Validating a methodology to measure frailty syndromes at hospital level utilising administrative data.

BACKGROUND: Identifying older people with clinical frailty, reliably and at scale, is a research priority. We measured frailty in older people using a novel methodology coding frailty syndromes on routinely collected administrative data, developed on a national English secondary care population, and explored its performance of predicting inpatient mortality and long length of stay at a single acute hospital. METHODOLOGY: We included patient spells from Secondary User Service (SUS) data for those ≥65 years with attendance to the emergency department or admission to West Middlesex University Hospital between 01 July 2016 to 01 July 2017. We created eight groups of frailty syndromes using diagnostic coding groups. We used descriptive statistics and logistic regression to explore performance of diagnostic coding groups for the above outcomes. RESULTS: We included 17,199 patient episodes in the analysis. There was at least one frailty syndrome present in 7,004 (40.7%) patient episodes. The resultant model had moderate discrimination for inpatient mortality (area under the receiver operating characteristic curve (AUC) 0.74; 95% confidence interval (CI) 0.72-0.76) and upper quartile length of stay (AUC 0.731; 95% CI 0.722-0.741). There was good negative predictive value for inpatient mortality (98.1%). CONCLUSIONS: Coded frailty syndromes significantly predict outcomes. Model diagnostics suggest the model could be used for screening of elderly patients to optimise their care

Volume 3: Ethnographies of Islam : Ritual Performances and Everyday Practices

This comparative approach to the various uses of the ethnographic method in research about Islam in anthropology and other social sciences is particularly relevant in the current climate. Political discourses and stereotypical media portrayals of Islam as a monolithic civilisation have prevented the emergence of cultural pluralism and individual freedom. This book counters such discourses by showing the diversity and plurality of Muslim societies and by promoting reflection on how the ethnographic method allows the description, representation and analysis of the social and cultural complexity of Muslim societies in the discourse of anthropology.https://ecommons.aku.edu/uk_ismc_series_emc/1006/thumbnail.jp

Mixed ice accretion on aircraft wings

Ice accretion is a problematic natural phenomenon that an effects a wide range of engineering applications including power cables, radio masts and wind turbines. Accretion on aircraft wings occurs when supercooled water droplets freeze instantaneously on impact to form rime ice or runback as water along the wing to form glaze ice. Most models to date have ignored the accretion of mixed ice, which is a combination of rime and glaze. A parameter we term the `freezing fraction', is defined as the fraction of a supercooled droplet that freezes on impact with the top surface of the accretion ice to explore the concept of mixed ice accretion. Additionally we consider different `packing densities' of rime ice, mimicking the different bulk rime densities observed in nature. Ice accretion is considered in four stages: rime, primary mixed, secondary mixed and glaze ice. Predictions match with existing models and experimental data in the limiting rime and glaze cases. The mixed ice formulation consequently however provides additional insight into the composition of the overall ice structure, which ultimately influences adhesion and ice thickness; and shows that for similar atmospheric parameter ranges, this simple mixed ice description leads to very different accretion rates. A simple one-dimensional energy balance was solved to show how this freezing fraction parameter increases with decrease in atmospheric temperature, with lower freezing fraction promoting glaze ice accretion

A retrospective observational analysis to identify patient and treatment-related predictors of outcomes in a community mental health programme

OBJECTIVES: This study aims to identify patient and treatment factors that affect clinical outcomes of community psychological therapy through the development of a predictive model using historic data from 2 services in London. In addition, the study aims to assess the completeness of data collection, explore how treatment outcomes are discriminated using current criteria for classifying recovery, and assess the feasibility and need for undertaking a future larger population analysis. DESIGN: Observational, retrospective discriminant analysis. SETTING: 2 London community mental health services that provide psychological therapies for common mental disorders including anxiety and depression. PARTICIPANTS: A total of 7388 patients attended the services between February 2009 and May 2012, of which 4393 (59%) completed therapy, or there was an agreement to end therapy, and were included in the study. PRIMARY AND SECONDARY OUTCOME MEASURES: Different combinations of the clinical outcome scores for anxiety Generalised Anxiety Disorder-7 and depression Patient Health Questionnaire-9 were used to construct different treatment outcomes. RESULTS: The predictive models were able to assign a positive or negative clinical outcome to each patient based on 5 independent pre-treatment variables, with an accuracy of 69.4% and 79.3%, respectively: initial severity of anxiety and depression, ethnicity, deprivation and gender. The number of sessions attended/missed were also important factors identified in recovery. CONCLUSIONS: Predicting whether patients are likely to have a positive outcome following treatment at entry might allow suitable modification of scheduled treatment, possibly resulting in improvements in outcomes. The model also highlights factors not only associated with poorer outcomes but inextricably linked to prevalence of common mental disorders, emphasising the importance of social determinants not only in poor health but also poor recovery

Are the Epworth Sleepiness Scale and Stop-Bang Model effective at predicting the severity of Obstructive Sleep Apnoea (OSA); in particular OSA requiring treatment?

Obstructive sleep apnoea (OSA) is a condition characterised by repetitive upper airway collapse during sleep. The condition carries a range of health sequelae that can prove fatal in cases with co-existing risk factors for the condition, such as obesity and hypertension. Utilisation of a high-performance screening tool for OSA is thus important. A retrospective audit using the ESS and Stop-Bang scores, alongside Apnoea–Hypopnea Index values, for patients who underwent polysomnography over 1 year. Multinomial logistic regression was used to compare the predictive abilities of ESS, SBM, and body mass index (BMI) for the patient outcome groups, “None” (No OSA), “Notreat” (OSA not requiring treatment) and “treat” (OSA requiring treatment). The influences of age, gender and BMI on outcome group were also assessed. 126 bariatric and 66 non-bariatric patients were included. Multinomial logistic regression failed to demonstrate predictive ability of ESS. A higher Stop-Bang score significantly increases the risk being in the “treat” group. In addition, male gender, greater age and a higher BMI each individually increase the risk of OSA requiring treatment. Stop-Bang failed to demonstrate predictive significance when age and gender were controlled for. ESS is not an appropriate screening tool for OSA. Stop-Bang, however, remains a useful screening tool, with the ability to detect patient with OSA in need of treatment. Further study may benefit the development and implementation of a concise and more specific screening tool that considers high evidence-based risk factors for OSA, including male gender, greater age and raised BMI