Postprandial dyslipidemia in insulin resistant states in adolescent populations
Bibliographic record
Abstract
Obesity and the metabolic syndrome are becoming increasingly prevalent not only in adults, but also in adolescents. The metabolic syndrome, a complex cluster of metabolic abnormalities, increases one's risk of developing type 2 diabetes and cardiovascular disease (CVD). Dyslipidemia, a key component of the metabolic syndrome, is highly associated with insulin resistance and contributes to increased CVD risk. Dyslipidemia has traditionally been assessed using a fasting lipid profile [<i>i.e</i>. fasting triglycerides, total cholesterol, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C)]. However, the postprandial state predominates over the course of a day and non-fasting triglycerides independently predict CVD risk. In insulin resistant states, the intestine overproduces triglyceride-rich lipoprotein (TRL) particles, termed chylomicrons (CMs), following ingestion of a fat-containing meal, as well as in the fasting state. Along with elevated hepatic TRLs (<i>i.e</i>. very-low density lipoproteins), CMs contribute to remnant lipoprotein accumulation, small dense LDL particles, and reduced HDL-C, which collectively increase CVD risk. Given the early genesis of atherosclerosis and physiological metabolic changes during adolescence, studying postprandial dyslipidemia in the adolescent population is an important area of study. Postprandial dyslipidemia in the pediatric population poses a significant public health concern, warranting a better understanding of its pathogenesis and association with insulin resistance and CVD. This review discusses the metabolic syndrome, focusing on the link between insulin resistance, postprandial dyslipidemia, and CVD risk. Furthermore, the clinical significance and functional assessment of postprandial dyslipidemia, specifically in the adolescent population, is discussed in more detail.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".