Temporal stability of defibrillation thresholds with cardiac resynchronization therapy.

BACKGROUND: Defibrillation thresholds (DFTs) are typically stable over time among patients with implantable cardioverter-defibrillators (ICDs). However, the impact of cardiac resynchronization therapy (CRT) on DFTs has not been studied systematically. OBJECTIVE: This study prospectively evaluated the effect of CRT and left ventricular (LV) chamber reverse remodeling on DFTs. METHODS: This prospective, multicenter study evaluated 54 cardiac resynchronization therapy defibrillator (CRT-D) patients. Echocardiography and DFTs were performed both at implantation and at 6 months after implantation. All patients received dual-coil leads and a CRT-D pulse generator. DFTs were measured using a binary search method and tuned biphasic waveforms, where the shock pulse widths were determined by the measured shock impedance. Echocardiograms were analyzed by an independent core laboratory with a responder defined as a decrease of left ventricular end systolic volume >15%. RESULTS: The study cohort was 74% male, with a mean age of 68.7 ± 10.9 years. The baseline ejection fraction was 0.245 ± 0.076, and the mean New York Heart Association class was 2.9 ± 0.4. In CRT responders (n = 32) the mean DFT was 415.6 ± 108.1 V at implantation vs. 415.6 ± 124.7 V at 6 months (P = .9), and in nonresponders (n = 19) the mean DFT was 452.6 ± 102 V at implantation vs. 447.4 ± 112.4 V at 6 months (P = .8). There was no significant change in DFT peak voltage, delivered energy, or shock impedance over time. CONCLUSION: DFTs were unchanged at 6 months in CRT patients with or without LV chamber reverse remodeling.

An ontological knowledge framework for adaptive medical workflow.

As emerging technologies, semantic Web and SOA (Service-Oriented Architecture) allow BPMS (Business Process Management System) to automate business processes that can be described as services, which in turn can be used to wrap existing enterprise applications. BPMS provides tools and methodologies to compose Web services that can be executed as business processes and monitored by BPM (Business Process Management) consoles. Ontologies are a formal declarative knowledge representation model. It provides a foundation upon which machine understandable knowledge can be obtained, and as a result, it makes machine intelligence possible. Healthcare systems can adopt these technologies to make them ubiquitous, adaptive, and intelligent, and then serve patients better. This paper presents an ontological knowledge framework that covers healthcare domains that a hospital encompasses-from the medical or administrative tasks, to hospital assets, medical insurances, patient records, drugs, and regulations. Therefore, our ontology makes our vision of personalized healthcare possible by capturing all necessary knowledge for a complex personalized healthcare scenario involving patient care, insurance policies, and drug prescriptions, and compliances. For example, our ontology facilitates a workflow management system to allow users, from physicians to administrative assistants, to manage, even create context-aware new medical workflows and execute them on-the-fly.