Search

Objectives Because of fundamental differences in healthcare systems, US readmission data cannot be extrapolated to the European setting: To investigate the opinions of readmitted patients, their carers, nurses and physicians on predictability and preventability of readmissions and using majority consensus to determine contributing factors that could potentially foresee (preventable) readmissions. Design Prospective observational study. Readmitted patients, their carers, and treating professionals were surveyed during readmission to assess the discharge process and the predictability and preventability of the readmission. Cohen's Kappa measured pairwise agreement of considering readmission as predictable/preventable by patients, carers and professionals. Subsequently, multivariable logistic regressionidentified factors associated with predictability/preventability. Setting 15 hospitals in four European countries Participants 1398 medical patients readmitted unscheduled within 30 days Main Outcome(s) and Measure(s) (1) Agreement between the interviewed groups on considering readmissions likely predictable or preventable;® Factors distinguishing predictable from non-predictable and preventable from non-preventable readmissions. Results The majority deemed 27.8% readmissions potentially predictable and 14.4% potentially preventable. The consensus on predictability and preventability was poor, especially between patients and professionals (kappas ranged from 0.105 to 0.173). The interviewed selected different factors as potentially associated with predictability and preventability. When a patient reported that he was ready for discharge during index admission, the readmission was deemed less likely by the majority (predictability: OR 0.55; 95% CI 0.40 to 0.75; preventability: OR 0.35; 95% CI 0.24 to 0.49). Conclusions There is no consensus between readmitted patients, their carers and treating professionals about predictability and preventability of readmissions, nor associated risk factors. A readmitted patient reporting not feeling ready for discharge at index admission was strongly associated with preventability/predictability. Therefore, healthcare workers should question patients' readiness to go home timely before discharge. [ABSTRACT FROM AUTHOR]

Objective To examine (1) the impact of pictorial cigarette warning labels on changes in self-reported warning label responses: warning salience, cognitive responses, forgoing cigarettes and avoiding warnings, and (2) whether these changes differed by smokers' educational level. Methods Longitudinal data of smokers from two survey waves of the International Tobacco Control (ITC) Europe Surveys were used. In France and the UK, pictorial warning labels were implemented on the back of cigarette packages between the two survey waves. In Germany and the Netherlands, the text warning labels did not change. Findings Warning salience decreased between the surveys in France (OR=0.81, p=0.046) and showed a non-significant increase in the UK (OR=1.30, p=0.058), cognitive responses increased in the UK (OR=1.34, p<0.001) and decreased in France (OR=0.70, p=0.002), forgoing cigarettes increased in the UK (OR=1.65, p<0.001) and decreased in France (OR=0.83, p=0.047), and avoiding warnings increased in France (OR=2.93, p<0.001) and the UK (OR=2.19, p<0.001). Warning salience and cognitive responses decreased in Germany and the Netherlands, forgoing did not change in these countries and avoidance increased in Germany. In general, these changes in warning label responses did not differ by education. However, in the UK, avoidance increased especially among low (OR=2.25, p=0.001) and moderate educated smokers (OR=3.21, p<0.001). Conclusions The warning labels implemented in France in 2010 and in the UK in 2008 with pictures on one side of the cigarette package did not succeed in increasing warning salience, but did increase avoidance. The labels did not increase educational inequalities among continuing smokers. [ABSTRACT FROM AUTHOR]

Objective: Patients with repaired tetralogy of Fallot (TOF) are followed serially by cardiac magnetic resonance (CMR) for surveillance of RV dilation and dysfunction. We sought to define the prevalence of progressive RV disease and the optimal time interval between CMR evaluations.Methods: Candidates were selected from a multicentre TOF registry and were included if ≥2 CMR studies performed ≥6 months apart were available without interval cardiovascular interventions. Patients with 'disease progression' (defined as increase in RV end-diastolic volume index (RVEDVi) ≥30 mL/m(2), decrease in RVEF ≥10% or decrease in LVEF ≥10%) were compared with those with 'disease non-progression' (defined as RVEDVi increase ≤5 mL/m(2), RVEF decrease ≤3% and LVEF decrease ≤3%).Results: A total of 849 CMR studies in 339 patients (median age at first CMR 23.6 years) were analysed. Over a median interval of 2.2 years between CMR pairs, RVEDVi increased 4±18 mL/m(2) (p<0.001), RV end-systolic volume index increased 3±13 mL/m(2) (p<0.001), RVEF decreased 1%±6% (p=0.02) and LVEF decreased 1%±6% (p=0.001). Disease progression was observed in 15% (n=76) and non-progression in 26% (n=133). There were no significant differences between those with and without progression in baseline demographic, anatomic, ECG, exercise or baseline CMR characteristics. The optimal time interval between CMR studies for detection of progression was a 3-year interval (63% sensitivity, 65% specificity, area under the receiver operating characteristic curve 0.65).Conclusions: Although progressive RV dilation and decline in biventricular systolic function occur at a slow pace in the majority of adults with repaired TOF, 15% of patients experience rapid disease progression. The results of this study support the practice of serial CMR examinations to identify progressive disease at a time interval of up to 3 years. [ABSTRACT FROM AUTHOR]

