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BackgroundIn recent years many mobile devices able to record health-related data in ambulatory patients have emerged. However, well-organised programs to incorporate these devices are sparse. Hartwacht Arrhythmia (HA) is such a program, focusing on remote arrhythmia detection using the AliveCor Kardia Mobile (KM) and its algorithm.ObjectivesThe aim of this study was to assess the benefit of the KM device and its algorithm in detecting cardiac arrhythmias in a real-world cohort of ambulatory patients.MethodsAll KM ECGs recorded in the HA program between January 2017 and March 2018 were included. Classification by the KM algorithm was compared with that of the Hartwacht team led by a cardiologist. Statistical analyses were performed with respect to detection of sinus rhythm (SR), atrial fibrillation (AF) and other arrhythmias.Results5,982 KM ECGs were received from 233 patients (mean age 58 years, 52% male). The KM algorithm categorised 59% as SR, 22% as possible AF, 17% as unclassified and 2% as unreadable. According to the Hartwacht team, 498 (8%) ECGs were uninterpretable. Negative predictive value for detection of AF was 98%. However, positive predictive value as well as detection of other arrhythmias was poor. In 81% of the unclassified ECGs, the Hartwacht team was able to provide a diagnosis.ConclusionsThis study reports on the first symptom-driven remote arrhythmia monitoring program in the Netherlands. Less than 10% of the ECGs were uninterpretable. However, the current performance of the KM algorithm makes the device inadequate as a stand-alone application, supporting the need for manual ECG analysis in HA and similar programs.

IntroductionInterventions to reduce the impact of modifiable risk factors, such as hypercholesterolaemia, smoking, and overweight, have the potential to significantly decrease the cardiovascular disease burden. The majority of the global population is unaware of their own risk of developing cardiovascular disease. Parallel to the lack of awareness, a rise in obesity and diabetes is observed. e‑Health tools for lifestyle improvement have shown to be effective in changing unhealthy behaviour. In this study we report on the results of three different trials assessing the effectiveness of MyCLIC, an e‑Coaching lifestyle intervention tool.MethodsFrom 2008 to 2016 we conducted three trials: 1) HAPPY NL: a prospective cohort study in the Netherlands, 2) HAPPY AZM: a prospective cohort study with employees of Maastricht UMC+ and 3) HAPPY LONDON: a single-centre, randomised controlled trial with asymptomatic individuals who have a high 10-year CVD risk.ResultsHAPPY NL and HAPPY AZM showed that e‑Coaching reduced cardiovascular risk. Both prospective trials showed a 20–25% relative reduction in 10-year cardiovascular disease risk. A lesser effect was seen in the HAPPY LONDON trial. A low frequency of logins suggests a low degree of content engagement in the e‑Coaching group, which could be age related as the mean age of the participants in the HAPPY LONDON study was high.Conclusione-Coaching using MyCLIC is a low cost and effective method to perform lifestyle interventions and has the potential to reduce the 10-year cardiovascular disease risk.

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