Vision Screening Assessment (VISA) tool: diagnostic accuracy validation of a novel screening tool in detecting visual impairment among stroke survivors.

PURPOSE: Screening for visual problems in stroke survivors is not standardised. Visual problems that remain undetected or poorly identified can create unmet needs for stroke survivors. We report the validation of a new Vision Impairment Screening Assessment (VISA) tool intended for use by the stroke team to improve identification of visual impairment in stroke survivors. METHODS: We conducted a prospective case cohort comparative study in four centres to validate the VISA tool against a specialist reference vision assessment. VISA is available in print or as an app (Medicines and Healthcare products Regulatory Agency regulatory approved); these were used equally for two groups. Both VISA and the comprehensive reference vision assessment measured case history, visual acuity, eye alignment, eye movements, visual field and visual inattention. The primary outcome measure was the presence or absence of visual impairment. RESULTS: Two hundred and twenty-one stroke survivors were screened. Specialist reference vision assessment was by experienced orthoptists. Full completion of screening and reference vision assessment was achieved for 201 stroke survivors. VISA print was completed for 101 stroke survivors; VISA app was completed for 100. Sensitivity and specificity of VISA print was 97.67% and 66.67%, respectively. Overall agreement was substantial; K=0.648. Sensitivity and specificity of VISA app was 88.31% and 86.96%, respectively. Overall agreement was substantial; K=0.690. Lowest agreement was found for screening of eye movement and near visual acuity. CONCLUSIONS: This validation study indicates acceptability of VISA for screening of potential visual impairment in stroke survivors. Sensitivity and specificity were high indicating the accuracy of this screening tool. VISA is available in print or as an app allowing versatile uptake across multiple stroke settings.

Robotic technology for palliative and supportive care: Strengths, weaknesses, opportunities and threats.

BACKGROUND: Medical robots are increasingly used for a variety of applications in healthcare. Robots have mainly been used to support surgical procedures, and for a variety of assistive uses in dementia and elderly care. To date, there has been limited debate about the potential opportunities and risks of robotics in other areas of palliative, supportive and end-of-life care. AIM: The objective of this article is to examine the possible future impact of medical robotics on palliative, supportive care and end-of-life care. Specifically, we will discuss the strengths, weaknesses, opportunities and threats (SWOT) of this technology. METHODS: A SWOT analysis to understand the strengths, weaknesses, opportunities and threats of robotic technology in palliative and supportive care. RESULTS: The opportunities of robotics in palliative, supportive and end-of-life care include a number of assistive, therapeutic, social and educational uses. However, there are a number of technical, societal, economic and ethical factors which need to be considered to ensure meaningful use of this technology in palliative care. CONCLUSION: Robotics could have a number of potential applications in palliative, supportive and end-of-life care. Future work should evaluate the health-related, economic, societal and ethical implications of using this technology. There is a need for collaborative research to establish use-cases and inform policy, to ensure the appropriate use (or non-use) of robots for people with serious illness.

Flexible selection of heterogeneous and unreliable services in large-scale grids.

As grids become larger and more interconnected in nature, scientists can benefit from a growing number of distributed services that may be invoked on demand to complete complex computational workflows. However, it also means that these scientists become dependent on the cooperation of third-party service providers, whose behaviour may be uncertain, failure prone and highly heterogeneous. To address this, we have developed a novel decision-theoretic algorithm that automatically selects appropriate services for the tasks of an abstract workflow and deals with failures through redundancy and dynamic re-invocation of functionally equivalent services. In this paper, we summarize our approach, describe in detail how it can be applied to a real-world bioinformatics workflow and show that it offers a significant improvement over current service selection techniques.