Central and Brachial Blood Pressures, Statins, and Low-Density Lipoprotein Cholesterol
Bibliographic record
Abstract
Central blood pressure may be a better predictor of cardiovascular disease than brachial pressure. Although statins reduce brachial pressure, their impact on central pressure remains unknown. Furthermore, whether this effect is mediated through a decrease in low-density lipoprotein cholesterol (LDL-c) is unknown. This study aims to characterize the association of statins and LDL-c with central and brachial blood pressures and to quantify their respective effects. Of the 20 004 CARTaGENE participants, 16 507 had available central blood pressure, LDL-c, and Framingham risk score. Multivariate analyses were used to evaluate the association between central pressure and LDL-c in subjects with or without statins. The impact of LDL-c on the association between statin and pressure parameters was determined through mediation analyses. LDL-c was positively associated with systolic and diastolic central pressure in nonusers (β=0.077 and 0.106; P <0.001) and in participants with statins for primary (β=0.086 and 0.114; P <0.001) and secondary prevention (β=0.120 and 0.194; P <0.003). Statins as primary prevention were associated with lower central systolic, diastolic, and pulse pressures (−3.0, −1.6, and −1.3 mm Hg; P <0.001). Mediation analyses showed that LDL-c reduction contributed to 15% of central systolic and 44% of central diastolic pressure changes associated with statins and attenuated 22% of the effects on central pulse pressure. Similar results were found with brachial pressure components. In conclusion, reduction of LDL-c was associated with only a fraction of the lower blood pressures in statin user and seemed to be mostly associated with improvement of steady (diastolic) pressure, whereas non–LDL-c–mediated pathways were mostly associated with changes in pulsatile pressure components.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".