Artificial Intelligence Electrocardiography to Predict Atrial Fibrillation in Patients With Chronic Lymphocytic Leukemia

IF 12 1区医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS

Jacc: Cardiooncology Pub Date : 2024-04-01 DOI:10.1016/j.jaccao.2024.02.006

Georgios Christopoulos MD , Zachi I. Attia PhD , Sara J. Achenbach MS , Kari G. Rabe MS , Timothy G. Call MD , Wei Ding MD, PhD , Jose F. Leis MD, PhD , Eli Muchtar MD , Saad S. Kenderian MD , Yucai Wang MD, PhD , Paul J. Hampel MD , Amber B. Koehler PA-C , Neil E. Kay MD , Prashant Kapoor MD , Susan L. Slager PhD , Tait D. Shanafelt MD , Peter A. Noseworthy MD , Paul A. Friedman MD , Joerg Herrmann MD , Sameer A. Parikh MD

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Abstract

Background

The use of an artificial intelligence electrocardiography (AI-ECG) algorithm has demonstrated its reliability in predicting the risk of atrial fibrillation (AF) within the general population.

Objectives

This study aimed to determine the effectiveness of the AI-ECG score in identifying patients with chronic lymphocytic leukemia (CLL) who are at high risk of developing AF.

Methods

We estimated the probability of AF based on AI-ECG among patients with CLL extracted from the Mayo Clinic CLL database. Additionally, we computed the Mayo Clinic CLL AF risk score and determined its ability to predict AF.

Results

Among 754 newly diagnosed patients with CLL, 71.4% were male (median age = 69 years). The median baseline AI-ECG score was 0.02 (range = 0-0.93), with a value ≥0.1 indicating high risk. Over a median follow-up of 5.8 years, the estimated 10-year cumulative risk of AF was 26.1%. Patients with an AI-ECG score of ≥0.1 had a significantly higher risk of AF (HR: 3.9; 95% CI: 2.6-5.7; P < 0.001). This heightened risk remained significant (HR: 2.5; 95% CI: 1.6-3.9; P < 0.001) even after adjusting for the Mayo CLL AF risk score, heart failure, chronic kidney disease, and CLL therapy. In a second cohort of CLL patients treated with a Bruton tyrosine kinase inhibitor (n = 220), a pretreatment AI-ECG score ≥0.1 showed a nonsignificant increase in the risk of AF (HR: 1.7; 95% CI: 0.8-3.6; P = 0.19).

Conclusions

An AI-ECG algorithm, in conjunction with the Mayo CLL AF risk score, can predict the risk of AF in patients with newly diagnosed CLL. Additional studies are needed to determine the role of AI-ECG in predicting AF risk in CLL patients treated with a Bruton tyrosine kinase inhibitor.

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人工智能心电图预测慢性淋巴细胞白血病患者的心房颤动

背景人工智能心电图（AI-ECG）算法的使用证明了它在预测普通人群心房颤动（AF）风险方面的可靠性。方法我们根据梅奥诊所 CLL 数据库中提取的 CLL 患者的 AI-ECG 估算了心房颤动的概率。此外，我们还计算了梅奥诊所 CLL 房颤风险评分，并确定了其预测房颤的能力。结果在 754 名新确诊的 CLL 患者中，71.4% 为男性（中位年龄 = 69 岁）。基线 AI-ECG 评分的中位数为 0.02（范围 = 0-0.93），≥0.1 表示高风险。在中位 5.8 年的随访中，房颤的 10 年累积风险估计为 26.1%。AI-ECG评分≥0.1的患者发生房颤的风险明显更高（HR：3.9；95% CI：2.6-5.7；P <；0.001）。即使对梅奥CLL房颤风险评分、心力衰竭、慢性肾脏病和CLL治疗进行调整后，这种风险的增加仍然很明显（HR：2.5；95% CI：1.6-3.9；P <；0.001）。在第二组接受布鲁顿酪氨酸激酶抑制剂治疗的CLL患者（n = 220）中，治疗前AI-ECG评分≥0.1的患者发生房颤的风险无显著增加（HR：1.7；95% CI：0.8-3.6；P = 0.19）。需要进行更多的研究来确定 AI-ECG 在预测接受布鲁顿酪氨酸激酶抑制剂治疗的 CLL 患者房颤风险中的作用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Jacc: Cardiooncology Multiple-

CiteScore

12.50

自引率

6.30%

发文量

106

期刊介绍： JACC: CardioOncology is a specialized journal that belongs to the esteemed Journal of the American College of Cardiology (JACC) family. Its purpose is to enhance cardiovascular care for cancer patients by publishing high-quality, innovative scientific research and sharing evidence-based knowledge. The journal aims to revolutionize the field of cardio-oncology and actively involve and educate professionals in both cardiovascular and oncology fields. It covers a wide range of topics including pre-clinical, translational, and clinical research, as well as best practices in cardio-oncology. Key areas of focus include understanding disease mechanisms, utilizing in vitro and in vivo models, exploring novel and traditional therapeutics (across Phase I-IV trials), studying epidemiology, employing precision medicine, and investigating primary and secondary prevention. Amyloidosis, cardiovascular risk factors, heart failure, and vascular disease are some examples of the disease states that are of particular interest to the journal. However, it welcomes research on other relevant conditions as well.

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