14 research outputs found

    Abstracts from the NIHR INVOLVE Conference 2017

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    Crowdsourcing hypothesis tests: Making transparent how design choices shape research results

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    To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer fiveoriginal research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams renderedstatistically significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to +0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for two hypotheses, and a lack of support for three hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim.</div

    The James Webb Space Telescope Mission

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    Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least 4m4m. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the 6.5m6.5m James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

    Bi-allelic Loss-of-Function CACNA1B Mutations in Progressive Epilepsy-Dyskinesia.

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    The occurrence of non-epileptic hyperkinetic movements in the context of developmental epileptic encephalopathies is an increasingly recognized phenomenon. Identification of causative mutations provides an important insight into common pathogenic mechanisms that cause both seizures and abnormal motor control. We report bi-allelic loss-of-function CACNA1B variants in six children from three unrelated families whose affected members present with a complex and progressive neurological syndrome. All affected individuals presented with epileptic encephalopathy, severe neurodevelopmental delay (often with regression), and a hyperkinetic movement disorder. Additional neurological features included postnatal microcephaly and hypotonia. Five children died in childhood or adolescence (mean age of death: 9 years), mainly as a result of secondary respiratory complications. CACNA1B encodes the pore-forming subunit of the pre-synaptic neuronal voltage-gated calcium channel Cav2.2/N-type, crucial for SNARE-mediated neurotransmission, particularly in the early postnatal period. Bi-allelic loss-of-function variants in CACNA1B are predicted to cause disruption of Ca2+ influx, leading to impaired synaptic neurotransmission. The resultant effect on neuronal function is likely to be important in the development of involuntary movements and epilepsy. Overall, our findings provide further evidence for the key role of Cav2.2 in normal human neurodevelopment.MAK is funded by an NIHR Research Professorship and receives funding from the Wellcome Trust, Great Ormond Street Children's Hospital Charity, and Rosetrees Trust. E.M. received funding from the Rosetrees Trust (CD-A53) and Great Ormond Street Hospital Children's Charity. K.G. received funding from Temple Street Foundation. A.M. is funded by Great Ormond Street Hospital, the National Institute for Health Research (NIHR), and Biomedical Research Centre. F.L.R. and D.G. are funded by Cambridge Biomedical Research Centre. K.C. and A.S.J. are funded by NIHR Bioresource for Rare Diseases. The DDD Study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003), a parallel funding partnership between the Wellcome Trust and the Department of Health, and the Wellcome Trust Sanger Institute (grant number WT098051). We acknowledge support from the UK Department of Health via the NIHR comprehensive Biomedical Research Centre award to Guy's and St. Thomas' National Health Service (NHS) Foundation Trust in partnership with King's College London. This research was also supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre. J.H.C. is in receipt of an NIHR Senior Investigator Award. The research team acknowledges the support of the NIHR through the Comprehensive Clinical Research Network. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, Department of Health, or Wellcome Trust. E.R.M. acknowledges support from NIHR Cambridge Biomedical Research Centre, an NIHR Senior Investigator Award, and the University of Cambridge has received salary support in respect of E.R.M. from the NHS in the East of England through the Clinical Academic Reserve. I.E.S. is supported by the National Health and Medical Research Council of Australia (Program Grant and Practitioner Fellowship)

    Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

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    IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

    12‐hour shifts:Prevalence, views and impact

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    The provision of 24-hour nursing care inevitably involves shift work and flexible working, including “long days” or 12-hour shifts (Newey and Hood 2004, Lorenz 2008). However, these shift patterns have become increasingly controversial, with concerns raised over performance, fatigue, stress and patient safety. Historically, traditional shift work patterns were based on three eight-hour shifts per day (Ferguson and Dawson 2011, Estabrooks et al. 2009), but over the past 20 years there has been a tendency to move away from this pattern of working in preference for the 12-hour shift (Todd et al. 1989, McGettrick and O’Neill 2006).In the UK, many hospitals utilise 12-hour shifts primarily because managers believe it is a more cost effective way of providing 24-hour care, with lower costs and greater continuity of staffing (Estabrooks et al. 2009). Some nurses also prefer to work longer daily hours with fewer shifts, which gives them greater flexibility and more days away from work (Josten et al. 2003). As the majority of the nursing workforce is female, this may also make it easier to balance work and personal responsibilities (Messing 1997, Josten et al. 2003). However, there are increasing concerns over potential threats to patient safety and quality of care (Stimpfel and Aiken 2013), and some employers now question the benefits of such extended hours and are choosing to revert to eight-hour shifts (Geiger-Brown and Trinkoff 2010). Although the handover period has been criticised for being unproductive, with no formal ‘overlap’ 12-hour shifts can have a negative impact on opportunities for ward meetings, teaching, mentorship, teambuilding and research (Sprinks 2012). A study in the US by Stimpfel and colleagues published in 2013 found that nurses who worked shifts of 12-hours or longer were significantly more likely to report poor quality care and poor patient safety when compared to those working eight-hour shifts. Patients also reported lowersatisfaction with care in hospitals where staff worked longer shifts (Stimpfel et al. 2012).Shift work is a common feature across many industries. Fatigue associated with long shifts has been linked with disasters such as the Chernobyl nuclear accident, Three Mile Island incident and the grounding of the Exxon Valdez (Miller 2011). However, research to date is equivocal and some studies have found little differences in terms of cost or productivity (Williamson et al. 1994) or levels of fatigue (Duchon et al. 1994) by shift length. A systematic review by Smith et al. (1998) compared eight and 12-hour shifts across a broad range of industries and concluded that longer shifts increased fatigue but also led to an increase in job performance. Tucker et al. (1998) examined the effect of shift length on alertness. Their findings showed that more rest days between shifts were associated with slightly higher levels of alertness and lower levels of fatigue.In nursing, Geiger-Brown and Trinkoff (2010) reviewed studies up until 2008. In five of the seven studies reviewed, those working 12-hour shifts were significantly more fatigued. Estabrooks et al. (2009) reviewed 12 studies comparing the effect of eight and 12-hour shifts on quality of care and health care provider outcomes. They found insufficient evidence to conclude that shift length had an effect on patient or healthcare outcomes. A common question asked by health care employers and employees around shift work is “is it OK to work 12-hour shifts?” (Ferguson and Dawson 2011, p. 519). Our current study brings together findings from previously published studies and from new analysis of previously collected data, to address this question.AimThe aim of this study is to review existing data sources to identify what we know about the prevalence of 12-hour shifts in nursing and the impact on both staff and patients. Specifically, this study aims to address the following questions:What is the prevalence of 12-hour shifts in nursing?How much internal variation in shift length is there in NHS hospitals?What impact does shift length have on quality of patient care and staff experience?<br/

    Crowdsourcing hypothesis tests: making transparent how design choices shape research results

    Get PDF
    To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer five original research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams rendered statistically significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to +0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for two hypotheses, and a lack of support for three hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim
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