Technology and Device Management
This patient-facing educational handout explains the process, risks, and safeguards involved when patients with legacy (non–MRI-conditional) pacemakers or implantable cardioverter defibrillators (ICDs) undergo MRI imaging. It is designed to support…
Read MoreThis patient-facing educational handout provides clear, step-by-step guidance to help reduce infection risk and support optimal recovery for patients undergoing implantable cardiac device procedures. Designed for use before pacemaker, ICD,…
Read MoreThe Cardiocases website provides example device tracings and useful explanations to help clinicians improve their skills. The content is provided in English and French – just click on the appropriate…
Read MorePresentations and Graphics: In this slideshow presentation, the learner will explore the mission and history of the FDA and Center for Device and Radiological Health (CDRH), how the CDRH and FDA contribute to a device’s classification, approval, and post-approval maintenance, and an overview of the Total Product Lifecycle Advisory Program Pilot.
Read MorePresentations and Graphics: In this presentation, the learner will explore the purpose and structure of a medical device advisory committee, how they function, and recent guidance.
Read MorePresentations and Graphics: Slideshow presentation that explores collaborative communities, early feasibility studies, and the EP EFS initiative.
Read MorePresentations and Graphics: Slideshow presentation that explore what an investigational device exemption is, significant risk versus non-significant risk device studies, and how IRB’s and the FDA factor in to decisions around device studies.
Read MorePresentations and Graphics: Succinct presentation slides exploring heart rhythm device recalls, FDA’s roles and responsibilities relating to recalls, and recall communications. Also includes risk assessment and mitigation for recalled devices.
Read MoreJournal Articles: Atrial fibrillation (AF) is the most common cardiac arrhythmia diagnosed and treated in the world. The treatment of patients’ symptoms as well as the prevention of stroke and heart failure is dependent on accurate detection and characterization of AF. A variety of electrocardiographic (ECG) monitoring techniques are being used for these purposes. However, these intermittent ECG monitoring techniques have been shown to underdiagnose AF events while having limited ability to characterize AF burden and density. Continuous long-term implantable loop recorder (ILR)–based ECG monitoring has been designed to overcome these limitations. This technology is being increasingly used to diagnose episodes of AF in high-risk patients and to improve characterization of AF episodes in patients with known AF. This review aims to review the potential clinical utility of ILR-based ECG monitoring while highlighting some inherent limitations of the current technology. An understanding of these limitations is important when considering the use of ILR-based ECG monitoring and clinical decision making based on the information being stored within these devices.
Read MoreJournal Articles: BACKGROUND Multiple smart devices capable to detect atrial fibrillation (AF) are presently available. Sensitivity and specificity for the detection of AF may differ between available smart devices, and this has not yet been adequately investigated. OBJECTIVES The aim was to assess the accuracy of 5 smart devices in identifying AF compared with a physician interpreted 12-lead electrocardiogram as the reference standard in a real-world cohort of patients. METHODS We consecutively enrolled patients presenting to a cardiology service at a tertiary referral center in a prospective, diagnostic study. RESULTS We prospectively analyzed 201 patients (31% women, median age 66.7 years). AF was present in 62 (31%) patients. Sensitivity and specificity for the detection of AF were comparable between devices: 85% and 75% for the Apple Watch 6, 85% and 75% for the Samsung Galaxy Watch 3, 58% and 75% for the Withings Scanwatch, 66% and 79% for the Fitbit Sense, and 79% and 69% for the AliveCor KardiaMobile, respectively. The rate of inconclusive tracings (the algorithm was unable to determine the heart rhythm) was 18%, 17%, 24%, 21%, and 26% for the Apple Watch 6, Samsung Galaxy Watch 3, Withings Scan Watch, Fitbit Sense, and AliveCor KardiaMobile (P < 0.01 for pairwise comparison), respectively. By manual review of inconclusive tracings, the rhythm could be determined in 955 (99%) of 969 single-lead electrocardiograms. Regarding patient acceptance, the Apple Watch was ranked first (39% of participants). CONCLUSIONS In this clinical validation of 5 direct-to-consumer smart devices, we found differences in the amount of inconclusive tracings diminishing sensitivity and specificity of the smart devices. In a clinical setting, manual review of tracings is required in about one-fourth of cases.
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