The Relationship Between Ambulatory Arterial Stiffness Index and Cardiovascular Outcomes in Women
Bibliographic record
Abstract
BACKGROUND: The ambulatory arterial stiffness index (AASI) obtained during ambulatory blood pressure monitoring (ABPM) has been cited as an independent predictor of major adverse cardiovascular events (MACEs) including cardiovascular death, stroke and worsening chronic kidney disease (CKD) among mixed-sex adult populations. This study aimed to determine the relationship between AASI and MACE and its predictive precision in women. METHODS: This work follows the guidelines of the STROBE initiative for cohort studies. This was a retrospective single-center observational study of adult women (aged 18 - 75 years), who underwent 24-h ABPM for the diagnosis of hypertension or its control. The primary endpoint was a composite MACE of cardiovascular death, acute limb ischemia, stroke, acute coronary syndrome (ACS), or progression to stage V CKD. RESULTS: A total of 219 women aged 57.4 ± 13.3 years were followed up for a median (interquartile range (IQR)) of 25.5 (18.3 - 31.3) months. Overall, 16 (7.3%) patients suffered one or more MACE events. AASI was significantly higher in patients with known coronary artery disease (CAD), diabetes mellitus, peripheral vascular disease (PVD), heart failure, previous stroke, or transient ischemic attack (TIA). AASI was a significant predictor of MACE (area under the curve: 0.78; P < 0.001) with an optimal cut-off of ≥ 0.56. On Kaplan-Meier analysis AASI ≥ 0.56 was significantly associated with MACE (log-rank test, P < 0.001). The only independent predictors of MACE on Cox proportional hazard analysis were diabetes mellitus, low high-density lipoprotein (HDL) levels, cumulative AASI values, or AASI ≥ 0.56. CONCLUSIONS: An AASI of ≥ 0.56 is an independent predictor of MACE in women. A further validation study in a larger cohort of women is recommended.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".