Development of the Guernsey Community Participation and Leisure Assessment – Revised (GCPLA-R).

A sufficiently psychometrically robust measure of community and leisure participation of adults with intellectual disabilities was not in existence, despite research identifying this as an important outcome and a key contributor to quality of life. The current study aimed to update the Guernsey Community Participation and Leisure Assessment (GCPLA). Adults with intellectual disabilities, carers and experts were consulted in creating a revised pool of 46 items. These were then tested and data from 326 adults with intellectual disabilities were analysed for their component structure and psychometric properties. Principal Component analysis discovered a stable set of components describing seven different clusters. This revised measure (the GCPLA-R) was demonstrated to have satisfactory reliability, and scores were related to challenging behaviour and adaptive behaviour in theoretically consistent ways and were correlated with scores on comparable measures

A systematic review of community participation measures for people with intellectual disabilities

Background: Community participation is considered a fundamental aspect of quality of life and one of the essential goals of services for people with intellectual disabilities (ID), yet there is no agreed way of measuring community participation. Method: Two systematic searches were performed across eight electronic databases to identify measures of community participation and identify validation studies for each measure. Measures were included if they were developed for adults with ID, measured extent of participation and had published information regarding content and psychometric properties. Each measure was evaluated on the basis of psychometric properties and in relation to coverage of nine domains of community participation from the International Classification of Functioning, Disability and Health (ICF). Results: Eleven measures were selected with the quality rating scores varying substantially ranging from 2-11 of a possible 16. Conclusions: The majority of measures were not sufficiently psychometrically tested. Findings suggest a need for the development of a psychometrically robust instrument

Ab-initio theory of NMR chemical shifts in solids and liquids

We present a theory for the ab-initio computation of NMR chemical shifts (sigma) in condensed matter systems, using periodic boundary conditions. Our approach can be applied to periodic systems such as crystals, surfaces, or polymers and, with a super-cell technique, to non-periodic systems such as amorphous materials, liquids, or solids with defects. We have computed the hydrogen sigma for a set of free molecules, for an ionic crystal, LiH, and for a H-bonded crystal, HF, using density functional theory in the local density approximation. The results are in excellent agreement with experimental data.Comment: to appear in Physical Review Letter

Prophylactic levofloxacin to prevent infections in newly diagnosed symptomatic myeloma: the TEAMM RCT.

