TY - JOUR AU - Goni, Leticia AU - de la O, Víctor AU - Barrio-López, Teresa M. AU - Ramos, Pablo AU - Tercedor, Luis AU - Ibañez-Criado, Luis Jose AU - Castellanos, Eduardo AU - Ibañez Criado, Alicia AU - Macias Ruiz, Rosa AU - García-Bolao, Ignacio AU - Almendral, Jesus AU - Martínez-González, Ángel Miguel AU - Ruiz-Canela, Miguel PY - 2020/12/7 TI - A Remote Nutritional Intervention to Change the Dietary Habits of Patients Undergoing Ablation of Atrial Fibrillation: Randomized Controlled Trial JO - J Med Internet Res SP - e21436 VL - 22 IS - 12 KW - atrial fibrillation KW - secondary prevention KW - remote intervention KW - Mediterranean diet KW - olive oil N2 - Background: The Prevention With Mediterranean Diet (PREDIMED) trial supported the effectiveness of a nutritional intervention conducted by a dietitian to prevent cardiovascular disease. However, the effect of a remote intervention to follow the Mediterranean diet has been less explored. Objective: This study aims to assess the effectiveness of a remotely provided Mediterranean diet?based nutritional intervention in obtaining favorable dietary changes in the context of a secondary prevention trial of atrial fibrillation (AF). Methods: The PREvention of recurrent arrhythmias with Mediterranean diet (PREDIMAR) study is a 2-year multicenter, randomized, controlled, single-blinded trial to assess the effect of the Mediterranean diet enriched with extra virgin olive oil (EVOO) on the prevention of atrial tachyarrhythmia recurrence after catheter ablation. Participants in sinus rhythm after ablation were randomly assigned to an intervention group (Mediterranean diet enriched with EVOO) or a control group (usual clinical care). The remote nutritional intervention included phone contacts (1 per 3 months) and web-based interventions with provision of dietary recommendations, and participants had access to a web page, a mobile app, and printed resources. The information is divided into 6 areas: Recommended foods, Menus, News and Online resources, Practical tips, Mediterranean diet classroom, and Your personal experience. At baseline and at 1-year and 2-year follow-up, the 14-item Mediterranean Diet Adherence Screener (MEDAS) questionnaire and a semiquantitative food frequency questionnaire were collected by a dietitian by phone. Results: A total of 720 subjects were randomized (365 to the intervention group, 355 to the control group). Up to September 2020, 560 subjects completed the first year (560/574, retention rate 95.6%) and 304 completed the second year (304/322, retention rate 94.4%) of the intervention. After 24 months of follow-up, increased adherence to the Mediterranean diet was observed in both groups, but the improvement was significantly higher in the intervention group than in the control group (net between-group difference: 1.8 points in the MEDAS questionnaire (95% CI 1.4-2.2; P<.001). Compared with the control group, the Mediterranean diet intervention group showed a significant increase in the consumption of fruits (P<.001), olive oil (P<.001), whole grain cereals (P=.002), pulses (P<.001), nuts (P<.001), white fish (P<.001), fatty fish (P<.001), and white meat (P=.007), and a significant reduction in refined cereals (P<.001), red and processed meat (P<.001), and sweets (P<.001) at 2 years of intervention. In terms of nutrients, the intervention group significantly increased their intake of omega-3 (P<.001) and fiber (P<.001), and they decreased their intake of carbohydrates (P=.02) and saturated fatty acids (P<.001) compared with the control group. Conclusions: The remote nutritional intervention using a website and phone calls seems to be effective in increasing adherence to the Mediterranean diet pattern among AF patients treated with catheter ablation. Trial Registration: ClinicalTrials.gov NCT03053843; https://www.clinicaltrials.gov/ct2/show/NCT03053843 UR - http://www.jmir.org/2020/12/e21436/ UR - http://dx.doi.org/10.2196/21436 UR - http://www.ncbi.nlm.nih.gov/pubmed/33284131 ID - info:doi/10.2196/21436 ER - TY - JOUR AU - de Lusignan, Simon AU - Hobbs, Richard F. D. AU - Liyanage, Harshana AU - Ferreira, Filipa AU - Tripathy, Manasa AU - Munro, Neil AU - Feher, Michael AU - Joy, Mark PY - 2020/11/9 TI - Improving the Management of Atrial Fibrillation in General Practice: Protocol for a Mixed Methods Study JO - JMIR Res Protoc SP - e21259 VL - 9 IS - 11 KW - atrial fibrillation KW - medical record systems, computerized KW - general practice KW - cross-sectional studies KW - qualitative research N2 - Background: Atrial fibrillation (AF) is one of the commonest arrhythmias observed in general practice. The thromboembolic complications of AF include transient ischemic attack, stroke, and pulmonary embolism. Early recognition of AF can lead to early intervention with managing the risks of these complications. Objective: The primary aim of this study is to investigate if patients are managed in general practice according to current national guidelines. In addition, the study will evaluate the impact of direct oral anticoagulant use with respect to AF complications in a real-world dataset. The secondary aims of the study are to develop a dashboard that will allow monitoring the management of AF in general practice and evaluate the usability of the dashboard. Methods: The study was conducted in 2 phases. The initial phase was a quantitative analysis of routinely collected primary care data from the Oxford Royal College of General Practitioners Research and Surveillance Center (RCGP RSC) sentinel network database. AF cases from 2009 to 2019 were identified. The study investigated the impact of the use of anticoagulants on complications of AF over this time period. We used this dataset to examine how AF was managed in primary care during the last decade. The second phase involved development of an online dashboard for monitoring management of AF in general practice. We conducted a usability evaluation for the dashboard to identify usability issues and performed enhancements to improve usability. Results: We received funding for both phases in January 2019 and received approval from the RCGP RSC research committee in March 2019. We completed data extraction for phase 1 in May 2019 and completed analysis in December 2019. We completed building the AF dashboard in May 2019. We started recruiting participants for phase 1 in May 2019 and concluded data collection in July 2019. We completed data analysis for phase 2 in October 2019. The results are expected to be published in the second half of 2020. As of October 2020, the publications reporting the results are under review. Conclusions: Results of this study will provide an insight into the current trends in management of AF using real-world data from the Oxford RCGP RSC database. We anticipate that the outcomes of this study will be used to guide the development and implementation of an audit-based intervention tool to assist practitioners in identifying and managing AF in primary care. International Registered Report Identifier (IRRID): RR1-10.2196/21259 UR - https://www.researchprotocols.org/2020/11/e21259 UR - http://dx.doi.org/10.2196/21259 UR - http://www.ncbi.nlm.nih.gov/pubmed/33164903 ID - info:doi/10.2196/21259 ER - TY - JOUR AU - Jiang, Jiang AU - Gu, Xiang AU - Cheng, Chen-Di AU - Li, Hong-Xiao AU - Sun, Xiao-Lin AU - Duan, Ruo-Yu AU - Zhu, Ye AU - Sun, Lei AU - Chen, Fu-Kun AU - Bao, Zheng-Yu AU - Zhang, Yi AU - Shen, Jian-Hua PY - 2020/10/21 TI - The Hospital-Community-Family?Based Telemedicine (HCFT-AF) Program for Integrative Management of Patients With Atrial Fibrillation: Pilot Feasibility Study JO - JMIR Mhealth Uhealth SP - e22137 VL - 8 IS - 10 KW - atrial fibrillation KW - integrative management KW - telemedicine KW - self-management KW - feasibility study N2 - Background: The potential effectiveness of integrated management in further improving the prognosis of patients with atrial fibrillation has been demonstrated; however, the best strategy for implementation remains to be discovered. Objective: The aim of this study was to ascertain the feasibility of implementing integrated atrial fibrillation care via the Hospital-Community-Family?Based Telemedicine (HCFT-AF) program. Methods: In this single-arm, pre-post design pilot study, a multidisciplinary teamwork, supported by efficient infrastructures, provided patients with integrated atrial fibrillation care following the Atrial fibrillation Better Care (ABC) pathway. Eligible patients were continuously recruited and followed up for at least 4 months. The patients? drug adherence, and atrial fibrillation?relevant lifestyles and behaviors were assessed at baseline and at 4 months. The acceptability, feasibility, and usability of the HCFT-AF technology devices and engagement with the HCFT-AF program were assessed at 4 months. Results: A total of 73 patients (mean age, 68.42 years; 52% male) were enrolled in November 2019 with a median follow up of 132 days (IQR 125?138 days). The patients? drug adherence significantly improved after the 4-month intervention (P<.001). The vast majority (94%, 64/68) of indicated patients received anticoagulant therapy at 4 