Association between triglyceride-glucose index and the risk of cardiometabolic diseases in metabolically healthy obese individuals: a prospective cohort study
Bibliographic record
Abstract
Background Metabolically healthy obese (MHO) individuals meet the criteria for obesity with normal blood glucose and lipid metabolism parameters, absence of hypertension, and no concurrent cardiovascular diseases. However, the association between the triglyceride-glucose (TyG) index and the risk of cardiometabolic disease (CMD) in MHO individuals remains unclear. Methods and results This study included obese individuals who underwent health examinations at Kailuan Group from 2006 to 2010, whom without a history of hypertension, diabetes, hyperlipidemia, cardiovascular disease, as the study participants. A total of 4750 participants were included in this study. The TyG index was calculated as ln[TG (mg/dL) × FPG (mg/dL)/2] and divided into four groups based on quartiles: Q1 group (<8.18); Q2 group (8.18-8.41); Q3 group (8.42-8.62); Q4 group (≥8.63). The Cox proportional hazards model was used to assess the relationship between the TyG index and risk of CMD incidence. During a median follow-up period of 11 (IQR 10.3, 11.2) years, 826 participants experienced CMD, among whom 131 participants developed coronary heart disease, 215 participants developed stroke, and 542 participants developed diabetes. After adjusting for multiple confounding factors, compared with the Q1 group, the adjusted HRs (95% CI) for CMD in the Q2-Q4 groups were 1.33 (1.03, 1.65), 1.37 (1.04, 1.82), and 2.04 (1.56, 2.68) ( P <0.0001). A similar trend was found in the subtypes of CMD in coronary heart disease, stroke, and diabetes. Restrictive cubic spline analysis revealed a linear dose-response relationship between the TyG index and the risk of CMD. Conclusions A high TyG index increases the risk of CMD in MHO individuals. Monitoring and maintaining an appropriate TyG index may contribute to the prevention of CMD risk in MHO individuals.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".