Association of high-density lipoprotein cholesterol with non-fatal cardiac and non-cardiac events: a CANHEART substudy
Bibliographic record
Abstract
Background: Emerging evidence has questioned the role of high-density lipoprotein cholesterol (HDL-C) as an independent and modifiable risk factor for cardiovascular disease. We sought to understand the relationship between HDL-C levels and subsequent non-fatal clinical events. Methods: Individuals without prior cardiovascular disease or cancer were identified. Outcomes of interest were classified as non-fatal cardiovascular, cancer and infectious. Sex-stratified, multivariable, cause-specific Cox proportional hazards models were created. The reference level HDL-C for both women and men was 51-60 mg/dL. Results: Our cohort consisted of 631 762 individuals. For cardiovascular events, there was a consistent inverse relationship, with higher adjusted HRs for the lower HDL-C strata in both men and women. This relationship was also seen in the composite of non-cardiovascular outcomes. In women, the HR in the <30 mg/dL HDL-C category was 2.10 (95% CI 1.66 to 2.57) and 1.86 (95% CI 1.27 to 2.72) for cardiovascular and non-cardiovascular outcomes, respectively; in contrast, in the >90 mg/dL group, it was 0.87 (95% CI 0.74 to 1.02) and 0.81 (95% CI 0.63 to 1.06). For men, HRs were 2.02 (95% CI 1.79 to 2.28) and 1.84 (95% CI 1.47 to 2.31) in the <30 mg/dL HDL-C category for cardiovascular and non-cardiovascular outcomes, respectively, compared with 0.73 (95% CI 0.53 to 1.00) and 1.07 (95% CI 0.67 to 1.70) in the >90 mg/dL group. Conclusions: We found an inverse relationship between HDL-C and a wide spectrum of non-fatal outcomes, suggesting that HDL-C is a heavily confounded factor that may be a marker of poor overall health, rather than an independent and modifiable risk factor.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".