months, and none of them received antiplatelet therapy unless there was an additional indication. The atrial fibrillation?relevant lifestyles and behaviors ameliorated to varying degrees at the end of the study. In general, the majority of patients provided good feedback on the HCFT-AF intervention. More than three-quarters (76%, 54/71) of patients used the software or website more than once a week and accomplished clinic visits as scheduled. Conclusions: The atrial fibrillation?integrated care model described in this study is associated with improved drug adherence, standardized therapy rate, and lifestyles of patients, which highlights the possibility to better deliver integrated atrial fibrillation management. Trial Registration: Clinicaltrials.gov NCT04127799; https://clinicaltrials.gov/ct2/show/NCT04127799 UR - http://mhealth.jmir.org/2020/10/e22137/ UR - http://dx.doi.org/10.2196/22137 UR - http://www.ncbi.nlm.nih.gov/pubmed/33084588 ID - info:doi/10.2196/22137 ER - TY - JOUR AU - Giebel, D. Godwin PY - 2020/10/6 TI - Use of mHealth Devices to Screen for Atrial Fibrillation: Cost-Effectiveness Analysis JO - JMIR Mhealth Uhealth SP - e20496 VL - 8 IS - 10 KW - mHealth KW - atrial fibrillation KW - screening devices KW - strokes KW - cost-effectiveness KW - photoplethysmography N2 - Background: With an estimated prevalence of around 3% and an about 2.5-fold increased risk of stroke, atrial fibrillation (AF) is a serious threat for patients and a high economic burden for health care systems all over the world. Patients with AF could benefit from screening through mobile health (mHealth) devices. Thus, an early diagnosis is possible with mHealth devices, and the risk for stroke can be markedly reduced by using anticoagulation therapy. Objective: The aim of this work was to assess the cost-effectiveness of algorithm-based screening for AF with the aid of photoplethysmography wrist-worn mHealth devices. Even if prevented strokes and prevented deaths from stroke are the most relevant patient outcomes, direct costs were defined as the primary outcome. Methods: A Monte Carlo simulation was conducted based on a developed state-transition model; 30,000 patients for each CHA2DS2-VASc (Congestive heart failure, Hypertension, Age?75 years, Diabetes mellitus, Stroke, Vascular disease, Age 65-74 years, Sex category [female]) score from 1 to 9 were simulated. The first simulation served to estimate the economic burden of AF without the use of mHealth devices. The second simulation served to simulate the economic burden of AF with the use of mHealth devices. Afterwards, the groups were compared in terms of costs, prevented strokes, and deaths from strokes. Results: The CHA2DS2-VASc score as well as the electrocardiography (ECG) confirmation rate had the biggest impact on costs as well as number of strokes. The higher the risk score, the lower were the costs per prevented stroke. Higher ECG confirmation rates intensified this effect. The effect was not seen in groups with lower risk scores. Over 10 years, the use of mHealth (assuming a 75% ECG confirmation rate) resulted in additional costs (?1=US $1.12) of ?441, ?567, ?536, ?520, ?606, ?625, ?623, ?692, and ?847 per patient for a CHA2DS2-VASc score of 1 to 9, respectively. The number of prevented strokes tended to be higher in groups with high risk for stroke. Higher ECG confirmation rates led to higher numbers of prevented strokes. The use of mHealth (assuming a 75% ECG confirmation rate) resulted in 25 (7), ?68 (?54), 98 (?5), 266 (182), 346 (271), 642 (440), 722 (599), 1111 (815), and 1116 (928) prevented strokes (fatal) for CHA2DS2-VASc score of 1 to 9, respectively. Higher device accuracy in terms of sensitivity led to even more prevented fatal strokes. Conclusions: The use of mHealth devices to screen for AF leads to increased costs but also a reduction in the incidence of stroke. In particular, in patients with high CHA2DS2-VASc scores, the risk for stroke and death from stroke can be markedly reduced. UR - http://mhealth.jmir.org/2020/10/e20496/ UR - http://dx.doi.org/10.2196/20496 UR - http://www.ncbi.nlm.nih.gov/pubmed/33021489 ID - info:doi/10.2196/20496 ER - TY - JOUR AU - Cher, Piang Boon AU - Kembhavi, Gayatri AU - Toh, Yee Kai AU - Audimulam, Jananie AU - Chia, Aloysius Wei-Yan AU - Vrijhoef, JM Hubertus AU - Lim, Wei Yee AU - Lim, Wei Toon PY - 2020/9/17 TI - Understanding the Attitudes of Clinicians and Patients Toward a Self-Management eHealth Tool for Atrial Fibrillation: Qualitative Study JO - JMIR Hum Factors SP - e15492 VL - 7 IS - 3 KW - mHealth KW - qualitative research KW - atrial fibrillation KW - self-management KW - chronic disease KW - mobile phone N2 - Background: Atrial fibrillation (AF) is the most common heart rhythm disorder and poses a growing disease burden worldwide because of an aging population. A multidisciplinary approach with an emphasis on patient education and self-management has been demonstrated to improve outcomes for AF through the engagement of patients in their own care. Although electronic tools (e-tools) such as apps have been proposed to provide patient education and facilitate self-management, there have been few studies to guide the development of these tools for patients with AF. Objective: This study aims to explore the perceptions of patients and health care providers (HCPs) and their attitudes toward the use of e-tools for the self-management of AF. It also seeks to elicit the factors that contribute to these attitudes. Methods: Semistructured qualitative interviews with HCPs and patients were conducted to understand the interpretations and expectations of an e-tool that would be used for the self-management of AF. Interview data were analyzed using an exploratory thematic analysis approach to uncover emergent themes and infer ideas of preferred features in a device. A modified technology acceptance model was developed as a framework to help interpret these findings. Data from the HCPs and patients were compared and contrasted. Results: Both patients and HCPs thought that an e-tool would be useful in the self-management of AF. Although both groups favored educational content and monitoring of blood pressure, patients expressed more passivity toward self-care and an ambivalence toward the use of technology to monitor their medical condition. This appears to be related to factors such as a patient?s age, social support, and their attitudes toward technology. Instead, they favored using the app to contact their HCPs. Conclusions: This study provides insights into significant differences in the attitudes of patients and HCPs toward the use of e-tools for self-care against their priorities. Understanding patients? motivations and their needs are key to ensuring higher acceptance of such tools. UR - http://humanfactors.jmir.org/2020/3/e15492/ UR - http://dx.doi.org/10.2196/15492 UR - http://www.ncbi.nlm.nih.gov/pubmed/32940611 ID - info:doi/10.2196/15492 ER - TY - JOUR AU - Guhl, Emily AU - Althouse, D. Andrew AU - Pusateri, M. Alexandra AU - Kimani, Everlyne AU - Paasche-Orlow, K. Michael AU - Bickmore, W. Timothy AU - Magnani, W. Jared PY - 2020/9/4 TI - The Atrial Fibrillation Health Literacy Information Technology Trial: Pilot Trial of a Mobile Health App for Atrial Fibrillation JO - JMIR Cardio SP - e17162 VL - 4 IS - 1 KW - atrial fibrillation KW - health-related quality of life KW - medication adherence KW - health literacy KW - mobile phone N2 - Background: Atrial fibrillation (AF) is a common arrhythmia that adversely affects health-related quality of life (HRQoL). We conducted a pilot trial of individuals with AF using a smartphone to provide a relational agent as well as rhythm monitoring. We employed our pilot to measure acceptability and adherence and to assess its effectiveness in improving HRQoL and adherence. Objective: This study aims to measure acceptability and adherence and to assess its effectiveness to improve HRQoL and adherence. Methods: Participants were recruited from ambulatory clinics and randomized to a 30-day intervention or usual care. We collected baseline characteristics and conducted baseline and 30-day assessments of HRQoL using the Atrial Fibrillation Effect on Quality of Life (AFEQT) measure and self-reported adherence to anticoagulation. The intervention consisted of a smartphone-based relational agent, which simulates face-to-face counseling and delivered content on AF education, adherence, and symptom monitoring with prompted rhythm monitoring. We compared differences in AFEQT and adherence at 30 days, adjusted for baseline values. We quantified participants? use and acceptability of the intervention. Results: A total of 120 participants were recruited and randomized (59 to control and 61 to intervention) to the pilot trial (mean age 72.1 years, SD 9.10; 62/120, 51.7% women). The control group had a 95% follow-up, and the intervention group had a 93% follow-up. The intervention group demonstrated significantly higher improvement in total AFEQT scores (adjusted mean difference 4.5; 95% CI 0.6-8.3; P=.03) and in daily activity (adjusted mean difference 7.1; 95% CI 1.8-12.4; P=.009) compared with the control between