Statistical methods for polyhedral shape classification with incomplete data - application to cryo-electron tomographic images

A certain type of bacterial inclusion, known as a bacterial microcompartment, was recently identified and imaged through cryo-electron tomography. A reconstructed 3D object from single-axis limited angle tilt-series cryo-electron tomography contains missing regions and this problem is known as the missing wedge problem. Due to missing regions on the reconstructed images, analyzing their 3D structures is a challenging problem. The existing methods overcome this problem by aligning and averaging several similar shaped objects. These schemes work well if the objects are symmetric and several objects with almost similar shapes and sizes are available. Since the bacterial inclusions studied here are not symmetric, are deformed, and show a wide range of shapes and sizes, the existing approaches are not appropriate. This research develops new statistical methods for analyzing geometric properties, such as volume, symmetry, aspect ratio, polyhedral structures etc., of these bacterial inclusions in presence of missing data. These methods work with deformed and non-symmetric varied shaped objects and do not necessitate multiple objects for handling the missing wedge problem. The developed methods and contributions include: (a) an improved method for manual image segmentation, (b) a new approach to 'complete' the segmented and reconstructed incomplete 3D images, (c) a polyhedral structural distance model to predict the polyhedral shapes of these microstructures, (d) a new shape descriptor for polyhedral shapes, named as polyhedron profile statistic, and (e) the Bayes classifier, linear discriminant analysis and support vector machine based classifiers for supervised incomplete polyhedral shape classification. Finally, the predicted 3D shapes for these bacterial microstructures belong to the Johnson solids family, and these shapes along with their other geometric properties are important for better understanding of their chemical and biological characteristics.

Career choice in medicine

Background: Career Choice in Medicine is an important and problematic topic. Medical education has been framed as professional identity development, yet career choice has not been viewed as a matter of identity. My primary aim was to offer new insights by exploring career choice using Figured Worlds theory, a socio-cultural theory of identity. Graduate retention is a challenge for many countries, including Ireland. My secondary aim was to address a gap in the data on postgraduate trainees in Ireland and to use the Irish case to illustrate points transferable to other contexts. Methodology & Methods: This was a predominantly qualitative Mixed Methods programme of research. My qualitative studies were oriented towards social constructionism. I collated existing data from the Royal College of Physicians of Ireland (RCPI) and HSE-MET to describe trainees and their career paths. I surveyed Basic Specialist Training trainees (n=333) about their career plans. I surveyed new trainees (n=527) about their expectations of training and all RCPI trainees about their experiences of training (n=1246). I conducted semi-structured interviews with 18 medical students and doctors. A subgroup (n=6) provided longitudinal data. Figured Worlds theory and Gee’s discourse tools were used for analysis. Results: I have used the case of medical training and career choice in Ireland to explain how social, political and cultural context, and day to day experiences in the cultural world of medicine, shaped doctors’ career choices. My qualitative findings described a unifying model of career choice, consisting of priming, exposure, positioning and open-endedness, which can guide the design of interventions to shape and support career choice. Conclusion: My original contribution has been to demonstrate the fruitfulness of framing career choice in terms of identity development. This represents a turn in the conversation about career choice, which brings new starting points and moves the dialogue forward.

Development of an intervention to support medication management in patients with multimorbidity in primary care

The overarching aim of this thesis was to develop an intervention to support patient-centred prescribing in the context of multimorbidity in primary care. Methods A range of research methods were used to address different components of the Medical Research Council, UK (MRC) guidance on the development and evaluation of complex interventions in health care. The existing evidence on GPs’ perceptions of the management of multimorbidity was systematically reviewed. In qualitative interviews, chart-stimulated recall was used to explore the challenges experienced by GPs when prescribing for multimorbid patients. In a cross-sectional study, the psychosocial issues that complicate the management of multimorbidity were examined. To develop the complex intervention, the Behaviour Change Wheel (BCW) was used to integrate behavioural theory with the findings of these three studies. A feasibility study of the new intervention was then conducted with GPs. Results The systematic review revealed four domains of clinical practice where GPs experienced difficulties in multimorbidity. The qualitative interview study showed that GPs responded to these difficulties by ‘satisficing’. In multimorbid patients perceived as stable, GPs preferred to ‘maintain the status quo’ rather than actively change medications. In the cross-sectional study, the significant association between multimorbidity and negative psychosocial factors was shown. These findings informed the development of the ‘Multimorbidity Collaborative Medication Review and Decision-making’ (MY COMRADE) intervention. The intervention involves peer support: two GPs review the medications prescribed to a complex multimorbid patient together. In the feasibility study, GPs reported that the intervention was appropriate for the context of general practice; was widely applicable to their patients with multimorbidity; and recommendations for optimising medications arose from all collaborative reviews. Conclusion Applying theory to empirical data has led to an intervention that is implementable in clinical practice, and has the potential to positively change GPs’ behaviour in the management of medications for patients with multimorbidity.

