JMIR Cardio
Cardiovascular medicine with focus on electronic, mobile, and digital health approaches in cardiology and for cardiovascular health
Editor-in-Chief:
Andrew J. Coristine, PhD, Affiliate Faculty, Department of Medicine (Division of Cardiology), McGill University (Canada); Scientific Editor, JMIR Publications (Canada)
Impact Factor 2025 CiteScore 3.5
Recent Articles
To prevent the development of cardiovascular diseases, it is a growing priority worldwide to detect a wide range of patients with untreated hypertension and practice adequate blood pressure control with drug therapy. However, few effective tools have been identified that facilitate the initiation of antihypertensive medications in patients with untreated hypertension.
Heart failure (HF) is a complex syndrome associated with high morbidity and mortality and increased healthcare utilisation. Patient education is key to improving health outcomes, achieved by promoting self-management to optimise medical management. Newer digital tools like text messaging and smartphone applications provide novel patient education approaches.
For a decade, despite results from many studies, telemedicine systems have suffered from a lack of recommendations for chronic heart failure (CHF) care because of variable study results. Another limitation is the hospital-based architecture of most telemedicine systems. Some systems use an algorithm based on daily weight, transcutaneous oxygen measurement, and heart rate to detect and treat acute heart failure (AHF) in patients with CHF as early on as possible.
Heart failure (HF) is a burdensome condition and a leading cause of 30-day hospital readmissions in the United States. Clinical and social factors are key drivers of hospitalization. These 2 strategies, digital platforms and home-based social needs care, have shown preliminary effectiveness in improving adherence to clinical care plans and reducing acute care use in HF. Few studies, if any, have tested combining these 2 strategies in a single intervention.
The key to reducing the immense morbidity and mortality burdens of cardiovascular diseases is to help people keep their blood pressure (BP) at safe levels. This requires that more people with hypertension be identified, diagnosed, and given tools to lower their BP. BP monitors are critical to hypertension diagnosis and management. However, there are characteristics of conventional BP monitors (oscillometric cuff sphygmomanometers) that hinder rapid and effective hypertension diagnosis and management. Calibration-free, software-only BP monitors that operate on ubiquitous mobile devices can enable on-demand BP monitoring, overcoming the hardware barriers of conventional BP monitors.
Patients with heart failure (HF) are the most commonly readmitted group of adult patients in Germany. Most patients with HF are readmitted for noncardiovascular reasons. Understanding the relevance of HF management outside the hospital setting is critical to understanding HF and factors that lead to readmission. Application of machine learning (ML) on data from statutory health insurance (SHI) allows the evaluation of large longitudinal data sets representative of the general population to support clinical decision-making.
Heart failure (HF) contributes greatly to morbidity, mortality, and health care costs worldwide. Hospital readmission rates are tracked closely and determine federal reimbursement dollars. No current modality or technology allows for accurate measurement of relevant HF parameters in ambulatory, rural, or underserved settings. This limits the use of telehealth to diagnose or monitor HF in ambulatory patients.
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