Using Coronary Artery Calcium Score as Diagnostic Tool in Symptomatic Chronic Coronary Syndrome Patients in a Real-Life Setting.

Background: The coronary artery calcium (CAC) score can be used to increase (CAC score > 0) or decrease (CAC score = 0) the likelihood of coronary artery disease (CAD). We compared the CAC score with the pre-test probability (PTP) for CAD (low, intermediate, and high). Furthermore, we compared the CAC score with exercise electrocardiography (ECG) and compared both tests with coronary angiography. Methods and Results: We retrospectively identified patients with angina and/or dyspnea for whom CAC score was used to increase or decrease the likelihood of CAD. Of 882 patients, majority had low (45%) or intermediate (44%) PTP. Patients with higher PTP had significantly higher CAC scores (Cramer's V = 0.29, p < 0.0001). Most patients (57%) had a CAC score of zero, especially those with low (73%) and intermediate (49%) PTP. However, 20% of patients with high PTP had CAC score of zero. Higher CAC scores were observed in patients with abnormal exercise ECG, but association was weak and not significant (Cramer's V = 0.13, p = 0.08). Moreover, more than 40% of patients with an abnormal exercise ECG had CAC score of zero. Higher CAC scores were associated with more severe abnormalities on coronary angiography (Cramer's V = 0.43, p < 0.0001), whereas there was no association between results of exercise ECG and coronary angiography (Cramer's V = 0.11, p = 0.91). Conclusion: CAC score can be used in addition to PTP to increase or decrease the likelihood of CAD, and it might be more useful than exercise ECG in the diagnostic work-up of chest pain.

Usefulness, pitfalls and interpretation of handheld single­lead electrocardiograms.

Single­lead electrocardiograms (1 L-ECGs) are increasingly used in (pre)clinical settings for the detection and monitoring of a range of rhythm and conduction disorders. In this short communication paper, we aim to provide an overview of the usefulness and potential pitfalls when implementing 1 L-ECGs into everyday clinical practice. Moreover, we provide recommendations for improving signal quality, as well as a systematic approach to the interpretation of 1 L-ECGs, which is somewhat different from standard 12­lead ECGs. Clinicians can use our illustrations and checklist as guidance when recording and interpreting 1 L-ECGs.

Design and Development of a Mobile Health (mHealth) Platform for Dementia Prevention in the Prevention of Dementia by Mobile Phone Applications (PRODEMOS) Project.

Background: Mobile health (mHealth) has the potential to bring preventive healthcare within reach of populations with limited access to preventive services, by delivering personalized support at low cost. Although numerous mHealth interventions are available, very few have been developed following an evidence-based rationale or have been tested for efficacy. This article describes the systematic development of a coach-supported mHealth application to improve healthy lifestyles for the prevention of dementia and cardiovascular disease in the United Kingdom (UK) and China. Methods: Development of the Prevention of Dementia by Mobile Phone applications (PRODEMOS) platform built upon the experiences with the Healthy Aging Through Internet Counseling in the Elderly (HATICE) eHealth platform. In the conceptualization phase, experiences from the HATICE trial and needs and wishes of the PRODEMOS target population were assessed through semi-structured interviews and focus group sessions. Initial technical development of the platform was based on these findings and took place in consecutive sprint sessions. Finally, during the evaluation and adaptation phase, functionality and usability of the platform were evaluated during pilot studies in UK and China. Results: The PRODEMOS mHealth platform facilitates self-management of a healthy lifestyle by goal setting, progress monitoring, and educational materials on healthy lifestyles. Participants receive remote coaching through a chat functionality. Based on lessons learned from the HATICE study and end-users, we made the intervention easy-to-use and included features to personalize the intervention. Following the pilot studies, in which in total 77 people used the mobile application for 6 weeks, the application was made more intuitive, and we improved its functionalities. Conclusion: Early involvement of end-users in the development process and during evaluation phases improved acceptability of the mHealth intervention. The actual use and usability of the PRODEMOS intervention will be assessed during the ongoing PRODEMOS randomized controlled trial, taking a dual focus on effectiveness and implementation outcomes.