Vision-Related Quality of Life and Treatment Satisfaction Following Panretinal Photocoagulation in Diabetic Retinopathy—A Panel Study

Background and Objectives: The aim of the study was to evaluate vision-related quality of life (VR-QOL) and treatment satisfaction (TS) in patients with diabetic retinopathy treated with panretinal photocoagulation (PRP). Material and Methods: The panel study included 95 patients who underwent PRP for diabetic retinopathy. Eligible patients with no history of previous PRP were interviewer-administered the National Eye Institute Visual Function Questionnaire (NEI VFQ-25) and Retinopathy Treatment Satisfaction Questionnaire (RetTSQ) beforehandand one month after the last session of laser application. The study was conducted between June 2017 and June 2019 at tertiary care center in Serbia, Belgrade. We assessed pre- to post-PRP values of the composite score and subscale scores of VFQ-25 and RetTSQ, using a paired samples t-test. Univariate logistic regression was used to analyze the relationship between binary outcomes and potential predictors. Multivariate regression included predictors from univariate analyses that were statistically significant. Results: The mean VFQ-25 composite score was 65.4 ± 17.4 before and 63.3 ± 19.5 after PRP (p = 0.045). Subscale analysis showed that two of the 11 items achieved a significant decrease after laser application (general vision and dependency). The mean RetTSQ score at baseline was 60.0 ± 11.8 and at the exit visit was 60.3 ± 12.3 (p = 0.858). Sub-scale analysis showed significant deterioration for five of the 13 items. Multivariate logistic regression found that significant predictor of VFQ-25 composite score reduction was fewer laser burns (p = 0.002) while significant predictor of RetTSQ total score reduction was presence of hyperlipidaemia (p = 0.021). Conclusion: The use of vision-related quality of life and treatment satisfaction questionnaires in conjunction with clinical examination, appears to provide a more comprehensive overview of an individual’s daily well-being following PRP. Laser treatment for diabetic retinopathy leads to deterioration of some of the patients’ perceived VR-QOL and TS. Health-care providers should inform patients about their treatment options and together decide which therapeutic method is best for them

Underwater mixed environments

In this chapter we give a systematic overview over Virtual Reality (VR) and Augmented Reality (AR) in underwater settings. Based on a novel classification scheme we illustrate the broad range of available and future implementation options. Whilst we find a variety of previous work on creating and using virtual underwater worlds, quite few examples of real underwater settings exist up to now. So we concentrate on this new category, sketch attractive application areas that go beyond entertainment and derive requirements for Underwater Mixed Environments (UWME). Combined with a short summary on relevant aspects of underwater optics, we formulate some topics of future research to overcome current limitations of UWME

Emerging Techniques and Materials for Water Pollutants Detection

Rapid industrialization and population boom have led to deterioration of water quality, rising health issues and environmental damage, which made it imperative to monitor and regulate the water pollutants. Earlier, water samples were monitored using grab sampling method and then analysis was performed in the laboratory. This process is arduous and time consuming; also, there are poor chances of detecting a periodic pollution. For a proactive response sensor technology is popular these days for pollutant monitoring. A variety of sensing techniques and materials are available. But recently nanomaterials have absorbed attention for fabricating sensors owing to their high surface to volume ratio, ease of functionalization which enable them to have high specificity and sensitivity. This chapter intends to review the emerging materials used for making water pollutant sensors and gives an insight into the emerging techniques like microfluidic sensors, biosensors, wireless sensor network and smart sensors