Components of Metabolic Syndrome and 5-Year Chance in Insulin Clearance - The Resistance Atherosclerosis Study (IRAS)
Bibliographic record
Abstract
Aims Cross-sectional evidence indicates that abdominal adiposity, hypertension, dyslipidaemia and glycaemia are associated with reduced metabolic clearance rate of insulin (MCRI). Little is known about the progression of MCRI and whether components of metabolic syndrome are associated with the change in MCRI. In this study, we examined the association between components of metabolic syndrome and the 5-year change of MCRI. Methods At baseline and 5-year follow-up, we measured fasting plasma triglycerides (TG), high-density lipoprotein (HDL) cholesterol, blood pressure (BP), waist circumference (WC) and fasting blood glucose (FBG) in 784 non-diabetic participants in the Insulin Resistance Atherosclerosis Study. MCRI, insulin sensitivity (SI) and acute insulin response (AIR) were determined from frequently sampled intravenous glucose tolerance tests. Results We observed a 29% decline of MCRI at follow-up. TG, systolic BP and WC at baseline were inversely associated with a decline of MCRI regression models adjusted for age, sex, ethnicity, smoking, alcohol consumption, energy expenditure, family history of diabetes, BMI, SI and AIR [β = −0.057 (95% confidence interval, CI: −0.11, −0.0084) for TG, β = −0.0019 (95% CI: −0.0035, −0.00023) for systolic BP and β = −0.0084 (95% CI: −0.013, −0.0039) for WC; all p < 0.05]. Higher HDL cholesterol at baseline was associated with an increase in MCRI [multivariable-adjusted β = 0.0029 (95% CI: 0.0010, 0.0048), p = 0.002]. FBG at baseline was not associated with MCRI at follow-up [multivariable-adjusted β = 0.0014 (95% CI: −0.0026, 0.0029)]. Conclusions MCRI declined progressively over 5 years in a non-diabetic cohort. Components of metabolic syndrome at baseline were associated with a significant change in MCRI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".