Ophthalmia neonatorum and the role of primary care

We thank Maqsood and Mahmood for their article on herpes simplex keratitis in neonates,1 which includes pointers on distinguishing HSV keratitis from other infective causes. While this is an interesting clinical point, we feel that it lacks a primary care perspective. ‘Sticky eye’ is a common presentation in newborns, and is usually due to immature nasolacrimal duct formation, which requires no treatment unless it fails to improve by 1 year of age. Ophthalmia neonatorum, whether bacterial or viral, requires urgent secondary care input for full assessment and treatment.2 As discussed in the article by Maqsood and Mahmood, eye infections in the newborn are unlikely to present with features that clearly distinguish benign infections from more significant causes. While the frequency with which HSV causes eye infections in newborns is not stated, we presume that it is uncommon enough that many GPs will not see a case during their career. It is difficult to have a high index of suspicion for such a specific yet infrequently occurring event. We therefore suggest that primary care practitioners need only to distinguish infective from non-infective causes of ocular discharge in neonates, and urgently refer all neonates with suspected infection, while avoiding unnecessary treatment for a newborn with a blocked tear duct

Gaussian Approximation Potentials: the accuracy of quantum mechanics, without the electrons

We introduce a class of interatomic potential models that can be automatically generated from data consisting of the energies and forces experienced by atoms, derived from quantum mechanical calculations. The resulting model does not have a fixed functional form and hence is capable of modeling complex potential energy landscapes. It is systematically improvable with more data. We apply the method to bulk carbon, silicon and germanium and test it by calculating properties of the crystals at high temperatures. Using the interatomic potential to generate the long molecular dynamics trajectories required for such calculations saves orders of magnitude in computational cost.Comment: v3-4: added new material and reference

Probabilistic Inference for Fast Learning in Control

We provide a novel framework for very fast model-based reinforcement learning in continuous state and action spaces. The framework requires probabilistic models that explicitly characterize their levels of confidence. Within this framework, we use flexible, non-parametric models to describe the world based on previously collected experience. We demonstrate learning on the cart-pole problem in a setting where we provide very limited prior knowledge about the task. Learning progresses rapidly, and a good policy is found after only a hand-full of iterations

Knot selection in sparse Gaussian processes with a variational objective function

Sparse, knot‐based Gaussian processes have enjoyed considerable success as scalable approximations of full Gaussian processes. Certain sparse models can be derived through specific variational approximations to the true posterior, and knots can be selected to minimize the Kullback‐Leibler divergence between the approximate and true posterior. While this has been a successful approach, simultaneous optimization of knots can be slow due to the number of parameters being optimized. Furthermore, there have been few proposed methods for selecting the number of knots, and no experimental results exist in the literature. We propose using a one‐at‐a‐time knot selection algorithm based on Bayesian optimization to select the number and locations of knots. We showcase the competitive performance of this method relative to optimization of knots simultaneously on three benchmark datasets, but at a fraction of the computational cost

Protocolised non-invasive compared with invasive weaning from mechanical ventilation for adults in intensive care : the Breathe RCT

