Relationship between BMI and aortic stiffness: influence of anthropometric indices in hypertensive men and women
Bibliographic record
Abstract
BACKGROUND: Increased aortic stiffness could be one of the mechanisms by which obesity increases cardiovascular risk independently of traditional risk factors. Studies have suggested that anthropometric indices may be predictors of cardiovascular risk but few studies have investigated their relations with aortic stiffness in high cardiovascular risk population. We investigated the strength of correlation between different anthropometric indices with aortic stiffness in hypertensive and diabetic patients. METHODS: A cross-sectional study was performed in 474 hypertensive patients. Anthropometric indices were calculated: BMI, waist circumference, waist-hip ratio, and waist-height ratio (WHtR). Aortic stiffness was assessed by measurement of carotid-femoral pulse wave velocity (PWV). Correlations between indices and PWV were investigated by linear regression analyses and hierarchical analyses after adjusting for cardiovascular risk factors. RESULTS: Regional anthropometric indices were more strongly correlated with PWV than BMI in both sexes. In linear regression analyses, WHtR presented the highest correlation with PWV than other indices in our study population. In adjusted hierarchical regression used, WHtR had the highest additive value on top of BMI while there no additive value of BMI on top of WHtR. These differences remained after adjustment on cardiovascular events. In men WHtR was more closely correlated with PWV than others. In women, waist-hip ratio and WHtR were equally correlated with PWV compared with BMI. CONCLUSION: Regional anthropometric indices are more closely correlated with PWV than BMI in hypertensive patients. WHtR presents the highest correlation with PWV beyond BMI. REGISTRATION: The study was registered in the French National Agency for Medicines and Health Products Safety (No. 2013-A00227-38) and was approved by the Advisory Committee for Protection of Persons in Biomedical Research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".