Background: Priority setting, identification of unmet and changing healthcare needs, service and policy planning, and the capacity to evaluate the impact of health interventions requires valid and reliable methods for quantifying disease and injury burden. The methodology developed for the Global Burden of Disease (GBD) studies has been adopted to estimate the burden of disease in national, regional and global projects. However, there has been little validation of the methods for estimating injury burden using empirical data. Objective: To provide valid estimates of the burden of non-fatal injury using empirical data. Setting: Data from prospective cohort studies of injury outcomes undertaken in the UK, USA, Australia, New Zealand and The Netherlands. Design and participants: Meta-analysis of deidentified, patient-level data from over 40 000 injured participants in six prospective cohort studies: Victorian State Trauma Registry, Victorian Orthopaedic Trauma Outcomes Registry, UK Burden of Injury study, Prospective Outcomes of Injury study, National Study on Costs and Outcomes of Trauma and the Dutch Injury Patient Survey. Analysis: Data will be systematically analysed to evaluate and refine injury classification, development of disability weights, establishing the duration of disability and handling of cases with more than one injury in burden estimates. Developed methods will be applied to incidence data to compare and contrast various methods for estimating non-fatal injury burden. Contribution to the field: The findings of this international collaboration have the capacity to drive how injury burden is measured for future GBD estimates and for individual country or region-specific studies. [ABSTRACT FROM AUTHOR]

Objectives To measure changes in prevalence and predictors of home smoking bans (HSBs) among smokers in four European countries after the implementation of national smoke-free legislation. Design Two waves of the International Tobacco Control Policy Evaluation Project Europe Surveys, which is a prospective panel study. Pre- and post-legislation data were used from Ireland, France, Germany and the Netherlands. Two pre-legislation waves from the UK were used as control. Participants 4634 respondents from the intervention countries and 1080 from the control country completed both baseline and follow-up and were included in the present analyses. Methods Multiple logistic regression models to identify predictors of having or of adopting a total HSB, and Generalised Estimating Equation models to compare patterns of change after implementation of smoke-free legislation to a control country without such legislation. Results Most smokers had at least partial smoking restrictions in their home, but the proportions varied significantly between countries. After implementation of national smoke-free legislation, the proportion of smokers with a total HSB increased significantly in all four countries. Among continuing smokers, the number of cigarettes smoked per day either remained stable or decreased significantly. Multiple logistic regression models indicated that having a young child in the household and supporting smoking bans in bars were important correlates of having a pre-legislation HSB. Prospective predictors of imposing a HSB between survey waves were planning to quit smoking, supporting a total smoking ban in bars and the birth of a child. Generalised Estimating Equation models indicated that the change in total HSB in the intervention countries was greater than that in the control country. Conclusions The findings suggest that smoke-free legislation does not lead to more smoking in smokers' homes. On the contrary, our findings demonstrate that smoke-free legislation may stimulate smokers to establish total smoking bans in their homes. [ABSTRACT FROM AUTHOR]

Background Finite mixture models posit the existence of a latent categorical variable and can be used for probabilistic classification. The authors illustrate the use of mixture models for dietary pattern analysis. An advantage of this approach is taking classification uncertainty into account. Methods Participants were a random sample of women from the European Prospective Investigation into Cancer. Food consumption was measured using dietary questionnaires. Mixture models identified latent classes in food consumption data, which were interpreted as dietary patterns. Results Among various assumptions examined, models allowing the variance of foods to vary within and between classes fit better than alternatives assuming constant variance (the K-means method of cluster analysis also makes the latter assumption). An eight-class model was best fitting and five patterns validated well in a second random sample. Patterns with lower classification uncertainty tended to be better validated. One pattern showed low consumption of foods despite being associated with moderate body mass index. Conclusion Mixture modelling for dietary pattern analysis has advantages over both factor and cluster analysis. In contrast to these other methods, it is easy to estimate pattern prevalence, to describe patterns and to use patterns to predict disease taking classification uncertainty into account. Owing to substantial error in food consumptions, any analysis will usually find some patterns that cannot be well validated. While knowledge of classification uncertainty may aid pattern evaluation, any method will better identify patterns from food consumptions measured with less error. Mixture models may be useful to identify individuals who under-report food consumption. [ABSTRACT FROM AUTHOR]