Correlation of Pulse Wave Velocity with Left Ventricular Mass in Patients with Hypertension Once Blood Pressure has been Normalized
Bibliographic record
Abstract
Vascular stiffness has been proposed as a simple method to assess arterial loading conditions of the heart which induce left ventricular hypertrophy (LVH). There is some controversy as to whether the relationship of vascular stiffness to LVH is independent of blood pressure, and which measurement of arterial stiffness, augmentation index (AI) or pulse wave velocity (PWV) is best. Carotid pulse wave contor and pulse wave velocity of patients (n=20) with hypertension whose blood pressure (BP) was under control (<140/90 mmHg) with antihypertensive drug treatment medications, and without valvular heart disease, were measured. Left ventricular mass, calculated from 2D echocardiogram, was adjusted for body size using two different methods: body surface area and height. There was a significant (P<0.05) linear correlation between LV mass index and pulse wave velocity. This was not explained by BP level or lower LV mass in women, as there was no significant difference in PWV according to gender (1140.1+67.8 vs 1110.6+57.7 cm/s). In contrast to PWV, there was no significant correlation between LV mass and AI. In summary, these data suggest that aortic vascular stiffness is an indicator of LV mass even when blood pressure is controlled to less than 140/90 mmHg in hypertensive patients. The data further suggest that PWV is a better proxy or surrogate marker for LV mass than AI and the measurement of PWV may be useful as a rapid and less expensive assessment of the presence of LVH in this patient population.
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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 | 0.002 |
| 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 | 0.000 | 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".