Background: Invasive mechanical ventilation (IMV) is a life-saving intervention. Following resolution of the condition that necessitated IMV, a spontaneous breathing trial (SBT) is used to determine patient readiness for IMV discontinuation. In patients who fail one or more SBTs, there is uncertainty as to the optimum management strategy. Objective: To evaluate the clinical effectiveness and cost-effectiveness of using non-invasive ventilation (NIV) as an intermediate step in the protocolised weaning of patients from IMV. Design: Pragmatic, open-label, parallel-group randomised controlled trial, with cost-effectiveness analysis. Setting: A total of 51 critical care units across the UK. Participants: Adult intensive care patients who had received IMV for at least 48 hours, who were categorised as ready to wean from ventilation, and who failed a SBT. Interventions: Control group (invasive weaning): patients continued to receive IMV with daily SBTs. A weaning protocol was used to wean pressure support based on the patient’s condition. Intervention group (non-invasive weaning): patients were extubated to NIV. A weaning protocol was used to wean inspiratory positive airway pressure, based on the patient’s condition. Main outcome measures: The primary outcome measure was time to liberation from ventilation. Secondary outcome measures included mortality, duration of IMV, proportion of patients receiving antibiotics for a presumed respiratory infection and health-related quality of life. Results: A total of 364 patients (invasive weaning, n = 182; non-invasive weaning, n = 182) were randomised. Groups were well matched at baseline. There was no difference between the invasive weaning and non-invasive weaning groups in median time to liberation from ventilation {invasive weaning 108 hours [interquartile range (IQR) 57–351 hours] vs. non-invasive weaning 104.3 hours [IQR 34.5–297 hours]; hazard ratio 1.1, 95% confidence interval [CI] 0.89 to 1.39; p = 0.352}. There was also no difference in mortality between groups at any time point. Patients in the non-invasive weaning group had fewer IMV days [invasive weaning 4 days (IQR 2–11 days) vs. non-invasive weaning 1 day (IQR 0–7 days); adjusted mean difference –3.1 days, 95% CI –5.75 to –0.51 days]. In addition, fewer non-invasive weaning patients required antibiotics for a respiratory infection [odds ratio (OR) 0.60, 95% CI 0.41 to 1.00; p = 0.048]. A higher proportion of non-invasive weaning patients required reintubation than those in the invasive weaning group (OR 2.00, 95% CI 1.27 to 3.24). The within-trial economic evaluation showed that NIV was associated with a lower net cost and a higher net effect, and was dominant in health economic terms. The probability that NIV was cost-effective was estimated at 0.58 at a cost-effectiveness threshold of £20,000 per quality-adjusted life-year. Conclusions: A protocolised non-invasive weaning strategy did not reduce time to liberation from ventilation. However, patients who underwent non-invasive weaning had fewer days requiring IMV and required fewer antibiotics for respiratory infections. Future work: In patients who fail a SBT, which factors predict an adverse outcome (reintubation, tracheostomy, death) if extubated and weaned using NIV? Trial registration: Current Controlled Trials ISRCTN15635197. Funding: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 23, No. 48. See the NIHR Journals Library website for further project information

Adoption of total quality management in the educational sector: case study of Engineering Institutions

Abstract : Due to the aspirations of various institutional stakeholders clamoring for improvement in the quality of education in their various institutions, the concept of total quality management has gained so much attention to this regard. In the recent time, several emphases have been made on the need for quality improvement and efforts are been put in place on the possible ways of increasing the standard of education globally. The productivity of any tertiary institution, especially the Engineering colleges is centered on the quality culture of such institutions, also, the customer’s satisfaction is another thing to put into consideration, to achieve the desired productivity. Generally, there are some constructs which are the major critical success factors that enhances quality improvement in any organization, customer satisfaction has been identified as another important factor to put into consideration to achieve optimum quality of products as well as services. This paper gives an insight on how the implementation of Total Quality Management in an Engineering educational system can aid the Quality of Engineering Education

Targeting Methylglyoxal in Diabetic Kidney Disease Using the Mitochondria-Targeted Compound MitoGamide.

Diabetic kidney disease (DKD) remains the number one cause of end-stage renal disease in the western world. In experimental diabetes, mitochondrial dysfunction in the kidney precedes the development of DKD. Reactive 1,2-dicarbonyl compounds, such as methylglyoxal, are generated from sugars both endogenously during diabetes and exogenously during food processing. Methylglyoxal is thought to impair the mitochondrial function and may contribute to the pathogenesis of DKD. Here, we sought to target methylglyoxal within the mitochondria using MitoGamide, a mitochondria-targeted dicarbonyl scavenger, in an experimental model of diabetes. Male 6-week-old heterozygous Akita mice (C57BL/6-Ins2-Akita/J) or wildtype littermates were randomized to receive MitoGamide (10 mg/kg/day) or a vehicle by oral gavage for 16 weeks. MitoGamide did not alter the blood glucose control or body composition. Akita mice exhibited hallmarks of DKD including albuminuria, hyperfiltration, glomerulosclerosis, and renal fibrosis, however, after 16 weeks of treatment, MitoGamide did not substantially improve the renal phenotype. Complex-I-linked mitochondrial respiration was increased in the kidney of Akita mice which was unaffected by MitoGamide. Exploratory studies using transcriptomics identified that MitoGamide induced changes to olfactory signaling, immune system, respiratory electron transport, and post-translational protein modification pathways. These findings indicate that targeting methylglyoxal within the mitochondria using MitoGamide is not a valid therapeutic approach for DKD and that other mitochondrial targets or processes upstream should be the focus of therapy

