Nanoparticle-Mediated Drug Delivery for the Treatment of Cardiovascular Diseases

Cardiovascular diseases (CVDs) are one of the foremost causes of high morbidity and mortality globally. Preventive, diagnostic, and treatment measures available for CVDs are not very useful, which demands promising alternative methods. Nanoscience and nanotechnology open a new window in the area of CVDs with an opportunity to achieve effective treatment, better prognosis, and less adverse effects on non-target tissues. The application of nanoparticles and nanocarriers in the area of cardiology has gathered much attention due to the properties such as passive and active targeting to the cardiac tissues, improved target specificity, and sensitivity. It has reported that more than 50% of CVDs can be treated effectively through the use of nanotechnology. The main goal of this review is to explore the recent advancements in nanoparticle-based cardiovascular drug carriers. This review also summarizes the difficulties associated with the conventional treatment modalities in comparison to the nanomedicine for CVDs

Strategic Intelligence Monitor on Personal Health Systems (SIMPHS): Market Structure and Innovation Dynamics

Personal Health Systems (PHS) and Remote Patient Monitoring and Treatment (RMT) have the potential to alter the way healthcare is provided by increasing the quantity and quality of care. This report explores the current status of PHS and, more specifically of the RMT market in Europe. It addresses the question of how these technologies can contribute facing some of the challenges standing in front of the European healthcare delivery systems causes by higher demand pressures through chronic diseases and demographic change combined with diminishing resources for health care. An uptake and diffusion of these services would potentially lead to benefits through a reduction in death rates, and avoid recurring hospitalisation in a cost-effective manner. Yet the report identifies different categories of barriers hampering a full deployment of RMT in Europe. In the concluding part the reports provides a number of tentative policy options specifically aimed at fostering EU-wide deployment of RMT/PHS.JRC.DDG.J.4-Information Societ

Cardiovascular health promotion : A systematic review involving effectiveness of faith-based institutions in facilitating maintenance of normal blood pressure

Globally, faith institutions have a range of beneficial social utility, but a lack of understanding remains regarding their role in cardiovascular health promotion, particularly for hypertension. Our objective was assessment of modalities, mechanisms and effectiveness of hypertension health promotion and education delivered through faith institutions. A result-based convergent mixed methods review was conducted with 24 databases including MEDLINE, Embase and grey literature sources searched on 30 March 2021, results independently screened by three researchers, and data extracted based on behaviour change theories. Quality assessment tools were selected by study design, from Cochrane risk of bias, ROBINS I and E, and The Joanna Briggs Institute's Qualitative Assessment and Review Instrument tools. Twenty-four publications contributed data. Faith institution roles include cardiovascular health/disease teaching with direct lifestyle linking, and teaching/ encouragement of personal psychological control. Also included were facilitation of: exercise/physical activity as part of normal lifestyle, nutrition change for cardiovascular health, cardiovascular health measurements, and opportunistic blood pressure checks. These demand relationships of trust with local leadership, contextualisation to local sociocultural realities, volitional participation but prior consent by faith / community leaders. Limited evidence for effectiveness: significant mean SBP reduction of 2.98 mmHg (95%CI -4.39 to -1.57), non-significant mean DBP increase of 0.14 mmHg (95%CI -2.74 to +3.01) three months after interventions; and significant mean SBP reduction of 0.65 mmHg (95%CI -0.91 to -0.39), non-significant mean DBP reduction of 0.53 mmHg (95%CI -1.86 to 0.80) twelve months after interventions. Body weight, waist circumference and multiple outcomes beneficially reduced for cardiovascular health: significant mean weight reduction 0.83kg (95% CI -1.19 to -0.46), and non-significant mean waist circumference reduction 1.48cm (95% CI -3.96 to +1.00). In addressing the global hypertension epidemic the cardiovascular health promotion roles of faith institutions probably hold unrealised potential. Deliberate cultural awareness, intervention contextualisation, immersive involvement of faith leaders and alignment with religious practice characterise their deployment as healthcare assets

Statistical Models for Detecting Existence of Obstructive Sleep Apnea, Predicting Its Severity, and Forecasting Future Episodes

