Improving public services through open data: public toilets

Bichard’s work for the TACT3 project (Bichard REF Output 3) found that UK toilet provision is not centrally collated and no national map or database of toilets exists. In contrast, the UK government’s white paper Open Public Services (2011) emphasised its commitment to incorporating the use of Open Data in public services provision that could be tailored to community preferences, and therefore be more sustainable. Incorporating Open Data on public toilet provision, Bichard and Knight (RCA) developed The Great British Public Toilet Map (GBPTM). Whilst a number of other websites and applications map toilets by ‘crowd surfing’, GBPTM is entirely populated by Open Data, and not only uses the data as information for users, but informs members of the public that such information is available and accessible for their use. This paper presents the development of the GBPTM, including inclusive design research and studies that compare accuracy of information directly provided by users with Open Data collected by local authorities. It suggests that, to meet the health and well-being of an ageing population, a sustainable and cost-effective solution must be found for ‘publicly accessible’ toilet provision, including opening up provision beyond that ‘for customers only’ and providing accurate information on current public provision. The paper highlights the barriers encountered in the production of Open Data by local authorities. A review of the paper in the journal Civil Engineering (May 2013) described the design of the GBPTM as a ‘simple and elegant solution’. The development of a digital output and an understanding of digitally based research led to Bichard’s successful submission to an EPSRC Digital Economy sandpit, in which she developed an interdisciplinary project with the Universities of Newcastle, Bournemouth and the West of England. The project, Family Rituals 2.0, secured £750,000 in research funding with Bichard as co-investigator (2013–15)

Rationale, design and methods of the Study of Work and Pain (SWAP): a cluster randomised controlled trial testing the addition of a vocational advice service to best current primary care for patients with musculoskeletal pain (ISRCTN 52269669)

Background Musculoskeletal pain is a major contributor to short and long term work absence. Patients seek care from their general practitioner (GP) and yet GPs often feel ill-equipped to deal with work issues. Providing a vocational case management service in primary care, to support patients with musculoskeletal problems to remain at or return to work, is one potential solution but requires robust evaluation to test clinical and cost-effectiveness. Methods/Design This protocol describes a cluster randomised controlled trial, with linked qualitative interviews, to investigate the effect of introducing a vocational advice service into general practice, to provide a structured approach to managing work related issues in primary care patients with musculoskeletal pain who are absent from work or struggling to remain in work. General practices (n = 6) will be randomised to offer best current care or best current care plus a vocational advice service. Adults of working age who are absent from or struggling to remain in work due to a musculoskeletal pain problem will be invited to participate and 330 participants will be recruited. Data collection will be through patient completed questionnaires at baseline, 4 and 12 months. The primary outcome is self-reported work absence at 4 months. Incremental cost-utility analysis will be undertaken to calculate the cost per additional QALY gained and incremental net benefits. A linked interview study will explore the experiences of the vocational advice service from the perspectives of GPs, nurse practitioners (NPs), patients and vocational advisors. Discussion This paper presents the rationale, design, and methods of the Study of Work And Pain (SWAP) trial. The results of this trial will provide evidence to inform primary care practice and guide the development of services to provide support for musculoskeletal pain patients with work-related issues. Trial registration Current Controlled Trials ISRCTN52269669

The Role of Eye Movement Consistency in Aging-Related Decline in Face Recognition

Face recognition is shown to involve a prolonged developmental process where one gradually develops a more consistent but idiosyncratic visual routine with increasing age. In contrast to this developmental trend, here we found that aging was associated with decreased eye movement consistency during face recognition, which in turn contributed to declined face recognition performance. Although aging was not associated with changes in eye movement pattern, a less eyes-focused eye movement pattern predicted poorer face recognition performance together with lower eye movement consistency and age in older adults, suggesting that the idiosyncratic eye movement patterns acquired during early adulthood continue to account for their face recognition performance. Their decreased eye movement consistency was associated with declines in selective attention and inhibition control, suggesting difficulties in the execution of the learned visual routines. These findings have important implications for ways to facilitate older adults' face recognition to promote healthy aging

Genome-Wide Survey and Expression Profiling of CCCH-Zinc Finger Family Reveals a Functional Module in Macrophage Activation

