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The feasibility of the prediction engine as a clinical tool, the SafeHeart Platform, is assessed during the feasibility study.<br /><br /> Development study recruitment commenced in 2021. The feasibility study starts in 2022.<br /><br /> SafeHeart is the first study to prospectively collect a multimodal data set to construct a personalized prediction engine for ICD therapy. Moreover, SafeHeart explores the integration and added value of detailed objective accelerometer data in the prediction of clinical events. The translation of the SafeHeart Platform to clinical practice is examined during the feasibility study.<br /><br />SafeHeart is the first study to prospectively collect a multimodal data set to construct a personalized prediction engine for ICD therapy. Moreover, SafeHeart explores the integration and added value of detailed objective accelerometer data in the prediction of clinical events. The translation of the SafeHeart Platform to clinical practice is examined during the feasibility study.<br /><br /> Using mobile health, vital signs such as heart rate (HR) can be used to assess a patient's recovery process from acute events including acute myocardial infarction (AMI).<br /><br /> We aimed to characterize clinical correlates associated with HR change in the subacute period among patients recovering from AMI.<br /><br /> HR measurements were collected from 91 patients (4447 HR recordings) enrolled in the MiCORE study using the Apple Watch and Corrie smartphone application. Mixed regression models were used to estimate the associations of patient-level characteristics during hospital admission with HR changes over 30 days postdischarge.<br /><br /> The mean daily HR at admission was 78.0 beats per minute (bpm) (95% confidence interval 76.1 to 79.8), declining 0.2 bpm/day (-0.3 to -0.1) under a linear model of HR change. History of coronary artery bypass graft, history of depression, or being discharged on anticoagulants was associated with a higher admission HR. Having a history of hypertension, type 2 diabetes mellitus (T2DM), or hyperlipidemia was associated with a slower decrease in HR over time, but not with HR during admission.<br /><br /> While a declining HR was observed in AMI patients over 30 days postdischarge, patients with hypertension, T2DM, or hyperlipidemia showed a slower decrease in HR relative to their counterparts. This study demonstrates the feasibility of using wearables to model the recovery process of patients with AMI and represents a first step in helping pinpoint patients vulnerable to decompensation.<br /><br />While a declining HR was observed in AMI patients over 30 days postdischarge, patients with hypertension, T2DM, or hyperlipidemia showed a slower decrease in HR relative to their counterparts. This study demonstrates the feasibility of using wearables to model the recovery process of patients with AMI and represents a first step in helping pinpoint patients vulnerable to decompensation.<br /><br /> Telemedicine and commercial wearable devices capable of detecting atrial fibrillation (AF) have revolutionized arrhythmia care during coronavirus disease 2019. However, not much is known about virtual patient-provider interactions or device sharing behaviors.<br /><br /> The purpose of this study was to characterize how participants with or at risk of AF are engaging with their providers in the context of telemedicine and using commercially wearable devices to manage their health.<br /><br /> We developed a survey to describe participant behaviors around telemedicine encounters and commercial wearable device use. The survey was distributed to participants diagnosed with AF or those at risk of AF (as determined by being at least 65 years old and having a CHA<br /><br /> DS<br /><br /> -VASc stroke risk score of &gt;2) in the University of Massachusetts Memorial Health Care system.<br /><br /> The survey was distributed to 23,530 patients, and there were 1222 (5.19%) participant responses. Among the participants, 327 (26.8%) had AF and 895 (73.2%) were at riskdata, telemedicine engagement, and technology use and ownership.<br /><br /> Current symptom management approaches for patients with atrial fibrillation (AF) focus on addressing heart rhythm and do not include management of behavioral or emotional contributors to symptom manifestation or severity.<br /><br /> To inform content development of a digitally delivered AF symptom self-management program by exploring patients' experiences of the impact of AF symptoms and their perspectives on behavioral approaches to symptom management.<br /><br /> This was a qualitative study of 3 focus groups composed of adults living with symptomatic AF. Group transcripts underwent thematic content analysis to identify themes and subthemes. Themes were matched to available self-management strategies that could be adapted for use in a digitally delivered AF symptom self-management program.<br /><br /> Six major themes (with subthemes) were identified symptoms (anxiety, fatigue, stress/other negative emotions, AF-specific symptoms, heart rhythm); social aspects (social impact, social support); AF treatments (medication, procedures); health behaviors (sleep, physical activity, hydration, breathing/mindfulness/relaxation); positive emotions; and AF education and information gathering. Symptom self-management strategies were identified that could be used to address these symptom-related themes.<br /><br /> Patients with AF reported a wide range of emotional, physical, and social impacts of the condition. They endorsed attempts to self-manage symptoms and an interest in learning more about how to effectively self-manage. Findings indicate the potential for a digital self-management program to address existing gaps in AF symptom-related care.<br /><br />Patients with AF reported a wide range of emotional, physical, and social impacts of the condition. They endorsed attempts to self-manage symptoms and an interest in learning more about how to effectively self-manage. Findings indicate the potential for a digital self-management program to address existing gaps in AF symptom-related care.