Determinants of Cardio-Ankle Vascular Index and Heart-Thigh β Index in the MESA
Bibliographic record
Abstract
BACKGROUND: The cardio-ankle vascular index (CAVI) and heart-thigh β index (htβ) assess arterial stiffness by correcting pulse wave velocity for blood pressure to achieve less dependency on blood pressure variations. Normative data for these markers among US communities are lacking. We aimed to assess the determinants and normative values of CAVI and htβ. METHODS: MESA (Multi-Ethnic Study of Atherosclerosis) participants with CAVI and htβ measurements were included (N=2950). A subgroup selected to define normative values included only participants without previous cardiovascular disease, diabetes, smoking, antihypertensive use, and with blood pressure <140/90 mm Hg, body mass index <35 kg/m 2 , and creatinine <1.5 mg/dL. Associations were assessed by multivariable linear regressions. All continuous variables were standardized. RESULTS: Among 2950 participants (mean age, 73.6 years; 47.2% male), older age (β for CAVI=0.39, P <0.001 and htβ=0.41, P <0.001), and male sex (β for CAVI=0.30, P <0.001 and htβ=0.11, P <0.001) were associated with higher arterial indices. Participants with higher blood pressure, height, and diabetes exhibited higher CAVI and htβ. A higher waist circumference was associated with lower CAVI and htβ. Among the normative value subgroup (N=676), the mean CAVI was 8.7 (2 Z score range, 6.5–11.2), and the mean htβ was 8.9 (2 Z score range, 4.3–13.6). Among participants without cardiovascular disease, higher CAVI and htβ were associated with higher predicted 10-year cardiovascular risk estimated by pooled cohort equations (per SD of CAVI=3.6%, P <0.001 and htβ=3.3%, P <0.001). CONCLUSIONS: We report determinants and normative values of CAVI and htβ in a multiethnic community-based US population. Future studies should focus on the prognostic utility of CAVI and htβ.
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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 | 0.001 | 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".