Atherosclerosis is a diffuse disease which may lead to the development of unstable atherosclerotic plaque. Its rupture can result in acute ischemic event. The atherosclerotic plaques with a mobile component are typical presentations of such instability and patients with these plaques are at high risk of acute ischemic events. In the current literature, substantial data regarding the mobile atherosclerotic plaques in carotid arteries and thoracic aorta is published. However there are almost no data concerning the mobile plaques in the peripheral arteries of the lower limbs. We present a rare case of a patient with generalized atherosclerosis, in whom an asymptomatic mobile atherosclerotic plaque in the common femoral artery with a high embolic potential was diagnosed. This plaque was successfully removed by femoral endarterectomy. On the basis of this case, we review the possibilities and limitations of the current imaging methods in detection of mobile plaques in the peripheral arteries. Moreover optimal therapeutic approaches in such patients are discussed.
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Front Digit Health
November 2024
Hello Heart, Inc., Menlo Park, CA, United States.
Background: Current atherosclerotic cardiovascular disease (ASCVD) risk assessment tools like the Pooled Cohort Equations (PCEs) and PREVENT™ scores offer long-term predictions but may not effectively drive behavior change. Short-term risk predictions using mobile health (mHealth) data and electronic health records (EHRs) could enhance clinical decision-making and patient engagement. The aim of this study was to develop a short-term ASCVD risk prediction model for hypertensive individuals using mHealth and EHR data and compare its performance to existing risk assessment tools.
View Article and Find Full Text PDFWest Afr J Med
November 2024
Department of Medicine, University of Jos/Jos University Teaching Hospital, Jos. Email:
Introduction/background: Assessing cardiovascular disease (CVD) risk is necessary in preventive cardiology. Studies have imputed CVD risk factors in algorithms to predict ASCVD. These various scores were derived from risk equations acquired from other populations.
View Article and Find Full Text PDFWest Afr J Med
November 2024
Department of Medicine, University of Jos/Jos University Teaching Hospital, Jos. Email:
Introduction/background: Assessing cardiovascular disease (CVD) risk is necessary in preventive cardiology. Studies have imputed CVD risk factors in algorithms to predict ASCVD. These various scores were derived from risk equations acquired from other populations.
View Article and Find Full Text PDFJMIR Public Health Surveill
October 2024
Faculty of Health Sciences, University of Maribor, Maribor, Slovenia.
Front Cardiovasc Med
September 2024
CHANGE Research Working Group, Carrera de Medicina Humana, Facultad de Ciencias de la Salud, Universidad Científica del Sur, Lima, Peru.
Introduction: mHealth apps (MHA) are emerging as promising tools for cardiovascular risk assessment, but few meet the standards required for clinical use. We aim to evaluate the quality and functionality of mHealth apps for cardiovascular risk assessment by healthcare professionals.
Methods: We conducted a systematic review of MHA for cardiovascular risk assessment in the Apple Store, Play Store, and Microsoft Store until August 2023.
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