Computationally efficient methods for fitting mixed models to electronic health records data

Motivated by two case studies using primary care records from the Clinical Practice Research Datalink, we describe statistical methods that facilitate the analysis of tall data, with very large numbers of observations. Our focus is on investigating the association between patient characteristics and an outcome of interest, while allowing for variation among general practices. We explore ways to fit mixed effects models to tall data, including predictors of interest and confounding factors as covariates, and including random intercepts to allow for heterogeneity in outcome among practices. We introduce: (1) weighted regression and (2) meta-analysis of estimated regression coefficients from each practice. Both methods reduce the size of the dataset, thus decreasing the time required for statistical analysis. We compare the methods to an existing subsampling approach. All methods give similar point estimates, and weighted regression and meta-analysis give similar standard errors for point estimates to analysis of the entire dataset, but the subsampling method gives larger standard errors. Where all data are discrete, weighted regression is equivalent to fitting the mixed model to the entire dataset. In the presence of a continuous covariate, meta-analysis is useful. Both methods are easy to implement in standard statistical softwareThe authors are grateful to the CPRD team at the University of Cambridge. In particular, we thank Carol Wilson and Anna Cassel for providing access to the case study datasets that they spent much time preparing for analysis. Kirsty Rhodes was funded by Medical Research Council Unit Programmes U105260558 and MC_UU_00002/5. Rebecca Turner and Ian White were funded by Medical Research Council Unit Programmes U105260558 and MC_UU_12023/2

The virtual maze: A behavioural tool for measuring trust

Trusting another person may depend on our level of generalised trust in others, as well as perceptions of that specific person's trustworthiness. However, many studies measuring trust outcomes have not discussed generalised versus specific trust. To measure specific trust in others, we developed a novel behavioural task. Participants navigate a virtual maze and make a series of decisions about how to proceed. Before each decision, they may ask for advice from two virtual characters they have briefly interviewed earlier. We manipulated the virtual characters' trustworthiness during the interview phase and measured how often participants approached and followed advice from each character. We also measured trust through ratings and an investment game. Across three studies we found participants followed advice from a trustworthy character significantly more than an untrustworthy character, demonstrating the validity of the maze task. Behaviour in the virtual maze reflected specific trust rather than generalised trust, whereas the investment game picked up on generalised trust as well as specific trust. Our data suggests the virtual maze task may provide an alternative behavioural approach to measuring specific trust in future research, and we demonstrate how the task may be used in traditional laboratories

The Epidemiology of Multimorbidity in Primary Care

Background: Multimorbidity places a substantial burden on patients and the healthcare system but few contemporary data are available. Aim: To describe the epidemiology of multimorbidity in adults in England and quantify associations between multimorbidity and health service utilisation. Design: Retrospective cohort study Setting: A random sample of 403,985 adult patients (≥18 years) in England who were registered with a general practice on 1 January 2012 and included in the Clinical Practice Research Datalink. Methods: We defined multimorbidity as having two or more of 36 long-term conditions recorded in patients’ medical records and quantified associations between multimorbidity and health service utilisation (GP consultations, prescriptions, and hospitalisations) over four years. Results: 27.2% of patients were multimorbid. The most prevalent conditions were hypertension (18.2%), depression or anxiety (10.3%), and chronic pain (10.1%). Prevalence of multimorbidity was higher in females than males (30% vs. 24.4% respectively) and among those with lower socioeconomic status (33.8% in the most deprived quintile vs. 24.2% in the least deprived quintile). Physical-mental comorbidity contributed a much greater proportion of overall morbidity in both younger patients and those patients with lower socioeconomic status. Multimorbidity was strongly associated with health service utilisation. Multimorbid patients accounted for 53% of GP consultations, 79% of prescriptions, and 56% percent of hospital admissions. Conclusion: Multimorbidity is common, socially patterned, and associated with increased health service utilisation. These findings support the need to improve the quality and efficiency of health services providing care to multimorbid patients at the practice and national-level.This study received no specific funding. Kirsty Rhodes was supported by the UK Medical Research Council (grant number: U105260558)

Speciation by host switch in brood parasitic indigobirds

A growing body of empirical and theoretical work supports the plausibility of sympatric speciation(1-3), but there remain few examples in which all the essential components of the process are well understood. The African indigobirds Vidua spp. are host-specific brood parasites. Indigobird nestlings are reared along with host young, and mimic the mouth markings of their respective hosts(4-6). As adults, male indigobirds mimic host song(4-7), whereas females use these songs to choose both their mates and the nests they parasitize(8). These behavioural mechanisms promote the cohesion of indigobird populations associated with a given host species, and provide a mechanism for reproductive isolation after a new host is colonized. Here we show that all indigobird species are similar genetically, but are significantly differentiated in both mitochondrial haplotype and nuclear allele frequencies. These data support a model of recent sympatric speciation. In contrast to the cuckoo Cuculus canorus, in which only female lineages are faithful to specific hosts(9,10), host switches have led to speciation in indigobirds because both males and females imprint on their hosts(8,11).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62510/1/nature01863.pd