Artefact detection and removal algorithms for EEG diagnostic systems

The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be administered within minutes rather than hours. However, as typical EEG signals are of the order of microvolts (μV ), contamination by signals arising from sources other than the brain is frequent. These extra-cerebral sources, known as artefacts, can significantly distort the EEG signal, making its interpretation difficult, and can dramatically disimprove automatic neurological event detection classification performance. This thesis therefore, contributes to the further improvement of auto- mated neurological event detection systems, by identifying some of the major obstacles in deploying these EEG systems in ambulatory and clinical environments so that the EEG technologies can emerge from the laboratory towards real-world settings, where they can have a real-impact on the lives of patients. In this context, the thesis tackles three major problems in EEG monitoring, namely: (i) the problem of head-movement artefacts in ambulatory EEG, (ii) the high numbers of false detections in state-of-the-art, automated, epileptiform activity detection systems and (iii) false detections in state-of-the-art, automated neonatal seizure detection systems. To accomplish this, the thesis employs a wide range of statistical, signal processing and machine learning techniques drawn from mathematics, engineering and computer science. The first body of work outlined in this thesis proposes a system to automatically detect head-movement artefacts in ambulatory EEG and utilises supervised machine learning classifiers to do so. The resulting head-movement artefact detection system is the first of its kind and offers accurate detection of head-movement artefacts in ambulatory EEG. Subsequently, addtional physiological signals, in the form of gyroscopes, are used to detect head-movements and in doing so, bring additional information to the head- movement artefact detection task. A framework for combining EEG and gyroscope signals is then developed, offering improved head-movement arte- fact detection. The artefact detection methods developed for ambulatory EEG are subsequently adapted for use in an automated epileptiform activity detection system. Information from support vector machines classifiers used to detect epileptiform activity is fused with information from artefact-specific detection classifiers in order to significantly reduce the number of false detections in the epileptiform activity detection system. By this means, epileptiform activity detection which compares favourably with other state-of-the-art systems is achieved. Finally, the problem of false detections in automated neonatal seizure detection is approached in an alternative manner; blind source separation techniques, complimented with information from additional physiological signals are used to remove respiration artefact from the EEG. In utilising these methods, some encouraging advances have been made in detecting and removing respiration artefacts from the neonatal EEG, and in doing so, the performance of the underlying diagnostic technology is improved, bringing its deployment in the real-world, clinical domain one step closer.

Reflections on the transformation of my meaning making to support the organic growth of a firm

