Background: Hypertension is common, affecting over one billion people worldwide. Importantly, in Sub-Saharan Africa hypertensive disease not only affects the older population group, but is becoming increasingly prevalent in younger patients. In South Africa, over 30% of the adult population has hypertension, making it the single most common cardiovascular risk factor and the predominant contributor to cardiovascular disease and mortality. In non-cardiac surgical patients, elevated blood pressure is the most common perioperative comorbidity encountered with an overall prevalence of 20-25%, and it remains poorly controlled in low and middle-income countries. Furthermore, hypertension in the perioperative setting may adversely affect patient outcome. It thus not only flags possible perioperative challenges to anaesthesiologists, but also identifies patients at risk of long-term morbidity and mortality. Objectives: The primary objective of this study was to determine the prevalence and severity of hypertension in elective adult surgical patients in the Western Cape. Results: The study population included all non-cardiac, non-obstetric, elective surgical patients from seven hospitals in the Western Cape during a one-week period. Hypertension, defined as having had a previous diagnosis of hypertension or meeting the blood pressure criteria of more than 140/90 mmHg, was identified in 51.8% of patients during the preoperative assessment. Significantly, newly diagnosed hypertension was present in 9.6% of all patients presenting for elective surgery. Although 98.1% of the known hypertensive patients were on antihypertensive therapy, 36.9% were inadequately controlled. Numerous reasons exist for this but notably 32% of patients admitted to forgetting to take their medication, making patient factors the most common cause for treatment non-compliance. Conclusion: This study suggests that the perioperative period may be an important opportunity to identify undiagnosed hypertensive patient. The perioperative encounter may have a significant public health implication in facilitating appropriate referral and treatment of hypertension to decrease long-term cardiovascular complications in South Africa.

Mobile health (mHealth) promises a paradigm shift towards digital medicine where biomarkers in individuals are continuously monitored with wearable biosensors in decentralized locations to facilitate improved diagnosis and treatment of disease. Despite recent progress, the impact of wearables in health monitoring remains limited due to the lack of devices that measure meaningful health data and are accurate, minimally invasive, and unobtrusive. Therefore, next-generation biosensors must be developed to realize the vision of mHealth. To that end, in this dissertation, we develop wearable biochemical and biophysical sensors for health monitoring that can serve as platforms for future mHealth devices. First, we developed a skin patch biosensor for minimally invasive quantification of endogenous biochemical analytes in dermal interstitial fluid. The patch consisted of a polyacrylamide hydrogel microfilament array with covalently-tethered fluorescent aptamer sensors. Compared to prior approaches for hydrogel-based sensing, the microfilaments enable in situ sensing without invasive injection or removal. The patch was fabricated via replica molding with high-percentage polyacrylamide that provided high elastic modulus in the dehydrated state and optical transparency in the hydrated state. The microfilaments could penetrate the skin with low pain and without breaking, elicited minimal inflammation upon insertion, and were easily removed from the skin. To enable functional sensing, the polyacrylamide was co-polymerized with acrydite-modified aptamer sensors for phenylalanine that demonstrated reversible sensing with fast response time in vitro. In the future, hydrogel microfilaments could be integrated with a wearable fluorometer to serve as a platform for continuous, minimally invasive monitoring of intradermal biomarkers. Next, we shift focus to biophysical signals and the required signal processing, particularly towards the development of cuffless blood pressure (BP) monitors. Cuffless BP measurement could enable early detection and treatment of abnormal BP patterns and improved cardiovascular disease risk stratification. However, the accuracy of emerging cuffless monitoring methods is compromised by arm movement due to variations in hydrostatic pressure, limiting their clinical utility. To overcome this limitation, we developed a method to correct hydrostatic pressure errors in noninvasive BP measurements. The method tracks arm position using wearable inertial sensors at the wrist and a deep learning model that estimates parameterized arm-pose coordinates; arm position is then used for analytical hydrostatic pressure compensation. We demonstrated the approach with BP measurements derived from pulse transit time, one of the most well-studied modalities for cuffless BP measurement. Across hand heights of 25 cm above or below the heart, mean errors for diastolic and systolic BP were 0.7 ± 5.7 mmHg and 0.7 ± 4.9 mmHg, respectively, and did not differ significantly across arm positions. This method for correcting hydrostatic pressure may facilitate the development of cuffless devices that can passively monitor BP during everyday activities. Finally, towards a fully integrated device suitable for ambulatory BP monitoring, we developed a deep learning model for BP prediction from photoplethysmography waveforms acquired at a single measurement site. In contrast to competing methods that require thousands of measurements for adaptation to new users, our proposed approach enables accurate BP prediction following calibration with a single reference measurement. The model uses a convolutional neural network with temporal attention for feature extraction and a Siamese architecture for effective calibration. To prevent overfitting to person-specific variations that fail to generalize, we introduced an adversarial patient classification task to encourage the learning of patient-invariant features. Following calibration, the model accurately predicted diastolic and systolic BP over 24 hours, with mean errors of -0.07 ± 3.86 mmHg and -0.94 ± 7.32 mmHg, respectively, which meets the accuracy criteria for clinical validation. The proposed deep learning model could integrate with wearable photoplethysmography sensors, such as those in smartwatches, to enable cuffless ambulatory BP monitoring. Underlying this work is the development of minimally invasive biosensors that can integrate with wearable mHealth devices to facilitate passive monitoring of health parameters. The proliferation of mHealth wearables will enable the widespread collection of meaningful health data that provide actionable insights and a more comprehensive understanding of patient health. In a step towards this vision, we leveraged innovations in materials, multi-sensor fusion, and data-driven signal processing to develop sensors for measuring biochemical and biophysical markers. Overall, this work serves as an example of how the adoption of new technologies can facilitate the development of next-generation wearable biosensors.

