Clinical outcomes of Staphylococcus capitis isolation from neonates, England, 2015-2021: a retrospective case-control study.

OBJECTIVE: Staphylococcus capitis, a coagulase-negative staphylococci (CoNS) species, has been increasingly detected from UK sterile site samples and has caused neonatal unit outbreaks worldwide. We compared survival to discharge and 30-day mortality for the detection of S. capitis versus other CoNS species. METHODS: In this retrospective case-control study, we included hospitalised infants with any CoNS species detected from a normally sterile body site up to 90 days of age. We linked English laboratory reports from the Second Generation Surveillance System database, mortality data from the Personal Demographics Service, and neonatal unit admissions from the National Neonatal Research Database. In primary analysis, multivariable logistic regression was used, with two co-primary outcomes: survival to discharge and death within 30 days of positive specimen date. Sensitivity analyses using multiply imputed datasets followed. RESULTS: We identified 16 636 CoNS episodes relating to 13 745 infants. CoNS episodes were highest among infants born extremely preterm (22-27 weeks) and with extremely low birth weight (400-999 g). In primary analysis, there were no differences in survival to discharge (p=0.71) or 30-day mortality (p=0.77) between CoNS species. In sensitivity analyses, there were no differences in outcomes between infection with four of the most common CoNS species (Staphylococcus epidermidis, S. capitis, Staphylococcus haemolyticus and Staphylococcus warneri) but the remaining CoNS species were at higher risk of adverse outcomes when treated in aggregate. CONCLUSION: Infants with S. capitis detected from sterile site samples did not experience significant differences in either survival to discharge or 30-day mortality compared with infants with detection of other common CoNS species.

Data Mining and Fusion Framework for In-Home Monitoring Applications.

Sensor Data Fusion (SDT) algorithms and models have been widely used in diverse applications. One of the main challenges of SDT includes how to deal with heterogeneous and complex datasets with different formats. The present work utilised both homogenous and heterogeneous datasets to propose a novel SDT framework. It compares data mining-based fusion software packages such as RapidMiner Studio, Anaconda, Weka, and Orange, and proposes a data fusion framework suitable for in-home applications. A total of 574 privacy-friendly (binary) images and 1722 datasets gleaned from thermal and Radar sensing solutions, respectively, were fused using the software packages on instances of homogeneous and heterogeneous data aggregation. Experimental results indicated that the proposed fusion framework achieved an average Classification Accuracy of 84.7% and 95.7% on homogeneous and heterogeneous datasets, respectively, with the help of data mining and machine learning models such as Naïve Bayes, Decision Tree, Neural Network, Random Forest, Stochastic Gradient Descent, Support Vector Machine, and CN2 Induction. Further evaluation of the Sensor Data Fusion framework based on cross-validation of features indicated average values of 94.4% for Classification Accuracy, 95.7% for Precision, and 96.4% for Recall. The novelty of the proposed framework includes cost and timesaving advantages for data labelling and preparation, and feature extraction.

Implementing and measuring person-centredness using an APP for knowledge transfer: the iMPAKT app.

OBJECTIVE: The aim of the study was to evaluate a technological solution in the form of an App to implement and measure person-centredness in nursing. The focus was to enhance the knowledge transfer of a set of person-centred key performance indicators and the corresponding measurement framework used to inform improvements in the experience of care. DESIGN: The study used an evaluation approach derived from the work of the Medical Research Council to assess the feasibility of the App and establish the degree to which the App was meeting the aims set out in the development phase. Evaluation data were collected using focus groups (n = 7) and semi-structured interviews (n = 7) to capture the impact of processes experienced by participating sites. SETTING: The study was conducted in the UK and Australia in two organizations, across 11 participating sites. PARTICIPANTS: 22 nurses from 11 sites in two large health care organizations were recruited on a voluntary basis. INTERVENTION: Implementing the KPIs and measurement framework via the APP through two cycles of data collection. MAIN OUTCOME MEASURES: The main outcome was to establish feasibility in the use of the App. RESULTS: The majority of nurse/midwife participants found the App easy to use. There was broad consensus that the App was an effective method to measure the patient experience and generated clear, concise reports in real time. CONCLUSIONS: The implementation of the person-centred key performance indicators using the App enhanced the generation of meaningful data to evidence patient experience across a range of different clinical settings.

Genetic diversity of Nile tilapia (Oreochromis niloticus) throughout West Africa.