The objective of my Portfolio is to explore the working hypothesis that the organic growth of a firm is governed by the perspectives of individuals and such perspectives are governed by their meaning-making. The Portfolio presents explorations of the transformation of my meaning making and in adopting new practices to support the organic growth of a firm. I use the work of other theorists to transition my understanding of how the world works. This transition process is an essential tool to engage with and understand the perspectives of others and develop a mental capacity to “train one’s imagination to go visiting” (Arendt, 1982; p.43). The Portfolio, therefore, is primarily located in reflective research. Using Kegan’s (1994) approach to Adult Mental Development, and Sowell’s (2007) understanding of the visions which silently shape our thoughts I organise the developments of my meaning making around three transformation pillars of change. In pillar one I seek to transform an unthinking respect for authority and break down a blind pervasiveness of thought within my reasoning process arising from an instinct for attachment and support from others whom I trust. In pillar two I seek to discontinue using autocratic leadership and learn to use the thoughts and contributions of a wider team to make improved choices about uncertain future events. In pillar three I explore the use of a more reflective thinking framework to test the accuracy of my perceptions and apply a high level of integrity in my reasoning process. The transformation of my meaning making has changed my perspectives and in turn my preferred practices to support the organic growth of a firm. I identify from practice that a transformative form of leadership is far more effective that a transactional form of leadership to stimulate the trust and teamwork required to sustain the growth a firm. Creating an environment where one feels free to share thoughts and feelings with others is an essential tool to build a team to critique the thoughts of one other. Furthermore, the entrepreneurial wisdom to grow a firm must come from a wider team, located both inside and outside the boundaries of a firm. No individual or small team has the mental capacity to provide the entrepreneurship required to drive the organic growth of a firm. I address my Portfolio to leaders in organisations who have no considered framework on the best practices required to lead a social organisation. These individuals may have no sense of what they implicitly believe drives social causation and they may have no understanding if their meaning making supports or curtails the practices required to grow a firm. They may have a very limited capacity to think in a logical manner, with the result they are using guesses from their ‘gut’ to make poor judgements in the management of a firm.

Nutrition, growth and body composition in preterm infants

The goal of neonatal nutrition in the preterm infant is to achieve postnatal growth and body composition approximating that of a normal fetus of the same postmenstrual age and to obtain a functional outcome comparable to infants born at term. However, in clinical practice such a pattern is seldom achieved, with growth failure and altered body composition being extensively reported. The BabyGrow preterm nutrition study was a longitudinal, prospective, observational study designed to investigate nutrition and growth in 59 preterm infants following the implementation of evidence-based nutrition guidelines in the neonatal unit at Cork University Maternity Hospital. Nutrient delivery was precisely measured during the entire hospital stay and intakes were compared with current international recommendations. Barriers to nutrient delivery were identified across the phases of nutritional support i.e. exclusive parenteral nutrition and transition (establishment of enteral feeds) phases of nutrition and nutritional strategies to optimise nutrient delivery were proposed according to these phases. Growth was measured from birth up to 2 months corrected age and body composition was assessed in terms of fat mass and lean body mass by air displacement plethysmography (PEA POD) at 34 weeks gestation, term corrected age and 2 months corrected age. Anthropometric and body composition data in the preterm cohort were compared with a term reference group from the Cork BASELINE Birth Cohort Study (n=1070) at similar time intervals. The clinical and nutritional determinants of growth and body composition during the neonatal period were reported for the first time. These data have international relevance, informing authoritative agencies developing evidence-based practice guidelines for neonatal nutritional support. In the future, the nutritional management of preterm infants may need to be individualised to consider gestational age, birth weight as well as preterm morbidity.

Pharmacotherapy optimization in older patients by a structured clinical pharmacist assessment and intervention

Introduction: Older individuals are particularly vulnerable to potentially inappropriate prescribing (PIP), drug related problems (DRPs) and adverse drug reactions (ADRs). A number of different interventions have been proposed to address these issues. However to-date there is a paucity of well-designed trials examining the impact of such interventions. Therefore the aims of this work were to: (i) establish a baseline PIP prevalence both nationally and internationally using the STOPP, Beers and PRISCUS criteria, (ii) identify the most comprehensive method of assessing PIP in older individuals, (iii) develop a structured pharmacist intervention supported by a computer decisions support system (CDSS) and (iv) examine the impact of this intervention on prescribing and incidence of ADRs. Results: This work identified high rates of PIP across all three healthcare settings in Ireland, 84.7% in the long term care, 70.7% in secondary care and 43.3% in primary care being reported. This work identified that for a comprehensive assessment of prescribing to be undertaken, an amalgamation of all three criteria should be deployed simultaneously. High prevalences of DRPs and PIP in older hospitalised individuals were identified. With 82.0% and 76.3% of patients reported to have at least one DRP or PIP instance respectively. The structured pharmacist intervention demonstrated a positive impact on prescribing, with a significant reduction MAI scores being reported. It also resulted in the intervention patients’ having a reduced risk of experiencing an ADR when compared to the control patients (absolute risk reduction of 6.8 (95% CI 1.5% - 12.3%)) and the number needed to treat = 15 (95% CI 8 - 68). However the intervention was found to have no significant effect on length of stay or mortality rate. Conclusion: This work shows that PIP is highly prevalent in older individuals across three healthcare settings in Ireland. This work also demonstrates that a structured pharmacist intervention support by a dedicated CDSS can significantly improve the appropriateness of prescribing and reduce the incidence of ADRs in older acutely ill hospitalised individuals.

