The inhibiting factors that principal investigators experience in leading publicly funded research

Securing public funding to conduct research and leading it by being a principal investigator (PI) is seen as significant career development step. Such a role brings professional prestige but also new responsibilities beyond research leadership to research management. If public funding brings financial and infrastructure support, little is understood about the inhibiting factors that publicly funded PIs face given the research autonomy offered by publicly funded research. Our study finds that there are three key PI inhibiting factors (1) political and environmental, (2) institutional and (3) project based. Traditional knowledge, skills and technical know-how of publicly funded PIs are insufficient to deal with the increasing managerial demands and expectations i.e. growing external bureaucracy of public funding agencies. Public funding is no longer the 'freest form of support' as suggested by Chubin and Hackett (Peerless science: peer review and US science policy. Suny Press, New York, 1990) and the inhibiting factors experienced by publicly funded PIs limits their research autonomy. We also argue that PIs have little influence in overcoming these inhibiting factors despite their central role in conducting publicly funded research

Computational Notebooks as Co-Design Tools: Engaging Young Adults Living with Diabetes, Family Carers, and Clinicians with Machine Learning Models

Engaging end user groups with machine learning (ML) models can help align the design of predictive systems with people’s needs and expectations. We present a co-design study investigating the benefits and challenges of using computational notebooks to inform ML models with end user groups. We used a computational notebook to engage young adults, carers, and clinicians with an example ML model that predicted health risk in diabetes care. Through codesign workshops and retrospective interviews, we found that participants particularly valued using the interactive data visualisations of the computational notebook to scaffold multidisciplinary learning, anticipate benefits and harms of the example ML model, and create fictional feature importance plots to highlight care needs. Participants also reported challenges, from running code cells to managing information asymmetries and power imbalances. We discuss the potential of leveraging computational notebooks as interactive co-design tools to meet end user needs early in ML model lifecycles

Co-designing opportunities for human-centred machine learning in supporting type 1 diabetes decision-making

Type 1 Diabetes (T1D) self-management requires hundreds of daily decisions. Diabetes technologies that use machine learning have significant potential to simplify this process and provide better decision support, but often rely on cumbersome data logging and cognitively demanding reflection on collected data. We set out to use co-design to identify opportunities for machine learning to support diabetes self-management in everyday settings. However, over nine months of interviews and design workshops with 15 people with T1D, we had to re-assess our assumptions about user needs. Our participants reported confidence in their personal knowledge and rejected machine learning based decision support when coping with routine situations, but highlighted the need for technological support in the context of unfamiliar or unexpected situations (holidays, illness, etc.). However, these are the situations where prior data are often lacking and drawing data-driven conclusions is challenging. Reflecting this challenge, we provide suggestions on how machine learning and other artificial intelligence approaches, e.g., expert systems, could enable decision-making support in both routine and unexpected situations

Using Football Cultures as a Vehicle to Improve Mental Health in Men: The Case of the Redcar and Cleveland Boot Room

This paper sets out to appraise (from the perspective of members) the impact of a localized, football-based mental health intervention. Commissioned in late 2015, the ‘Redcar and Cleveland Boot Room (BR)’ was implemented in response to mass redundancy in the local area, coupled with regional suicide rates in men that exceed the national average. Interactive discussions with BR members revealed that: (a) the language of football and shared identity were important for initiating and sustaining engagement in the BR; (b) peer-support and mentoring combined with member-led activities were active ingredients of the BR and (c) that the BR was an effective vehicle for building mental health resilience. This evaluation adds to the evidence base on the value of football as a context to engage adult males in community-based interventions targeting mental health resilience

Observational needs for improving ocean and coupled reanalysis, S2S prediction, and decadal prediction

Developments in observing system technologies and ocean data assimilation (DA) are symbiotic. New observation types lead to new DA methods and new DA methods, such as coupled DA, can change the value of existing observations or indicate where new observations can have greater utility for monitoring and prediction. Practitioners of DA are encouraged to make better use of observations that are already available, for example, taking advantage of strongly coupled DA so that ocean observations can be used to improve atmospheric analyses and vice versa. Ocean reanalyses are useful for the analysis of climate as well as the initialization of operational long-range prediction models. There are many remaining challenges for ocean reanalyses due to biases and abrupt changes in the ocean-observing system throughout its history, the presence of biases and drifts in models, and the simplifying assumptions made in DA solution methods. From a governance point of view, more support is needed to bring the ocean-observing and DA communities together. For prediction applications, there is wide agreement that protocols are needed for rapid communication of ocean-observing data on numerical weather prediction (NWP) timescales. There is potential for new observation types to enhance the observing system by supporting prediction on multiple timescales, ranging from the typical timescale of NWP, covering hours to weeks, out to multiple decades. Better communication between DA and observation communities is encouraged in order to allow operational prediction centers the ability to provide guidance for the design of a sustained and adaptive observing network

Consequences Matter : Compassion in Conservation Means Caring for Individuals, Populations and Species

Funding This research received no external funding. Acknowledgments The manuscript benefitted from significant input from Dan Brockington, J.B. Callicott, Peter Coals, Tim Hodgetts, David Macdonald and Jeremy Wilson. Conflicts of Interest The authors declare no conflict of interest.Peer reviewedPublisher PD

Biomarker-guided antibiotic stewardship in suspected ventilator-associated pneumonia (VAPrapid2) : a randomised controlled trial and process evaluation

