Phase 3 trial of human islet-after-kidney transplantation in type 1 diabetes
Bibliographic record
Abstract
Allogeneic islet transplant offers a minimally invasive option for β cell replacement in the treatment of type 1 diabetes (T1D). The CIT consortium trial of purified human pancreatic islets (PHPI) in patients with T1D after kidney transplant (CIT06), a National Institutes of Health–sponsored phase 3, prospective, open-label, single-arm pivotal trial of PHPI, was conducted in 24 patients with impaired awareness of hypoglycemia while receiving intensive insulin therapy. PHPI were manufactured using standardized processes. PHPI transplantation was effective with 62.5% of patients achieving the primary endpoint of freedom from severe hypoglycemic events and HbA 1c ≤ 6.5% or reduced by ≥ 1 percentage point at 1 year posttransplant. Median HbA 1c declined from 8.1% before to 6.0% at 1 year and 6.3% at 2 and 3 years following transplant ( P < .001 for all vs baseline), with related improvements in hypoglycemia awareness and glucose variability. The improved metabolic control was associated with better health-related and diabetes-related quality of life. The procedure was safe and kidney allograft function remained stable after 3 years. These results add to evidence establishing allogeneic islet transplant as a safe and effective treatment for patients with T1D and unstable glucose control despite intensive insulin treatment, supporting the indication for PHPI in the post–renal transplant setting.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".