This dissertation presents three statistical models based on data mining and nonlinear time-series analysis techniques as an alternative method for the diagnosis and treatment of obstructive sleep apnea disease (OSA). From a diagnosis perspective, our method reduces the time and cost associated with the conventional method by first screening a non-OSA subject from the population, then individually determining the OSA�s severity by utilizing the data from a single-lead electrocardiogram (ECG) device that is worn overnight at the subject�s location. Our OSA forecasting model can be used to activate an OSA therapy device such as a continuous positive airway pressure (CPAP) machine or a hypoglossal nerve stimulator (HNS) as needed or before an OSA episode so that the latter can be averted in real time.In particular, our contributions are: 1) Detect the existence of OSA in an individual based on the pattern of biological physiology and simple clinical data with a low false negative rate and reasonable accuracy (FNR: 5.3%, Accuracy: 84.47%). People with some degree of probability of having OSA will be confirmed by the next model. 2) Determine the OSA severity by classifying the OSA episode (event) from one-lead ECG data collected overnight (accuracy: 92.26% with 10,052 equally sampled events from 24 subjects). The advantage of our model is that the variations (i.e., different body build, age, gender, activity, health conditions, and race) have very little effect on the prediction because the neighboring patterns in the reconstructed phase spaces have very little or no correlation to those variations. This benefit can be seen from our model�s performance compared to two other models that exist in the literature. 3) Forecast an incoming OSA episode in real time using the one-lead ECG data (accuracy: 92%, 88%, and 87% for 1, 5, and 10 minutes ahead). This forecasting model with any appropriate OSA episode prevention device (i.e., HNS, and just-in-time CPAP) will allow for an effective OSA treatment method for CPAP nonadherence OSA sufferers. 4) Develop a wearable device that can collect the biological data via a single-lead ECG as a home sleep test (HST) device.Industrial Engineering & Managemen

Representación, interpretación y aprendizaje de flujos de trabajo basado en actividades para la estandarización de vías clínicas

Describir los mejores procesos para ejecutar correctamente una estrategia de una forma eficiente y con calidad no es siempre una tarea fácil. La estandarizaci ón de procesos en general y de Vías Clínicas en particular requiere de potentes herramientas de especificación e implementación que apoyen a los expertos en diseño. La utilización de modelos de Flujos de Trabajo (del inglés Work ows) facilita a los expertos en diseño la creación las reglas de ejecución de sus sistemas como si fueran programadores. Aún así debido a la gran mutabilidad de los procesos reales, es muy difícil conocer como los procesos se están ejecutando en la realidad. La utilización de técnicas de reconocimiento de formas pueden ayudar a los expertos en procesos a inferir, a partir de muestras de ejecución pasadas, modelos que expliquen la forma en la que estos procesos están efectivamente ejecutándose. Este paradigma es conocido como Aprendizaje de Flujos de Trabajo (del inglés Work ow Mining). Los cambios de estado en los procesos de cuidado existentes en las Vías Clínicas se basan en los resultados de las acciones. Los modelos actuales de Aprendizaje de Flujos de Trabajo no recogen esta información en sus corpus. Por eso, los actuales sistemas de aprendizaje no cubren las necesidades de problemas complejos como es el caso de las Vías Clínicas. En esta Tesis se van a estudiar los modelos de representación, interpretación y aprendizaje de Flujos de Trabajo con la intención de proponer un modelo adecuado para resolver los problemas que impiden a los diseñadores de procesos complejos, como Vías Clínicas, utilizar técnicas de Aprendizaje de Flujos de Trabajo. Para ello se va a definir un nuevo paradigma adecuado para el apoyo al diseño de Vías Clínicas, además de proporcionar herramientas para su uso. Por esto en esta Tesis se presenta además un modelo de representación de Flujos de Trabajo con una alta expresividad y legibilidad, una herramienta software capaz de ejecutar y simular Flujos de TrabFernández Llatas, C. (2009). Representación, interpretación y aprendizaje de flujos de trabajo basado en actividades para la estandarización de vías clínicas [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/4562Palanci

Designing wearable sensors for Preventative Health: An exploration of material, form and function

The financial burden on global healthcare systems has reached unprecedented levels and as a result, attention has been shifting from the traditional approach of disease management and treatment towards prevention (Swan, 2012). Wearable devices for Preventative Health have become a focus for innovation across academia and industry, thus this thesis explores the design of wearable biochemical and environmental sensors, which can provide users with an early warning, detection and monitoring system that could integrate easily into their existing lives. The research aims to generate new practical knowledge for the design and development of wearable sensors and, motivated by the identification of compelling design opportunities, merges three strands of enquiry. The research methodology supports this investigation into material, form and function through the use of key practice-based methods, which include Participatory Action Research (active immersion and participation in a particular community and user workshops) and the generation and evaluation of a diverse range of artefacts. Based on the user-centred investigation of the use case for biochemical and environmental sensing, the final collection of artefacts demonstrates a diverse range of concepts, which present biodegradable and recyclable nonwoven material substrates for the use in non-integrated sensors. These sensors can be skin-worn, body-worn or clothing-attached for in-situ detection and monitoring of both internal (from the wearer) and external (from the environment) stimuli. The research proposes that in order to engage a broad section of the population in a preventative lifestyle to significantly reduce the pressure on global healthcare systems, wearable sensors need to be designed so they can appeal to as many users as possible and integrate easily into their existing lifestyles, routines and outfits. The thesis argues that this objective could be achieved through the design and development of end-of-life considered and cost-effective substrate materials, non-integrated wearable form factors and meticulous consideration of a divergent range of user needs and preferences, during the early stages of design practice