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Total artificial hearts (TAHs) and biventricular assist devices (BVADs) have varying levels of acceptance and reliability, and the research on both focuses on their control mechanisms. Efforts generally aim to achieve a response to physiologic demand and left/right output balance, and beneficial cardiac output (CO) and effective control mechanisms have been achieved by eliciting a Starting-like response to preload and afterload. Such control mechanisms, however, generally base device output on a single parameter, such as the preload on the heart. Current TAHs and BVADs provide relatively fixed oxygen delivery to patients with large physiologically induced variations in oxygen consumption. This paper aims to document fluctuations in oxygen consumption that are normal in BVAD and TAH patients, identify a number of patient-generated signals that reflect these fluctuations, and describe a multitiered control algorithm based upon these signals. Such a control system may offer better response times and more physiologic cardiac outputs. There currently exists a microprocessor-based control mechanism that can be adapted to control TAHs and BVADs using input from a variety of sensors, and it can be found in modern implantable pulse generators (IPGs). Today's pacemakers are capable of rate control and can run diagnostic programs and store data that could be valuable in the evaluation of the patient's condition.

ObjectivesTo identify genetic factors that would be predictive of individuals who require an implantable cardioverter-defibrillator (ICD), we conducted a genome-wide association study among individuals with an ICD who experienced a life-threatening arrhythmia (LTA; cases) vs. those who did not over at least a 3-year period (controls).BackgroundMost individuals that receive implantable cardioverter-defibrillators never experience a life-threatening arrhythmia. Genetic factors may help identify who is most at risk.MethodsPatients with an ICD and extended follow-up were recruited from 34 clinical sites with the goal of oversampling those who had experienced LTA, with a cumulative 607 cases and 297 controls included in the analysis. A total of 1,006 Caucasian patients were enrolled during a time period of 13 months. Arrhythmia status of 904 patients could be confirmed and their genomic data were included in the analysis. In this cohort, there were 704 males, 200 females, and the average age was 73.3 years. We genotyped DNA samples using the Illumina Human660 W Genotyping BeadChip and tested for association between genotype at common variants and the phenotype of having an LTA.Results and ConclusionsWe did not find any associations reaching genome-wide significance, with the strongest association at chromosome 13, rs11856574 at P = 5×10−6. Loci previously implicated in phenotypes such as QT interval (measure of the time between the start of the Q wave and the end of the T wave as measured by electrocardiogram) were not found to be significantly associated with having an LTA. Although powered to detect such associations, we did not find common genetic variants of large effect associated with having a LTA in those of European descent. This indicates that common gene variants cannot be used at this time to guide ICD risk-stratification.Trial RegistrationClinicalTrials.gov NCT00664807

Implantable cardioverter-defibrillator (ICD) therapy is effective in primary and secondary prevention for patients who are at high risk of sudden cardiac death. However, the current risk stratification of patients who may benefit from this therapy is unsatisfactory. Single nucleotide polymorphisms (SNPs) are DNA sequence variations occurring when a single nucleotide in the genome differs among members of a species. A novel concept has emerged being that these common genetic variations might modify the susceptibility of a certain population to specific diseases. Thus, genetic factors may also modulate the risk for arrhythmias and sudden cardiac death, and identification of common variants could help to better identify patients at risk. The DISCOVERY study is an interventional, longitudinal, prospective, multi-centre diagnostic study that will enrol 1287 patients in approximately 80 European centres. In the genetic part of the DISCOVERY study, candidate gene polymorphisms involved in coding of the G-protein subunits will be correlated with the occurrence of ventricular arrhythmias in patients receiving an ICD for primary prevention. Furthermore, in order to search for additional sequence variants contributing to ventricular arrhythmias, a genome-wide association study will be conducted if sufficient a priori evidence can be gathered. In the second part of the study, associations of SNPs with ventricular arrhythmias will be sought and a search for potential new biological arrhythmic pathways will be investigated. As it is a diagnostic study, DISCOVERY will also investigate the impact of long-term device diagnostic data on the management of patients suffering from chronic cardiac disease as well as medical decisions made regarding their treatment.