Comparison of metabolic responses to the mixed meal tolerance test vs the oral glucose tolerance test after successful clinical islet transplantation
Bibliographic record
Abstract
Abstract Following islet transplantation, mixed meal tolerance tests (MMTs) are routinely utilized to assess graft function, but how the 90‐minute MMTT glucose value relates to a 120‐minute glucose concentration of ≥11.1 mmol/L used to diagnose diabetes following a standardized 75 g‐OGTT, is not known. We examined this relationship further. Thirteen subjects with Type 1 diabetes and stable transplant grafts, not on exogenous insulin with HbA1c < 7% (53 mmol/mol), were studied on 17 occasions with paired OGTTs and MMTTs. Receiver operating characteristic (ROC) curves were constructed to derive the 90‐minute MMTT glucose threshold associated with a 120‐minute glucose concentration following a 75 g‐OGTT (OGTT120) ≥11.1 mmol/L and their diagnostic accuracy. Studies with OGTT120 ≥11.1 mmol/L (n = 5) had diminished C‐peptide: glucose, greater integrated glucose and diminished insulin: glucose area under the curve (AUC) ratios (0‐120 minutes) and disposition indices; all P < .05, contrasting with MMTTs where no difference in the 90‐minute glucose concentrations, C‐peptide:glucose, integrated glucose, C‐peptide and C‐peptide: glucose AUCs (0‐90 minutes) was seen; all P > .05. A 90‐minute MMTT glucose concentration ≥8.0 mmol/L demonstrated a sensitivity and specificity of ≥80% for the diagnosis of OGTT120 ≥11.1 mmol/L; area under ROC curve (mean ± SEM) 73 ± 13%. A 90‐minute MMTT glucose ≥8.0 mmol/L, identifies islet transplant recipients who may require closer monitoring for graft dysfunction.
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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 | 0.002 | 0.007 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".