Associations of high-density lipoprotein cholesterol, particles and subspecies with the risk of hypertension: findings from the PREVEND prospective study
Bibliographic record
Abstract
OBJECTIVE: The prospective associations of high-density lipoprotein cholesterol (HDL-C), HDL particle (HDL-P) and subspecies concentrations with the risk of hypertension are uncertain. We aimed to evaluate the associations of HDL parameters with incident hypertension risk and their interplay with alcohol consumption in the PREVEND study. METHODS: HDL parameters as measured by nuclear magnetic resonance spectroscopy and self-reported alcohol consumption were assessed in 3263 participants (mean age, 49 years; 45.8% males) without a history of hypertension at baseline. Multivariable-adjusted hazard ratios (HRs) with 95% CIs for hypertension per 1 standard deviation increment in HDL parameters were calculated. RESULTS: During a median follow-up of 7.2 years, 825 participants developed hypertension. In analysis adjusted for several potential confounders, including alcohol consumption, there were inverse associations of HDL-C, HDL-P, medium HDL, HDL size, H3P and H4P with hypertension risk: HRs [95% confidence interval (CI) of 0.88 (0.81-0.97), 0.92 (0.86-0.99), 0.86 (0.80-0.93), 0.89 (0.82-0.98), 0.92 (0.85-0.98), and 0.87 (0.81-0.94), respectively]. Sex or alcohol consumption did not modify the associations of HDL parameters with hypertension risk. Compared with abstainers, the multivariable adjusted HRs (95% CI) of hypertension for occasional to light, moderate and heavy alcohol consumers were 0.84 (0.70-1.00), 0.83 (0.68-1.02), and 0.97 (0.69-1.37), respectively; the associations persisted on further adjustment for HDL parameters. CONCLUSIONS: There are inverse associations of HDL-C, HDL-P, medium HDL, HDL size, H3P and H4P with hypertension risk, which are not confounded or modified by alcohol consumption. Light and moderate alcohol consumption is modestly and inversely associated with hypertension risk, independently of HDL parameters.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".