Management of Hypoglycemic Unawareness and the Current Status of Clinical Allogeneic Islet Transplantation
Bibliographic record
Abstract
Problematic hypoglycemia is defined as a condition in which episodes of severe hypoglycemia are unpredictable and/or cannot be easily explained or prevented, typically associated with impaired awareness of hypoglycemia.The treatment algorithm for patients with type 1 diabetes and problematic hypoglycemia emphasizes the stepwise approach including structured education regarding multiple daily injections of insulin, use of technology such as sensor-augmented pump with low glucose suspension, and islet or pancreas transplantation.Although the prevalence of insulin independence at 5 years is 25~50% in most recent clinical trials of islet transplantation, both islet and pancreas transplantation are equally efficient to cure severe hypoglycemia for more than 5 years in about 70% of the recipients.To date, international cohorts of clinical islet transplantation such as the French-Swiss GRAGIL Network have successfully reproduced the long-term C-peptide positivity initially achieved with the Edmonton protocol, with long-term insulin independence demonstrated in selected cases.Several cases with partial islet graft function have been reported in Korea, with the first case of long-term insulin independence being reported in late 2015.Therefore, islet transplantation can offer freedom from life-threatening severe hypoglycemia for type 1 diabetes patients with problematic hypoglycemia, even in non-responders to the latest technology-based treatment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".