The apoB/apoA-I ratio and insulin resistance: sorting out the metabolic syndrome
Bibliographic record
Abstract
Sierra-Johnson et al.1 demonstrate that the apoB/apoA-I ratio is an independent predictor of insulin resistance in non-diabetic Americans. This was the case in men and women and was independent of the traditional risk factors, components of the metabolic syndrome, and inflammatory risk markers such as C-reactive protein (CRP). The strengths of this study are the meticulous construction of the NHANES database on which it is based and the meticulous analysis of it that was undertaken. Previously, these authors and others have shown that the apoB/apoA-I ratio becomes progressively more abnormal as the number of components of the metabolic syndrome increases2 and that apoB is more closely tied to dysglycaemia and inflammation than low-density lipoprotein (LDL) cholesterol or non-high-density lipoprotein (HDL) cholesterol.3–6 This is the first study, however, to examine systematically the relationship of the apoB/apoA-I ratio to insulin resistance in a large representative cohort. If nothing else, the metabolic syndrome has expanded the net of those labelled at high risk of vascular disease. The problem is that not all those caught are equal: the gradient in risk amongst those who qualify for the diagnosis is probably not much different from the gradient in risk amongst those who do not. Diluting the value of the high-risk label multiplies the costs and diminishes the benefits of therapeutic intervention. Moreover, lumping alikes with not-alikes ensures we will never work out the pathogenesis of either the individual components or their interaction.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".