BACKGROUND: Myeloma causes profound immunodeficiency and recurrent serious infections. There are approximately 5500 new UK cases of myeloma per annum, and one-quarter of patients will have a serious infection within 3 months of diagnosis. Newly diagnosed patients may benefit from antibiotic prophylaxis to prevent infection. However, the use of prophylaxis has not been established in myeloma and may be associated with health-care-associated infections (HCAIs), such as Clostridium difficile. There is a need to assess the benefits and cost-effectiveness of the use of antibacterial prophylaxis against any risks in a double-blind, placebo-controlled, randomised clinical trial. OBJECTIVES: To assess the risks, benefits and cost-effectiveness of prophylactic levofloxacin in newly diagnosed symptomatic myeloma patients. DESIGN: Multicentre, randomised, double-blind, placebo-controlled trial. A central telephone randomisation service used a minimisation computer algorithm to allocate treatments in a 1 : 1 ratio. SETTING: A total of 93 NHS hospitals throughout England, Northern Ireland and Wales. PARTICIPANTS: A total of 977 patients with newly diagnosed symptomatic myeloma. INTERVENTION: Patients were randomised to receive levofloxacin or placebo tablets for 12 weeks at the start of antimyeloma treatment. Treatment allocation was blinded and balanced by centre, estimated glomerular filtration rate and intention to give high-dose chemotherapy with autologous stem cell transplantation. Follow-up was at 4-week intervals up to 16 weeks, with a further follow-up at 1 year. MAIN OUTCOME MEASURES: The primary outcome was to assess the number of febrile episodes (or deaths) in the first 12 weeks from randomisation. Secondary outcomes included number of deaths and infection-related deaths, days in hospital, carriage and invasive infections, response to antimyeloma treatment and its relation to infection, quality of life and overall survival within the first 12 weeks and beyond. RESULTS: In total, 977 patients were randomised (levofloxacin, n = 489; placebo, n = 488). A total of 134 (27%) events (febrile episodes, n = 119; deaths, n = 15) occurred in the placebo arm and 95 (19%) events (febrile episodes, n = 91; deaths, n = 4) occurred in the levofloxacin arm; the hazard ratio for time to first event (febrile episode or death) within the first 12 weeks was 0.66 (95% confidence interval 0.51 to 0.86; p = 0.002). Levofloxacin also reduced other infections (144 infections from 116 patients) compared with placebo (179 infections from 133 patients; p-trend of 0.06). There was no difference in new acquisitions of C. difficile, methicillin-resistant Staphylococcus aureus and extended-spectrum beta-lactamase Gram-negative organisms when assessed up to 16 weeks. Levofloxacin produced slightly higher quality-adjusted life-year gains over 16 weeks, but had associated higher costs for health resource use. With a median follow-up of 52 weeks, there was no significant difference in overall survival (p = 0.94). LIMITATIONS: Short duration of prophylactic antibiotics and cost-effectiveness. CONCLUSIONS: During the 12 weeks from new diagnosis, the addition of prophylactic levofloxacin to active myeloma treatment significantly reduced febrile episodes and deaths without increasing HCAIs or carriage. Future work should aim to establish the optimal duration of antibiotic prophylaxis and should involve the laboratory investigation of immunity, inflammation and disease activity on stored samples funded by the TEAMM (Tackling Early Morbidity and Mortality in Myeloma) National Institute for Health Research Efficacy and Mechanism Evaluation grant (reference number 14/24/04). TRIAL REGISTRATION: Current Controlled Trials ISRCTN51731976. FUNDING DETAILS: This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 23, No. 62. See the NIHR Journals Library website for further project information

On the biaxiality of smectic C and ferroelectric liquid crystals

Ferroelectric liquid crystals (FLCs) were a major topic for research in the 1980s and 1990s, to which George Gray and his research family played a fundamental role in developing the field. The famous symbiotic relationship between the chemists at Hull University and device physicists at the Royal Signals and Radar Establishment (RSRE) continued throughout this period, providing the basis for the τVmin mode of FLC operation. The principal of this mode relies on the dielectric biaxiality inherent to the smectic C and ferroelectric smectic C* liquid crystal phases. As with nematics before, new materials and device physics developed hand-in-hand, allowing materials to be formulated with addressing times of 12μs at voltages below 30 V. After reviewing the material physics behind these devices, new measurements of the biaxial refractive indices and permittivities are presented, from which the biaxial order parameter C is determined

Action video game training reduces the Simon Effect

Abstract A number of studies have shown that training on action video games improves various aspects of visual cognition including selective attention and inhibitory control. Here, we demonstrate that action video game play can also reduce the Simon Effect, and, hence, may have the potential to improve response selection during the planning and execution of goal-directed action. Non-game-players were randomly assigned to one of four groups; two trained on a first-person shooter game (Call of Duty) on either Microsoft Xbox or Nintendo DS, one trained on a visual training game for Nintendo DS, and a control group who received no training. Response times were used to contrast performance before and after training on a behavioral assay designed to manipulate stimulus-response compatibility (the Simon Task). The results revealed significantly faster response times and a reduced cost of stimulusresponse incompatibility in the groups trained on the first-person-shooter game. No benefit of training was observed in the control group or the group trained on the visual training game. These findings are consistent with previous evidence that action game play elicits plastic changes in the neural circuits that serve attentional control, and suggest training may facilitate goal-directed action by improving players' ability to resolve conflict during response selection and execution

Diagnostic pathways in multiple myeloma and their relationship to end organ damage: an analysis from the Tackling Early Morbidity and Mortality in Myeloma (TEAMM) trial.