Background Ventilator-associated pneumonia is the most common intensive care unit (ICU)-acquired infection, yet accurate diagnosis remains difficult, leading to overuse of antibiotics. Low concentrations of IL-1β and IL-8 in bronchoalveolar lavage fluid have been validated as effective markers for exclusion of ventilator-associated pneumonia. The VAPrapid2 trial aimed to determine whether measurement of bronchoalveolar lavage fluid IL-1β and IL-8 could effectively and safely improve antibiotic stewardship in patients with clinically suspected ventilator-associated pneumonia. Methods VAPrapid2 was a multicentre, randomised controlled trial in patients admitted to 24 ICUs from 17 National Health Service hospital trusts across England, Scotland, and Northern Ireland. Patients were screened for eligibility and included if they were 18 years or older, intubated and mechanically ventilated for at least 48 h, and had suspected ventilator-associated pneumonia. Patients were randomly assigned (1:1) to biomarker-guided recommendation on antibiotics (intervention group) or routine use of antibiotics (control group) using a web-based randomisation service hosted by Newcastle Clinical Trials Unit. Patients were randomised using randomly permuted blocks of size four and six and stratified by site, with allocation concealment. Clinicians were masked to patient assignment for an initial period until biomarker results were reported. Bronchoalveolar lavage was done in all patients, with concentrations of IL-1β and IL-8 rapidly determined in bronchoalveolar lavage fluid from patients randomised to the biomarker-based antibiotic recommendation group. If concentrations were below a previously validated cutoff, clinicians were advised that ventilator-associated pneumonia was unlikely and to consider discontinuing antibiotics. Patients in the routine use of antibiotics group received antibiotics according to usual practice at sites. Microbiology was done on bronchoalveolar lavage fluid from all patients and ventilator-associated pneumonia was confirmed by at least 104 colony forming units per mL of bronchoalveolar lavage fluid. The primary outcome was the distribution of antibiotic-free days in the 7 days following bronchoalveolar lavage. Data were analysed on an intention-to-treat basis, with an additional per-protocol analysis that excluded patients randomly assigned to the intervention group who defaulted to routine use of antibiotics because of failure to return an adequate biomarker result. An embedded process evaluation assessed factors influencing trial adoption, recruitment, and decision making. This study is registered with ISRCTN, ISRCTN65937227, and ClinicalTrials.gov, NCT01972425. Findings Between Nov 6, 2013, and Sept 13, 2016, 360 patients were screened for inclusion in the study. 146 patients were ineligible, leaving 214 who were recruited to the study. Four patients were excluded before randomisation, meaning that 210 patients were randomly assigned to biomarker-guided recommendation on antibiotics (n=104) or routine use of antibiotics (n=106). One patient in the biomarker-guided recommendation group was withdrawn by the clinical team before bronchoscopy and so was excluded from the intention-to-treat analysis. We found no significant difference in the primary outcome of the distribution of antibiotic-free days in the 7 days following bronchoalveolar lavage in the intention-to-treat analysis (p=0·58). Bronchoalveolar lavage was associated with a small and transient increase in oxygen requirements. Established prescribing practices, reluctance for bronchoalveolar lavage, and dependence on a chain of trial-related procedures emerged as factors that impaired trial processes

The challenges of a randomised placebo-controlled trial of CTO PCI vs. placebo with optimal medical therapy: The ORBITA-CTO pilot study design and protocol

BackgroundPercutaneous coronary intervention (PCI) for coronary chronic total occlusion (CTO) has been performed for the improvement of symptoms and quality of life in patients with stable angina. The ORBITA study demonstrated the role of the placebo effect in contemporary PCI in non-CTO chronic coronary syndromes. However, the benefit of CTO PCI beyond that of a placebo has not been demonstrated.AimsThe ORBITA-CTO pilot study will be a double-blind, placebo-controlled study of CTO PCI randomising patients who have: (1) been accepted by a CTO operator for PCI; (2) experienced symptoms due to a CTO; (3) evidence of ischaemia; (4) evidence of viability within the CTO territory; and (5) a J-CTO score ≤3.MethodsPatients will undergo medication optimisation that will ensure they are on at least a minimum amount of anti-anginals and complete questionnaires. Patients will record their symptoms on an app daily throughout the study. Patients will undergo randomisation procedures, including an overnight stay, and be discharged the following day. All anti-anginals will be stopped after randomisation and re-initiated on a patient-led basis during the 6-month follow-up period. At follow-up, patients will undergo repeat questionnaires and unblinding, with a further 2-week unblinded follow-up.ResultsThe co-primary outcomes are feasibility (blinding) in this cohort and angina symptom score using an ordinal clinical outcome scale for angina. Secondary outcomes include changes in quality-of-life measures, Seattle Angina Questionnaire (SAQ), peak VO2, and anaerobic threshold on the cardiopulmonary exercise test.ConclusionThe feasibility of a placebo-controlled CTO PCI study will lead to future studies assessing efficacy. The impact of CTO PCI on angina measured using a novel daily symptom app may provide improved fidelity in assessing symptoms in patients with CTO's

Hybrid reconnaissance mission to the 30 October 2020 Aegean sea earthquake and tsunami (Izmir, Turkey & Samos, Greece): description of data collection methods and damage

On 30 October 2020, an earthquake of Mw 6.9 hit the Aegean coasts of Turkey and Greece. The epicentre was some 14 km northeast of Avlakia on Samos Island, and 25 km southwest of Seferihisar, Turkey, triggering also a tsunami. The event has been followed by >4,000 aftershocks up to Mw 5.2 The Earthquake Engineering Field Investigation Team (EEFIT) has immediately gathered a team to conduct a hybrid reconnaissance study,bringing together remote and field investigation techniques. The mission took place between 16 November and 17 December, inclusive of three sets of field study carried out by the field crews for building damage assessment in the affected areas in Turkey and Greece under the coordination of the remote team. The mission also aimed to assess the viability of alternative data sources for an appraisal of the future viability of hybrid missions. This paper summarises the mission setup and findings, and discusses the benefits of and difficulties encountered during this hybrid reconnaissance activity

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707