Data supporting the co-expression of PDHA1 gene and of its paralogue PDHA2 in somatic cells of a family

This article presents a dataset proving the simultaneous presence of a 5′UTR-truncated PDHA1 mRNA and a full-length PDHA2 mRNA in the somatic cells of a PDC-deficient female patient and all members of her immediate family (parents and brother). We have designed a large set of primer pairs in order to perform detailed RT-PCR assays allowing the clear identification of both PDHA1 and PDHA2 mRNA species in somatic cells. In addition, two different experimental approaches were used to elucidate the copy number of PDHA1 gene in the patient and her mother. The interpretation and discussion of these data, along with further extensive experiments concerning the origin of this altered gene expression and its potential therapeutic consequences, can be found in “Complex genetic findings in a female patient with pyruvate dehydrogenase complex deficiency: null mutations in the PDHX gene associated with unusual expression of the testis-specific PDHA2 gene in her somatic cells” (A. Pinheiro, M.J. Silva, C. Florindo, et al., 2016).

Genome-scale analysis of the non-cultivable Treponema pallidum reveals extensive within-patient genetic variation

Insights into the genomic adaptive traits of Treponema pallidum, the causative bacterium of syphilis, have long been hampered due to the absence of in vitro culture models and the constraints associated with its propagation in rabbits. Here, we have bypassed the culture bottleneck by means of a targeted strategy never applied to uncultivable bacterial human pathogens to directly capture whole-genome T. pallidum data in the context of human infection. This strategy has unveiled a scenario of discreet T. pallidum interstrain single-nucleotide-polymorphism-based microevolution, contrasting with a rampant within-patient genetic heterogeneity mainly targeting multiple phase-variable loci and a major antigen-coding gene (tprK). TprK demonstrated remarkable variability and redundancy, intra- and interpatient, suggesting ongoing parallel adaptive diversification during human infection. Some bacterial functions (for example, flagella- and chemotaxis-associated) were systematically targeted by both inter- and intrastrain single nucleotide polymorphisms, as well as by ongoing within-patient phase variation events. Finally, patient-derived genomes possess mutations targeting a penicillin-binding protein coding gene (mrcA) that had never been reported, unveiling it as a candidate target to investigate the impact on the susceptibility to penicillin. Our findings decode the major genetic mechanisms by which T. pallidum promotes immune evasion and survival, and demonstrate the exceptional power of characterizing evolving pathogen subpopulations during human infection.

Caregivers' experiences and coping strategies relating to patient's subjective treatment-related cognitive impairment following Haematopoietic Stem Cell Transplant (HSCT)

The treatments involved in cancers of the blood and bone marrow can be physically and psychologically challenging and be associated with adverse secondary effects, including cognitive impairment. The incidence and severity of treatment-related cognitive impairment varies widely, however it can significantly impact quality of life by interfering with patients’ activities of daily living, relationships and future plans. It can also pose challenges for the patients’ caregivers, an area which has received comparatively less research attention. The aim of this study was to investigate caregivers’ experiences of treatment-related cognitive impairment in patients who have undergone Haematopoietic Stem Cell Transplant (HSCT); how they coped, both practically and emotionally, and what supports they believe could help them. Participants were caregivers to individuals who had undergone HSCT within the past 20 years and who had reported cognitive changes at the HSCT Late Effects Clinic, Beatson West of Scotland Cancer Centre. Five participants completed a single semi-structured interview. The data was then analysed using Interpretative Phenomenological Analysis (IPA). Results of this analysis illustrated four super-ordinate themes: noticing change; managing expectations, managing personal feelings and commitment. Findings from the current study highlighted the importance of caregiver education regarding post HSCT cognitive and behavioural changes and providing caregiver emotional support. Future research should explore the mutual needs of both care recipient and caregiver.

