Amadio Jennifer M, Grogan Martha, Muchtar Eli, Lopez-Jimenez Francisco, Attia Zachi I, AbouEzzeddine Omar, Lin Grace, Dasari Surendra, Kapa Suraj, Borgeson Daniel D, Friedman Paul A, Gertz Morie A, Murphree Dennis H, Dispenzieri Angela
Department of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, USA.
Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA.
ESC Heart Fail. 2025 Feb;12(1):677-682. doi: 10.1002/ehf2.15061. Epub 2024 Aug 31.
We aim to determine if our previously validated, diagnostic artificial intelligence (AI) electrocardiogram (ECG) model is prognostic for survival among patients with cardiac amyloidosis (CA).
A total of 2533 patients with CA (1834 with light chain amyloidosis (AL), 530 with wild-type transthyretin amyloid protein (ATTRwt) and 169 with hereditary transthyretin amyloid (ATTRv)] were included. An amyloid AI ECG (A2E) score was calculated for each patient reflecting the likelihood of CA. CA stage was calculated using the European modification of the Mayo 2004 criteria for AL and Mayo stage for transthyretin amyloid (ATTR). Risk of death was modelled using Cox proportional hazards, and Kaplan-Meier was used to estimate survival.
Median age of the cohort was 67 [inter-quartile ratio (IQR) 59, 74], and 71.6% were male. The median overall survival for the cohort was 35.6 months [95% confidence interval (CI) 32.3, 39.5]. For AL, ATTRwt and ATTRv, respectively, median survival was 22.9 (95% CI 19.2, 28.2), 47.2 (95% CI 43.4, 52.3) and 61.4 (95% CI 48.7, 75.9) months. On univariate analysis, an increasing A2E score was associated with more than a two-fold risk of all-cause death. On multivariable analysis, the A2E score retained its importance with a risk ratio of 2.0 (95% CI 1.58, 2.55) in the AL group and 2.7 (95% CI 1.81, 4.24) in the ATTR group.
Among patients with AL and ATTR amyloidosis, the A2E model helps to stratify risk of CA and adds another dimension of prognostication.
我们旨在确定我们之前经验证的诊断性人工智能（AI）心电图（ECG）模型对心脏淀粉样变性（CA）患者的生存是否具有预后价值。
共纳入2533例CA患者（1834例轻链淀粉样变性（AL）、530例野生型转甲状腺素蛋白淀粉样变性（ATTRwt）和169例遗传性转甲状腺素蛋白淀粉样变性（ATTRv））。为每位患者计算反映CA可能性的淀粉样蛋白AI心电图（A2E）评分。使用欧洲对2004年梅奥AL标准的修订版以及转甲状腺素蛋白淀粉样变性（ATTR）的梅奥分期来计算CA分期。使用Cox比例风险模型对死亡风险进行建模，并使用Kaplan-Meier法估计生存率。
该队列的中位年龄为67岁[四分位间距（IQR）59,74]，男性占71.6%。该队列的中位总生存期为35.6个月[95%置信区间（CI）32.3,39.5]。对于AL、ATTRwt和ATTRv，中位生存期分别为22.9（95%CI 19.2,28.2）、47.2（95%CI 43.4,52.3）和61.4（95%CI 48.7,75.9）个月。单因素分析显示，A2E评分升高与全因死亡风险增加两倍以上相关。多变量分析显示，A2E评分在AL组的风险比为2.0（95%CI 1.58,2.55），在ATTR组为2.7（95%CI 1.81,4.24），仍具有重要意义。
在AL和ATTR淀粉样变性患者中，A2E模型有助于对CA风险进行分层，并增加了预后的另一个维度。
