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Abstract Background Allocating healthcare resources to local areas in proportion to need is an important element of many universal health care systems, aiming to provide equal access for equal need. The UK National Health Service allocates resources to relatively large areas in proportion to need, using needs-weighted capitation formulae. However, within those planning areas, local providers and commissioners also require robust methods for allocating resources to neighbourhoods in proportion to need to ensure equitable access. We therefore developed a local resource allocation formula for NHS district nursing services for a City in the North West of England, demonstrating a novel application of the national formulae principles for equitable resource allocation to small areas. Methods Using linked data from community health services, primary care, secondary care and social care, we used a zero-inflated Poisson regression to model the number of district nursing services contacts for each individual based on predictors of need, while including the supply of district nurses per head to account for historical supply induced patterns. Individual need was estimated based on the predictions from this model, keeping supply fixed at the average. We then compared the distribution of district nurses between neighbourhoods, based on our formula, to the current service staffing distribution. Results Key predictors of need for district nursing services were age, deprivation, chronic diseases such as, cardiovascular disease, chronic liver disease, neurological disease, mental ill health, learning disability living in a nursing home, living alone, and receiving palliative care. Need for district nursing services was highly weighted towards older and more deprived populations. The current distribution of staff was, however, more correlated with age than deprivation. Moving to a needs-based staffing distribution would shift staff from less deprived areas to more deprived areas potentially reducing inequalities. Conclusion A neighbourhood-level model for needs for district nursing is a useful tool that can potentially improve the allocation of resources, addressing unmet need and inequalities.

Abstract Background The challenging nature of studies with incarcerated populations and other offender groups can impede the conduct of research, particularly that involving complex study designs such as randomised control trials and clinical interventions. Providing an overview of study designs employed in this area can offer insights into this issue and how research quality may impact on health and justice outcomes. Methods We used a rule-based approach to extract study designs from a sample of 34,481 PubMed abstracts related to epidemiological criminology published between 1963 and 2023. The results were compared against an accepted hierarchy of scientific evidence. Results We evaluated our method in a random sample of 100 PubMed abstracts. An F1-Score of 92.2% was returned. Of 34,481 study abstracts, almost 40.0% (13,671) had an extracted study design. The most common study design was observational (37.3%; 5101) while experimental research in the form of trials (randomised, non-randomised) was present in 16.9% (2319). Mapped against the current hierarchy of scientific evidence, 13.7% (1874) of extracted study designs could not be categorised. Among the remaining studies, most were observational (17.2%; 2343) followed by systematic reviews (10.5%; 1432) with randomised controlled trials accounting for 8.7% (1196) of studies and meta-analysis for 1.4% (190) of studies. Conclusions It is possible to extract epidemiological study designs from a large-scale PubMed sample computationally. However, the number of trials, systematic reviews, and meta-analysis is relatively small – just 1 in 5 articles. Despite an increase over time in the total number of articles, study design details in the abstracts were missing. Epidemiological criminology still lacks the experimental evidence needed to address the health needs of the marginalized and isolated population that is prisoners and offenders.

IntroductionStructured medication reviews (SMRs), introduced in the United Kingdom (UK) in 2020, aim to enhance shared decision-making in medication optimisation, particularly for patients with multimorbidity and polypharmacy. Despite its potential, there is limited empirical evidence on the implementation of SMRs, and the challenges faced in the process. This study is part of a larger DynAIRx (Artificial Intelligence for dynamic prescribing optimisation and care integration in multimorbidity) project which aims to introduce Artificial Intelligence (AI) to SMRs and develop machine learning models and visualisation tools for patients with multimorbidity. Here, we explore how SMRs are currently undertaken and what barriers are experienced by those involved in them.MethodsQualitative focus groups and semi-structured interviews took place between 2022-2023. Six focus groups were conducted with doctors, pharmacists and clinical pharmacologists (n = 21), and three patient focus groups with patients with multimorbidity (n = 13). Five semi-structured interviews were held with 2 pharmacists, 1 trainee doctor, 1 policy-maker and 1 psychiatrist. Transcripts were analysed using thematic analysis.ResultsTwo key themes limiting the effectiveness of SMRs in clinical practice were identified: 'Medication Reviews in Practice' and 'Medication-related Challenges'. Participants noted limitations to the efficient and effectiveness of SMRs in practice including the scarcity of digital tools for identifying and prioritising patients for SMRs; organisational and patient-related challenges in inviting patients for SMRs and ensuring they attend; the time-intensive nature of SMRs, the need for multiple appointments and shared decision-making; the impact of the healthcare context on SMR delivery; poor communication and data sharing issues between primary and secondary care; difficulties in managing mental health medications and specific challenges associated with anticholinergic medication.ConclusionSMRs are complex, time consuming and medication optimisation may require multiple follow-up appointments to enable a comprehensive review. There is a need for a prescribing support system to identify, prioritise and reduce the time needed to understand the patient journey when dealing with large volumes of disparate clinical information in electronic health records. However, monitoring the effects of medication optimisation changes with a feedback loop can be challenging to establish and maintain using current electronic health record systems.

