Aortic Pulse Wave Velocity Determined with Oscillometric Pulse Wave Analysis Algorithm Antares Is an Independent Predictor of Major Adverse Cardiovascular Events: A Prospective Cohort Study

Background/Objectives: Aortic pulse wave velocity (aPWV) is a well-established surrogate marker of arterial stiffness. The Antares algorithm offers a method for determining aPWV from oscillometric blood pressure waveforms without requiring additional inputs. This prospective study aimed to evaluate the association and prognostic value of aPWV, determined by Antares, in predicting major adverse cardiovascular events (MACE). Methods: In total, 240 patients (median age 69, 25.4% female) underwent oscillometric blood pressure measurements, from which aPWV was calculated using the Antares algorithm. MACE, comprising myocardial infarction, stroke, or all-cause mortality, occurred in 19.2% of patients during a median follow-up of 43 months. Survival analyses were performed using continuous aPWV values, a 10 m/s threshold, and aPWV quartiles. Kaplan–Meier curves and log-rank tests were used to compare survival across aPWV groups. Cox proportional hazards models were applied to assess the independent predictive value of aPWV. Results: Patients with aPWV < 10 m/s showed significantly higher event-free survival compared to those with aPWV ≥ 10 m/s (log-rank p = 0.044). Quartile analysis reinforced this, with the highest event rate in the highest aPWV quartile (log-rank p < 0.01). Multivariable analysis confirmed aPWV as an independent predictor of MACE (HR per 1 m/s: 1.24, 95% CI: 1.08–1.41; HR per 1 SD: 1.53, 95% CI: 1.17–2.00, p = 0.002). Adding aPWV to a risk model improved predictive accuracy (C-index 0.68 to 0.71). Conclusions: In the investigated cohort, aPWV derived using the Antares algorithm is an independent predictor of cardiovascular events. This non-invasive approach is promising for improving simple outpatient risk stratification and targeting preventive measures.