Metabolic Syndrome
Bibliographic record
Abstract
OBJECTIVE: Little is known about the prevalence of the metabolic syndrome among elderly people in Italy, its association with all-cause mortality, and whether measurement of serum C-reactive protein (CRP) and interleukin (IL)-6 affects this association. RESEARCH DESIGN AND METHODS: The baseline prevalence of metabolic syndrome, diagnosed according to the National Cholesterol Education Program (NCEP) criteria, and all-cause mortality at 4 years were recorded in an Italian population-based cohort (981 subjects, 55% women, aged 65-97 years). A Cox model adjusted for sociodemographic, lifestyle, and medical variables was used to investigate 1) whether metabolic syndrome was a predictor of mortality and 2) how the association was affected by baseline high CRP (>3 mg/l) and IL-6 (>1.33 pg/ml). RESULTS: Overall, metabolic syndrome prevalence was 27.2% [95% CI 24.0-30.5] and higher in women (33.3% [28.7-38.0]) than in men (19.6% [15.5-24.2]). During follow-up, 137 deaths occurred. Using the no metabolic syndrome/no high IL-6 group as the reference, mortality was not associated with the metabolic syndrome alone (multivariable-adjusted hazard ratio 1.24 [0.60-2.59]), only weakly associated with high IL-6 alone (1.66 [1.04-2.63]), but strongly associated with the concurrent presence of metabolic syndrome and high IL-6 (3.26 [2.00-5.33]). High CRP was not a mortality predictor (0.83 [0.58-1.20]) nor did it affect the association of the other variables with mortality. CONCLUSIONS: Metabolic syndrome by NCEP criteria is highly prevalent in the Italian elderly population. It is not itself associated with mortality but may improve the usefulness of IL-6 as a mortality predictor in older age.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".