Disposition Index, Glucose Effectiveness, and Conversion to Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: Disposition index (DI) and glucose effectiveness (S(G)) are risk factors for diabetes. However, the effect of DI and S(G) on future diabetes has not been examined in large epidemiological studies using direct measures. RESEARCH DESIGN AND METHODS: Insulin sensitivity index (S(I)), acute insulin response (AIR), and S(G) were measured in 826 participants (aged 40-69 years) in the Insulin Resistance Atherosclerosis Study (IRAS) by the frequently sampled intravenous glucose tolerance test. DI was expressed as S(I) x AIR. At the 5-year follow-up examination, 128 individuals (15.5%) had developed diabetes. RESULTS: The area under the receiver operating characteristic curve of a model with S(I) and AIR was similar to that of DI (0.767 vs. 0.774, P = 0.543). In a multivariate logistic regression model that included both DI and S(G), conversion to diabetes was predicted by both S(G) (odds ratio x 1 SD, 0.61 [0.47-0.80]) and DI (0.68 [0.54-0.85]) after adjusting for demographic variables, fasting and 2-h glucose concentrations, family history of diabetes, and measures of obesity. Age, sex, race/ethnicity, glucose tolerance status, obesity, and family history of diabetes did not have a significant modifying impact on the relation of S(G) and DI to incident diabetes. CONCLUSIONS: The predictive power of DI is comparable to that of its components, S(I) and AIR. S(G) and DI independently predict conversion to diabetes similarly across race/ethnic groups, varying states of glucose tolerance, family history of diabetes, and obesity.
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 | 0.000 |
| 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".