<br /><br /> Atrial fibrillation (AF) is a common heart rhythm disorder that elevates stroke risk. Stroke survivors undergo routine heart rhythm monitoring for AF. Smartwatches are capable of AF detection and potentially can replace traditional cardiac monitoring in stroke patients.<br /><br /> The goal of Pulsewatch is to assess the accuracy, usability, and adherence of a smartwatch-based AF detection system in stroke patients.<br /><br /> The study will consist of two parts. Part I will have 6 focus groups with stroke patients, caretakers, and physicians, and a Hack-a-thon, to inform development of the Pulsewatch system. Part II is a randomized clinical trial with 2 phases designed to assess the accuracy and usability in the first phase (14 days) and adherence in the second phase (30 days). Participants will be randomized in a 31 ratio (intervention to control) for the first phase, and both arms will receive gold-standard electrocardiographic (ECG) monitoring. The intervention group additionally will receive a smartphone/smartwatch dyad with the Pulsewatch applications. Upon completion of 14 days, participants will be re-randomized in a 11 ratio. The intervention group will receive the Pulsewatch system and a handheld ECG device, while the control group will be passively monitored. Participants will complete questionnaires at enrollment and at 14- and 44-day follow-up visits to assess various psychosocial measures and health behaviors.<br /><br /> Part I was completed in August 2019. Enrollment for Part II began September 2019, with expected completion by the end of2021.<br /><br /> Pulsewatch aims to demonstrate that a smartwatch can be accurate for real-time AF detection, and that older stroke patients will find the system usable and will adhere to monitoring.<br /><br />Pulsewatch aims to demonstrate that a smartwatch can be accurate for real-time AF detection, and that older stroke patients will find the system usable and will adhere to monitoring.<br /><br /> Six million Americans suffer from atrial fibrillation (AF), a heart rhythm abnormality that significantly increases the risk of stroke. AF is responsible for 15% of ischemic strokes, which lead to permanent disability in 60% of cases and death in up to 20%. Anticoagulation (AC) is the mainstay for stroke prevention in patients with AF. Despite guidelines recommending AC for patients, up to half of eligible patients are not on AC. Clinical decision support tools in the electronic health record (EHR) can help bridge the disparity in AC prescription for patients with AF.<br /><br /> To enhance and assess the effectiveness of our previous rule-based alert on AC initiation and persistence in a diverse patient population from UMass-Memorial Medical Center and University of Florida at Jacksonville.<br /><br /> Using the EHR, we will track AC initiation and persistence. We will interview both patients and providers to determine a measure of satisfaction with AC management. We will track digital crumbs to better understand the alert's mechanism of effect and further add enhancements. These enhancements will be used to refine the alert and aid in developing an implementation toolkit to facilitate use of the alert at other health systems.<br /><br /> If the number of AC starts, the likelihood of persisting on AC, and the frequency alert use are found to be higher among intervention vs control providers, we believe such findings will confirm our hypothesis on the effectiveness of our alert.<br /><br />If the number of AC starts, the likelihood of persisting on AC, and the frequency alert use are found to be higher among intervention vs control providers, we believe such findings will confirm our hypothesis on the effectiveness of our alert.<br /><br /> Personal digital devices may offer insights into patient recovery and an approach for remote monitoring after procedures.<br /><br /> To examine associations between activity measured using personal digital devices, patient-reported outcome measures (PROMs), and clinical events among patients after catheter ablation for atrial fibrillation (AF) or bariatric surgery.<br /><br /> We aggregated personal digital device, PROM, and electronic health record data in a study conducted at 2 health systems. We used Fitbit devices for step count assessments, KardiaMobile for cardiac rhythm assessments, and PROMs for pain and palpitations over 5 weeks.<br /><br /> Among 59 patients, 30 underwent AF ablation and 29 bariatric surgery. Thirty-six patients (63%) reported pain. [https://www.selleckchem.com/products/azd4547.html selleckchem] There was no difference in median [interquartile range] daily steps between patients with and those without pain (4419 [3286-7041] vs 3498 [2609-5888]; <br /><br /> = .23). Among AF ablation patients, 21 (70%) reported palpitations. Median daily steps were lower among those with palpitations than among those without (4668 [3021-6116] vs 8040 [6853-10,394]; <br /><br /> = .03). When accounting for within-subject correlation, recordings of AF were associated with a significant mean decrease in median daily steps (-351; 95% confidence interval -524 to -177; <br /><br /> &lt;.01). Patients who received a new antiarrhythmic drug prescription had AF recorded in a median of 5 [5-5] of 5 total weeks, whereas patients who did not receive a new antiarrhythmic recorded AF in a median of 1 [0-3] week (<br /><br /> =.02).<br /><br /> Personal digital device and PROM data can provide insight into postprocedural recovery outside of usual clinical settings and may inform follow-up and clinical decision-making. (ClinicalTrials.gov Identifier NCT03436082).<br /><br />Personal digital device and PROM data can provide insight into postprocedural recovery outside of usual clinical settings and may inform follow-up and clinical decision-making. (ClinicalTrials.gov Identifier NCT03436082).