Cancer related fatigue and self-care while undergoing chemotherapy: patients' perspectives

Background: Cancer related fatigue (CRF) is considered the most severe, debilitating and under-managed symptom of cancer. Patients receiving chemotherapy experience high levels of CRF which profoundly impacts on their lives. Aim: 1). To explore and measure CRF and determine the most effective self-care strategies used to combat CRF in a cohort of patients with a diagnosis of cancer (breast cancer, colorectal cancer, Hodgkin’s and Non-Hodgkin’s lymphoma) 2). To explore self-care agency and its relationship to CRF. Method: A mixed methods study which incorporated a descriptive, comparative, correlational design and qualitative descriptions of patients’ (n=362) experiences gleaned through open ended questions and use of a diary. The study utilised The Revised Pipers Fatigue Scale, the Appraisal of Self-Care Agency and a researcher developed Fatigue Visual Analogue Scale, Fatigue Self-Care Survey, and Diary. Findings: Having breast cancer, Hodgkin’s lymphoma, non-Hodgkin’s lymphoma; using the strategies of counselling, taking a 20–30 minute nap, resting and sleeping, self-monitoring and complementary therapies were all associated with increased odds of developing fatigue. Increased self-care agency; being in the divorced / separated cohort; being widowed; increased length of time since commencement of chemotherapy; engagement in exercise, and socializing were associated with a reduced risk of developing fatigue. Females had 20% higher fatigue levels than males (p=<.001). Receiving support was the strategy used most frequently and rated most effective. Fatigue was very problematic and distressing, four key qualitative categories emerged: the behavioural impact, affective impact, the sensory impact, and the cognitive impact. Keeping a diary was considered very beneficial and cathartic. Conclusions: Fatigue severely impacted on the daily lives of patients undergoing chemotherapy. There are a range of self-care strategies that patients should be encouraged to use e.g. exercise, socializing, and enhancement of psychological well-being. The enhancement of self-care agency and use of diaries should also be considered.

Optimizing perioperative analgesia for patients undergoing operative fixation of hip fractures

This PhD thesis describes work carried out on investigation of various interventions with the aim to optimise the anaesthetic management of patients scheduled to undergo operative fixation of hip fractures. We analysed the perioperative effects of continuous femoral nerve block, single preoperative dose of i.v. dexamethasone, the intention to deposit local anaesthetic in different locations around the femoral nerve during ultrasound guided femoral nerve block, continuous spinal anaesthesia and peri-surgical site infiltration with local anaesthetic after surgical fixation of hip fractures. Continuous femoral nerve block provided more effective preoperative analgesia six hours after the insertion of the perineural catheter compared to a standard opiate-based regimen in patients undergoing operative fixation of fractured hip. A single low dose of preoperative dexamethasone in the intervention group decreased pain scores by 75% six hours after the surgery. Both interventions had no major effect on the functional recovery in the first year after the surgical fixation of fractured hip. The results of the ultrasound guided femoral nerve block trial showed no clinical advantage of intending to deposit local anaesthetic circumferentially during performing femoral nerve block. Using the Dixon and Massey’s “up- and-down” method, we demonstrated that intrathecal 0.26 ml of 0.5% bupivacaine provided adequate surgical anaesthesia within 15 minutes in 50% of patients undergoing operative fixation of hip fracture. Finally, we demonstrated that local anaesthetic infiltration had no effect on pain scores 12 hours after the surgical fixation of fractured neck of femur. In addition to this original body of work, a review article was published on femoral nerve block highlighting the use of ultrasound guidance. In conclusion, the results of this thesis offer an insight into interventions aimed at optimising perioperative analgesia in patients scheduled to undergo operative fixation of hip fractures.