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness.^ Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.^ Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems.^ To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].^

Use of flucinolone acetonide for patients with diabetic macular oedema:patient selection criteria and early outcomes in real world setting

Introduction: Fluocinolone acetonide slow release implant (Iluvien®) was approved in December 2013 in UK for treatment of eyes which are pseudophakic with DMO that is unresponsive to other available therapies. This approval was based on evidence from FAME trials which were conducted at a time when ranibizumab was not available. There is a paucity of data on implementation of guidance on selecting patients for this treatment modality and also on the real world outcome of fluocinolone therapy especially in those patients that have been unresponsive to ranibizumab therapy. Method: Retrospective study of consecutive patients treated with fluocinolone between January and August 2014 at three sites were included to evaluate selection criteria used, baseline characteristics and clinical outcomes at 3-month time point. Results: Twenty two pseudophakic eyes of 22 consecutive patients were included. Majority of patients had prior therapy with multiple intravitreal anti-VEGF injections. Four eyes had controlled glaucoma. At baseline mean VA and CRT were 50.7 letters and 631 μm respectively. After 3 months, 18 patients had improved CRT of which 15 of them also had improved VA. No adverse effects were noted. One additional patient required IOP lowering medication. Despite being unresponsive to multiple prior therapies including laser and anti-VEGF injections, switching to fluocinolone achieved treatment benefit. Conclusion: The patient level selection criteria proposed by NICE guidance on fluocinolone appeared to be implemented. This data from this study provides new evidence on early outcomes following fluocinolone therapy in eyes with DMO which had not responded to laser and other intravitreal agents.

Secure and Privacy-aware Data Collection and Processing in Mobile Health Systems

Healthcare systems have assimilated information and communication technologies in order to improve the quality of healthcare and patient's experience at reduced costs. The increasing digitalization of people's health information raises however new threats regarding information security and privacy. Accidental or deliberate data breaches of health data may lead to societal pressures, embarrassment and discrimination. Information security and privacy are paramount to achieve high quality healthcare services, and further, to not harm individuals when providing care. With that in mind, we give special attention to the category of Mobile Health (mHealth) systems. That is, the use of mobile devices (e.g., mobile phones, sensors, PDAs) to support medical and public health. Such systems, have been particularly successful in developing countries, taking advantage of the flourishing mobile market and the need to expand the coverage of primary healthcare programs. Many mHealth initiatives, however, fail to address security and privacy issues. This, coupled with the lack of specific legislation for privacy and data protection in these countries, increases the risk of harm to individuals. The overall objective of this thesis is to enhance knowledge regarding the design of security and privacy technologies for mHealth systems. In particular, we deal with mHealth Data Collection Systems (MDCSs), which consists of mobile devices for collecting and reporting health-related data, replacing paper-based approaches for health surveys and surveillance. This thesis consists of publications contributing to mHealth security and privacy in various ways: with a comprehensive literature review about mHealth in Brazil; with the design of a security framework for MDCSs (SecourHealth); with the design of a MDCS (GeoHealth); with the design of Privacy Impact Assessment template for MDCSs; and with the study of ontology-based obfuscation and anonymisation functions for health data.

Structured professional judgement approach to risk assessment: generalisability across patient groups for the prediction of adverse outcomes in secure mental health care

This is a redacted version of the the final thesis. Copyright material has been removed to comply with UK Copyright Law.

Agent based risk patient management

This paper explores the role of information and communication technologies in managing risk and early discharge patients, and suggests innovative actions in the area of E-Health services. Treatments of chronic illnesses, or treatments of special needs such as cardiovascular diseases, are conducted in long-stay hospitals, and in some cases, in the homes of patients with a follow-up from primary care centre. The evolution of this model is following a clear trend: trying to reduce the time and the number of visits by patients to health centres and derive tasks, so far as possible, toward outpatient care. Also the number of Early Discharge Patients (EDP) is growing, thus permiting a saving in the resources of the care center. The adequacy of agent and mobile technologies is assessed in light of the particular requirements of health care applications. A software system architecture is outlined and discussed. The major contributions are: first, the conceptualization of multiple mobile and desktop devices as part of a single distributed computing system where software agents are being executed and interact from their remote locations. Second, the use of distributed decision making in multiagent systems, as a means to integrate remote evidence and knowledge obtained from data that is being collected and/or processed by distributed devices. The system will be applied to patients with cardiovascular or Chronic Obstructive Pulmonary Diseases (COPD) as well as to ambulatory surgery patients. The proposed system will allow to transmit the patient's location and some information about his/her illness to the hospital or care centre

Effects of fibrosis morphology on reentrant ventricular tachycardia inducibility and simulation fidelity in patient-derived models

