Abstract 12197: Causes of Death in Patients With Symptomatic Peripheral Artery Disease After Lower Extremity Revascularization: Insights From Voyager Pad
Bibliographic record
Abstract
Background: In trials of patients with coronary artery disease (CAD), unknown deaths (e.g. out of hospital) are often categorized as sudden/presumed cardiovascular (CV) based on observations that recurrent coronary events are a major cause of mortality. Such conventions are applied broadly to CV trials, including those in peripheral artery disease (PAD). Recent trials in patients selected on the basis symptomatic PAD, such as EUCLID trial, report that only ~1/3 have known CAD. Therefore, understanding the causes of death in patients in trials of symptomatic PAD may help elucidate whether different conventions should be considered. Hypothesis and Methods: VOYAGER PAD enrolled patients with symptomatic PAD after lower extremity revascularization. Source documents were collected for all deaths and cause was adjudicated by an independent blinded CEC using accepted CV trial conventions for those dying out of hospital. For this post-hoc analysis, source documents were re-reviewed to provide further details regarding specific causes of deaths. Results: 6564 patients were randomized and followed for a median of 28 months. A total of 637 deaths occurred, and of these, 35% were CV, 22% were unknown (e.g. out of hospital, sudden deaths), and 43% were non-CV. Of the CV deaths, 40% (14% of all deaths) were atherothrombotic (e.g. acute MI, stroke, PE), while 60% (21% of all deaths) were not atherothrombotic (e.g. heart failure, shock). Deaths due to cancer (17%) and infection (15%) were more frequent than atherothrombotic deaths. Conclusions: Patients recruited into trials for symptomatic PAD die of diverse causes. Atherothrombosis caused a minority of deaths, while heart failure, cancer, and infection are as or more frequent. These observations suggest that causes of death differ in populations selected on the basis of PAD versus CAD and that assumptions underlying categorization of deaths of unknown etiology should be carefully considered in these distinct populations.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".