Association of comorbidity and health service usage among patients with dementia in the UK: a population-based study

$\textbf{BACKGROUND}$: The majority of people with dementia have other long-term diseases, the presence of which may affect the progression and management of dementia. This study aimed to identify subgroups with higher healthcare needs, by analysing how primary care consultations, number of prescriptions and hospital admissions by people with dementia varies with having additional long-term diseases (comorbidity). $\textbf{METHODS}$: A retrospective cohort study based on health data from the Clinical Practice Research Datalink (CPRD) was conducted. Incident cases of dementia diagnosed in the year starting 1/3/2008 were selected and followed for up to 5 years. The number of comorbidities was obtained from a set of 34 chronic health conditions. Service usage (primary care consultations, hospitalisations and prescriptions) and time-to-death were determined during follow-up. Multilevel negative binomial regression and Cox regression, adjusted for age and gender, were used to model differences in service usage and death between differing numbers of comorbidities. $\textbf{RESULTS}$: Data from 4999 people (14 866 person-years of follow-up) were analysed. Overall, 91.7% of people had 1 or more additional comorbidities. Compared with those with 2 or 3 comorbidities, people with ≥6 comorbidities had higher rates of primary care consultations (rate ratio (RR) 1.31, 95% CI 1.25 to 1.36), prescriptions (RR 1.68, 95% CI 1.57 to 1.81), and hospitalisation (RR 1.62, 95% CI 1.44 to 1.83), and higher risk of death (HR 1.56, 95% CI 1.37 to 1.78). $\textbf{DISCUSSION}$: In the UK, people with dementia with higher numbers of comorbidities die earlier and have considerably higher health service usage in terms of primary care consultations, hospital admissions and prescribing. This study provides strong evidence that comorbidity is a key factor that should be considered when allocating resources and planning care for people with dementia

A novel regulatory circuit specifies cell fate in the Arabidopsis root epidermis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75165/1/j.1399-3054.2006.00606.x.pd

Mobile applications for obesity and weight management: current market characteristics

Mobile-Health (mHealth) is the fastest-developing eHealth sector, with over 100 000 health applications (apps) currently available. Overweight/obesity is a problem of wide public concern that is potentially treatable/preventable through mHealth. This study describes the current weight-management app-market. Five app stores (Apple, Google, Amazon, Windows and Blackberry) in UK, US, Russia, Japan and Germany, Italy, France, China, Australia and Canada were searched for keywords: 'weight', 'calorie', 'weight-loss', 'slimming', 'diet', 'dietitian' and 'overweight' in January/February 2016 using App-Annie software. The 10 most downloaded apps in the lifetime of an app were recorded. Developers' lists and the app descriptions were searched to identify any professional input with keywords 'professional', 'dietitian' and 'nutritionist'. A total of 28 905 relevant apps were identified as follows: Apple iTunes=8559 (4634, 54% paid), Google Play=1762 (597, 33.9% paid), Amazon App=13569 (4821, 35.5% paid), Windows=2419 (819, 17% paid) and Blackberry=2596 (940, 36% paid). The 28 905 identified apps focused mainly on physical activity (34%), diet (31%), and recording/monitoring of exercise, calorie intake and body weight (23%). Only 17 apps (0.05%) were developed with identifiable professional input. Apps on weight management are widely available and very popular but currently lack professional content expertise. Encouraging app development based on evidence-based online approaches would assure content quality, allowing healthcare professionals to recommend their use

Histone deacetylase adaptation in single ventricle heart disease and a young animal model of right ventricular hypertrophy.

BackgroundHistone deacetylase (HDAC) inhibitors are promising therapeutics for various forms of cardiac diseases. The purpose of this study was to assess cardiac HDAC catalytic activity and expression in children with single ventricle (SV) heart disease of right ventricular morphology, as well as in a rodent model of right ventricular hypertrophy (RVH).MethodsHomogenates of right ventricle (RV) explants from non-failing controls and children born with a SV were assayed for HDAC catalytic activity and HDAC isoform expression. Postnatal 1-day-old rat pups were placed in hypoxic conditions, and echocardiographic analysis, gene expression, HDAC catalytic activity, and isoform expression studies of the RV were performed.ResultsClass I, IIa, and IIb HDAC catalytic activity and protein expression were elevated in the hearts of children born with a SV. Hypoxic neonatal rats demonstrated RVH, abnormal gene expression, elevated class I and class IIb HDAC catalytic activity, and protein expression in the RV compared with those in the control.ConclusionsThese data suggest that myocardial HDAC adaptations occur in the SV heart and could represent a novel therapeutic target. Although further characterization of the hypoxic neonatal rat is needed, this animal model may be suitable for preclinical investigations of pediatric RV disease and could serve as a useful model for future mechanistic studies