baseline and 30 days. The intervention group showed significantly improved self-reported adherence to anticoagulation therapy at 30 days (intervention 3.5%; control 23.2%; adjusted difference 16.6%; 95% CI 2.8%-30.4%; P<.001). Qualitative assessments of acceptability identified that participants found the relational agent useful, informative, and trustworthy. Conclusions: Individuals randomized to a 30-day smartphone intervention with a relational agent and rhythm monitoring showed significant improvement in HRQoL and adherence. Participants had favorable acceptability of the intervention with both objective use and qualitative assessments of acceptability. UR - http://cardio.jmir.org/2020/1/e17162/ UR - http://dx.doi.org/10.2196/17162 UR - http://www.ncbi.nlm.nih.gov/pubmed/32886070 ID - info:doi/10.2196/17162 ER - TY - JOUR AU - Andersen, Osman Tariq AU - Langstrup, Henriette AU - Lomborg, Stine PY - 2020/7/20 TI - Experiences With Wearable Activity Data During Self-Care by Chronic Heart Patients: Qualitative Study JO - J Med Internet Res SP - e15873 VL - 22 IS - 7 KW - consumer health information KW - wearable electronic devices KW - self-care KW - chronic illness KW - patient experiences N2 - Background: Most commercial activity trackers are developed as consumer devices and not as clinical devices. The aim is to monitor and motivate sport activities, healthy living, and similar wellness purposes, and the devices are not designed to support care management in a clinical context. There are great expectations for using wearable sensor devices in health care settings, and the separate realms of wellness tracking and disease self-monitoring are increasingly becoming blurred. However, patients? experiences with activity tracking technologies designed for use outside the clinical context have received little academic attention. Objective: This study aimed to contribute to understanding how patients with a chronic disease experience activity data from consumer self-tracking devices related to self-care and their chronic illness. Our research question was: ?How do patients with heart disease experience activity data in relation to self-care and chronic illness?? Methods: We conducted a qualitative interview study with patients with chronic heart disease (n=27) who had an implanted cardioverter-defibrillator. Patients were invited to wear a FitBit Alta HR wearable activity tracker for 3-12 months and provide their perspectives on their experiences with step, sleep, and heart rate data. The average age was 57.2 years (25 men and 2 women), and patients used the tracker for 4-49 weeks (mean 26.1 weeks). Semistructured interviews (n=66) were conducted with patients 2?3 times and were analyzed iteratively in workshops using thematic analysis and abductive reasoning logic. Results: Of the 27 patients, 18 related the heart rate, sleep, and step count data directly to their heart disease. Wearable activity trackers actualized patients? experiences across 3 dimensions with a spectrum of contrasting experiences: (1) knowing, which spanned gaining insight and evoking doubts; (2) feeling, which spanned being reassured and becoming anxious; and (3) evaluating, which spanned promoting improvements and exposing failure. Conclusions: Patients? experiences could reside more on one end of the spectrum, could reside across all 3 dimensions, or could combine contrasting positions and even move across the spectrum over time. Activity data from wearable devices may be a resource for self-care; however, the data may simultaneously constrain and create uncertainty, fear, and anxiety. By showing how patients experience self-tracking data across dimensions of knowing, feeling, and evaluating, we point toward the richness and complexity of these data experiences in the context of chronic illness and self-care. UR - https://www.jmir.org/2020/7/e15873 UR - http://dx.doi.org/10.2196/15873 UR - http://www.ncbi.nlm.nih.gov/pubmed/32706663 ID - info:doi/10.2196/15873 ER - TY - JOUR AU - Ferguson, Caleb AU - Inglis, C. Sally AU - Breen, P. Paul AU - Gargiulo, D. Gaetano AU - Byiers, Victoria AU - Macdonald, S. Peter AU - Hickman, D. Louise PY - 2020/6/18 TI - Clinician Perspectives on the Design and Application of Wearable Cardiac Technologies for Older Adults: Qualitative Study JO - JMIR Aging SP - e17299 VL - 3 IS - 1 KW - technology KW - arrhythmia KW - monitoring KW - older people KW - cardiology KW - qualitative KW - wearable N2 - Background: New wearable devices (for example, AliveCor or Zio patch) offer promise in detecting arrhythmia and monitoring cardiac health status, among other clinically useful parameters in older adults. However, the clinical utility and usability from the perspectives of clinicians is largely unexplored. Objective: This study aimed to explore clinician perspectives on the use of wearable cardiac monitoring technology for older adults. Methods: A descriptive qualitative study was conducted using semistructured focus group interviews. Clinicians were recruited through purposive sampling of physicians, nurses, and allied health staff working in 3 tertiary-level hospitals. Verbatim transcripts were analyzed using thematic content analysis to identify themes. Results: Clinicians representing physicians, nurses, and allied health staff working in 3 tertiary-level hospitals completed 4 focus group interviews between May 2019 and July 2019. There were 50 participants (28 men and 22 women), including cardiologists, geriatricians, nurses, and allied health staff. The focus groups generated the following 3 overarching, interrelated themes: (1) the current state of play, understanding the perceived challenges of patient cardiac monitoring in hospitals, (2) priorities in cardiac monitoring, what parameters new technologies should measure, and (3) cardiac monitoring of the future, ?the ideal device.? Conclusions: There remain pitfalls related to the design of wearable cardiac technology for older adults that present clinical challenges. These pitfalls and challenges likely negatively impact the uptake of wearable cardiac monitoring in routine clinical care. Partnering with clinicians and patients in the co-design of new wearable cardiac monitoring technologies is critical to optimize the use of these devices and their uptake in clinical care. UR - http://aging.jmir.org/2020/1/e17299/ UR - http://dx.doi.org/10.2196/17299 UR - http://www.ncbi.nlm.nih.gov/pubmed/32554377 ID - info:doi/10.2196/17299 ER - TY - JOUR AU - Kwon, Soonil AU - Hong, Joonki AU - Choi, Eue-Keun AU - Lee, Byunghwan AU - Baik, Changhyun AU - Lee, Euijae AU - Jeong, Eui-Rim AU - Koo, Bon-Kwon AU - Oh, Seil AU - Yi, Yung PY - 2020/5/21 TI - Detection of Atrial Fibrillation Using a Ring-Type Wearable Device (CardioTracker) and Deep Learning Analysis of Photoplethysmography Signals: Prospective Observational Proof-of-Concept Study JO - J Med Internet Res SP - e16443 VL - 22 IS - 5 KW - atrial fibrillation KW - deep learning KW - diagnosis KW - photoplethysmography KW - wearable electronic devices N2 - Background: Continuous photoplethysmography (PPG) monitoring with a wearable device may aid the early detection of atrial fibrillation (AF). Objective: We aimed to evaluate the diagnostic performance of a ring-type wearable device (CardioTracker, CART), which can detect AF using deep learning analysis of PPG signals. Methods: Patients with persistent AF who underwent cardioversion were recruited prospectively. We recorded PPG signals at the finger with CART and a conventional pulse oximeter before and after cardioversion over a period of 15 min (each instrument). Cardiologists validated the PPG rhythms with simultaneous single-lead electrocardiography. The PPG data were transmitted to a smartphone wirelessly and analyzed with a deep learning algorithm. We also validated the deep learning algorithm in 20 healthy subjects with sinus rhythm (SR). Results: In 100 study participants, CART generated a total of 13,038 30-s PPG samples (5850 for SR and 7188 for AF). Using the deep learning algorithm, the diagnostic accuracy, sensitivity, specificity, positive-predictive value, and negative-predictive value were 96.9%, 99.0%, 94.3%, 95.6%, and 98.7%, respectively. Although the diagnostic accuracy decreased with shorter sample lengths, the accuracy was maintained at 94.7% with 10-s measurements. For SR, the specificity decreased with higher variability of peak-to-peak intervals. However, for AF, CART maintained consistent sensitivity regardless of variability. Pulse rates had a lower impact on sensitivity than on specificity. The performance of CART was comparable to that of the conventional device when using a proper threshold. External validation showed that 94.99% (16,529/17,400) of the PPG samples from the control group were correctly identified with SR. Conclusions: A ring-type wearable device with deep learning analysis of PPG signals could accurately diagnose AF without relying on electrocardiography. With this device, continuous monitoring for AF may be promising in high-risk populations. Trial Registration: ClinicalTrials.gov NCT04023188; https://clinicaltrials.gov/ct2/show/NCT04023188 UR - http://www.jmir.org/2020/5/e16443/ UR - http://dx.doi.org/10.2196/16443 UR - http://www.ncbi.nlm.nih.gov/pubmed/32348254 ID - info:doi/10.2196/16443 ER - TY - JOUR AU - Biersteker, E. Tom AU - Boogers, J. Mark AU - de Lind van Wijngaarden, AF Robert AU - Groenwold, HH Rolf AU - Trines, A. Serge AU - van Alem, P. Anouk AU - Kirchhof, JHJ Charles AU - van Hof, Nicolette AU - Klautz, JM Robert AU - Schalij, J. Martin AU - Treskes, W. Roderick PY - 2020/4/21 TI - Use of Smart Technology for the Early Diagnosis of Complications After Cardiac Surgery: The Box 2.0 Study Protocol JO - JMIR Res Protoc SP - e16326 VL - 9 IS - 4 KW - mHealth KW - cardiac surgery KW - atrial fibrillation KW - postoperative care KW - ambulatory electrocardiography N2 - Background: Atrial fibrillation (AF), sternal wound infection, and cardiac decompensation are complications that can occur after cardiac surgery. Early detection of these complications is clinically relevant, as early treatment is associated with better clinical outcomes. Remote monitoring with the use of a smartphone (mobile health [mHealth]) might improve the early detection of complications after cardiac surgery. Objective: The primary aim of this study is to compare the detection rate of AF diagnosed with an mHealth solution to the detection rate of AF diagnosed with standard care. Secondary objectives include detection of sternal wound infection and cardiac decompensation, as well as assessment of quality of life, patient satisfaction, and cost-effectiveness. Methods: The Box 2.0 is a study with a prospective intervention group and a historical control group for comparison. Patients undergoing cardiac surgery at Leiden University Medical Center are eligible for enrollment. In this study, 365 historical patients will be used as controls and 365 other participants will be asked to receive either The Box 2.0 intervention consisting of seven home measurement devices along with a video consultation 2 weeks after discharge or standard cardiac care for 3 months. Patient information will be analyzed according to the intention-to-treat principle. The Box 2.0 devices include a blood pressure monitor, thermometer, weight scale, step count watch, single-lead electrocardiogram (ECG) device, 12-lead ECG device, and pulse oximeter. Results: The study started in November 2018. The primary outcome of this study is the detection rate of AF in both groups. Quality of life is measured with the five-level EuroQol five-dimension (EQ-5D-5L) questionnaire. Cost-effectiveness is calculated from a society perspective using prices from Dutch costing guidelines and quality of life data from the study. In the historical cohort, 93.9% (336/358) completed the EQ-5D-5L and patient satisfaction questionnaires 3 months after cardiac surgery. Conclusions: The rationale and design of a study to investigate mHealth devices in postoperative cardiac surgery patients are presented. The first results are expected in September 2020. Trial Registration: ClinicalTrials.gov NCT03690492; http://clinicaltrials.gov/show/NCT03690492 International Registered Report Identifier (IRRID): DERR1-10.2196/16326 UR - http://www.researchprotocols.org/2020/4/e16326/ UR - http://dx.doi.org/10.2196/16326 UR - http://www.ncbi.nlm.nih.gov/pubmed/32314974 ID - info:doi/10.2196/16326 ER - TY - JOUR AU - Inui, Tomohiko AU - Kohno, Hiroki AU - Kawasaki, Yohei AU - Matsuura, Kaoru AU - Ueda, Hideki AU - Tamura, Yusaku AU - Watanabe, Michiko AU - Inage, Yuichi AU - Yakita, Yasunori AU - Wakabayashi, Yutaka AU - Matsumiya, Goro PY - 2020/1/22 TI - Use of a Smart Watch for Early Detection of Paroxysmal Atrial Fibrillation: Validation Study JO - JMIR Cardio SP - e14857 VL - 4 IS - 1 KW - Apple Watch KW - Fitbit Charge HR KW - paroxysmal atrial fibrillation KW - photoplethysmography KW - mobile health KW - heart rate KW - validation KW - wrist-banded devices N2 - Background: Wearable devices with photoplethysmography (PPG) technology can be useful for detecting paroxysmal atrial fibrillation (AF), which often goes uncaptured despite being a leading cause of stroke. Objective: This study is the first part of a 2-phase study that aimed at developing a method for immediate detection of paroxysmal AF using PPG-integrated wearable devices. In this study, the diagnostic performance of 2 major smart watches, Apple Watch Series 3 and Fitbit (FBT) Charge HR Wireless Activity Wristband, each equipped with a PPG sensor, was compared, and the pulse rate data outputted from those devices were analyzed for precision and accuracy in reference to the heart rate data from electrocardiography (ECG) during AF. Methods: A total of 40 subjects from patients who underwent cardiac surgery at a single center between September 2017 and March 2018 were monitored for postoperative AF using telemetric ECG and PPG devices. AF was diagnosed using a 12-lead ECG by qualified physicians. Each subject was given a pair of smart watches, Apple Watch and FBT, for simultaneous pulse rate monitoring. The heart rate of all subjects was also recorded on the telemetry system. Time series pulse rate trends and heart rate trends were created and analyzed for trend pattern similarities. Those trend data were then used to determine the accuracy of PPG-based pulse rate measurements in reference to ECG-based heart rate measurements during AF. Results: Of the 20 AF events in group FBT, 6 (30%) showed a moderate or higher correlation (cross-correlation function>0.40) between pulse rate trend patterns and heart rate trend patterns. Of the 16 AF events in group Apple Watch (workout [W] mode), 12 (75%) showed a moderate or higher correlation between the 2 trend patterns. Linear regression analyses also showed a significant correlation between the pulse rates and the heart rates during AF in the subjects with Apple Watch. This correlation was not observed with FBT. The regression formula for Apple Watch W mode and FBT was X=14.203 + 0.841Y and X=58.225 + 0.228Y, respectively (where X denotes the mean of all average pulse rates during AF and Y denotes the mean of all corresponding average heart rates during AF), and the coefficient of determination (R2) was 0.685 and 0.057, respectively (P<.001 and .29, respectively). Conclusions: In this validation study, the detection precision of AF and measurement accuracy during AF were both better with Apple Watch W mode than with FBT. UR - http://cardio.jmir.org/2020/1/e14857/ UR - http://dx.doi.org/10.2196/14857 UR - http://www.ncbi.nlm.nih.gov/pubmed/32012044 ID - info:doi/10.2196/14857 ER - TY - JOUR AU - Giannola, Gabriele AU - Torcivia, Riccardo AU - Airò Farulla, Riccardo AU - Cipolla, Tommaso PY - 2019/12/18 TI - Outsourcing the Remote Management of Cardiac Implantable Electronic Devices: Medical Care Quality Improvement Project JO - JMIR Cardio SP - e9815 VL - 3 IS - 2 KW - remote monitoring KW - telemonitoring KW - cardiac implantable electronic devices KW - implantable defibrillators KW - pacemaker KW - implantable cardioverter defibrillator KW - triage outsourcing KW - follow-up N2 - Background: Remote management is partially replacing routine follow-up in patients implanted with cardiac implantable electronic devices (CIEDs). Although it reduces clinical staff time compared with standard in-office follow-up, a new definition of roles and responsibilities may be needed to review remote transmissions in an effective, efficient, and timely manner. Whether remote triage may be outsourced to an external remote monitoring center (ERMC) is still unclear. Objective: The aim of this health care quality improvement project was to evaluate the feasibility of outsourcing remote triage to an ERMC to improve patient care and health care resource utilization. Methods: Patients (N=153) with implanted CIEDs were followed up for 8 months. An ERMC composed of nurses and physicians reviewed remote transmissions daily following a specific remote monitoring (RM) protocol. A 6-month benchmarking phase where patients? transmissions were managed directly by hospital staff was evaluated as a term of comparison. Results: A total of 654 transmissions were recorded in the RM system and managed by the ERMC team within 2 working days, showing a significant time reduction compared with standard RM management (100% vs 11%, respectively, within 2 days; P<.001). A total of 84.3% (551/654) of the transmissions did not include a prioritized event and did not require escalation to the hospital clinician. High priority was assigned to 2.3% (15/654) of transmissions, which were communicated to the hospital team by email within 1 working day. Nonurgent device status events occurred in 88 cases and were communicated to the hospital within 2 working days. Of these, 11% (10/88) were followed by a hospitalization. Conclusions: The outsourcing of RM management to an ERMC safely provides efficacy and efficiency gains in patients? care compared with a standard in-hospital management. Moreover, the externalization of RM management could be a key tool for saving dedicated staff and facility time with possible positive economic impact. Trial Registration: ClinicalTrials.gov NCT01007474; http://clinicaltrials.gov/ct2/show/NCT01007474 