Triglyceride/High‐Density Lipoprotein Cholesterol Ratio: A Clue to Metabolic Syndrome, Insulin Resistance, and Severe Atherosclerosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High serum levels of triglycerides (Tg) and low levels of high-density lipoprotein cholesterol (HDL-C) are characteristic of the Metabolic Syndrome (MetS). We assessed the ratio of Tg to HDL-C as a way to identify MetS and insulin resistance. We also evaluated its association with severity of carotid atherosclerosis. Data were analyzed from three cohorts totaling 13,908 participants. MetS was defined according to the International Diabetes Federation criteria. Optimal cut-off for Tg/HDL-C ratio was obtained using Youden's index in receiver-operating characteristic (ROC) curve analyses. The risk of MetS and IR in those with a Tg/HDL-C ratio above the optimum cutoff was evaluated by logistic regression analysis. A Tg/HDL-C ratio above the optimal cutoff level significantly increased the odds ratio for MetS in the three cohorts (OR 6.00, 4.04, and 3.50, least in the healthy population), identified insulin resistance defined by the homeostatic model of insulin resistance (HOMA-IR) (p < 0.0001), and was strongly associated with atherosclerosis severity (p = 0.0001). Tg/HDL-C ratio identifies persons with MetS, insulin resistance, and severe atherosclerosis. It should be used more widely to identify patients at high risk. This is clinically important because insulin resistance is treatable.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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 it