Multiple myeloma is associated with significant early morbidity and mortality, with considerable end organ damage often present at diagnosis. The Tackling EArly Morbidity and Mortality in Multiple Myeloma (TEAMM) trial was used to evaluate routes to diagnosis in patients with myeloma and the relationship between diagnostic pathways, time to diagnosis and disease severity. A total of 915 participants were included in the study. Fifty-one per cent were diagnosed by direct referral from primary care to haematology; 29% were diagnosed via acute services and 20% were referred via other secondary care specialties. Patients diagnosed via other secondary care specialties had a longer diagnostic interval (median 120 days vs. 59 days) without an increase in features of severe disease, suggesting they had a relatively indolent disease. Marked intrahospital delay suggests possible scope for improvement. A quarter of those diagnosed through acute services reported >30 days from initial hospital consultation to haematology assessment. Participants diagnosed through acute services had poorer performance status (P < 0·0001) and higher burden of end organ damage (P < 0·0001) with no difference in the overall length of diagnostic pathway compared to those diagnosed by direct referral (median 59 days). This suggests that advanced disease in patients presenting through acute services predominantly reflects disease aggression

Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015

Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric history, lack of validation, and restriction to a single classifier (logistic regression). Consequently, predictive performance remains low, and risk quantification has not been adopted into antenatal practice. The study population consisted of all births to women in Western Australia from 1980 to 2015, excluding terminations. After all exclusions there were 947,025 livebirths and 5,788 stillbirths. Predictive models for stillbirth were developed using multiple machine learning classifiers: regularised logistic regression, decision trees based on classification and regression trees, random forest, extreme gradient boosting (XGBoost), and a multilayer perceptron neural network. We applied 10-fold cross-validation using independent data not used to develop the models. Predictors included maternal socio-demographic characteristics, chronic medical conditions, obstetric complications and family history in both the current and previous pregnancy. In this cohort, 66% of stillbirths were observed for multiparous women. The best performing classifier (XGBoost) predicted 45% (95% CI: 43%, 46%) of stillbirths for all women and 45% (95% CI: 43%, 47%) of stillbirths after the inclusion of previous pregnancy history. Almost half of stillbirths could be potentially identified antenatally based on a combination of current pregnancy complications, congenital anomalies, maternal characteristics, and medical history. Greatest sensitivity is achieved with addition of current pregnancy complications. Ensemble classifiers offered marginal improvement for prediction compared to logistic regression

Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015

Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric history, lack of validation, and restriction to a single classifier (logistic regression). Consequently, predictive performance remains low, and risk quantification has not been adopted into antenatal practice. The study population consisted of all births to women in Western Australia from 1980 to 2015, excluding terminations. After all exclusions there were 947,025 livebirths and 5,788 stillbirths. Predictive models for stillbirth were developed using multiple machine learning classifiers: regularised logistic regression, decision trees based on classification and regression trees, random forest, extreme gradient boosting (XGBoost), and a multilayer perceptron neural network. We applied 10-fold cross-validation using independent data not used to develop the models. Predictors included maternal socio-demographic characteristics, chronic medical conditions, obstetric complications and family history in both the current and previous pregnancy. In this cohort, 66% of stillbirths were observed for multiparous women. The best performing classifier (XGBoost) predicted 45% (95% CI: 43%, 46%) of stillbirths for all women and 45% (95% CI: 43%, 47%) of stillbirths after the inclusion of previous pregnancy history. Almost half of stillbirths could be potentially identified antenatally based on a combination of current pregnancy complications, congenital anomalies, maternal characteristics, and medical history. Greatest sensitivity is achieved with addition of current pregnancy complications. Ensemble classifiers offered marginal improvement for prediction compared to logistic regression