Islet Transplantation Provides Superior Glycemic Control With Less Hypoglycemia Compared With Continuous Subcutaneous Insulin Infusion or Multiple Daily Insulin Injections
Bibliographic record
Abstract
BACKGROUND: The aim was to compare efficacy of multiple daily injections (MDI), continuous subcutaneous insulin infusion (CSII) and islet transplantation to reduce hypoglycemia and glycemic variability in type 1 diabetes subjects with severe hypoglycemia. METHODS: This was a within-subject, paired comparison of MDI and CSII and CSII with 12 months postislet transplantation in 10 type 1 diabetes subjects referred with severe hypoglycemia, suitable for islet transplantation. Individuals were assessed with HbA1c, Edmonton Hypoglycemia Score (HYPOscore), continuous glucose monitoring (CGM) and in 8 subjects measurements of glucose variability using standard deviation of glucose (SD glucose) from CGM and continuous overlapping net glycemic action using a 4 hour interval (CONGA4). RESULTS: After changing from MDI to CSII before transplantation, 10 subjects reduced median HYPOscore from 2028 to 1085 (P < 0.05) and hypoglycemia events from 24 to 8 per patient-year (P < 0.05). While HbA1c, mean glucose and median percent time hypoglycemic on CGM were unchanged with CSII, SD glucose and CONGA4 reduced significantly (P < 0.05). At 12 months posttransplant 9 of 10 were C-peptide positive, (5 insulin independent). Twelve months postislet transplantation, there were significant reductions in all baseline parameters versus CSII, respectively, HbA1c (6.4% cf 8.2%), median HYPOscore (0 cf 1085), mean glucose (7.1 cf 8.6 mmol L), SD glucose (1.7 cf 3.2 mmol/L), and CONGA4 (1.6 cf 3.0). CONCLUSIONS: In subjects with severe hypoglycemia suitable for islet transplantation, CSII decreased hypoglycemia frequency and glycemic variability compared with MDI whereas islet transplantation resolved hypoglycemia and further improved glycemic variability regardless of insulin independence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".