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Journal articleFusari G, Gibbs E, Hoskin L, et al., 2020,
Protocol for a feasibility study of OnTrack: a digital system for upper limb rehabilitation after stroke., BMJ Open, Vol: 10, Pages: 1-10, ISSN: 2044-6055
INTRODUCTION: Arm weakness is a common problem after stroke (affecting 450 000 people in the UK) leading to loss of independence. Repetitive activity is critical for recovery but research shows people struggle with knowing what or how much to do, and keeping track of progress. Working with more than 100 therapists (occupational therapists and physiotherapists) and patients with stroke, we codeveloped the OnTrack intervention-consisting of software for smart devices and coaching support-that has the potential to address this problem. This is a protocol to assess the feasibility of OnTrack for evaluation in a randomised control trial. METHODS AND ANALYSIS: A mixed-method, single-arm study design will be used to evaluate the feasibility of OnTrack for hospital and community use. A minimum sample of 12 participants from a stroke unit will be involved in the study for 14 weeks. During week 1, 8 and 14 participants will complete assessments relating to their arm function, arm impairment and activation. During weeks 2-13, participants will use OnTrack to track their arm movement in real time, receive motivational messages and face-to-face sessions to address problems, gain feedback on activity and receive self-management skills coaching. All equipment will be loaned to study participants. A parallel process evaluation will be conducted to assess the intervention's fidelity, dose and reach, using a mixed-method approach. A public and patient involvement group will oversee the study and help with interpretation and dissemination of qualitative and quantitative data findings. ETHICS AND DISSEMINATION: Ethical approval granted by the National Health Service Health Research Authority, Health and Care Research Wales, and the London-Surrey Research Ethics Committee (ref. 19/LO/0881). Trial results will be submitted for publication in peer review journals, presented at international conferences and disseminated among stroke communities. The results of this trial will inform
Journal articleGoiana-da-Silva F, Severo M, Cruz-E-Silva D, et al., 2020,
Projected impact of the Portuguese sugar-sweetened beverages tax on obesity incidence across different age groups: a modelling study, PLoS Medicine, Vol: 17, Pages: 1-17, ISSN: 1549-1277
BackgroundExcessive consumption of sugar has a well-established link with obesity. Preliminary results show that a tax levied on sugar-sweetened beverages (SSBs) by the Portuguese government in 2017 led to a drop in sales and reformulation of these products. This study models the impact the market changes triggered by the tax levied on SSBs had on obesity incidence across various age groups in Portugal.Methods and findingsWe performed a national market analysis and population-wide modelling study using market data for the years 2014–2018 from the Portuguese Association of Non-Alcoholic Drinks (GlobalData and Nielsen Consumer Panel), dietary data from a national survey (IAN-AF 2015–2016), and obesity incidence data from several cohort studies. Dietary energy density from SSBs was calculated by dividing the energy content (kcal/gram) of all SSBs by the total food consumption (in grams). We used the potential impact fraction (PIF) equation to model the projected impact of the tax-triggered change in sugar consumption on obesity incidence, through both volume reduction and reformulation. Results showed a reduction of 6.6 million litres of SSBs sold per year. Product reformulation led to a decrease in the average energy density of SSBs by 3.1 kcal/100 ml. This is estimated to have prevented around 40–78 cases of obesity per year between 2016 and 2018, with the biggest projected impact observed in adolescents 10 to <18 years old. The model shows that the implementation of this tax allowed for a 4 to 8 times larger projected impact against obesity than would be achieved though reformulation alone. The main limitation of this study is that the model we used includes data from various sources, which can result in biases—despite our efforts to mitigate them—related to the methodological differences between these sources.ConclusionsThe tax triggered both a reduction in demand and product reformulation. These, together, can reduce obesity levels
Journal articleMazzucato M, Li HL, Darzi A, 2020,
Conference paperDryden S, Anastasova S, Satta G, et al., 2020,
150 million people worldwide suffer one or more urinary tract infections (UTIs) annually. UTIs are a significant health burden: societal costs of UTI exceed $3.5 billion in the U.S. alone; 5% of sepsis cases arise from a urinary source; and UTIs are a prominent contributor toward antimicrobial resistance (AMR). Current diagnostic frameworks exacerbate this burden by providing inaccurate and delayed diagnosis. Rapid point-of-care bacterial identification will allow for early precision treatment, fundamentally altering the UTI paradigm. Raman spectroscopy has a proven ability to provide rapid bacterial identification but is limited by weak bacterial signal and a susceptibility to background fluorescence. These limitations may be overcome using surface enhanced Raman spectroscopy (SERS), provided close and consistent application of bacteria to the SERS-active surface can be achieved. Physical filtration provides a means of capturing uropathogens, separating them from the background solution and acting as SERS-active surface. This work demonstrates that filters can provide a means of aggregating bacteria, thereby allowing subsequent enhancement of the acquired Raman signal using metallic nanoparticles. 60 bacterial suspensions of common uropathogens were vacuum filtered onto commercial polyvinylidene fluoride membrane filters and Raman signals were enhanced by the addition of silver nanoparticles directly onto the filter surface. SERS spectra were acquired using a commercial Raman spectrometer (Ocean Optics, Inc.). Principal Component – Linear Discriminant Analysis provided discrimination of infected from control samples (accuracy: 88.75%, 95% CI: 79.22-94.59%, p-value <0.05). Amongst infected samples uropathogens were classified with 80% accuracy. This study has demonstrated that combining Raman spectroscopy with membrane filtration and SERS can provide identification of infected samples and rapid bacterial classification.
