Artificial Intelligence-Enhanced Electrocardiogram for Longitudinal Evaluation of Right Ventricular Dysfunction After Acute Pulmonary Embolism: Rational and Design of CURES-CARE Study

20 May 2026

Feiya XuYanshuang LyuZijing LiGuohui FanJing MaXiaomeng ZhangXiaomao XuLisong QiaoYaodan LiangYong QiJunyi ShangJing HanWeijia LiuChengpeng GaoKun YanFajiu LiXuechun WangYue LiZhe ChengShijia GengAili LiPeiran YangShenda HongZhenguo ZhaiDingyi Wang

https://doi.org/10.1002/pul2.70312 

 

Abstract

Right ventricular dysfunction (RVD) due to pulmonary embolism (PE) is associated with poor prognosis and serves as a potential contributor to the occurrence and development of post-PE syndrome (PPES). However, the longitudinal evolution of right ventricular function remains poorly understood due to the limited feasibility of repeated assessments. We aim to characterize the dynamic progression of RVD after acute PE using longitudinal electrocardiogram (ECG) signals analyzed with artificial intelligence (AI), together with selected biomarkers. China pUlmonary thromboembolism REgistry Study-CARioElectro (CURES-CARE) study, a prospective multicenter cohort study, will enroll 500 patients with intermediate- or high-risk acute PE from seven tertiary hospitals in China. All enrolled patients will be followed up for 12 months. During hospitalization, patients will undergo continuous ECG monitoring for 72 h, followed by daily ECG recording by a portable device throughout the follow-up period. Blood samples will be collected at admission, discharge, and at 3, 6, and 12 months. AI-based approaches will be applied to identify dynamic patterns in ECG signals and biomarker trajectories, integrated with biomarkers and imaging, to identify phenotypes of RVD progression and prognosis. CURES-CARE study will determine the incidence and risk factors of persistent RVD after acute PE, explore ECG-derived features associated with RV function, and evaluate the predictive value of multimodal data integration for long-term outcomes of PE. The study is expected to provide new insights into evolution of RVD, enable earlier risk stratification, and inform personalized management strategies to improve long-term outcomes in PE survivors.

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