Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
J Am Coll Cardiol. 2024 Dec 3;84(23):2278-2289. doi: 10.1016/j.jacc.2024.06.054.
The determination of left ventricular diastolic function (LVDF) in patients with significant (≥moderate) mitral regurgitation (MR) poses a complex challenge. We recently validated an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm to estimate LVDF.
This study sought to evaluate the risk of all-cause mortality across AI-ECG LVDF-derived myocardial disease (MD) grades in MR.
This was a retrospective study including all patients in the AI-ECG LVDF study testing group who underwent comprehensive transthoracic echocardiography confirming significant MR and electrocardiogram within 14 days of each other at the Mayo Clinic between September 2001 and April 2023. AI-ECG LVDF status was determined based on the index electrocardiogram and used to categorize patients into 3 stages of MD: MD-1, normal or grade 1 LVDF; MD-2, grade 2 LVDF; and MD-3, grade 3 LVDF.
Of 4,019 patients with significant MR (mean age 69.8 years; 49.0% women), 1,175 (29.2%), 1,881 (46.8%), and 963 (24.0%) were classified by AI-ECG as MD-1, MD-2, and MD-3, respectively. The median mitral effective regurgitant orifice area was 26 mm (Q1-Q3: 20-36 mm). Over a median follow-up of 3.5 years, 1,636 (40.7%) patients died. In multivariable survival analysis adjusted for multiple risk factors, a higher diastolic function grade was independently associated with an increased death risk (MD-2, adjusted HR [aHR]: 1.99; 95% CI: 1.62-2.45; MD-3, aHR: 2.65; 95% CI: 2.11-3.34). These findings were consistent when accounting for mitral valve intervention and across various sensitivity and subgroup analyses.
In patients with significant MR, the grading of LVDF by AI-ECG is independently associated with all-cause mortality.
对于有明显（≥中度）二尖瓣反流（MR）的患者，确定左心室舒张功能（LVDF）是一个复杂的挑战。我们最近验证了一种基于人工智能的心电图（AI-ECG）算法来评估 LVDF。
本研究旨在评估 AI-ECG 左心室舒张功能障碍（MD）分级在 MR 中的全因死亡率风险。
这是一项回顾性研究，纳入了 2001 年 9 月至 2023 年 4 月期间在梅奥诊所接受 AI-ECG LVDF 研究测试组的所有患者，这些患者均接受了全面的经胸超声心动图检查，证实有明显的 MR，并在 14 天内进行了心电图检查。AI-ECG LVDF 状态基于标准心电图确定，并将患者分为 3 个 MD 阶段：MD-1，LVDF 正常或 1 级；MD-2，LVDF 2 级；MD-3，LVDF 3 级。
在 4019 例有明显 MR（平均年龄 69.8 岁；49.0%为女性）的患者中，1175 例（29.2%）、1881 例（46.8%）和 963 例（24.0%）分别被 AI-ECG 分类为 MD-1、MD-2 和 MD-3。二尖瓣有效反流口面积中位数为 26mm（Q1-Q3：20-36mm）。在中位随访 3.5 年后，有 1636 例（40.7%）患者死亡。在多变量生存分析中，调整了多个危险因素后，较高的舒张功能分级与死亡风险增加独立相关（MD-2，调整后的 HR [aHR]：1.99；95%CI：1.62-2.45；MD-3，aHR：2.65；95%CI：2.11-3.34）。当考虑到二尖瓣瓣膜干预和各种敏感性亚组分析时，这些发现是一致的。
在有明显 MR 的患者中，AI-ECG 左心室舒张功能分级与全因死亡率独立相关。
