Dörr Marcus, Lapp Harald, Richter Stefan, Stäuber Alexander, Bahls Martin, Gross Stefan, Ohlow Marc-Alexander, Eckert Siegfried, Stäuber Franziska, Hoppe Matthias Wilhelm, Baulmann Johannes
Department of Internal Medicine B, University Medicine Greifswald, 17475 Greifswald, Germany.
German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, 17475 Greifswald, Germany.
J Clin Med. 2024 Nov 21;13(23):7035. doi: 10.3390/jcm13237035.
: 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). : 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. : Patients with aPWV < 10 m/s showed significantly higher event-free survival compared to those with aPWV ≥ 10 m/s (log-rank = 0.044). Quartile analysis reinforced this, with the highest event rate in the highest aPWV quartile (log-rank < 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, = 0.002). Adding aPWV to a risk model improved predictive accuracy (C-index 0.68 to 0.71). : 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.
主动脉脉搏波速度(aPWV)是一种公认的动脉僵硬度替代标志物。安塔瑞斯算法提供了一种从示波血压波形中确定aPWV的方法,无需额外输入。这项前瞻性研究旨在评估由安塔瑞斯算法确定的aPWV在预测主要不良心血管事件(MACE)中的相关性和预后价值。
总共240例患者(中位年龄69岁,25.4%为女性)接受了示波血压测量,并使用安塔瑞斯算法计算aPWV。在中位随访43个月期间,19.2%的患者发生了MACE,包括心肌梗死、中风或全因死亡率。使用连续的aPWV值、10米/秒的阈值和aPWV四分位数进行生存分析。采用Kaplan-Meier曲线和对数秩检验比较不同aPWV组的生存率。应用Cox比例风险模型评估aPWV的独立预测价值。
与aPWV≥10米/秒的患者相比,aPWV<10米/秒的患者无事件生存率显著更高(对数秩=0.044)。四分位数分析强化了这一点,aPWV最高四分位数的事件发生率最高(对数秩<0.01)。多变量分析证实aPWV是MACE的独立预测因子(每1米/秒的HR:1.24,95%CI:1.08-1.41;每1标准差的HR:1.53,95%CI:1.17-2.00,P=0.002)。将aPWV添加到风险模型中可提高预测准确性(C指数从0.68提高到0.71)。
在该研究队列中,使用安塔瑞斯算法得出的aPWV是心血管事件的独立预测因子。这种非侵入性方法有望改善简单的门诊风险分层并针对性采取预防措施。