UR - https://cardio.jmir.org/2019/2/e9815 UR - http://dx.doi.org/10.2196/cardio.9815 UR - http://www.ncbi.nlm.nih.gov/pubmed/31845898 ID - info:doi/10.2196/cardio.9815 ER - TY - JOUR AU - Waring, E. Molly AU - Hills, T. Mellanie AU - Lessard, M. Darleen AU - Saczynski, S. Jane AU - Libby, A. Brooke AU - Holovatska, M. Marta AU - Kapoor, Alok AU - Kiefe, I. Catarina AU - McManus, D. David PY - 2019/11/14 TI - Characteristics Associated With Facebook Use and Interest in Digital Disease Support Among Older Adults With Atrial Fibrillation: Cross-Sectional Analysis of Baseline Data From the Systematic Assessment of Geriatric Elements in Atrial Fibrillation (SAGE-AF) Cohort JO - JMIR Cardio SP - e15320 VL - 3 IS - 2 KW - atrial fibrillation KW - social media KW - information seeking behavior N2 - Background: Online support groups for atrial fibrillation (AF) and apps to detect and manage AF exist, but the scientific literature does not describe which patients are interested in digital disease support. Objective: The objective of this study was to describe characteristics associated with Facebook use and interest in digital disease support among older patients with AF who used the internet. Methods: We used baseline data from the Systematic Assessment of Geriatric Elements in Atrial Fibrillation (SAGE-AF), a prospective cohort of older adults (?65 years) with AF at high stroke risk. Participants self-reported demographics, clinical characteristics, and Facebook and technology use. Online patients (internet use in the past 4 weeks) were asked whether they would be interested in participating in an online support AF community. Mobile users (owns smartphone and/or tablet) were asked about interest in communicating with their health care team about their AF-related health using a secure app. Logistic regression models identified crude and multivariable predictors of Facebook use and interest in digital disease support. Results: Online patients (N=816) were aged 74.2 (SD 6.6) years, 47.8% (390/816) were female, and 91.1% (743/816) were non-Hispanic white. Roughly half (52.5%; 428/816) used Facebook. Facebook use was more common among women (adjusted odds ratio [aOR] 2.21, 95% CI 1.66-2.95) and patients with mild to severe depressive symptoms (aOR 1.50, 95% CI 1.08-2.10) and less common among patients aged ?85 years (aOR 0.27, 95% CI 0.15-0.48). Forty percent (40.4%; 330/816) reported interest in an online AF patient community. Interest in an online AF patient community was more common among online patients with some college/trade school or Bachelors/graduate school (aOR 1.70, 95% CI 1.10-2.61 and aOR 1.82, 95% CI 1.13-2.92, respectively), obesity (aOR 1.65, 95% CI 1.08-2.52), online health information seeking at most weekly or multiple times per week (aOR 1.84, 95% CI 1.32-2.56 and aOR 2.78, 95% CI 1.86-4.16, respectively), and daily Facebook use (aOR 1.76, 95% CI 1.26-2.46). Among mobile users, 51.8% (324/626) reported interest in communicating with their health care team via a mobile app. Interest in app-mediated communication was less likely among women (aOR 0.48, 95% CI 0.34-0.68) and more common among online patients who had completed trade school/some college versus high school/General Educational Development (aOR 1.95, 95% CI 1.17-3.22), sought online health information at most weekly or multiple times per week (aOR 1.86, 95% CI 1.27-2.74 and aOR 2.24, 95% CI 1.39-3.62, respectively), and had health-related apps (aOR 3.92, 95% CI 2.62-5.86). Conclusions: Among older adults with AF who use the internet, technology use and demographics are associated with interest in digital disease support. Clinics and health care providers may wish to encourage patients to join an existing online support community for AF and explore opportunities for app-mediated patient-provider communication. UR - http://cardio.jmir.org/2019/2/e15320/ UR - http://dx.doi.org/10.2196/15320 UR - http://www.ncbi.nlm.nih.gov/pubmed/31758791 ID - info:doi/10.2196/15320 ER - TY - JOUR AU - Giebel, Denk Godwin AU - Gissel, Christian PY - 2019/6/16 TI - Accuracy of mHealth Devices for Atrial Fibrillation Screening: Systematic Review JO - JMIR Mhealth Uhealth SP - e13641 VL - 7 IS - 6 KW - mHealth KW - atrial fibrillation KW - wearable KW - app N2 - Background: Mobile health (mHealth) devices can be used for the diagnosis of atrial fibrillation. Early diagnosis allows better treatment and prevention of secondary diseases like stroke. Although there are many different mHealth devices to screen for atrial fibrillation, their accuracy varies due to different technological approaches. Objective: We aimed to systematically review available studies that assessed the accuracy of mHealth devices in screening for atrial fibrillation. The goal of this review was to provide a comprehensive overview of available technologies, specific characteristics, and accuracy of all relevant studies. Methods: PubMed and Web of Science databases were searched from January 2014 until January 2019. Our systematic review was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analyses. We restricted the search by year of publication, language, noninvasive methods, and focus on diagnosis of atrial fibrillation. Articles not including information about the accuracy of devices were excluded. Results: We found 467 relevant studies. After removing duplicates and excluding ineligible records, 22 studies were included. The accuracy of mHealth devices varied among different technologies, their application settings, and study populations. We described and summarized the eligible studies. Conclusions: Our systematic review identifies different technologies for screening for atrial fibrillation with mHealth devices. A specific technology?s suitability depends on the underlying form of atrial fibrillation to be diagnosed. With the suitable use of mHealth, early diagnosis and treatment of atrial fibrillation are possible. Successful application of mHealth technologies could contribute to significantly reducing the cost of illness of atrial fibrillation. UR - http://mhealth.jmir.org/2019/6/e13641/ UR - http://dx.doi.org/10.2196/13641 UR - http://www.ncbi.nlm.nih.gov/pubmed/31199337 ID - info:doi/10.2196/13641 ER - TY - JOUR AU - Kwon, Soonil AU - Hong, Joonki AU - Choi, Eue-Keun AU - Lee, Euijae AU - Hostallero, Earl David AU - Kang, Ju Wan AU - Lee, Byunghwan AU - Jeong, Eui-Rim AU - Koo, Bon-Kwon AU - Oh, Seil AU - Yi, Yung PY - 2019/6/6 TI - Deep Learning Approaches to Detect Atrial Fibrillation Using Photoplethysmographic Signals: Algorithms Development Study JO - JMIR Mhealth Uhealth SP - e12770 VL - 7 IS - 6 KW - atrial fibrillation KW - deep learning KW - photoplethysmography KW - pulse oximetry KW - diagnosis N2 - Background: Wearable devices have evolved as screening tools for atrial fibrillation (AF). A photoplethysmographic (PPG) AF detection algorithm was developed and applied to a convenient smartphone-based device with good accuracy. However, patients with paroxysmal AF frequently exhibit premature atrial complexes (PACs), which result in poor unmanned AF detection, mainly because of rule-based or handcrafted machine learning techniques that are limited in terms of diagnostic accuracy and reliability. Objective: This study aimed to develop deep learning (DL) classifiers using PPG data to detect AF from the sinus rhythm (SR) in the presence of PACs after successful cardioversion. Methods: We examined 75 patients with AF who underwent successful elective direct-current cardioversion (DCC). Electrocardiogram and pulse oximetry data over a 15-min period were obtained before and after DCC and labeled as AF or SR. A 1-dimensional convolutional neural network (1D-CNN) and recurrent neural network (RNN) were chosen as the 2 DL architectures. The PAC indicator estimated the burden of PACs on the PPG dataset. We defined a metric called the confidence level (CL) of AF or SR diagnosis and compared the CLs of true and false diagnoses. We also compared the diagnostic performance of 1D-CNN and RNN with previously developed AF detectors (support vector machine with root-mean-square of successive difference of RR intervals and Shannon entropy, autocorrelation, and ensemble by combining 2 previous methods) using 10 5-fold cross-validation processes. Results: Among the 14,298 training samples containing PPG data, 7157 samples were obtained during the post-DCC period. The PAC indicator estimated 29.79% (2132/7157) of post-DCC samples had PACs. The diagnostic accuracy of AF versus SR was 99.32% (70,925/71,410) versus 95.85% (68,602/71,570) in 1D-CNN and 98.27% (70,176/71,410) versus 96.04% (68,736/71,570) in RNN methods. The area under receiver operating characteristic curves of the 2 DL classifiers was 0.998 (95% CI 0.995-1.000) for 1D-CNN and 0.996 (95% CI 0.993-0.998) for RNN, which were significantly higher than other AF detectors (P<.001). If we assumed that the dataset could emulate a sufficient number of patients in training, both DL classifiers improved their diagnostic performances even further especially for the samples with a high burden of PACs. The average CLs for true versus false classification were 98.56% versus 