Supplemental Islet Infusions Restore Insulin Independence After Graft Dysfunction in Islet Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: The ability of supplemental islet infusions (SII) to restore insulin independence in islet transplant recipients with graft dysfunction has been attributed to the coadministration of exenatide. However, improving islet transplant outcomes could explain the success of SII. We aimed to determine the effect on islet graft function and insulin independence of SII using these new protocols, without the use of exenatide. METHODS: Seventeen islet transplant recipients underwent SIIs after developing graft dysfunction requiring insulin use. For induction therapy, four subjects received daclizumab induction therapy, whereas 13 subjects received thymoglobulin and etanercept. Maintenance immunosuppression consisted of sirolimus+tacrolimus or tacrolimus+cellcept. RESULTS: SII was performed 49.3+/-4.8 months (mean+/-SEM) after the preceding islet transplant. Subjects received significantly lower islet mass with their SII compared with initial transplant(s) (6076+/-492 vs. 9071+/-796 IEQ/kg; P=0.003). Fifteen of the 17 subjects (88.2%) became insulin independent 2.4+/-0.5 months after SII. Insulin-independent duration after SII exceeded that of the initial transplant(s) (24.8+/-2.2 vs. 14.2+/-2.6 months by Kaplan-Meier analysis, P=0.009). Subjects show improved glycemic control after SII (HbA1c 7.0%+/-0.2% pre-SII vs. 6.1%+/-0.2% post-SII, P=0.005) and did not become immunosensitized. CONCLUSION: Using current protocols, SII in the absence of exenatide results in impressive insulin-independence rates and the durability of insulin independence seems to be promising. However, a beneficial effect of exenatide should not be discounted until tested in randomized controlled studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 |
| 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 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".