF (78%) and one with suboptimal PGF (20%) (P � 0.01, log-rank test). Graft survival was not significantly influenced by HLA mismatches or by preexisting islet autoantibodies. A1C, mean glucose,
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".