Barriers to completing oral glucose tolerance testing in women at risk of gestational diabetes.

AIM: Complications of gestational diabetes (GDM) can be mitigated if the diagnosis is recognized. However, some at-risk women do not complete antenatal diagnostic oral glucose tolerance testing (OGTT). We aimed to understand reasons contributing to non-completion, particularly to identify modifiable factors. METHODS: Some 1906 women attending a tertiary UK obstetrics centre (2018-2019) were invited for OGTT based on risk-factor assessment. Demographic information, test results and reasons for non-completion were collected from the medical record. Logistic regression was used to analyse factors associated with non-completion. RESULTS: Some 242 women (12.3%) did not complete at least one OGTT, of whom 32.2% (n = 78) never completed testing. In adjusted analysis, any non-completion was associated with younger maternal age [≤ 30 years; odds ratio (OR) 2.3, 95% confidence interval (CI) 1.6-3.4; P < 0.001], Black African ethnicity (OR 2.7, 95% CI 1.2-5.5; P = 0.011), lower socio-economic status (OR 0.9, 95% CI 0.8-1.0; P = 0.021) and higher parity (≥ 2; OR 1.8, 95% CI 1.1-2.8; P = 0.013). Non-completion was more likely if testing indications included BMI ≥ 30 kg/m2 (OR 1.7, 95% CI 1.1-2.4; P = 0.009) or family history of diabetes (OR 2.2, 95% CI 1.5-3.3; P < 0.001) and less likely if the indication was an ultrasound finding (OR 0.4, 95% CI 0.2-0.9; P = 0.035). We identified a common overlapping cluster of reasons for non-completion, including inability to tolerate test protocol (21%), social/mental health issues (22%), and difficulty keeping track of multiple antenatal appointments (15%). CONCLUSIONS: There is a need to investigate methods of testing that are easier for high-risk groups to schedule and tolerate, with fuller explanation of test indications and additional support for vulnerable groups.Catherine Aiken is supported by an Isaac Newton Trust[12.21(a)]/Wellcome Trust ISSF [105602/Z/14/Z]/ University of Cambridge Joint Research Grant. Claire Meek is supported by the Diabetes UK Harry Keen intermediate clinical fellowship (17/0005712) and the European Foundation for the Study of Diabetes/ Novo Nordisk Foundation Futures Leader’s Award (NNF19SA058974). Juliet Usher-Smith is supported by a Cancer Research UK Prevention Fellowship (C55650/A21464)

Marginal role for 53 common genetic variants in cardiovascular disease prediction.

OBJECTIVE: We investigated discrimination and calibration of cardiovascular disease (CVD) risk scores when genotypic was added to phenotypic information. The potential of genetic information for those at intermediate risk by a phenotype-based risk score was assessed. METHODS: Data were from seven prospective studies including 11 851 individuals initially free of CVD or diabetes, with 1444 incident CVD events over 10 years' follow-up. We calculated a score from 53 CVD-related single nucleotide polymorphisms and an established CVD risk equation 'QRISK-2' comprising phenotypic measures. The area under the receiver operating characteristic curve (AUROC), detection rate for given false-positive rate (FPR) and net reclassification improvement (NRI) index were estimated for gene scores alone and in addition to the QRISK-2 CVD risk score. We also evaluated use of genetic information only for those at intermediate risk according to QRISK-2. RESULTS: The AUROC was 0.635 for QRISK-2 alone and 0.623 with addition of the gene score. The detection rate for 5% FPR improved from 11.9% to 12.0% when the gene score was added. For a 10-year CVD risk cut-off point of 10%, the NRI was 0.25% when the gene score was added to QRISK-2. Applying the genetic risk score only to those with QRISK-2 risk of 10%-<20% and prescribing statins where risk exceeded 20% suggested that genetic information could prevent one additional event for every 462 people screened. CONCLUSION: The gene score produced minimal incremental population-wide utility over phenotypic risk prediction of CVD. Tailored prediction using genetic information for those at intermediate risk may have clinical utility

Student budgets and widening participation: Comparative experiences of finance in low and higher income undergraduates at a Northern Red Brick University

Drawing on a thematic analysis of longitudinal qualitative data (ntotal = 118), this article takes a “whole student lifecycle” approach to examine how lower and higher income students at an English northern red brick university variously attempted to manage their individual budgets. It explores how students reconcile their income—in the form of loans, grants, and bursaries—with the cost of living. Four arenas of interest are described: planning, budgeting, and managing “the student loan”; disruptions to financial planning; the role of familial support; and strategies of augmenting the budget. In detailing the micro‐level constraints on the individual budgets of lower and higher income undergraduates, the article highlights the importance of non‐repayable grants and bursaries in helping to sustain meaningful participation in higher tariff, more selective, higher education institutions. It also supports an emerging body of literature that suggests that the continuing amendments to the system of funding higher education in England are unlikely to address inequality of access, participation, and outcome

Reducing weight gain in people with schizophrenia, schizoaffective disorder, and first episode psychosis: describing the process of developing the STructured lifestyle Education for People With SchizophrEnia (STEPWISE) intervention

