The concept of cardiometabolic risk: Bridging the fields of diabetology and cardiology
Bibliographic record
Abstract
The lack of physical activity and the adoption of poor nutritional habits is the major cause of the obesity epidemic that is currently sweeping the world. The expansion of adipose tissue mass, especially of the visceral adipose tissue depot, is observed in the vast majority of individuals carrying the clinical features of the metabolic syndrome, an important (and reversible) risk factor of type 2 diabetes and cardiovascular disease. As waist circumference can be used as a crude estimate of visceral fat accumulation, its measurement provides further information on cardiovascular and type 2 diabetes risk, at any given body mass index value. However, an elevated waist circumference might also be the result of an increased 'cardioprotective' subcutaneous adipose tissue mass. We have proposed that the measurement of plasma triglycerides along with waist circumference, the so-called 'hypertriglyceridemic waist' might better quantify visceral obesity and its health hazards than waist circumference alone. "Hypertriglyceridemic waist" is thought to represent an altered, dysfunctional, and highly lipolytic adipose tissue that is a major culprit abnormality behind the metabolic syndrome and associated cardiometabolic risk, independently from classical cardiovascular disease risk factors such as age, sex, and plasma low density lipoprotein (LDL) cholesterol levels.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".