Myocardial fibrosis detected via delayed-enhanced magnetic resonance imaging (MRI) has been shown to be a strong indicator for ventricular tachycardia (VT) inducibility. However, little is known regarding how inducibility is affected by the details of the fibrosis extent, morphology, and border zone configuration. The objective of this article is to systematically study the arrhythmogenic effects of fibrosis geometry and extent, specifically on VT inducibility and maintenance. We present a set of methods for constructing patient-specific computational models of human ventricles using in vivo MRI data for patients suffering from hypertension, hypercholesterolemia, and chronic myocardial infarction. Additional synthesized models with morphologically varied extents of fibrosis and gray zone (GZ) distribution were derived to study the alterations in the arrhythmia induction and reentry patterns. Detailed electrophysiological simulations demonstrated that (1) VT morphology was highly dependent on the extent of fibrosis, which acts as a structural substrate, (2) reentry tended to be anchored to the fibrosis edges and showed transmural conduction of activations through narrow channels formed within fibrosis, and (3) increasing the extent of GZ within fibrosis tended to destabilize the structural reentry sites and aggravate the VT as compared to fibrotic regions of the same size and shape but with lower or no GZ. The approach and findings represent a significant step toward patient-specific cardiac modeling as a reliable tool for VT prediction and management of the patient. Sensitivities to approximation nuances in the modeling of structural pathology by image-based reconstruction techniques are also implicated.

Comparison of 1-year outcome in patients with severe aorta stenosis treated conservatively or by aortic valve replacement or by percutaneous transcatheter aortic valve implantation (data from a multicenter Spanish registry)

The factors that influence decision making in severe aortic stenosis (AS) are unknown. Our aim was to assess, in patients with severe AS, the determinants of management and prognosis in a multicenter registry that enrolled all consecutive adults with severe AS during a 1-month period. One-year follow-up was obtained in all patients and included vital status and aortic valve intervention (aortic valve replacement [AVR] and transcatheter aortic valve implantation [TAVI]). A total of 726 patients were included, mean age was 77.3 ± 10.6 years, and 377 were women (51.8%). The most common management was conservative therapy in 468 (64.5%) followed by AVR in 199 (27.4%) and TAVI in 59 (8.1%). The strongest association with aortic valve intervention was patient management in a tertiary hospital with cardiac surgery (odds ratio 2.7, 95% confidence interval 1.8 to 4.1, p <0.001). The 2 main reasons to choose conservative management were the absence of significant symptoms (136% to 29.1%) and the presence of co-morbidity (128% to 27.4%). During 1-year follow-up, 132 patients died (18.2%). The main causes of death were heart failure (60% to 45.5%) and noncardiac diseases (46% to 34.9%). One-year survival for patients treated conservatively, with TAVI, and with AVR was 76.3%, 94.9%, and 92.5%, respectively, p <0.001. One-year survival of patients treated conservatively in the absence of significant symptoms was 97.1%. In conclusion, most patients with severe AS are treated conservatively. The outcome in asymptomatic patients managed conservatively was acceptable. Management in tertiary hospitals is associated with valve intervention. One-year survival was similar with both interventional strategies.

New graduate nurses' developmental trajectories for capability beliefs concerning core competencies for healthcare professionals : A national cohort study on patient-centered care, teamwork and evidence-based practice.

Background: This study aimed to describe the developmental trajectories of registered nurses' capability beliefs during their first 3 years of practice. The focus was on three core competencies for health professionals-patient-centered care, teamwork, and evidence-based practice. Methods: A national cohort of registered nurses (n = 1,205) was recruited during their nursing education and subsequently surveyed yearly during the first 3 years of working life. The survey included 16 items on capability beliefs divided into three subscales for the assessment of patient-centered care, teamwork, and evidence-based practice, and the data were analyzed with linear latent growth modeling. Results: The nurses' capability beliefs for patient-centered care increased over the three first years of working life, their capability beliefs for evidence-based practice were stable over the 3 years, and their capability beliefs for teamwork showed a downward trend. Linking evidence to action: Through collaboration between nursing education and clinical practice, the transition to work life could be supported and competence development in newly graduated nurses could be enhanced to help them master the core competencies. Future research should focus on determining which factors impact the development of capability beliefs in new nurses and how these factors can be developed by testing interventions.