Background Obesity is twice as common in people with schizophrenia as the general population and associated with significantly worsened psychiatric and physical health. Despite National Institute for Health and Care Excellence guidelines for the management of psychosis recommending that mental health services offer lifestyle programmes to people with schizophrenia to improve physical health, this is not currently occurring. The aim of the STEPWISE research programme was to develop a lifestyle intervention addressing obesity and preventing weight gain in people with schizophrenia, schizoaffective disorder, or first episode psychosis taking antipsychotic medication, through an approach and fundamental principles drawn from existing diabetes and diabetes prevention interventions. This paper describes the often under-reported process of developing such an intervention from first principles. Methods Following an extensive literature review, an iterative cycle of development with input from people with schizophrenia, mental healthcare professionals, facilitators, and other stakeholders, a new weight management intervention for the target group was developed. A set of four core weekly sessions was piloted in Sheffield, followed at 3-monthly intervals by three booster sessions and telephone support contact once every 2 weeks, to form an intervention lasting 12 months. Facilitators were provided with a 4-day training package to support delivery of the intervention. Results This paper reports the process of development, including challenges and how these were addressed. It describes how user input influenced the structure, topics, and approach of the intervention. The outcome of this process was a feasible and acceptable lifestyle intervention to support people with schizophrenia, schizoaffective disorder, or first episode psychosis to manage their weight. This pilot provided opportunities for refinement of the intervention and facilitator training prior to testing in a multi-centre randomised controlled trial. Key findings from the pilot were linked to accessibility, focus, uptake, and retention, which influenced session length, travel arrangements, refreshment, breaks, and supporting tools to incentivise participants. Conclusions The STEPWISE intervention has been evaluated in a randomised controlled trial in 10 mental health trusts in England, and the results will be published in the British Journal of Psychiatry and the NIHR Journals Library

Enhanced Invitations Using the Question-Behavior Effect and Financial Incentives to Promote Health Check Uptake in Primary Care

Background: Uptake of health checks for cardiovascular risk assessment in primary care in England is lower than anticipated. The question-behavior effect (QBE) may offer a simple, scalable intervention to increase health check uptake. Purpose: The present study aimed to evaluate the effectiveness of enhanced invitation methods employing the QBE, with or without a financial incentive to return the questionnaire, at increasing uptake of health checks. Methods: We conducted a three-arm randomized trial including all patients at 18 general practices in two London boroughs, who were invited for health checks from July 2013 to December 2014. Participants were randomized to three trial arms: (i) Standard health check invitation letter only; (ii) QBE questionnaire followed by standard invitation letter; or (iii) QBE questionnaire with offer of a financial incentive to return the questionnaire, followed by standard invitation letter. In intention to treat analysis, the primary outcome of completion of health check within 6 months of invitation, was evaluated using a p value of .0167 for significance. Results: 12,459 participants were randomized. Health check uptake was evaluated for 12,052 (97%) with outcome data collected. Health check uptake within 6 months of invitation was: standard invitation, 590 / 4,095 (14.41%); QBE questionnaire, 630 / 3,988 (15.80%); QBE questionnaire and financial incentive, 629 / 3,969 (15.85%). Difference following QBE questionnaire, 1.43% (95% confidence interval −0.12 to 2.97%, p = .070); following QBE questionnaire and financial incentive, 1.52% (−0.03 to 3.07%, p = .054). Conclusions: Uptake of health checks following a standard invitation was low and not significantly increased through enhanced invitation methods using the QBE

Energy model, boundary object and societal lens: 35 years of the MARKAL model in the UK

Abstract Technical energy models operate within social systems and those that perform particular social as well as technical functions are more likely to be used. We illustrate this with the example of the MARKAL energy system model in the UK, a model that is also widely used internationally. In the UK, MARKAL modelling has a long history helping underpin government energy and climate policy. We trace the use of the model from its initial development in the mid-1970s to the present day, highlighting attributes that contribute to its role as a successful ‘boundary object’ for different but interconnecting energy policy communities. We suggest that changing images of the energy policy problem have enabled MARKAL to shift from an initial role in identifying technologies to reduce oil dependency to playing a key role in target-oriented climate policy. Furthermore, we argue that the ability of MARKAL to perform different roles for different groups has served to embed and institutionalise the model in the energy policy community. Moreover, the capacity of the model to represent detailed technology options has accorded with a technological focus that has suited prevailing, shared conceptions of the energy-climate policy problem

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome

Construction of a Computational Framework to Automatically Interpret Chest X-rays and Diagnose Pneumonia

This study aimed to systematically diagnose pneumonia directly from paediatric chest X-ray images using a computational framework. The project research goals were 1) to establish a high-quality dataset of pneumonia labelled X-ray images, 2) to extend existing deep learning architectures for pneumonia diagnoses, and 3) to construct a computational pipeline, enabling members of the broader community to interface with the computational models to diagnose pneumonia from X-ray images. The paediatric chest x-ray images were derived from 1) a WHO-supported surveillance study at Dhaka Shishu Hospital (DSH), from 2) a community site at Kumudini Women’s Medical College (KWMCH), and from 3) the WHO Chest Radiography in Epidemiological Studies (WHO CRES) working group. The images were interpreted by at least two trained clinicians / radiologists for the presence of 1) primary end-point pneumonia (PEP), 2) other lung infiltrates, and/or 3) pleural fluid in either the left or right lung, for a total of six possible binary outcomes, which will henceforth be called “labels”. A third reader resolved discordant PEP labels found between the first and second readers. An X-ray image were included in this study if 1) the age of the child for whom the X-ray was performed was ≤59 months, 2) the X-ray was performed in one of the two study hospitals or from the WHO CRES reference image set, and 3) the image captured the lung area. Any Image that was marked “uninterpretable” (features of the images were not interpretable with respect to presence or absence of PEP) by two readers were excluded. The deposited datasets contain the resulting labels from the multiple readers for each dataset described above.Saha, Samir. (2021). Construction of a Computational Framework to Automatically Interpret Chest X-rays and Diagnose Pneumonia, 2013-2021 [dataset]. The University of Edinburgh. Usher Institute. NIHR Global Health Research Unit on Respiratory Health (RESPIRE). https://doi.org/10.7488/ds/3258