Arm and ankle blood pressure indices, and peripheral artery disease, and mortality: a cohort study
Bibliographic record
Abstract
BACKGROUND AND AIMS: Few studies have compared arm and ankle blood pressures (BPs) with regard to peripheral artery disease (PAD) and mortality. These relationships were assessed using data from three large prospective clinical trials. METHODS: Baseline BP indices included arm systolic BP (SBP), diastolic BP (DBP), pulse pressure (arm SBP minus DBP), ankle SBP, ankle-brachial index (ABI, ankle SBP divided by arm SBP), and ankle-pulse pressure difference (APPD, ankle SBP minus arm pulse pressure). These measurements were categorized into four groups using quartiles. The outcomes were PAD (the first occurrence of either peripheral revascularization or lower-limb amputation for vascular disease), the composite of PAD or death, and all-cause death. RESULTS: Among 40 747 participants without baseline PAD (age 65.6 years, men 68.3%, diabetes 50.2%) from 53 countries, 1071 (2.6%) developed PAD, and 4955 (12.2%) died during 5 years of follow-up. Incident PAD progressively rose with higher arm BP indices and fell with ankle BP indices. The strongest relationships were noted for ankle BP indices. Compared with people whose ankle BP indices were in the highest fourth, adjusted hazard ratios (95% confidence interval) for each lower fourth were 1.64 (1.31-2.04), 2.59 (2.10-3.20), and 4.23 (3.44-5.21) for ankle SBP; 1.19 (0.95-1.50), 1.66 (1.34-2.05), and 3.34 (2.75-4.06) for ABI; and 1.41 (1.11-1.78), 2.04 (1.64-2.54), and 3.63 (2.96-4.45) for APPD. Similar patterns were observed for mortality. Ankle BP indices provided the highest c-statistics and classification indices in predicting future PAD beyond established risk factors. CONCLUSIONS: Ankle BP indices including the ankle SBP and the APPD best predicted PAD and mortality.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".