A Bayesian Nonparametric Approach to Modeling Motion Patterns

The most difficult—and often most essential— aspect of many interception and tracking tasks is constructing motion models of the targets to be found. Experts can often provide only partial information, and fitting parameters for complex motion patterns can require large amounts of training data. Specifying how to parameterize complex motion patterns is in itself a difficult task. In contrast, nonparametric models are very flexible and generalize well with relatively little training data. We propose modeling target motion patterns as a mixture of Gaussian processes (GP) with a Dirichlet process (DP) prior over mixture weights. The GP provides a flexible representation for each individual motion pattern, while the DP assigns observed trajectories to particular motion patterns. Both automatically adjust the complexity of the motion model based on the available data. Our approach outperforms several parametric models on a helicopter-based car-tracking task on data collected from the greater Boston area

Patient experience and reflective learning (PEARL): a mixed methods protocol for staff insight development in acute and intensive care medicine in the UK

INTRODUCTION: Patient and staff experiences are strongly influenced by attitudes and behaviours, and provide important insights into care quality. Patient and staff feedback could be used more effectively to enhance behaviours and improve care through systematic integration with techniques for reflective learning. We aim to develop a reflective learning framework and toolkit for healthcare staff to improve patient, family and staff experience. METHODS & ANALYSIS: Local project teams including staff and patients from the acute medical units (AMUs) and intensive care units (ICUs) of three National Health Service trusts will implement two experience surveys derived from existing instruments: a continuous patient and relative survey and an annual staff survey. Survey data will be supplemented by ethnographic interviews and observations in the workplace to evaluate barriers to and facilitators of reflective learning. Using facilitated iterative co-design, local project teams will supplement survey data with their experiences of healthcare to identify events, actions, activities and interventions which promote personal insight and empathy through reflective learning. Outputs will be collated by the central project team to develop a reflective learning framework and toolkit which will be fed back to the local groups for review, refinement and piloting. The development process will be mapped to a conceptual theory of reflective learning which combines psychological and pedagogical theories of learning, alongside theories of behaviour change based on capability, opportunity and motivation influencing behaviour. The output will be a locally-adaptable workplace-based toolkit providing guidance on using reflective learning to incorporate patient and staff experience in routine clinical activities. ETHICS & DISSEMINATION: The PEARL project has received ethics approval from the London Brent Research Ethics Committee (REC Ref 16/LO/224). We propose a national cluster randomised step-wedge trial of the toolkit developed for large-scale evaluation of impact on patient outcomes

Towards Better Integration of Surrogate Models and Optimizers

Surrogate-Assisted Evolutionary Algorithms (SAEAs) have been proven to be very effective in solving (synthetic and real-world) computationally expensive optimization problems with a limited number of function evaluations. The two main components of SAEAs are: the surrogate model and the evolutionary optimizer, both of which use parameters to control their respective behavior. These parameters are likely to interact closely, and hence the exploitation of any such relationships may lead to the design of an enhanced SAEA. In this chapter, as a first step, we focus on Kriging and the Efficient Global Optimization (EGO) framework. We discuss potentially profitable ways of a better integration of model and optimizer. Furthermore, we investigate in depth how different parameters of the model and the optimizer impact optimization results. In particular, we determine whether there are any interactions between these parameters, and how the problem characteristics impact optimization results. In the experimental study, we use the popular Black-Box Optimization Benchmarking (BBOB) testbed. Interestingly, the analysis finds no evidence for significant interactions between model and optimizer parameters, but independently their performance has a significant interaction with the objective function. Based on our results, we make recommendations on how best to configure EGO