β-Cell Dysfunction in Subjects With Impaired Glucose Tolerance and Early Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: Methods to assess beta-cell function in clinical studies are limited. The aim of the current study was to compare a direct measure of insulin secretion with fasting surrogate markers in relation to glucose tolerance status. RESEARCH DESIGN AND METHODS: In 1,380 individuals from the Insulin Resistance Atherosclerosis Study, beta-cell function was assessed using a frequently sampled intravenous glucose tolerance test (first-phase insulin secretion; acute insulin response [AIR]), homeostasis model assessment of beta-cell function (HOMA-B), proinsulin levels, and the proinsulin-to-insulin ratio. Beta-cell function was cross-sectionally analyzed by glucose tolerance categories (normal glucose tolerance [NGT], n = 712; impaired glucose tolerance [IGT], n = 353; newly diagnosed diabetes by 2-h glucose from an oral glucose tolerance test [OGTT] [DM2h], n = 80; newly diagnosed diabetes by fasting glucose [DMf], n = 135; or newly diagnosed diabetes by fasting and 2-h glucose and established diabetes on diet/exercise only [DM], n = 100). RESULTS: In Spearman correlation analyses, proinsulin and the proinsulin-to-insulin ratio were only modestly inversely related to AIR (r values from -0.02 to -0.27), and AIR was strongly related to HOMA-B (r values 0.56 and 0.58). HOMA-B markedly underestimated the magnitude of the beta-cell defect across declining glucose tolerance, especially for IGT and new DM by OGTT compared with AIR. Analyses adjusting for insulin sensitivity showed that beta-cell function was compromised in IGT, DM2h, DMf, and DM, relative to NGT, by 13, 12, 59, and 62% (HOMA-B) and by as much as 40, 60, 80, and 75%, using AIR. CONCLUSIONS: Subjects with IGT and early-stage, asymptomatic type 2 diabetic patients have more pronounced beta-cell defects than previously estimated from epidemiological studies using homeostasis model assessment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".