Operationalizing High Ischemic Risk After the 2026 ACC Scientific Statement: a disease-based, bleeding-filtered algorithm for aspirin in primary prevention

Abstract

PREPRINT, NOT PEER REVIEWED. Deposited to establish a dated public record of authorship while the manuscript is under journal review. Background and aims. Guideline statements sometimes name a treatment target without an operational definition. The 2026 American College of Cardiology (ACC) Scientific Statement illustrates this: it restricts aspirin in primary prevention to adults with high ischemic risk and low bleeding risk, and states that high bleeding risk causes net harm regardless of calcium score, but does not define high ischemic risk operationally. This work describes a reproducible method for converting such recommendations into evidence-graded algorithms, applied here to the ACC statement. Methods. A four-step method: identify a guideline target lacking an operational definition; derive candidate criteria from a structured synthesis of trials, guidelines, vascular imaging and bleeding-risk literature; grade each decision node for strength of evidence; and test the algorithm against standardized clinical vignettes, compared qualitatively with score-based decisions. Twenty vignettes were used for the aspirin case. Results. In contemporary statin-treated populations the absolute benefit of aspirin is small and often offset by immediate bleeding harm. Carotid or femoral plaque of at least 1.5 mm and elevated coronary artery calcium identify people whose risk approaches the upper tier of high-risk primary prevention more consistently than probability alone. A bleeding filter applied before any indication reproduces, in operational form, the ACC finding that high bleeding risk causes net harm. Conclusions. The proposal is hypothesis generating and does not replace guidelines. Beyond the aspirin application, the underlying method offers a reproducible way to operationalize other guideline statements that name a target without an operational definition.