Andrew Cave

Open Access Integrated Therapeutic and Diagnostic Platforms for Personalized Cardiovascular Medicine

It is undeniable that the increasing costs in healthcare are a concern. Although technological advancements have been made in healthcare systems, the return on investment made by governments and payers has been poor. The current model of care is unsustainable and is due for an upgrade. In developed nations, a law of diminishing returns has been noted in population health standards, whilst in the developing world, westernized chronic illnesses, such as diabetes and cardiovascular disease have become emerging problems. The reasons for these trends are complex, multifactorial and not easily reversed. Personalized medicine has the potential to have a significant impact on these issues, but for it to be truly successful, interdisciplinary mass collaboration is required. We propose here a vision for open-access advanced analytics for personalized cardiac diagnostics using imaging, electrocardiography and genomics.

ECG-derived spatial QRS-T angle is associated with ICD implantation, mortality and heart failure admissions in patients with LV systolic dysfunction

Background Increased spatial QRS-T angle has been shown to predict appropriate implantable cardioverter defibrilIator (ICD) therapy in patients with left ventricular systolic dysfunction (LVSD). We performed a retrospective cohort study in patients with left ventricular ejection fraction (LVEF) 31–40% to assess the relationship between the spatial QRS-T angle and other advanced ECG (A-ECG) as well as echocardiographic metadata, with all-cause mortality or ICD implantation for secondary prevention. Methods 534 patients ≤75 years of age with LVEF 31–40% were identified through an echocardiography reporting database. Digital 12-lead ECGs were retrospectively matched to 295 of these patients, for whom echocardiographic and A-ECG metadata were then generated. Data mining was applied to discover novel ECG and echocardiographic markers of risk. Machine learning was used to develop a model to predict possible outcomes. Results 49 patients (17%) had events, defined as either mortality (n = 16) or ICD implantation for secondary prevention (n = 33). 72 parameters (58 A-ECG, 14 echocardiographic) were univariately different (p<0.05) in those with vs. without events. After adjustment for multiplicity, 24 A-ECG parameters and 3 echocardiographic parameters remained different (p<2x10-3). These included the posterior-to-leftward QRS loop ratio from the derived vectorcardiographic horizontal plane (previously associated with pulmonary artery pressure, p = 2x10-6); spatial mean QRS-T angle (134 vs. 112°, p = 1.6x10-4); various repolarisation vectors; and a previously described 5-parameter A-ECG score for LVSD (p = 4x10-6) that also correlated with echocardiographic global longitudinal strain (R2 = - 0.51, P < 0.0001). A spatial QRS-T angle >110° had an adjusted HR of 3.4 (95% CI 1.6 to 7.4) for secondary ICD implantation or all-cause death and adjusted HR of 4.1 (95% CI 1.2 to 13.9) for future heart failure admission. There was a loss of complexity between A-ECG and echocardiographic variables with an increasing degree of disease. Conclusion Spatial QRS-T angle >110° was strongly associated with arrhythmic events and all-cause death. Deep analysis of global ECG and echocardiographic metadata revealed underlying relationships, which otherwise would not have been appreciated. Delivered at scale such techniques may prove useful in clinical decision making in the future.

Advanced Electrocardiography Identifies Left Ventricular Systolic Dysfunction in Non-Ischemic Cardiomyopathy and Tracks Serial Change over Time

Electrocardiogram (ECG)-based detection of left ventricular systolic dysfunction (LVSD) has poor specificity and positive predictive value, even when including major ECG abnormalities, such as left bundle branch block (LBBB) within the criteria for diagnosis. Although machine-read ECG algorithms do not provide information on LVSD, advanced ECG (A-ECG), using multiparameter scores, has superior diagnostic utility to strictly conventional ECG for identifying various cardiac pathologies, including LVSD. Methods: We evaluated the diagnostic utility of A-ECG in a case-control study of 40 patients with LVSD (LV ejection fraction < 50% by echocardiography), due to non-ischemic cardiomyopathy (NICM), and 39 other patients without LVSD. Diagnostic sensitivity and specificity for LVSD were determined after applying a previously validated probabilistic A-ECG score for LVSD to stored standard (10 s) clinical 12L ECGs. In 25 of the NICM patients who had serial ECGs and echocardiograms, changes in the A-ECG score versus in echocardiographic LV ejection fraction were also studied to determine the level of agreement between the two tests. Results: Analyses by A-ECG had a sensitivity of 95% for LVSD (93% if excluding N = 11 patients with LBBB) and specificity of 95%. In the 29 NICM patients without LBBB who had serial ECGs, sensitivity improved to 97% when all ECGs were considered. By comparison, human readers in a busy clinical environment had a sensitivity of 90% and specificity of 63%. A-ECG score trajectories demonstrated improvement, deterioration or no change in LVSD, which agreed with echocardiography, in 76% of cases (n = 25). Conclusion: A-ECG scoring detects LVSD due to NICM with high sensitivity and specificity. Serial A-ECG score trajectories also represent a method for inexpensively demonstrating changes in LVSD. A-ECG scoring may be of particular value in areas where echocardiography is unavailable, or as a gatekeeper for echocardiography.