Understanding the mechanisms behind unexplained abnormal heart rhythms is important for diagnosis and prevention of arrhythmias. Many studies have investigated the mechanisms at organ, tissue, cellular and molecular levels. There is considerable information available from tissue level experiments that investigate local action potential properties and from optical imaging to observe activity propagation properties at an organ level. By combining those electrophysiological properties together, in the present study we developed a simulation model that can help in estimation of the resulting body surface potentials from a specific electrical activity pattern within the myocardium. Some of the potential uses of our model include: 1) providing visualization of an entire electrophysiological event, i.e. surface potentials and associated source which would be optical imaging data, 2) estimation of QT intervals resulting from local action potential property changes, 3) aiding in improving defibrillation therapy by determining optimal timing and location of shocks.

<p>BACKGROUND</p> <p>For ST-segment elevation myocardial infarction (STEMI) patients received by emergency medical services (EMS), prehospital identification with 12-lead electrocardiogram/cardiography (ECG) and advanced notification of the receiving centre may increase access to primary reperfusion and reduce mortality, compared to standard cardiac monitoring. The lifetime benefits and costs of upgrading to a 12-lead ECG system are uncertain.</p> <p>OBJECTIVE</p> <p>To determine the cost-effectiveness of prehospital identification with 12-lead ECG and advanced notification vs. no prehospital identification and no advanced notification.</p> <p>METHODS</p> <p>A probabilistic Markov model was designed from a government payer perspective. Outcomes were lifetime incremental quality-adjusted life-years (QALYs) and healthcare costs. Type of primary reperfusion, 30-day and one-year mortality were from a cohort study conducted in Ontario. Reinfarction, stroke and revascularization rates were derived from the literature. Inpatient costs and professional fees came from the Ontario government; follow-up costs from published literature. The analysis was stratified by eligibility to bypass to a percutaneous coronary intervention (PCI) centre.</p> <p>RESULTS</p> <p>In bypass eligible settings, prehospital identification and advanced notification led to an average 0.23 additional QALYs and $1,501 additional costs over no prehospital identification and no advanced notification. In bypass ineligible settings, it led to an average 0.15 fewer QALYs and $130 additional costs. It was a cost-effective strategy 87% and 40% of the time in bypass eligible and ineligible settings, respectively, at a willingness-to-pay of $50,000/QALY.</p> <p>CONCLUSIONS</p> <p>In bypass eligible settings, prehospital identification with 12-lead ECG and advanced notification is a cost-effective intervention. In bypass ineligible settings, there is no evidence of cost-effectiveness.</p> / Master of Science (MSc)

Introduction: Computed electrocardiographic imaging (CEI) is a method that uses ST- segment deviations from the 12-lead electrocardiogram (ECG) and has been tested on a small number of patients.Aim: To extend the testing material of the CEI method and deduce a threshold using ECGs recorded pre- and during acute occlusion. The performance of the CEI and ST elevation myocardial infarction (STEMI) criteria will be compared. Method: Two CEI images were generated from each of 99 patients before and during complete occlusion in the left anterior descending (LAD), right coronary artery (RCA) and left circumflex coronary artery (LCx). Result: The sensitivity and specificity of STEMI criteria was 61% and 96% respectively for the whole occlusion group. The sensitivities and specificities were 74 %, 97% (LAD); 60%, 94% (RCA); 35%, 100% (LCx) respectively, for STEMI criteria. A threshold of 998 units was deduced from the CEI method. Conclusion: The CEI method has similar diagnostic performance of an occlusion as STEMI criteria.

In today’s research and market, IT applications for health-care are gaining huge interest of both IT and medical researchers. Cardiovascular diseases (CVDs) are considered the largest cause of death for both men and women regardless of ethnic backgrounds. More efficient treatments and most importantly efficient methods of cardiac diagnosis that examine heart diseases are desired. Electrocardiography (ECG) is an essential method used to diagnose heart diseases. However, diagnosing any cardiovascular disease based on the 12-lead ECG printout from an ECG machine using human eye might seriously impair analysis accuracy. To meet this challenge of today’s ECG analysis methodology, a more reliable solution that can analyze huge amount of patient’s data in real-time is desired. The software solution presented in this article is aimed to reduce the risk while diagnosing cardiovascular diseases (CVDs) by human eye, computation of large-scale patient’s data in real-time at the patient’s location and sending the required results or summary to the doctor/nurse. Keeping in mind the importance of real-time analysis of patient’s data, the software system has built upon small individual algorithms/modules designed for multi-core architecture, where each module is supposed to be processed by an individual core/processor in parallel. All the input and output processes to the analysis system are made automated, which reduces operator’s interaction to the system and thus reducing the cost. The outputs/results of the processing are summarized to smaller files in both ASCII and binary formats to meet the requirement of exchanging the data over Voice and Data Networks.