The Impact of Left Ventricular Mass on Diastolic Blood Pressure Targets for Patients With Coronary Artery Disease
Bibliographic record
Abstract
BACKGROUND: Defining the optimal diastolic blood pressure (DBP) for patients with hypertension and coronary artery disease (CAD) is an ongoing challenge in part because of the concern that low DBP may have adverse cardiac effects (the J curve hypothesis). METHODS: Left ventricular mass (LV mass) was measured on the echocardiogram of individuals (N = 92) with CAD who had coronary blood flow (CBF) in the left anterior descending (LAD) artery estimated from artery diameter and DBP distal to coronary stenosis. RESULTS: CBF approached 0 in a small but defined proportion of persons at DBP of 70mm Hg. CBF was significantly lower in persons with higher LV mass (above the median of 83g/m(2)) when DBP was ≥75mm Hg. Higher electrocardiogram QRS voltage (sum of S V1 and R in V6), in the absence of LV hypertrophy (LVH), identified persons with significantly lower CBF at DBP ≥ 80mm Hg. In multivariate analysis, LV mass was a significant CBF determinant after adjusting for DBP and CAD severity. LV mass has a major impact on CBF when DBP is >70mm Hg, while DBP is the primary determinant of CBF when DBP is ≤70mm Hg. Multivariate analysis confirmed a significant interaction between LV mass and DBP. CONCLUSIONS: DBP ≤ 70mm Hg is associated with a progressively greater proportion in whom CBF in the LAD approaches 0. For DBP > 70mm Hg, persons with higher LV mass, even in the absence of LVH, have lower CBF, suggesting LV mass is an important consideration when DBP is reduced in patients with CAD.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| 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".