Exploring the cardiovascular disease continuum: blood pressure and target organ damage

Introduction The objectives of this thesis are to: (1) examine how ambulatory blood pressure monitoring (ABPM) refines office blood pressure (BP) measurement; (2) determine if absolute ambulatory BP or dipping status is better associated with target organ damage (TOD); (3) explore the association of isolated nocturnal hypertension (INH) with TOD; and (4) investigate the association of night-time BP with ultrasound markers of cardiovascular damage. Methods Data from the Mitchelstown Cohort Study was analysed to deliver objectives 1 and 2. Objective 3 was addressed by a systematic review and analysis of data from the Mitchelstown Study. A sample of participants from the Mitchelstown Study underwent an echocardiogram for speckle tracking analysis and carotid ultrasound to achieve objective 4. Results ABPM reclassifies hypertension status in approximately a quarter of individuals, with white coat and masked hypertension prevalence rates of 11% and 13% respectively. Night-time systolic BP is better associated with TOD than daytime systolic BP and dipping level. In multi-variable models the odds ratio (OR) for LVH was 1.4 (95% CI 1.1 -1.8) and for albumin:creatinine ratio ≥ 1.1 mg/mmol was 1.5 (95% CI 1.2 – 1.8) for each 10 mmHg rise in night-time systolic BP. The evidence for the association of INH with TOD is inconclusive. Night-time systolic BP is significantly associated with global longitudinal strain (GLS) (beta coefficient 0.85 for every 10 mmHg rise, 95% CI 0.3 – 1.4) and carotid plaques (OR 1.9 for every 10 mmHg rise, 95% CI 1.1 – 3.2) in univariable analysis. The findings persist for GLS in sex and age adjusted models but not in multivariable models. Discussion Hypertension cannot be effectively managed without using ABPM. Night-time systolic BP is better associated with TOD than daytime systolic BP and dipping level, and therefore, may be a better therapeutic target in future studies.

Linearity analysis and comparison study on the epoc® point-of-care blood analysis system in cardiopulmonary bypass patients

The epoc® blood analysis system (Epocal Inc., Ottawa, Ontario, Canada) is a newly developed in vitro diagnostic hand-held analyzer for testing whole blood samples at point-of-care, which provides blood gas, electrolytes, ionized calcium, glucose, lactate, and hematocrit/calculated hemoglobin rapidly. The analytical performance of the epoc® system was evaluated in a tertiary hospital, see related research article “Analytical evaluation of the epoc® point-of-care blood analysis system in cardiopulmonary bypass patients” [1]. Data presented are the linearity analysis for 9 parameters and the comparison study in 40 cardiopulmonary bypass patients on 3 epoc® meters, Instrumentation Laboratory GEM4000, Abbott iSTAT, Nova CCX, and Roche Accu-Chek Inform II and Performa glucose meters.

Dynamic classifiers for neonatal brain monitoring

Brain injury due to lack of oxygen or impaired blood flow around the time of birth, may cause long term neurological dysfunction or death in severe cases. The treatments need to be initiated as soon as possible and tailored according to the nature of the injury to achieve best outcomes. The Electroencephalogram (EEG) currently provides the best insight into neurological activities. However, its interpretation presents formidable challenge for the neurophsiologists. Moreover, such expertise is not widely available particularly around the clock in a typical busy Neonatal Intensive Care Unit (NICU). Therefore, an automated computerized system for detecting and grading the severity of brain injuries could be of great help for medical staff to diagnose and then initiate on-time treatments. In this study, automated systems for detection of neonatal seizures and grading the severity of Hypoxic-Ischemic Encephalopathy (HIE) using EEG and Heart Rate (HR) signals are presented. It is well known that there is a lot of contextual and temporal information present in the EEG and HR signals if examined at longer time scale. The systems developed in the past, exploited this information either at very early stage of the system without any intelligent block or at very later stage where presence of such information is much reduced. This work has particularly focused on the development of a system that can incorporate the contextual information at the middle (classifier) level. This is achieved by using dynamic classifiers that are able to process the sequences of feature vectors rather than only one feature vector at a time.