Aortic-Femoral Stiffness Gradient and Cardiovascular Risk in Older Adults
Bibliographic record
Abstract
BACKGROUND: The aortic-femoral arterial stiffness gradient, calculated as the ratio of lower-limb pulse-wave velocity (PWV) to central (aortic) PWV, is a promising tool for assessing cardiovascular disease (CVD) risk, but whether it predicts incident CVD is unknown. METHODS: We examined the association of the aortic-femoral arterial stiffness gradient measures carotid-femoral stiffness gradient (femoral-ankle PWV divided by carotid-femoral PWV) and the heart-femoral stiffness gradient (femoral-ankle PWV divided by heart-femoral PWV), as well as PWV, with incident CVD (coronary disease, stroke, and heart failure) and all-cause mortality among 3109 participants of the Atherosclerosis Risk in Communities Study cohort (age, 75±5 years; carotid-femoral PWV, 11.5±3.0 m/s), free of CVD. Cox regression was used to estimate hazard ratios (HR) and 95% CIs. RESULTS: Over a median 7.4-year follow-up, there were 322 cases of incident CVD and 410 deaths. In fully adjusted models, only top quartiles of carotid-femoral stiffness gradient (quartile 4: HR, 1.43 [95% CI, 1.03-1.97]; and quartile 3: HR, 1.49 [95% CI, 1.08-2.05]) and heart-femoral stiffness gradient (quartile 4: HR, 1.77 [95% CI, 1.27-2.48]; and quartile 3: HR, 1.41 [95% CI, 1.00-2.00]) were significantly associated with a greater risk of incident CVD. Only high aortic stiffness in combination with low lower-limb stiffness was significantly associated with incident CVD (HR, 1.46 [95% CI, 1.06-2.02]) compared with the referent low aortic stiffness and high lower-limb stiffness. No PWVs were significantly associated with incident CVD. No exposures were associated with all-cause mortality. CONCLUSIONS: The aortic-femoral arterial stiffness gradient may enhance CVD risk assessment in older adults in whom the predictive capacity of traditional risk factors and PWV are attenuated.
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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".