78.75% for 1D-CNN and 98.37% versus 82.57% for RNN (P<.001 for all cases). Conclusions: New DL classifiers could detect AF using PPG monitoring signals with high diagnostic accuracy even with frequent PACs and could outperform previously developed AF detectors. Although diagnostic performance decreased as the burden of PACs increased, performance improved when samples from more patients were trained. Moreover, the reliability of the diagnosis could be indicated by the CL. Wearable devices sensing PPG signals with DL classifiers should be validated as tools to screen for AF. UR - http://mhealth.jmir.org/2019/6/e12770/ UR - http://dx.doi.org/10.2196/12770 UR - http://www.ncbi.nlm.nih.gov/pubmed/31199302 ID - info:doi/10.2196/12770 ER - TY - JOUR AU - Ding, Y. Eric AU - Han, Dong AU - Whitcomb, Cody AU - Bashar, Khairul Syed AU - Adaramola, Oluwaseun AU - Soni, Apurv AU - Saczynski, Jane AU - Fitzgibbons, P. Timothy AU - Moonis, Majaz AU - Lubitz, A. Steven AU - Lessard, Darleen AU - Hills, True Mellanie AU - Barton, Bruce AU - Chon, Ki AU - McManus, D. David PY - 2019/05/15 TI - Accuracy and Usability of a Novel Algorithm for Detection of Irregular Pulse Using a Smartwatch Among Older Adults: Observational Study JO - JMIR Cardio SP - e13850 VL - 3 IS - 1 KW - mobile health KW - mHealth KW - atrial fibrillation KW - screening KW - photoplethysmography KW - electrocardiography KW - smartwatch N2 - Background: Atrial fibrillation (AF) is often paroxysmal and minimally symptomatic, hindering its diagnosis. Smartwatches may enhance AF care by facilitating long-term, noninvasive monitoring. Objective: This study aimed to examine the accuracy and usability of arrhythmia discrimination using a smartwatch. Methods: A total of 40 adults presenting to a cardiology clinic wore a smartwatch and Holter monitor and performed scripted movements to simulate activities of daily living (ADLs). Participants? clinical and sociodemographic characteristics were abstracted from medical records. Participants completed a questionnaire assessing different domains of the device?s usability. Pulse recordings were analyzed blindly using a real-time realizable algorithm and compared with gold-standard Holter monitoring. Results: The average age of participants was 71 (SD 8) years; most participants had AF risk factors and 23% (9/39) were in AF. About half of the participants owned smartphones, but none owned smartwatches. Participants wore the smartwatch for 42 (SD 14) min while generating motion noise to simulate ADLs. The algorithm determined 53 of the 314 30-second noise-free pulse segments as consistent with AF. Compared with the gold standard, the algorithm demonstrated excellent sensitivity (98.2%), specificity (98.1%), and accuracy (98.1%) for identifying irregular pulse. Two-thirds of participants considered the smartwatch highly usable. Younger age and prior cardioversion were associated with greater overall comfort and comfort with data privacy with using a smartwatch for rhythm monitoring, respectively. Conclusions: A real-time realizable algorithm analyzing smartwatch pulse recordings demonstrated high accuracy for identifying pulse irregularities among older participants. Despite advanced age, lack of smartwatch familiarity, and high burden of comorbidities, participants found the smartwatch to be highly acceptable. UR - http://cardio.jmir.org/2019/1/e13850/ UR - http://dx.doi.org/10.2196/13850 UR - http://www.ncbi.nlm.nih.gov/pubmed/31758787 ID - info:doi/10.2196/13850 ER - TY - JOUR AU - Proesmans, Tine AU - Mortelmans, Christophe AU - Van Haelst, Ruth AU - Verbrugge, Frederik AU - Vandervoort, Pieter AU - Vaes, Bert PY - 2019/03/27 TI - Mobile Phone?Based Use of the Photoplethysmography Technique to Detect Atrial Fibrillation in Primary Care: Diagnostic Accuracy Study of the FibriCheck App JO - JMIR Mhealth Uhealth SP - e12284 VL - 7 IS - 3 KW - atrial fibrillation KW - electrocardiography KW - photoplethysmography KW - mobile phone KW - algorithm N2 - Background: Mobile phone apps using photoplethysmography (PPG) technology through their built-in camera are becoming an attractive alternative for atrial fibrillation (AF) screening because of their low cost, convenience, and broad accessibility. However, some important questions concerning their diagnostic accuracy remain to be answered. Objective: This study tested the diagnostic accuracy of the FibriCheck AF algorithm for the detection of AF on the basis of mobile phone PPG and single-lead electrocardiography (ECG) signals. Methods: A convenience sample of patients aged 65 years and above, with or without a known history of AF, was recruited from 17 primary care facilities. Patients with an active pacemaker rhythm were excluded. A PPG signal was obtained with the rear camera of an iPhone 5S. Simultaneously, a single?lead ECG was registered using a dermal patch with a wireless connection to the same mobile phone. PPG and single-lead ECG signals were analyzed using the FibriCheck AF algorithm. At the same time, a 12?lead ECG was obtained and interpreted offline by independent cardiologists to determine the presence of AF. Results: A total of 45.7% (102/223) subjects were having AF. PPG signal quality was sufficient for analysis in 93% and single?lead ECG quality was sufficient in 94% of the participants. After removing insufficient quality measurements, the sensitivity and specificity were 96% (95% CI 89%-99%) and 97% (95% CI 91%-99%) for the PPG signal versus 95% (95% CI 88%-98%) and 97% (95% CI 91%-99%) for the single?lead ECG, respectively. False-positive results were mainly because of premature ectopic beats. PPG and single?lead ECG techniques yielded adequate signal quality in 196 subjects and a similar diagnosis in 98.0% (192/196) subjects. Conclusions: The FibriCheck AF algorithm can accurately detect AF on the basis of mobile phone PPG and single-lead ECG signals in a primary care convenience sample. UR - http://mhealth.jmir.org/2019/3/e12284/ UR - http://dx.doi.org/10.2196/12284 UR - http://www.ncbi.nlm.nih.gov/pubmed/30916656 ID - info:doi/10.2196/12284 ER - TY - JOUR AU - Fan, Yong-Yan AU - Li, Yan-Guang AU - Li, Jian AU - Cheng, Wen-Kun AU - Shan, Zhao-Liang AU - Wang, Yu-Tang AU - Guo, Yu-Tao PY - 2019/03/05 TI - Diagnostic Performance of a Smart Device With Photoplethysmography Technology for Atrial Fibrillation Detection: Pilot Study (Pre-mAFA II Registry) JO - JMIR Mhealth Uhealth SP - e11437 VL - 7 IS - 3 KW - atrial fibrillation KW - photoplethysmography KW - detection KW - accuracy KW - mobile phone KW - smart band KW - algorithm N2 - Background: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. The asymptomatic nature and paroxysmal frequency of AF lead to suboptimal early detection. A novel technology, photoplethysmography (PPG), has been developed for AF screening. However, there has been limited validation of mobile phone and smart band apps with PPG compared to 12-lead electrocardiograms (ECG). Objective: We investigated the feasibility and accuracy of a mobile phone and smart band for AF detection using pulse data measured by PPG. Methods: A total of 112 consecutive inpatients were recruited from the Chinese PLA General Hospital from March 15 to April 1, 2018. Participants were simultaneously tested with mobile phones (HUAWEI Mate 9, HUAWEI Honor 7X), smart bands (HUAWEI Band 2), and 12-lead ECG for 3 minutes. Results: In all, 108 patients (56 with normal sinus rhythm, 52 with persistent AF) were enrolled in the final analysis after excluding four patients with unclear cardiac rhythms. The corresponding sensitivity and specificity of the smart band PPG were 95.36% (95% CI 92.00%-97.40%) and 99.70% (95% CI 98.08%-99.98%), respectively. The positive predictive value of the smart band PPG was 99.63% (95% CI 97.61%-99.98%), the negative predictive value was 96.24% (95% CI 93.50%-97.90%), and the accuracy was 97.72% (95% CI 96.11%-98.70%). Moreover, the diagnostic sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of mobile phones with PPG for AF detection were over 94%. There was no significant difference after further statistical analysis of the results from the different smart devices compared with the gold-standard ECG (P>.99). Conclusions: The algorithm based on mobile phones and smart bands with PPG demonstrated good performance in detecting AF and may represent a convenient tool for AF detection in at-risk individuals, allowing widespread screening of AF in the population. Trial Registration: Chinese Clinical Trial Registry ChiCTR-OOC-17014138; http://www.chictr.org.cn/showproj.aspx?proj=24191 (Archived by WebCite at http://www.webcitation/76WXknvE6) UR - http://mhealth.jmir.org/2019/3/e11437/ UR - http://dx.doi.org/10.2196/11437 UR - http://www.ncbi.nlm.nih.gov/pubmed/30835243 ID - info:doi/10.2196/11437 ER - TY - JOUR AU - Li, Christien Ka Hou AU - White, Anne Francesca AU - Tipoe, Timothy AU - Liu, Tong AU - Wong, CS Martin AU - Jesuthasan, Aaron AU - Baranchuk, Adrian AU - Tse, Gary AU - Yan, P. Bryan PY - 2019/02/15 TI - The Current State of Mobile Phone Apps for Monitoring Heart Rate, Heart Rate Variability, and Atrial Fibrillation: Narrative Review JO - JMIR Mhealth Uhealth SP - e11606 VL - 7 IS - 2 KW - mobile phone apps KW - atrial fibrillation KW - heart rate KW - arrhythmia KW - photoplethysmography KW - electrocardiography KW - mobile health N2 - Background: Mobile phone apps capable of monitoring arrhythmias and heart rate (HR) are increasingly used for screening, diagnosis, and monitoring of HR and rhythm disorders such as atrial fibrillation (AF). These apps involve either the use of (1) photoplethysmographic recording or (2) a handheld external electrocardiographic recording device attached to the mobile phone or wristband. Objective: This review seeks to explore the current state of mobile phone apps in cardiac rhythmology while highlighting shortcomings for further research. Methods: We conducted a narrative review of the use of mobile phone devices by searching PubMed and EMBASE from their inception to October 2018. