Ambulatory Arterial Stiffness Index as a Predictor of Cardiovascular Mortality in the Dublin Outcome Study
Bibliographic record
Abstract
We hypothesized that the dynamic relation between diastolic and systolic blood pressure over 24 hours provides a measure of arterial stiffness and might, therefore, predict cardiovascular mortality over and above pulse pressure. At baseline, while not on antihypertensive medication, 11 291 patients (mean age, 54.6 years; 5965 women) underwent ambulatory blood pressure monitoring. Using all of the blood pressure readings, we plotted diastolic against systolic blood pressure from each individual and calculated the regression slope. The ambulatory arterial stiffness index (AASI) was defined as 1 minus this regression slope. Over a median follow-up of 5.3 years, 566 cardiovascular deaths occurred, including 151 from stroke and 358 from cardiac disorders. Before and after adjustment for other cardiovascular risk factors, AASI and pulse pressure significantly predicted total cardiovascular mortality. AASI was a stronger predictor than pulse pressure for stroke (mutually adjusted relative hazard ratios for 1 SD increase, 1.21 versus 1.04; P=0.02 versus 0.66) with the opposite trend for cardiac mortality (relative hazard ratios, 1.03 versus 1.21; P=0.63 versus 0.002). In subjects with normal daytime ambulatory blood pressure (<135/<85 mm Hg), AASI was more predictive than pulse pressure of cardiovascular mortality (1.26 versus 0.96; P=0.04 versus 0.70) and of stroke mortality (1.81 versus 1.12; P=0.007 versus 0.58), whereas neither independently predicted cardiac mortality (1.11 versus 0.89; P=0.47 versus 0.40). AASI is a novel measure of arterial stiffness, which can be readily determined from ambulatory blood pressure recordings and which independently predicts cardiovascular mortality, even in normotensive subjects.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".