An exploration of treatment burden and patient capacity in people with stroke

Background and aims: Advances in modern medicine have led to improved outcomes after stroke, yet an increased treatment burden has been placed on patients. Treatment burden is the workload of health care for people with chronic illness and the impact that this has on functioning and well-being. Those with comorbidities are likely to be particularly burdened. Excessive treatment burden can negatively affect outcomes. Individuals are likely to differ in their ability to manage health problems and follow treatments, defined as patient capacity. The aim of this thesis was to explore the experience of treatment burden for people who have had a stroke and the factors that influence patient capacity. Methods: There were four phases of research. 1) A systematic review of the qualitative literature that explored the experience of treatment burden for those with stroke. Data were analysed using framework synthesis, underpinned by Normalisation Process Theory (NPT). 2) A cross-sectional study of 1,424,378 participants >18 years, demographically representative of the Scottish population. Binary logistic regression was used to analyse the relationship between stroke and the presence of comorbidities and prescribed medications. 3) Interviews with twenty-nine individuals with stroke, fifteen analysed by framework analysis underpinned by NPT and fourteen by thematic analysis. The experience of treatment burden was explored in depth along with factors that influence patient capacity. 4) Integration of findings in order to create a conceptual model of treatment burden and patient capacity in stroke. Results: Phase 1) A taxonomy of treatment burden in stroke was created. The following broad areas of treatment burden were identified: making sense of stroke management and planning care; interacting with others including health professionals, family and other stroke patients; enacting management strategies; and reflecting on management. Phase 2) 35,690 people (2.5%) had a diagnosis of stroke and of the 39 co-morbidities examined, 35 were significantly more common in those with stroke. The proportion of those with stroke that had >1 additional morbidities present (94.2%) was almost twice that of controls (48%) (odds ratio (OR) adjusted for age, gender and socioeconomic deprivation; 95% confidence interval: 5.18; 4.95-5.43) and 34.5% had 4-6 comorbidities compared to 7.2% of controls (8.59; 8.17-9.04). In the stroke group, 12.6% of people had a record of >11 repeat prescriptions compared to only 1.5% of the control group (OR adjusted for age, gender, deprivation and morbidity count: 15.84; 14.86-16.88). Phase 3) The taxonomy of treatment burden from Phase 1 was verified and expanded. Additionally, treatment burdens were identified as arising from either: the workload of healthcare; or the endurance of care deficiencies. A taxonomy of patient capacity was created. Six factors were identified that influence patient capacity: personal attributes and skills; physical and cognitive abilities; support network; financial status; life workload, and environment. A conceptual model of treatment burden was created. Healthcare workload and the presence of care deficiencies can influence and be influenced by patient capacity. The quality and configuration of health and social care services influences healthcare workload, care deficiencies and patient capacity. Conclusions: This thesis provides important insights into the considerable treatment burden experienced by people who have had a stroke and the factors that affect their capacity to manage health. Multimorbidity and polypharmacy are common in those with stroke and levels of these are high. Findings have important implications for the design of clinical guidelines and healthcare delivery, for example co-ordination of care should be improved, shared decision-making enhanced, and patients better supported following discharge from hospital.

Challenges and Opportunities of Machine Learning for Clinical and Omics Data

Clinical and omics data are a promising field of application for machine learning techniques even though these methods are not yet systematically adopted in healthcare institutions. Despite artificial intelligence has proved successful in terms of prediction of pathologies or identification of their causes, the systematic adoption of these techniques still presents challenging issues due to the peculiarities of the analysed data. The aim of this thesis is to apply machine learning algorithms to both clinical and omics data sets in order to predict a patient's state of health and get better insights on the possible causes of the analysed diseases. In doing so, many of the arising issues when working with medical data will be discussed while possible solutions will be proposed to make machine learning provide feasible results and possibly become an effective and reliable support tool for healthcare systems.

Data analysis with merge trees

Today’s data are increasingly complex and classical statistical techniques need growingly more refined mathematical tools to be able to model and investigate them. Paradigmatic situations are represented by data which need to be considered up to some kind of trans- formation and all those circumstances in which the analyst finds himself in the need of defining a general concept of shape. Topological Data Analysis (TDA) is a field which is fundamentally contributing to such challenges by extracting topological information from data with a plethora of interpretable and computationally accessible pipelines. We con- tribute to this field by developing a series of novel tools, techniques and applications to work with a particular topological summary called merge tree. To analyze sets of merge trees we introduce a novel metric structure along with an algorithm to compute it, define a framework to compare different functions defined on merge trees and investigate the metric space obtained with the aforementioned metric. Different geometric and topolog- ical properties of the space of merge trees are established, with the aim of obtaining a deeper understanding of such trees. To showcase the effectiveness of the proposed metric, we develop an application in the field of Functional Data Analysis, working with functions up to homeomorphic reparametrization, and in the field of radiomics, where each patient is represented via a clustering dendrogram.