High remnant cholesterol and atherosclerotic cardiovascular disease in healthy women and men aged 70–100
Bibliographic record
Abstract
AIMS: High remnant cholesterol has been increasingly recognized as an important risk factor for atherosclerotic cardiovascular disease (ASCVD). However, uncertainty remains regarding this association in old age. The aim of this study was to test the hypothesis that higher remnant cholesterol is associated with higher incidence of ASCVD in healthy women and men aged 70-100. METHODS AND RESULTS: A total of 90,875 women (57%) and men aged 20-100 and without ASCVD, diabetes, or lipid-lowering therapy at baseline were included in the Copenhagen General Population Study in 2003-15. During a median follow-up of 12.8 years, 7352 were diagnosed with ASCVD. Incidence rates and hazard ratios were calculated according to age and sex. The highest incidence rate of ASCVD was observed in individuals aged 70-100 with a remnant cholesterol level >1.0 mmol/L (>39 mg/dL) [23 per 1000 person-years; 95% confidence interval (CI): 21-25]. Likewise, incidence rates of ASCVD per 1.0 mmol/L (39 mg/dL) higher remnant cholesterol were highest in individuals aged 70-100. Multivariable adjusted hazard ratio for 1.0 mmol/L (39 mg/dL) higher remnant cholesterol was 1.31 (95% CI: 1.20-1.44) in those aged 70-100, which was comparable with hazard ratios in younger age groups. Similar relationships were observed for women and men separately. CONCLUSION: Higher remnant cholesterol was associated with higher incidence of ASCVD in those aged 70-100. The present results suggest that while relative rates of ASCVD for high vs. low remnant cholesterol do not increase with higher age, elevated remnant cholesterol contribute substantially to the absolute risk of ASCVD at age 70-100.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".