Nile tilapia (Oreochromis niloticus) is a globally significant aquaculture species rapidly gaining status as a farmed commodity. In West Africa, wild Nile tilapia genetic resources are abundant yet knowledge of fine-scale population structure and patterns of natural genetic variation are limited. Coinciding with this is a burgeoning growth in tilapia aquaculture in Ghana and other countries within the region underpinned by locally available genetic resources. Using 192 single nucleotide polymorphism (SNP) markers this study conducted a genetic survey of Nile tilapia throughout West Africa, sampling 23 wild populations across eight countries (Benin, Burkina Faso, Côte d'Ivoire, Ghana, Togo, Mali, Gambia and Senegal), representing the major catchments of the Volta, Niger, Senegal and Gambia River basins. A pattern of isolation-by-distance and significant spatial genetic structure was identified throughout West Africa (Global FST = 0.144), which largely corresponds to major river basins and, to a lesser extent, sub-basins. Two populations from the Gambia River (Kudang and Walekounda), one from the western Niger River (Lake Sélingué) and one from the upper Red Volta River (Kongoussi) showed markedly lower levels of diversity and high genetic differentiation compared to all other populations, suggesting genetically isolated populations occurring across the region. Genetic structure within the Volta Basin did not always follow the pattern expected for sub-river basins. This study identifies clear genetic structuring and differentiation amongst West African Nile tilapia populations, which concur with broad patterns found in previous studies. In addition, we provide new evidence for fine-scale genetic structuring within the Volta Basin and previously unidentified genetic differences of populations in Gambia. The 192 SNP marker suite used in this study is a useful tool for differentiating tilapia populations and we recommend incorporating this marker suite into future population screening of O. niloticus. Our results form the basis of a solid platform for future research on wild tilapia genetic resources in West Africa, and the identification of potentially valuable germplasm for use in ongoing breeding programs for aquaculture.

The Value of Including People with Dementia in the Co-Design of Personalized eHealth Technologies.

BACKGROUND: In this article, we discuss the benefits and implications of the shift from a user-centered to a co-creation approach in the processes of designing and developing eHealth and mHealth solutions for people with dementia. To this end, we illustrate the case study of a participatory design experience, implemented at the REMIND EU Project, Connected Health Summer School, which took place in June 2018 at Artimino (Italy). OBJECTIVES: The initiative was intended to reach two objectives: (1) help researchers specializing in a variety of fields (engineering, computing, psychology, nursing, and dementia care) develop a deeper understanding of how individuals living with dementia expect to be supported and/or enabled by eHealth and mHealth technologies and (2) prevent the tendency to focus on the impairments that characterize dementia at the expense of seeing the individual living with this condition as a whole person, striving to maintain a life that is as fulfilling as possible. METHOD: The Connected Health Summer School is an annual multidisciplinary training program, organized in collaboration with the REMIND EU Project, designed for early-stage researchers interested in the development of new eHealth and mHealth services and apps. For the 2018 program edition, REMIND end user partner Novilunio invited two members of the Irish Dementia Working Group to deliver keynote lectures, and engage in participatory workshops to facilitate the creation of digital technology applications based on their specific real-life needs, values, and expectations. Their involvement as participants and experts was aimed to give a clear message to early-stage researchers: a true personalized approach to eHealth and mHealth solutions can only emerge from a highly reflective and immersive appreciation of people's subjective accounts of their lived experience. RESULTS/CONCLUSIONS: The Connected Health Summer School early-stage researchers developed 6 app mock-ups based on their discussions and co-creation activities with the two experts with dementia. The reflections on this experience highlight a number of important issues that demand consideration when undertaking eHealth and mHealth research, co-design, and development with and for people with dementia. The evolution in design research from a user-centered approach to co-designing should pave the way to the development of technologies that neither disempower nor reinforce stigma, but instead provide a reliable support to living a life as active and meaningful as possible after a diagnosis of dementia. To this end, the motto of the peak global organization of people with dementia, Dementia Alliance International, says it all: "See the person and not the dementia."

Smart Sensing Technologies for Personalised e-Coaching.

People living in both developed and developing countries face serious health challenges related to sedentary lifestyles. It is therefore essential to find new ways to improve health so that people can live longer and age well. With an ever-growing number of smart sensing systems developed and deployed across the globe, experts are primed to help coach people to have healthier behaviors. The increasing accountability associated with app- and device-based behavior tracking not only provides timely and personalized information and support, but also gives us an incentive to set goals and do more. This paper outlines some of the recent efforts made towards automatic and autonomous identification and coaching of troublesome behaviors to procure lasting, beneficial behavioral changes.

