Evidence map›Paper›PMID 42254875›Full record

ArticlePulmonary circulation2026

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

Feiya Xu, Yanshuang Lyu, Zijing Li, Guohui Fan, Jing Ma, Xiaomeng Zhang, Xiaomao Xu, Lisong Qiao, Yaodan Liang, Yong Qi and 15 more

Abstract read
In one paragraph

Article in Pulmonary circulation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

25 authors.

Feiya XuChina-Japan Friendship Hospital (Institute of Clinical Medical Sciences) Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.
Yanshuang LyuState Key Laboratory of Respiratory Health and Multimorbidity, Department of Physiology, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College Beijing China.
Zijing LiChina-Japan Friendship Hospital (Institute of Clinical Medical Sciences) Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.
Guohui FanNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College; Department of Clinical research and Data management, Center of Respiratory Medicine China-Japan Friendship Hospital Beijing China.
Jing MaNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine China-Japan Friendship Hospital Beijing China.
Xiaomeng ZhangNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine China-Japan Friendship Hospital Beijing China.
Xiaomao XuDepartment of Pulmonary and Critical Care Medicine, Beijing Hospital; National Center of Gerontology; Institute of Geriatric Medicine Chinese Academy of Medical Sciences Beijing China.
Lisong QiaoDepartment of Pulmonary and Critical Care Medicine, Beijing Hospital; National Center of Gerontology; Institute of Geriatric Medicine Chinese Academy of Medical Sciences Beijing China.
Yaodan LiangDepartment of Pulmonary and Critical Care Medicine, Beijing Hospital; National Center of Gerontology; Institute of Geriatric Medicine Chinese Academy of Medical Sciences Beijing China.
Yong QiDepartment of Respiratory and Critical Care Medicine Henan Provincial People's Hospital Zhengzhou China.ORCID https://orcid.org/0000-0002-2653-1307
Junyi ShangDepartment of Respiratory and Critical Care Medicine Henan Provincial People's Hospital Zhengzhou China.ORCID https://orcid.org/0000-0002-1336-4941
Jing HanDepartment of Pulmonary and Critical Care Medicine Guizhou Provincial People's Hospital Guiyang China.
Weijia LiuGuizhou Health Vocational College Tongren Guizhou China.
Chengpeng GaoDepartment of Respiratory Medicine Weifang People's Hospital Weifang China.
Kun YanDepartment of Respiratory Medicine Weifang People's Hospital Weifang China.
Fajiu LiDepartment of Pulmonary and Critical Care Medicine The Sixth Hospital of Wuhan, Affiliated Hospital of Jianghan University Wuhan China.ORCID https://orcid.org/0009-0009-9594-5157
Xuechun WangDepartment of Pulmonary and Critical Care Medicine The Sixth Hospital of Wuhan, Affiliated Hospital of Jianghan University Wuhan China.
Yue LiDepartment of Pulmonary and Critical Care Medicine The First Affiliated Hospital of Zhengzhou University Zhengzhou China.
Zhe ChengDepartment of Pulmonary and Critical Care Medicine The First Affiliated Hospital of Zhengzhou University Zhengzhou China.
Shijia GengNational Institute of Health Data Science Peking University Beijing China.
Aili LiDepartment of Cardiology China-Japan Friendship Hospital Beijing China.
Peiran YangDepartment of Physiology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College Beijing China.
Shenda HongNational Institute of Health Data Science Peking University Beijing China.ORCID https://orcid.org/0000-0001-7521-5127
Zhenguo ZhaiNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine China-Japan Friendship Hospital Beijing China.ORCID https://orcid.org/0000-0002-7096-8792
Dingyi WangNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College; Department of Clinical research and Data management, Center of Respiratory Medicine China-Japan Friendship Hospital Beijing China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

artificial intelligenceechocardiographyelectrocardiogrampulmonary embolismright ventricular dysfunction

Identifiers

PMID42254875
PMCPMC13238698

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.