Previously, we have identified a novel CCCH zinc finger protein family as negative regulators of macrophage activation. To gain an overall insight into the entire CCCH zinc finger gene family and to evaluate their potential role in macrophage activation, here we performed a genome-wide survey of CCCH zinc finger genes in mouse and human. Totally 58 CCCH zinc finger genes in mouse and 55 in human were identified and most of them have not been reported previously. Phylogenetic analysis revealed that the mouse CCCH family was divided into 6 groups. Meanwhile, we employed quantitative real-time PCR to profile their tissue expression patterns in adult mice. Clustering analysis showed that most of CCCH genes were broadly expressed in all of tissues examined with various levels. Interestingly, several CCCH genes Mbnl3, Zfp36l2, Zfp36, Zc3h12a, Zc3h12d, Zc3h7a and Leng9 were enriched in macrophage-related organs such as thymus, spleen, lung, intestine and adipose. Consistently, a comprehensive assessment of changes in expression of the 58 members of the mouse CCCH family during macrophage activation also revealed that these CCCH zinc finger genes were associated with the activation of bone marrow-derived macrophages by lipopolysaccharide. Taken together, this study not only identified a functional module of CCCH zinc finger genes in the regulation of macrophage activation but also provided the framework for future studies to dissect the function of this emerging gene family

Prospective screening study of 0.5 Tesla dedicated magnetic resonance imaging for the detection of breast cancer in young, high-risk women

BACKGROUND: Evidence-based screening guidelines are needed for women under 40 with a family history of breast cancer, a BRCA1 or BRCA2 mutation, or other risk factors. An accurate assessment of breast cancer risk is required to balance the benefits and risks of surveillance, yet published studies have used narrow risk assessment schemata for enrollment. Breast density limits the sensitivity of film-screen mammography but is not thought to pose a limitation to MRI, however the utility of MRI surveillance has not been specifically examined before in women with dense breasts. Also, all MRI surveillance studies yet reported have used high strength magnets that may not be practical for dedicated imaging in many breast centers. Medium strength 0.5 Tesla MRI may provide an alternative economic option for surveillance. METHODS: We conducted a prospective, nonrandomized pilot study of 30 women age 25–49 years with dense breasts evaluating the addition of 0.5 Tesla MRI to conventional screening. All participants had a high quantitative breast cancer risk, defined as ≥ 3.5% over the next 5 years per the Gail or BRCAPRO models, and/or a known BRCA1 or BRCA2 germline mutation. RESULTS: The average age at enrollment was 41.4 years and the average 5-year risk was 4.8%. Twenty-two subjects had BIRADS category 1 or 2 breast MRIs (negative or probably benign), whereas no category 4 or 5 MRIs (possibly or probably malignant) were observed. Eight subjects had BIRADS 3 results, identifying lesions that were "probably benign", yet prompting further evaluation. One of these subjects was diagnosed with a stage T1aN0M0 invasive ductal carcinoma, and later determined to be a BRCA1 mutation carrier. CONCLUSION: Using medium-strength MRI we were able to detect 1 early breast tumor that was mammographically undetectable among 30 young high-risk women with dense breasts. These results support the concept that breast MRI can enhance surveillance for young high-risk women with dense breasts, and further suggest that a medium-strength instrument is sufficient for this application. For the first time, we demonstrate the use of quantitative breast cancer risk assessment via a combination of the Gail and BRCAPRO models for enrollment in a screening trial

Procalcitonin Is Not a Reliable Biomarker of Bacterial Coinfection in People With Coronavirus Disease 2019 Undergoing Microbiological Investigation at the Time of Hospital Admission

Admission procalcitonin measurements and microbiology results were available for 1040 hospitalized adults with coronavirus disease 2019 (from 48 902 included in the International Severe Acute Respiratory and Emerging Infections Consortium World Health Organization Clinical Characterisation Protocol UK study). Although procalcitonin was higher in bacterial coinfection, this was neither clinically significant (median [IQR], 0.33 [0.11–1.70] ng/mL vs 0.24 [0.10–0.90] ng/mL) nor diagnostically useful (area under the receiver operating characteristic curve, 0.56 [95% confidence interval, .51–.60])

Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study

Background Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions. Methods We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal–external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London). Findings 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal–external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [–0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model. Interpretation The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19