Definitions of Metabolic Syndrome: Where are We Now?
Bibliographic record
Abstract
The metabolic syndrome (MetS) is a cluster of metabolic abnormalities including abdominal obesity, glucose intolerance, hypertension and dyslipidaemia and is associated with an increased risk of vascular events. Since the initial description of the MetS, several expert groups produced different definitions. This variability led to confusion and absence of comparability between studies. Although there is agreement that the MetS is a major public health challenge worldwide and consistent evidence stresses the need for intervention, the definition of the syndrome remains a matter of debate. This review considers the different definitions of the MetS. These include those proposed by the World Health Organisation, the European Group for the Study of Insulin Resistance, the National Cholesterol Education Program Adult Treatment Panel III, the American College of Endocrinology and American Association of Clinical Endocrinologists and the latest International Diabetes Federation definition which includes ethnic-specific waist circumference cut-off points. These definitions share several features but also include important differences; all have limitations. Selected (after a Medline search) studies comparing the different definitions are also considered. There is a need for a standardised definition of the MetS. Furthermore, a definition tailored for children and adolescents is essential. Prospective long-term studies are needed to validate the prognostic power of these definitions. As new information becomes available the definition of the MetS might be further modified.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.007 |
| 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".