Systematic reviews of convalescent plasma in COVID-19 continue to be poorly conducted and reported: a systematic review.

OBJECTIVES: To suggest possible approaches to combatting the impact of the COVID-19 infodemic to prevent research waste in future health emergencies and in everyday research and practice. STUDY DESIGN AND SETTING: Systematic review. The Epistemonikos database was searched in June 2021 for systematic reviews on the effectiveness of convalescent plasma for COVID-19. Two reviewers independently screened the retrieved references with disagreements resolved by discussion. Data extraction was completed by one reviewer with a proportion checked by a second. We used the Assessment of Multiple Systematic Reviews to assess the quality of conduct and reporting of included reviews. RESULTS: Fifty one systematic reviews are included with 193 individual studies included within the systematic reviews. There was considerable duplication of effort; multiple reviews were conducted at the same time with inconsistencies in the evidence included. The reviews were of low methodological quality, poorly reported, and did not adhere to preferred reporting items for systematic reviews and meta-analysis guidance. CONCLUSION: Researchers need to conduct, appraise, interpret, and disseminate systematic reviews better. All in the research community (researchers, peer-reviewers, journal editors, funders, decision makers, clinicians, journalists, and the public) need to work together to facilitate the conduct of robust systematic reviews that are published and communicated in a timely manner, reducing research duplication and waste, increasing transparency and accessibility of all systematic reviews.

Can agent-based simulation be used as a tool to support polypharmacy prescribing practice?

Objective: We sought to develop a simulation modelling method to help better understand the complex interplay of factors that lead to people with type 2 diabetes and asthma not taking all of their medication as prescribed when faced with multiple medications (polypharmacy). Research design and methods: In collaboration with polypharmacy patients, general practitioners, pharmacists and polypharmacy researchers, we developed a map of factors that directly and indirectly affect somebody’s decision to take their medication as prescribed when faced with multiple type 2 diabetes and asthma medications. We then translated these behavioural influences into logical rules using data from the literature and developed a proof-of-concept agent-based simulation model that captures the medicine-taking behaviours of those with type 2 diabetes and asthma taking multiple medications and which predicts both the clinical effectiveness and rates of adherence for different combinations of medications. Conclusions: The model we have developed could be used as a prescription support tool or a way of estimating medicine-taking behaviour in cost-effectiveness analyses.

Manual choice reaction times in the rate-domain.

Over the last 150 years, human manual reaction times (RTs) have been recorded countless times. Yet, our understanding of them remains remarkably poor. RTs are highly variable with positively skewed frequency distributions, often modeled as an inverse Gaussian distribution reflecting a stochastic rise to threshold (diffusion process). However, latency distributions of saccades are very close to the reciprocal Normal, suggesting that "rate" (reciprocal RT) may be the more fundamental variable. We explored whether this phenomenon extends to choice manual RTs. We recorded two-alternative choice RTs from 24 subjects, each with 4 blocks of 200 trials with two task difficulties (easy vs. difficult discrimination) and two instruction sets (urgent vs. accurate). We found that rate distributions were, indeed, very close to Normal, shifting to lower rates with increasing difficulty and accuracy, and for some blocks they appeared to become left-truncated, but still close to Normal. Using autoregressive techniques, we found temporal sequential dependencies for lags of at least 3. We identified a transient and steady-state component in each block. Because rates were Normal, we were able to estimate autoregressive weights using the Box-Jenkins technique, and convert to a moving average model using z-transforms to show explicit dependence on stimulus input. We also found a spatial sequential dependence for the previous 3 lags depending on whether the laterality of previous trials was repeated or alternated. This was partially dissociated from temporal dependency as it only occurred in the easy tasks. We conclude that 2-alternative choice manual RT distributions are close to reciprocal Normal and not the inverse Gaussian. This is not consistent with stochastic rise to threshold models, and we propose a simple optimality model in which reward is maximized to yield to an optimal rate, and hence an optimal time to respond. We discuss how it might be implemented.

A non-participant observational study of health and social care waste disposal behaviour in the South West of England.

INTRODUCTION: The National Health Service in England has a large carbon footprint. Waste production and disposal contributes to this carbon footprint and costs the National Health Service England over £82 million per annum. This study builds on existing work regarding health care waste management in the United Kingdom where the potential for recycling has begun to be studied. The study focuses on a private hospital and social care organizations, and provides a more detailed study of the behaviour of individuals across a variety of waste management systems. METHODS: The study was an overt observational study at four health and social care sites in the South West of England. Systematic observations were made of the waste disposed of by employees in which the observer recorded: a description of the waste item; the bin into which the waste was placed; the type of employee who disposed of the waste; the material the waste comprised and the appropriateness of the disposal behaviour. RESULTS: The domestic waste bin was found to be most commonly used by employees to dispose of waste (51%), and the materials observed being disposed of most often were paper (26%), organic wastes (19%) and plastic (19%). There were significant differences between the four sites indicating that the activities performed at each site may have been influencing the waste being disposed of. CONCLUSION: It was concluded that the transfer of waste from the domestic waste stream to the recycling waste stream should be a central focus for the design of new health and social care waste management systems. Employees will require guidance and training in identifying and classifying waste materials for recycling.

Physical space and its impact on waste management in the neonatal care setting.

This paper reports an investigation intended to obtain some understanding of how the working environment might influence the practice and knowledge of those involved in the management of healthcare waste. The National Health Service (NHS) has a continuing waste problem, and the way it manages waste harms the environment and consumes resources. It has been estimated that the carbon footprint of the NHS in England is approximately 20 million tons of CO2e. It has been suggested that better waste segregation could lead to more effective recycling, saving up to 42,000 tonnes of CO2. This qualitative study employed non-participant observation and semi-structured interviews. The interviews were carried out with the key informants within the participating neonatal intensive care unit. Findings from this study indicate that space and the physical arrangement of the environment are significant and influential factors in clinical practice. Where the clinical environment is not supportive, poor infection control and waste management practice is likely to occur. However, proximity of staff caused by a lack of physical space might facilitate situated learning and a collective development of knowledge in practice. The implementation of sustainable waste management practices would be more likely to succeed in an environment that facilitates correct waste segregation.