Journal articleGeeson C, Wei L, Franklin BD, 2020,
ReportGhafur S, Fontana G, Halligan J, et al., 2020,
Journal articleVos J, Franklin BD, Chumbley G, et al., 2020,
Journal articleRunciman M, Avery J, Zhao M, et al., 2020,
Minimally Invasive Surgery (MIS) imposes a trade-off between non-invasive access and surgical capability. Treatment of early gastric cancers over 20 mm in diameter can be achieved by performing Endoscopic Submucosal Dissection (ESD) with a flexible endoscope; however, this procedure is technically challenging, suffers from extended operation times and requires extensive training. To facilitate the ESD procedure, we have created a deployable cable driven robot that increases the surgical capabilities of the flexible endoscope while attempting to minimize the impact on the access that they offer. Using a low-profile inflatable support structure in the shape of a hollow hexagonal prism, our robot can fold around the flexible endoscope and, when the target site has been reached, achieve a 73.16% increase in volume and increase its radial stiffness. A sheath around the variable stiffness structure delivers a series of force transmission cables that connect to two independent tubular end-effectors through which standard flexible endoscopic instruments can pass and be anchored. Using a simple control scheme based on the length of each cable, the pose of the two instruments can be controlled by haptic controllers in each hand of the user. The forces exerted by a single instrument were measured, and a maximum magnitude of 8.29 N observed along a single axis. The working channels and tip control of the flexible endoscope remain in use in conjunction with our robot and were used during a procedure imitating the demands of ESD was successfully carried out by a novice user. Not only does this robot facilitate difficult surgical techniques, but it can be easily customized and rapidly produced at low cost due to a programmatic design approach.
Conference paperLeiloglou M, Gkouzionis I, Avila-Rencoret FB, et al., 2020,
Snapshot hyperspectral system for breast conserving surgery guidance
There is an unmet need for accurate tumour localization in vivo during breast conserving surgery. Herein a novel snapshot hyperspectral system is presented for accurately detecting the intrinsic fluorescence signal in real-time fluorescence guided surgery.
Journal articleMcKinney SM, Sieniek M, Godbole V, et al., 2020,
Screening mammography aims to identify breast cancer at earlier stages of the disease, when treatment can be more successful1. Despite the existence of screening programmes worldwide, the interpretation of mammograms is affected by high rates of false positives and false negatives2. Here we present an artificial intelligence (AI) system that is capable of surpassing human experts in breast cancer prediction. To assess its performance in the clinical setting, we curated a large representative dataset from the UK and a large enriched dataset from the USA. We show an absolute reduction of 5.7% and 1.2% (USA and UK) in false positives and 9.4% and 2.7% in false negatives. We provide evidence of the ability of the system to generalize from the UK to the USA. In an independent study of six radiologists, the AI system outperformed all of the human readers: the area under the receiver operating characteristic curve (AUC-ROC) for the AI system was greater than the AUC-ROC for the average radiologist by an absolute margin of 11.5%. We ran a simulation in which the AI system participated in the double-reading process that is used in the UK, and found that the AI system maintained non-inferior performance and reduced the workload of the second reader by 88%. This robust assessment of the AI system paves the way for clinical trials to improve the accuracy and efficiency of breast cancer screening.
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