Model Based Analysis of QT Variability Independent of Heart Rate and Respiration
type: CreativeWork
description: Electrical instability in the ventricles of the heart predisposes patients to abnormal heart rhythms (ventricular arrhythmia) and sudden cardiac death (SCD). Current risk assessment strategies for identifying patients at high risk of SCD are mainly based on markers of structural dysfunction. However, most deaths occur in those deemed at low risk by traditional risk markers, stipulating the need for improvement of existing risk assessment strategies. Malignant neural modulation of the repolarisation process also contributes to arrhythmogenesis and increased risk of SCD. Improving the ability to sense instability in the repolarisation process and quantifying neural contribution to arrhythmia can improve the ability to predict the onset of ventricular arrhythmias and improve risk stratification strategies. The main aim of this thesis is to quantify repolarisation variability independent of heart rate and respiration, explore its prognostic value for improving risk prediction and examine its relationship to sympathetic neural activity. Parametric power contribution analysis methods and autoregressive modelling are used to quantify repolarisation variability independent of heart rate and respiration. Temporal ECG features that best capture the influence of sympathetic activation on repolarisation independent of other factors are identified by comparing LF powers of several features following increase in sympathetic activation elicited by orthostatic stress. Measurements of QTV independent of heart rate and respiration from single leads (II and V5) are compared to that of multi-lead approaches in a group of coronary artery disease patients to investigate the suitability of singlelead ECG for the analysis of repolarisation variability independent of heart rate and respiration. The influence of sympathetic activation elicited by orthostatic stress on this fraction of repolarisation variability is investigated in healthy adults and adolescents. Finally, survival analysis is …
abstract: Electrical instability in the ventricles of the heart predisposes patients to abnormal heart rhythms (ventricular arrhythmia) and sudden cardiac death (SCD). Current risk assessment strategies for identifying patients at high risk of SCD are mainly based on markers of structural dysfunction. However, most deaths occur in those deemed at low risk by traditional risk markers, stipulating the need for improvement of existing risk assessment strategies. Malignant neural modulation of the repolarisation process also contributes to arrhythmogenesis and increased risk of SCD. Improving the ability to sense instability in the repolarisation process and quantifying neural contribution to arrhythmia can improve the ability to predict the onset of ventricular arrhythmias and improve risk stratification strategies. The main aim of this thesis is to quantify repolarisation variability independent of heart rate and respiration, explore its prognostic value for improving risk prediction and examine its relationship to sympathetic neural activity. Parametric power contribution analysis methods and autoregressive modelling are used to quantify repolarisation variability independent of heart rate and respiration. Temporal ECG features that best capture the influence of sympathetic activation on repolarisation independent of other factors are identified by comparing LF powers of several features following increase in sympathetic activation elicited by orthostatic stress. Measurements of QTV independent of heart rate and respiration from single leads (II and V5) are compared to that of multi-lead approaches in a group of coronary artery disease patients to investigate the suitability of singlelead ECG for the analysis of repolarisation variability independent of heart rate and respiration. The influence of sympathetic activation elicited by orthostatic stress on this fraction of repolarisation variability is investigated in healthy adults and adolescents. Finally, survival analysis is …
author: El-Hamad, Fatima Jawad M
language: en
keywords: repolarisation variability, QT, ECG, autoregressive modelling, sympathetic activity
date published: 2022
date modified: 2026-07-24T00:50:56Z
provider: University of Adelaide
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Adelaide

PropertyValue
property ID: Handle
value: https://hdl.handle.net/2440/137553