Hyperbolic Relationship Between Insulin Secretion and Sensitivity on Oral Glucose Tolerance Test
Bibliographic record
Abstract
The utility of the disposition index as a measure of beta-cell compensatory capacity rests on the established hyperbolic relationship between its component insulin secretion and sensitivity measures as derived from the intravenous glucose tolerance test (IVGTT). If one is to derive an analogous measure of beta-cell compensation from the oral glucose tolerance test (OGTT), it is thus necessary to first establish the existence of this hyperbolic relationship between OGTT-based measures of insulin secretion and insulin sensitivity. In this context, we tested five OGTT-based measures of secretion (insulinogenic index, Stumvoll first phase, Stumvoll second phase, ratio of total area-under-the-insulin-curve to area-under-the-glucose-curve (AUC(ins/gluc)), and incremental AUC(ins/gluc)) with two measures of sensitivity (Matsuda index and 1/Homeostasis Model of Assessment for insulin resistance (HOMA-IR)). Using a model of log(secretion measure) = constant + beta x log(sensitivity measure), a hyperbolic relationship can be established if beta is approximately equal to -1, with 95% confidence interval (CI) excluding 0. In 277 women with normal glucose tolerance (NGT), the pairing of total AUC(ins/gluc) and Matsuda index was the only combination that satisfied these criteria (beta = -0.99, 95% CI (-1.66, -0.33)). This pairing also satisfied hyperbolic criteria in 53 women with impaired glucose tolerance (IGT) (beta = -1.02, (-1.72, -0.32)). In a separate data set, this pairing yielded distinct hyperbolae for NGT (n = 245) (beta = -0.99, (-1.67, -0.32)), IGT (n = 116) (beta = -1.18, (-1.84, -0.53)), and diabetes (n = 43) (beta = -1.37, (-2.46, -0.29)). Moreover, the product of AUC(ins/gluc) and Matsuda index progressively decreased from NGT (212) to IGT (193) to diabetes (104) (P < 0.001), consistent with declining beta-cell function. In summary, a hyperbolic relationship can be demonstrated between OGTT-derived AUC(ins/gluc) and Matsuda index across a range of glucose tolerance. Based on these findings, the product of these two indices emerges as a potential OGTT-based measure of beta-cell function.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".