The provided text contains only the journal's editorial board information and no clinical study data.
Does the ARC trade-off model predict net adverse clinical events in dual-risk patients undergoing percutaneous coronary intervention?
The ARC trade-off model successfully stratifies dual-risk PCI patients, identifying those at highest risk for adverse events who may benefit from personalized dual antiplatelet therapy strategies.
Abstract Dual antiplatelet therapy (DAPT) is essential after percutaneous coronary intervention (PCI). Current guidelines recommend 6 to 12 months of DAPT, but managing thrombotic and bleeding risks is challenging, especially in patients with both high bleeding risk (HBR) and high thrombotic risk (HTR). This study aimed to characterize a contemporary dual-risk PCI population (HBR and HTR) and used the Academic Research Consortium (ARC) trade-off model to determine the predominant risk (bleeding or thrombosis) to support personalized DAPT management. All patients who underwent PCI between November 2019 and December 2023 were screened. Dual-risk patients were identified using ARC-HBR criteria for bleeding and European Society of Cardiology (ESC) thrombotic criteria. The ARC trade-off model further stratified these patients into three groups: DRBRTR, based on whether the risk of death from bleeding was lower, similar, or higher than the risk of death from thrombosis. The primary outcome was net adverse clinical events (NACE), defined as a composite of all-cause death, myocardial infarction (MI), stent thrombosis (ST), or major bleeding. Secondary outcomes included individual components of NACE. Among 3,051 PCI patients, 12.4% were identified as dual-risk. The trade-off model stratified these patients into DRBRTR (14.3%) groups. At 18 months, the DRBR>TR group showed a significantly increased risk of NACE (HR 1.77, 95% CI, 1.04 to 3.03, p = 0.03) versus the DRBR=TR group, driven by higher rates of both major bleeding (HR 2.61, 95% CI, 1.08 to 6.67, p = 0.03) and MI/ST (HR 3.36, 95% CI, 1.21 to 9.30, p = 0.02). These findings were confirmed in competing risk analysis using Fine–Gray regression, both for bleeding (HR 3.0, 95% CI, 1.24 to 7.25; p = 0.015) and for thrombotic outcomes (HR 3.13, 95% CI, 1.14 to 8.64; p = 0.027). A contemporary trade-off model successfully stratified the dual-risk population, enabling personalized DAPT strategies for this complex population. Reducing bleeding risk in dual-risk patients may improve clinical outcomes.
Mauro et al. (Fri,) conducted a other in Dual-Risk Patients Undergoing Percutaneous Coronary Intervention. The provided text contains only the journal's editorial board information and no clinical study data.