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MSc (Nursing), Faculty of Health Sciences, University of the Witwatersrand, 2009 / Pregnancy induced hypertension (PIH) occurring during pregnancy, labour and puerperium is a major contributor to the high percentage of maternal morbidity and mortality in the Eastern Cape Province, and worldwide. In South Africa (SA), PIH is the second most common of all primary causes of maternal mortality reported in the triennium from 1999 to 2001. From 1999 to 2001, PIH was the cause of 20,7 % (n = 507) of all maternal mortalities in SA (Department of Health (DOH), 2001:38). In the light of these statistics and other statistics related to other causes of MMR, the National Confidential Committee on Enquiries into Maternal Deaths (NCCEMD) developed the National Guidelines for Maternity Care in South Africa, a Manual for Clinics, Community Health Centres and District Hospitals. The guidelines related to PIH were of particular interest in this study. A quantitative, descriptive and contextual survey was conducted to determine the implementation of the National Guidelines for Maternity Care for the management of PIH by the midwife at level-1 clinics in the Eastern Cape, and to make recommendations for the management of PIH by midwives at level-1 clinics with the intention of reducing maternal mortality and morbidity due to PIH. The research method comprised a retrospective record review of the records of all patients admitted with PIH at a level-3 hospital who were referred by a midwife from a level-1 clinic. Data were collected by means of a researcher-administered data collection tool based on the iii National Guidelines for Maternity Care in SA for the management of PIH. The researcher wished to determine whether the National Guidelines for Maternity Care in SA was being implemented for the management of PIH by midwives at level-1 clinics in East London. A purposive sample of 290 maternal records of mothers who had been admitted for PIH at level 3 after being referred from level-1 clinics from May 1999 to June 2003 were used. Data were analysed using descriptive statistics. Ethical issues were taken into consideration. Validity and reliability were ensured. In conclusion, given the study findings, the researcher has made recommendations with the intention of reducing mortality due to PHI in the Eastern Cape.

MSc (Nursing), Faculty of Health Sciences, University of the Witwatersrand / The purpose of the study was to describe and compare the limits of agreement between invasive blood pressure (IBP) and non-invasive blood pressure (NIBP) readings obtained on patients in the adult critical care units (CCU) of a tertiary health care institution, to describe the factors that affect accuracy of both techniques, to describe the difference in terms of accuracy and sensitivity and the reasons given by the clinical practitioners for their choice of blood pressure measurement technique. A non-experimental descriptive comparative, prospective design was utilized in this two part study. The sample comprised of CCU patients (n = 80) in five adult critical care units over a 3-month period. Non-probability purposive sampling was utilized to obtain the desired sample in part one of the study. Data collection was via IBP and NIBP measurements obtained by the researcher and a record review of the patient’s critical care charts. Part two of the study comprised of clinical practitioners (n=50) and convenience sampling method was utilized. Descriptive and inferential statistics were used to analyse data. At the 95% confidence interval, the limits of agreements were found to be in range of ± 35 mmhg of IBP and NIBP systolic, ± 19.5 mmHg of IBP and NIBP diastolic and ±19.3 mmhg IBP and NIBP of mean arterial pressure. In practical terms this means that IBP and NIBP can not be used interchangeably in CCUs as the two methods did not consistently provide similar measurements because there was a high level of disagreement that included clinically important discrepancy of more than 10 mmhg which is the cut off acceptable reference in terms of discrepancy between the two BP techniques and add to the growing literature suggesting that IBP remains the gold standard technique for measuring the blood pressure in critical care setting. Factors such as Inotropic/ vasopressor support, sedation / analgesia, mechanical ventilation and severity of illness (APACHE II score) did not show significant influence on the discrepancy of the two BP techniques. In the second part of the study, more than 80 % of the sample of clinical practitioners acknowledged that the IBP technique remains the gold standard.

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