Risk Analysis of Atrial Fibrillation Based on ECG Phenotypes: The RAF-ECP Study Protocol.

Aiguo Wang, Jiacheng He, Xujian Feng, Jingchun Luo, Wei Chen, Yong Wei, Cuiwei Yang

Abstract read

In one paragraph

Article in Phenomics (Cham, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Alkaline Phosphatase to Albumin Ratio as a Novel Predictor of All-Cause Mortality in Critically Ill Patients With Atrial Fibrillation.Cardiology research and practice · 2025
Article

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5 · Who and what money

Authors and funding

7 authors.

Aiguo Wang *Department of Cardiology, Xinghua City People's Hospital, Jiangsu, 225700 People's Republic of China.ORCID 0000-0001-5989-510X

Jiacheng He *Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200433 People's Republic of China.ORCID 0009-0007-1016-4040

Xujian Feng *Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200433 People's Republic of China.ORCID 0000-0002-8387-9748

Jingchun LuoHuman Phenome Institute, Fudan University, Shanghai, 201203 People's Republic of China.ORCID 0000-0001-5138-6458

Wei ChenCenter for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200433 People's Republic of China.ORCID 0000-0003-3720-718X

Yong WeiDepartment of Cardiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201620 People's Republic of China.ORCID 0000-0002-3996-1365

Cuiwei YangCenter for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200433 People's Republic of China.ORCID 0000-0003-3338-5835

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atrial fibrillation (AF) is the most common supraventricular arrhythmia in clinical practice, and many patients exhibit silent AF. Variables based on Electrocardiogram (ECG) have shown promise in assessing AF risk in the previous study. This study protocol proposes a systematic approach, named RAF-ECP, to evaluate the role of ECG phenotypes in assessing the risk of AF. The protocol aims to standardize the definition and calculation of ECG phenotypes, ensuring consistency and comparability across different research studies and healthcare settings. Data will be collected from multiple clinical laboratories, with an anticipated sample size of 10,000 cases (lead I and II, 10 s) evenly distributed between subjects with and without AF events in one-year time frame. By analyzing ECG data and baseline information, statistical tests and machine learning classifiers will be employed to identify significant risk factors and develop a comprehensive risk assessment model for AF. The anticipated outcomes include hazard ratio values, confidence intervals,

Indexed as

Atrial fibrillation riskElectrocardiogram phenotypesHeart rate variability analysisP-wave features analysisStatistical test

Identifiers

PMID40061824

DOI10.1007/s43657-023-00151-9

PMCPMC11889301

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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.