Augmented Two-Channel Arrhythmia Detection: An Efficient Diagnostic Method for Implantable Devices

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75624/1/j.1540-8159.1996.tb03164.x.pd

Relational grounding facilitates development of scientifically useful multiscale models

We review grounding issues that influence the scientific usefulness of any biomedical multiscale model (MSM). Groundings are the collection of units, dimensions, and/or objects to which a variable or model constituent refers. To date, models that primarily use continuous mathematics rely heavily on absolute grounding, whereas those that primarily use discrete software paradigms (e.g., object-oriented, agent-based, actor) typically employ relational grounding. We review grounding issues and identify strategies to address them. We maintain that grounding issues should be addressed at the start of any MSM project and should be reevaluated throughout the model development process. We make the following points. Grounding decisions influence model flexibility, adaptability, and thus reusability. Grounding choices should be influenced by measures, uncertainty, system information, and the nature of available validation data. Absolute grounding complicates the process of combining models to form larger models unless all are grounded absolutely. Relational grounding facilitates referent knowledge embodiment within computational mechanisms but requires separate model-to-referent mappings. Absolute grounding can simplify integration by forcing common units and, hence, a common integration target, but context change may require model reengineering. Relational grounding enables synthesis of large, composite (multi-module) models that can be robust to context changes. Because biological components have varying degrees of autonomy, corresponding components in MSMs need to do the same. Relational grounding facilitates achieving such autonomy. Biomimetic analogues designed to facilitate translational research and development must have long lifecycles. Exploring mechanisms of normal-to-disease transition requires model components that are grounded relationally. Multi-paradigm modeling requires both hyperspatial and relational grounding

Ischemia reperfusion dysfunction changes model-estimated kinetics of myofilament interaction due to inotropic drugs in isolated hearts

BACKGROUND: The phase-space relationship between simultaneously measured myoplasmic [Ca(2+)] and isovolumetric left ventricular pressure (LVP) in guinea pig intact hearts is altered by ischemic and inotropic interventions. Our objective was to mathematically model this phase-space relationship between [Ca(2+)] and LVP with a focus on the changes in cross-bridge kinetics and myofilament Ca(2+ )sensitivity responsible for alterations in Ca(2+)-contraction coupling due to inotropic drugs in the presence and absence of ischemia reperfusion (IR) injury. METHODS: We used a four state computational model to predict LVP using experimentally measured, averaged myoplasmic [Ca(2+)] transients from unpaced, isolated guinea pig hearts as the model input. Values of model parameters were estimated by minimizing the error between experimentally measured LVP and model-predicted LVP. RESULTS: We found that IR injury resulted in reduced myofilament Ca(2+ )sensitivity, and decreased cross-bridge association and dissociation rates. Dopamine (8 μM) reduced myofilament Ca(2+ )sensitivity before, but enhanced it after ischemia while improving cross-bridge kinetics before and after IR injury. Dobutamine (4 μM) reduced myofilament Ca(2+ )sensitivity while improving cross-bridge kinetics before and after ischemia. Digoxin (1 μM) increased myofilament Ca(2+ )sensitivity and cross-bridge kinetics after but not before ischemia. Levosimendan (1 μM) enhanced myofilament Ca(2+ )affinity and cross-bridge kinetics only after ischemia. CONCLUSION: Estimated model parameters reveal mechanistic changes in Ca(2+)-contraction coupling due to IR injury, specifically the inefficient utilization of Ca(2+ )for contractile function with diastolic contracture (increase in resting diastolic LVP). The model parameters also reveal drug-induced improvements in Ca(2+)-contraction coupling before and after IR injury

Understanding and Interpreting Dominant Frequency Analysis of AF Electrograms

Dominant frequency analysis of atrial electrograms has been used to understand the pathophysiology of atrial fibrillation (AF). Although dominant frequency is an effective tool to estimate activation rate during AF, other factors besides activation rate may alter the results. Therefore, an adequate conceptual understanding of frequency domain analysis is required to properly use this technique and interpret the results. This review, while avoiding the use of formulas and equations, aims to explain fundamental theory of how signals can be decomposed into sine waves and how these sine waves relate to the activation rate detected from the electrograms. Through a series of examples and illustrations this relationship can be easily conceptualized. This will in turn allow the strengths and limitations of dominant frequency analysis to be better understood and improve its applicability to potential clinical usages