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) mobile phone monitoring, (2) AF, (3) HR, and (4) HR variability (HRV). Results: The findings of this narrative review suggest that there is a role for mobile phone apps in the diagnosis, monitoring, and screening for arrhythmias and HR. Photoplethysmography and handheld electrocardiograph recorders are the 2 main techniques adopted in monitoring HR, HRV, and AF. Conclusions: A number of studies have demonstrated high accuracy of a number of different mobile devices for the detection of AF. However, further studies are warranted to validate their use for large scale AF screening. UR - http://mhealth.jmir.org/2019/2/e11606/ UR - http://dx.doi.org/10.2196/11606 UR - http://www.ncbi.nlm.nih.gov/pubmed/30767904 ID - info:doi/10.2196/11606 ER - TY - JOUR AU - Gliner, Vadim AU - Behar, Joachim AU - Yaniv, Yael PY - 2018/05/22 TI - Novel Method to Efficiently Create an mHealth App: Implementation of a Real-Time Electrocardiogram R Peak Detector JO - JMIR Mhealth Uhealth SP - e118 VL - 6 IS - 5 KW - atrial fibrillation KW - arrhythmia KW - heart rate variability KW - MATLAB Mobile KW - mobile device N2 - Background: In parallel to the introduction of mobile communication devices with high computational power and internet connectivity, high-quality and low-cost health sensors have also become available. However, although the technology does exist, no clinical mobile system has been developed to monitor the R peaks from electrocardiogram recordings in real time with low false positive and low false negative detection. Implementation of a robust electrocardiogram R peak detector for various arrhythmogenic events has been hampered by the lack of an efficient design that will conserve battery power without reducing algorithm complexity or ease of implementation. Objective: Our goals in this paper are (1) to evaluate the suitability of the MATLAB Mobile platform for mHealth apps and whether it can run on any phone system, and (2) to embed in the MATLAB Mobile platform a real-time electrocardiogram R peak detector with low false positive and low false negative detection in the presence of the most frequent arrhythmia, atrial fibrillation. Methods: We implemented an innovative R peak detection algorithm that deals with motion artifacts, electrical drift, breathing oscillations, electrical spikes, and environmental noise by low-pass filtering. It also fixes the signal polarity and deals with premature beats by heuristic filtering. The algorithm was trained on the annotated non?atrial fibrillation MIT-BIH Arrhythmia Database and tested on the atrial fibrillation MIT-BIH Arrhythmia Database. Finally, the algorithm was implemented on mobile phones connected to a mobile electrocardiogram device using the MATLAB Mobile platform. Results: Our algorithm precisely detected the R peaks with a sensitivity of 99.7% and positive prediction of 99.4%. These results are superior to some state-of-the-art algorithms. The algorithm performs similarly on atrial fibrillation and non?atrial fibrillation patient data. Using MATLAB Mobile, we ran our algorithm in less than an hour on both the iOS and Android system. Our app can accurately analyze 1 minute of real-time electrocardiogram signals in less than 1 second on a mobile phone. Conclusions: Accurate real-time identification of heart rate on a beat-to-beat basis in the presence of noise and atrial fibrillation events using a mobile phone is feasible. UR - http://mhealth.jmir.org/2018/5/e118/ UR - http://dx.doi.org/10.2196/mhealth.8429 UR - http://www.ncbi.nlm.nih.gov/pubmed/29789276 ID - info:doi/10.2196/mhealth.8429 ER - TY - JOUR AU - Hirschey, Jaclyn AU - Bane, Sunetra AU - Mansour, Moussa AU - Sperber, Jodi AU - Agboola, Stephen AU - Kvedar, Joseph AU - Jethwani, Kamal PY - 2018/03/15 TI - Evaluating the Usability and Usefulness of a Mobile App for Atrial Fibrillation Using Qualitative Methods: Exploratory Pilot Study JO - JMIR Hum Factors SP - e13 VL - 5 IS - 1 KW - nonvalvular atrial fibrillation KW - medication adherence KW - patient self-care KW - mobile application KW - exploratory research KW - pilot study KW - usability study KW - acceptability study KW - qualitative methods N2 - Background: Atrial fibrillation (AFib) is the most common form of heart arrhythmia and a potent risk factor for stroke. Nonvitamin K antagonist oral anticoagulants (NOACs) are routinely prescribed to manage AFib stroke risk; however, nonadherence to treatment is a concern. Additional tools that support self-care and medication adherence may benefit patients with AFib. Objective: The aim of this study was to evaluate the perceived usability and usefulness of a mobile app designed to support self-care and treatment adherence for AFib patients who are prescribed NOACs. Methods: A mobile app to support AFib patients was previously developed based on early stage interview and usability test data from clinicians and patients. An exploratory pilot study consisting of naturalistic app use, surveys, and semistructured interviews was then conducted to examine patients? perceptions and everyday use of the app. Results: A total of 12 individuals with an existing diagnosis of nonvalvular AFib completed the 4-week study. The average age of participants was 59 years. All participants somewhat or strongly agreed that the app was easy to use, and 92% (11/12) reported being satisfied or very satisfied with the app. Participant feedback identified changes that may improve app usability and usefulness for patients with AFib. Areas of usability improvement were organized by three themes: app navigation, clarity of app instructions and design intent, and software bugs. Perceptions of app usefulness were grouped by three key variables: core needs of the patient segment, patient workflow while managing AFib, and the app?s ability to support the patient?s evolving needs. Conclusions: The results of this study suggest that mobile tools that target self-care and treatment adherence may be helpful to AFib patients, particularly those who are newly diagnosed. Additionally, participant feedback provided insight into the varied needs and health experiences of AFib patients, which may improve the design and targeting of the intervention. Pilot studies that qualitatively examine patient perceptions of usability and usefulness are a valuable and often underutilized method for assessing the real-world acceptability of an intervention. Additional research evaluating the AFib Connect mobile app over a longer period, and including a larger, more diverse sample of AFib patients, will be helpful for understanding whether the app is perceived more broadly to be useful and effective in supporting patient self-care and medication adherence. UR - http://humanfactors.jmir.org/2018/1/e13/ UR - http://dx.doi.org/10.2196/humanfactors.8004 UR - http://www.ncbi.nlm.nih.gov/pubmed/29549073 ID - info:doi/10.2196/humanfactors.8004 ER - TY - JOUR AU - Kehl, Devin AU - Zimmer, Raymond AU - Sudan, Madhuri AU - Kedan, Ilan PY - 2018/03/08 TI - Handheld Ultrasound as a Novel Predictive Tool in Atrial Fibrillation: Prediction of Outcomes Following Electrical Cardioversion JO - JMIR Cardio SP - e7 VL - 2 IS - 1 KW - atrial fibrillation KW - cardioversion KW - recurrence KW - inferior vena cava KW - hand held ultrasound KW - point of care N2 - Background: Atrial fibrillation (AF) recurrence after successful direct current cardioversion (CV) is common, and clinical predictors may be useful. We evaluated the risk of early AF recurrence according to inferior vena cava (IVC) measurements by handheld ultrasound (HHU) at the time of CV. Objective: Assess HHU and objectively obtained measurements acquired at the point of care as potential clinical predictors of future clinical outcomes in patients with AF undergoing CV. Methods: Maximum IVC diameter (IVCd) and collapsibility with inspiration were measured by the Vscan HHU (General Electric Healthcare Division) in 128 patients immediately before and after successful CV for AF. Patients were followed by chart review for recurrence of AF. Results: Mean IVCd was 2.16 cm in AF pre-CV and 2.01 cm in sinus rhythm post-CV (P<.001). AF recurred within 30 days of CV in 34 of 128 patients (26.6%). Among patients with IVCd <2.1 cm pre-CV and decrease in IVCd