An adaptive semantic based mediation system for data interoperability among Health Information Systems.

Heterogeneity in the management of the complex medical data, obstructs the attainment of data level interoperability among Health Information Systems (HIS). This diversity is dependent on the compliance of HISs with different healthcare standards. Its solution demands a mediation system for the accurate interpretation of data in different heterogeneous formats for achieving data interoperability. We propose an adaptive AdapteR Interoperability ENgine mediation system called ARIEN, that arbitrates between HISs compliant to different healthcare standards for accurate and seamless information exchange to achieve data interoperability. ARIEN stores the semantic mapping information between different standards in the Mediation Bridge Ontology (MBO) using ontology matching techniques. These mappings are provided by our System for Parallel Heterogeneity (SPHeRe) matching system and Personalized-Detailed Clinical Model (P-DCM) approach to guarantee accuracy of mappings. The realization of the effectiveness of the mappings stored in the MBO is evaluation of the accuracy in transformation process among different standard formats. We evaluated our proposed system with the transformation process of medical records between Clinical Document Architecture (CDA) and Virtual Medical Record (vMR) standards. The transformation process achieved over 90 % of accuracy level in conversion process between CDA and vMR standards using pattern oriented approach from the MBO. The proposed mediation system improves the overall communication process between HISs. It provides an accurate and seamless medical information exchange to ensure data interoperability and timely healthcare services to patients.

ATHENA: a personalized platform to promote an active lifestyle and wellbeing based on physical, mental and social health primitives.

Technology provides ample opportunities for the acquisition and processing of physical, mental and social health primitives. However, several challenges remain for researchers as how to define the relationship between reported physical activities, mood and social interaction to define an active lifestyle. We are conducting a project, ATHENA(activity-awareness for human-engaged wellness applications) to design and integrate the relationship between these basic health primitives to approximate the human lifestyle and real-time recommendations for wellbeing services. Our goal is to develop a system to promote an active lifestyle for individuals and to recommend to them valuable interventions by making comparisons to their past habits. The proposed system processes sensory data through our developed machine learning algorithms inside smart devices and utilizes cloud infrastructure to reduce the cost. We exploit big data infrastructure for massive sensory data storage and fast retrieval for recommendations. Our contributions include the development of a prototype system to promote an active lifestyle and a visual design capable of engaging users in the goal of increasing self-motivation. We believe that our study will impact the design of future ubiquitous wellness applications.

Smart home technologies for health and social care support.

BACKGROUND: The integration of smart home technology to support health and social care is acquiring an increasing global significance. Provision is framed within the context of a rapidly changing population profile, which is impacting on the number of people requiring health and social care, workforce availability and the funding of healthcare systems. OBJECTIVES: To explore the effectiveness of smart home technologies as an intervention for people with physical disability, cognitive impairment or learning disability, who are living at home, and to consider the impact on the individual's health status and on the financial resources of health care. SEARCH STRATEGY: We searched the following databases for primary studies: (a) the Cochrane Effective Practice and Organisation of Care (EPOC) Group Register, (b) the Cochrane Central Register of Controlled Trials (CENTRAL), (The Cochrane Library, issue 1, 2007), and (c) bibliographic databases, including MEDLINE (1966 to March 2007), EMBASE (1980 to March 2007) and CINAHL (1982 to March 2007). We also searched the Database of Abstracts of Reviews of Effectiveness (DARE). We searched the electronic databases using a strategy developed by the EPOC Trials Search Co-ordinator. SELECTION CRITERIA: We included randomised controlled trials (RCTs), quasi-experimental studies, controlled before and after studies (CBAs) and interrupted time series analyses (ITS). Participants included adults over the age of 18, living in their home in a community setting. Participants with a physical disability, dementia or a learning disability were included. The included interventions were social alarms, electronic assistive devices, telecare social alert platforms, environmental control systems, automated home environments and 'ubiquitous homes'. Outcome measures included any objective measure that records an impact on a participant's quality of life, healthcare professional workload, economic outcomes, costs to healthcare provider or costs to participant. We included measures of service satisfaction, device satisfaction and healthcare professional attitudes or satisfaction. DATA COLLECTION AND ANALYSIS: One review author completed the search strategy with the support of a life and health sciences librarian. Two review authors independently screened titles and abstracts of results. MAIN RESULTS: No studies were identified which met the inclusion criteria. AUTHORS' CONCLUSIONS: This review highlights the current lack of empirical evidence to support or refute the use of smart home technologies within health and social care, which is significant for practitioners and healthcare consumers.