Lipid and apolipoprotein predictors of progression from asymptomatic state or impaired glucose tolerance to type 2 diabetes mellitus.
Bibliographic record
Abstract
SUMMARY Background. To relate lipoprotein profile, conventional lipid and glycemia along with abdominal fat to explore the possible risk factors associated with the progression from a non-diabetic, asymptomatic state to IGT, IGF and type-2 DM in Maltese Canadian population. Methods. We conducted analysis of 780 subjects using the ADA and WHO criteria to classify subjects into groups based on: 1) normal glucose tolerance with FBG 6.1 and 2hBG 8-12); and 4) combined IFG/IGT (FBG 6.16.9 and 2hBG 8-12). We compared the three groups for glycemia, insulin secretion, and insulin sensitivity based on their apolipoprotein levels and abdominal fat. Results. The subjects with higher apolipoprotein levels (12.8 (IGT) vs. 8.9 mg/dL (normal), P<0.001), WHR (0.91 (IfG) vs. 0.89 (normal), P<0.01) and higher abdominal fat were found to be suffering from IGF and IGT and were highly insulin resistant. There were significant differences in the 2-h glucose (5.2 for NGT vs. 9.1 for IGT and 13.4 mmol/L for T2DM, P<0.001) and insulin (37.1 vs. 89.3 vs. 53.2, μU/mL). Conclusions. Poor glycemia was associated with potentially more atherogenic lipoprotein profiles and led to the worsening of insulin resistance and insulin secretory dysfunction. The higher apolipoprotein C-III and B levels, BMI and abdominal fat were strongly associated with metabolic abnormalities and shown to be predictors of diabetes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".