post-CV, AF recurrence was 12.1%, compared to 31.6% in patients not meeting these parameters (odds ratio [OR] 0.299, P=.04). This association persisted after adjustment for age, ejection fraction <50%, left atrial enlargement, and amiodarone use (adjusted OR 0.185, P=.01). Among patients with IVCd post-CV <1.7 cm, AF recurrence was 13.5%, compared to 31.9% in patients not meeting this parameter (OR 0.185, P=.01). IVC parameters did not predict AF recurrence at 180 or 365 days. Conclusions: The presence of a normal IVCd pre-CV that becomes smaller post-CV and the presence of a small IVCd post-CV were each independently associated with reduced likelihood of early, but not late, AF recurrence. HHU assessment of IVCd at the time of CV may be useful to identify patients at low risk of early recurrence of AF after CV. UR - http://cardio.jmir.org/2018/1/e7/ UR - http://dx.doi.org/10.2196/cardio.9534 UR - http://www.ncbi.nlm.nih.gov/pubmed/31758780 ID - info:doi/10.2196/cardio.9534 ER - TY - JOUR AU - Kropp, Caley AU - Ellis, Jordan AU - Nekkanti, Rajasekhar AU - Sears, Samuel PY - 2018/02/21 TI - Monitoring Patients With Implantable Cardioverter Defibrillators Using Mobile Phone Electrocardiogram: Case Study JO - JMIR Cardio SP - e5 VL - 2 IS - 1 KW - atrial fibrillation KW - ICD KW - ECG KW - mobile phone monitoring KW - mobile health KW - electrophysiology N2 - Background: Preventable poor health outcomes associated with atrial fibrillation continue to make early detection a priority. A one-lead mobile electrocardiogram (mECG) device given to patients with an implantable cardioverter defibrillator (ICD) allowed users to receive real-time ECG readings in 30 seconds. Objective: Three cases were selected from an institutional review board-approved clinical trial aimed at assessing mECG device usage and satisfaction, patient engagement, quality of life (QoL), and cardiac anxiety. These three specific cases were selected to examine a variety of possible patient presentations and user experiences. Methods: Three ICD patients with mobile phones who were being seen in an adult device clinic were asked to participate. The participants chosen represented individuals with varying degrees of reported education and patient engagement. Participants were instructed to use the mECG device at least once per day for 30 days. Positive ECGs for atrial fibrillation were evaluated in clinic. At follow-up, information was collected regarding their frequency of use of the mECG device and three psychological outcomes in the domains of patient engagement, QoL, and cardiac anxiety. Results: Each patient used the technology approximately daily or every other day as prescribed. At the 30-day follow-up, usage reports indicated an average of 32 readings per month per participant. At 90-day follow-up, usage reports indicated an average of 34 readings per month per participant. Two of the three participants self-reported a significant improvement in their physical QoL from baseline to completion, while simultaneously self-reporting a significant decrease in their mental QoL. All three participants reported high levels of device acceptance and technology satisfaction. Conclusions: This case study demonstrates that ICD patients with varying degrees of education and patient engagement were relatively active in their use of mECGs. All three participants using the mECG technology reported high technology satisfaction and device acceptance. High sensitivity, specificity, and accuracy of mECG technology may allow routine atrial fibrillation screening at lower costs, in addition to improving patient outcomes. UR - http://cardio.jmir.org/2018/1/e5/ UR - http://dx.doi.org/10.2196/cardio.8710 UR - http://www.ncbi.nlm.nih.gov/pubmed/31758776 ID - info:doi/10.2196/cardio.8710 ER - TY - JOUR AU - Chen, Ying-Hsien AU - Hung, Chi-Sheng AU - Huang, Ching-Chang AU - Hung, Yu-Chien AU - Hwang, Juey-Jen AU - Ho, Yi-Lwun PY - 2017/09/26 TI - Atrial Fibrillation Screening in Nonmetropolitan Areas Using a Telehealth Surveillance System With an Embedded Cloud-Computing Algorithm: Prospective Pilot Study JO - JMIR Mhealth Uhealth SP - e135 VL - 5 IS - 9 KW - atrial fibrillation KW - screen KW - cloud-computing algorithm KW - electrocardiography N2 - Background: Atrial fibrillation (AF) is a common form of arrhythmia that is associated with increased risk of stroke and mortality. Detecting AF before the first complication occurs is a recognized priority. No previous studies have examined the feasibility of undertaking AF screening using a telehealth surveillance system with an embedded cloud-computing algorithm; we address this issue in this study. Objective: The objective of this study was to evaluate the feasibility of AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm. Methods: We conducted a prospective AF screening study in a nonmetropolitan area using a single-lead electrocardiogram (ECG) recorder. All ECG measurements were reviewed on the telehealth surveillance system and interpreted by the cloud-computing algorithm and a cardiologist. The process of AF screening was evaluated with a satisfaction questionnaire. Results: Between March 11, 2016 and August 31, 2016, 967 ECGs were recorded from 922 residents in nonmetropolitan areas. A total of 22 (2.4%, 22/922) residents with AF were identified by the physician?s ECG interpretation, and only 0.2% (2/967) of ECGs contained significant artifacts. The novel cloud-computing algorithm for AF detection had a sensitivity of 95.5% (95% CI 77.2%-99.9%) and specificity of 97.7% (95% CI 96.5%-98.5%). The overall satisfaction score for the process of AF screening was 92.1%. Conclusions: AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm is feasible. UR - https://mhealth.jmir.org/2017/9/e135/ UR - http://dx.doi.org/10.2196/mhealth.8290 UR - http://www.ncbi.nlm.nih.gov/pubmed/28951384 ID - info:doi/10.2196/mhealth.8290 ER - TY - JOUR AU - Desteghe, Lien AU - Kluts, Kiki AU - Vijgen, Johan AU - Koopman, Pieter AU - Dilling-Boer, Dagmara AU - Schurmans, Joris AU - Dendale, Paul AU - Heidbuchel, Hein PY - 2017/07/19 TI - The Health Buddies App as a Novel Tool to Improve Adherence and Knowledge in Atrial Fibrillation Patients: A Pilot Study JO - JMIR Mhealth Uhealth SP - e98 VL - 5 IS - 7 KW - mHealth KW - anticoagulants KW - medication adherence KW - education KW - atrial fibrillation N2 - Background: Atrial fibrillation (AF) constitutes an important risk for stroke, especially in an ageing population. A new app (Health Buddies) was developed as a tool to improve adherence to non-vitamin K antagonist oral anticoagulants (NOACs) in an elderly AF population by providing a virtual contract with their grandchildren, spelling out daily challenges for both. Objective: The aim of this pilot study was to assess the feasibility and usability of the Health Buddies app in AF patients. Methods: Two workshops were conducted to steer app development and to test a first prototype. The feasibility of the finalized app was investigated by assessing the number of eligible AF patients (based on current prescription of NOACs, the presence of grandchildren between 5 and 15 years old, availability of a mobile phone, computer, or tablet), and the proportion of those who were willing to participate. Participants had to use the app for 3 months. The motivation of the patients to use the app was assessed based on the number of logins to the app. Their perception of its usefulness was examined by specific questionnaires. Additionally, the effects on knowledge level about AF and its treatment, and adherence to NOAC intake were investigated. Results: Out of 830 screened AF patients, 410 were taking NOACs and 114 were eligible for inclusion. However, only 3.7% (15/410) of the total NOAC population or 13.2% of the eligible patients (15/114) were willing to participate. The main reasons for not participating were no interest to participate in general or in the concept in particular (29/99, 29%), not feeling comfortable using technology (22/99, 22%), no interest by the grandchildren or their parents (20/99, 20%), or too busy a lifestyle (12/99, 12%). App use significantly decreased towards the end of the study period in both patients (P=.009) and grandchildren (P<.001). NOAC adherence showed a taking adherence and regimen adherence of 88.6% (SD 15.4) and 81.8% (SD 18.7), respectively. Knowledge level increased from 64.6% (SD 14.7) to 70.4% (SD 10.4) after 3 months (P=.09). The app scored positively on clarity, novelty, stimulation, and attractiveness as measured with the user experience questionnaire. Patients evaluated the educational aspect of this app as a capital gain. Conclusions: Only a small proportion of the current AF population seems eligible for the innovative Health Buddies app in its current form. Although the app was positively rated by its users, a large subset of patients was not willing to participate in this study or to use the app. Efforts have to be made to expand the target group in the future. UR - http://mhealth.jmir.org/2017/7/e98/ UR - http://dx.doi.org/10.2196/mhealth.7420 UR - http://www.ncbi.nlm.nih.gov/pubmed/28724512 ID - info:doi/10.2196/mhealth.7420 ER -