Impaired Fasting Glucose and Impaired Glucose Tolerance Have Distinct Lipoprotein and Apolipoprotein Changes: The Insulin Resistance Atherosclerosis Study
Bibliographic record
Abstract
CONTEXT: Cardiovascular risk is increased in individuals with impaired glucose tolerance (IGT) and impaired fasting glucose (IFG); however, those with IGT appear to be at greater risk. Lipoprotein abnormalities occur also in the prediabetic state. OBJECTIVE: The authors examined lipoprotein composition in IGT and IFG. DESIGN AND SETTING: Cross-sectional analysis of a large epidemiological study was done. PARTICIPANTS: The Insulin Resistance Atherosclerosis Study had a total of 1107 participants. MAIN MEASURES: Lipoproteins and apolipoproteins were measured by conventional methods and lipoprotein composition by nuclear magnetic resonance spectroscopy. RESULTS: Compared with normal glucose tolerance, apolipoprotein B (105.2 vs 99.8 mg/dL, P < .05) was high in isolated IFG, triglyceride (1.48 vs 1.16 mmol/L, P < .001) was high in isolated IGT, and high-density lipoprotein cholesterol was low in combined IFG/IGT (1.12 vs 1.26 mmol/L, P < .001). Nuclear magnetic resonance spectroscopy revealed additional changes: increased total low-density lipoprotein (LDL) particles (1190 vs 1096 nmol/L, P < .01) in isolated IFG; increased large very-low-density lipoprotein (3.61 vs 2.47 nmol/L, P < .01) and small LDL subclass particles (665 vs 541 nmol/L, P < .05) and decreased large LDL subclass particles (447 vs 513 nmol/L, P < .01) in isolated IGT; and decreased large high-density lipoprotein subclass particles in combined IFG/IGT (4.24 vs 5.39 μmol/L, P < .001). CONCLUSIONS: Isolated IFG is characterized by increased apolipoprotein B and total LDL particles, whereas isolated IGT is associated with increased triglycerides, large very-low-density lipoprotein subclass particles, and structural remodeling of LDL particles. These results may help to explain differences in cardiovascular disease risk in the prediabetic state.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".