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Title: An investigation of the impedence cardiogram and electrocardiogram to enhance resuscitation therapy
Author: Howe, Andrew
ISNI:       0000 0004 5372 1522
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2014
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Introduction Cardiovascular disease remains the commonest cause of death in the western world with an estimated 50% of deaths occurring suddenly. Efforts to improve survival from sudden cardiac arrest (SCA) have focused on dissemination of automated external defibrillators (AEDs) and improvements in cardiopulmonary resuscitation (CPR). However survival from SCA remains poor (5- 10%) and new developments to refine and improve defibrillation strategy and CPR are required. Aims To investigate the impedance cardiogram (ICG) measured via defibrillator pads as a marker of chest compression efficacy during cardiac arrest and as a haemodynamic indicator during cardiac arrhythmia To investigate ventricular fibrillation (VF) waveform characteristics for prediction of defibrillation success Method A porcine model of cardiac arrest was performed with simultaneous measurement of ICG, mechanical and physiological indicators of efficacious CPR. A subsequent pilot study of cardiac arrest patients was performed with simultaneous ICG and compression depth measurements. Two studies of the ICG during cardiac catheterisation and electrophysiology studies were performed with simultaneous measurement of ECG, ICG and arterial blood pressure. A retrospective analysis of VF waveform characteristics in 44 patients suffering VF cardiac arrest was also performed Results The pre-clinical study confirmed strong correlations between ICG amplitude and mechanical and physiological indicators of chest compression efficacy. The subsequent pilot study confirmed the ICG as an accurate measure of compression rate but not depth. Analysis of the ICG during catheterisation studies confirmed circulatory and ventilatory waveform components but no feature accurately differentiated haemodynamic status. VF waveform analysis confirmed that AMSA and Slope most accurately predicted shock success with improved predictive performance using a Support Vector Machine (SVM) approach. Conclusion The combined studies investigated novel impedance and electrocardiogram analysis during cardiac arrest and demonstrated their potential to enhance AED functionality, improve CPR performance and optimise defibrillation to improve resuscitation outcome
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available