Valproate is the most effective treatment for idiopathic generalised epilepsy. Currently, its use is restricted in women of childbearing potential owing to high teratogenicity. Recent evidence extended this risk to men's offspring, prompting recommendations to restrict use in everybody aged

IntroductionAntipsychotic medication is increasingly prescribed to patients with serious mental illness. Patients with serious mental illness often have cardiovascular and metabolic comorbidities, and antipsychotics independently increase the risk of cardiometabolic disease. Despite this, many patients prescribed antipsychotics are discharged to primary care without planned psychiatric review. We explore perceptions of healthcare professionals and managers/directors of policy regarding reasons for increasing prevalence and management of antipsychotics in primary care.MethodsQualitative study using semi-structured interviews with 11 general practitioners (GPs), 8 psychiatrists, and 11 managers/directors of policy in the United Kingdom. Data was analysed using thematic analysis.ResultsRespondents reported competency gaps that impaired ability to manage patients prescribed antipsychotic medications, arising from inadequate postgraduate training and professional development. GPs lacked confidence to manage antipsychotic medications alone; psychiatrists lacked skills to address cardiometabolic risks and did not perceive this as their role. Communication barriers, lack of integrated care records, limited psychology provision, lowered expectation towards patients with serious mental illness by professionals, and pressure to discharge from hospital resulted in patients in primary care becoming 'trapped' on antipsychotics, inhibiting opportunities to deprescribe. Organisational and contractual barriers between services exacerbate this risk, with socioeconomic deprivation and lack of access to non-pharmacological interventions driving overprescribing. Professionals voiced fears of censure if a catastrophic event occurred after stopping an antipsychotic. Facilitators to overcome these barriers were suggested.ConclusionsPeople prescribed antipsychotics experience a fragmented health system and suboptimal care. Several interventions could be taken to improve care for this population, but inadequate availability of non-pharmacological interventions and socioeconomic factors increasing mental distress need policy change to improve outcomes. The role of professionals' fear of medicolegal or regulatory censure inhibiting antipsychotic deprescribing was a new finding in this study.

Background Gastrointestinal (GI) infections result in 17 million cases annually, with foodborne illness costing the National Health Service (NHS) £60m per year. The burden of GI infection is unequally distributed, with greater impact in more socioeconomically disadvantaged groups and areas. Local authorities (LA) provide vital services that protect public health and wellbeing. The impact of funding cuts to local services and their effect on public health is an area of concern. Environmental and regulatory (ER) services are responsible for roles such as food safety and infectious disease control. This study aims to understand the impact of local funding cuts on ER and GI infection outcomes. Methods We will conduct an ecological longitudinal study in England from 2010-2019 at the LA level to examine how changes in ER expenditure overtime have impacted ER and GI infection outcomes. Data will be gathered on food hygiene enforcement, food hygiene compliance levels, GI infection hospitalisation, NHS 111 calls relating to GI infection symptoms, GI infection pathogen data, deprivation, and population density. Measures will be aggregated to LA level and statistical analysis will be carried out. Ethics and dissemination University of Liverpool Ethics committee have confirmed ethical approval will not be required. All data will be aggregated and anonymised, therefore only data sharing agreements will be required. Findings will be disseminated to the stakeholder group in addition to outputs through conferences and publications. These findings will help understand impact of key services on public health and should inform government and public health policy and strategy.

BackgroundThe emerging field of epidemiological criminology studies the intersection between public health and justice systems. To increase the value of and reduce waste in research activities in this area, it is important to perform transparent research priority setting considering the needs of research beneficiaries and end users along with a systematic assessment of the existing research activities to address gaps and harness opportunities. ObjectiveIn this study, we aimed to examine published research outputs in epidemiological criminology to assess gaps between published outputs and current research priorities identified by prison stakeholders. MethodsA rule-based method was applied to 23,904 PubMed epidemiological criminology abstracts to extract the study determinants and outcomes (ie, “themes”). These were mapped against the research priorities identified by Australian prison stakeholders to assess the differences from research outputs. The income level of the affiliation country of the first authors was also identified to compare the ranking of research priorities in countries categorized by income levels. ResultsOn an evaluation set of 100 abstracts, the identification of themes returned an F1-score of 90%, indicating reliable performance. More than 53.3% (11,927/22,361) of the articles had at least 1 extracted theme; the most common was substance use (1533/11,814, 12.97%), followed by HIV (1493/11,814, 12.64%). The infectious disease category (2949/11,814, 24.96%) was the most common research priority category, followed by mental health (2840/11,814, 24.04%) and alcohol and other drug use (2433/11,814, 20.59%). A comparison between the extracted themes and the stakeholder priorities showed an alignment for mental health, infectious diseases, and alcohol and other drug use. Although behavior- and juvenile-related themes were common, they did not feature as prison priorities. Most studies were conducted in high-income countries (10,083/11,814, 85.35%), while countries with the lowest income status focused half of their research on infectious diseases (47/91, 52%). ConclusionsThe identification of research themes from PubMed epidemiological criminology research abstracts is possible through the application of a rule-based text mining method. The frequency of the investigated themes may reflect historical developments concerning disease prevalence, treatment advances, and the social understanding of illness and incarcerated populations. The differences between income status groups are likely to be explained by local health priorities and immediate health risks. Notable gaps between stakeholder research priorities and research outputs concerned themes that were more focused on social factors and systems and may reflect publication bias or self-publication selection, highlighting the need for further research on prison health services and the social determinants of health. Different jurisdictions, countries, and regions should undertake similar systematic and transparent research priority–setting processes.

Abstract Background There is strong evidence for the co-occurrence of mental health conditions and alcohol problems, yet physical health outcomes among this group are not well characterised. This study aimed to identify clusters of physical health conditions and their associations with mental health and problematic alcohol use in England’s general population. Methods Cross-sectional analysis of the 2014 Adult Psychiatric Morbidity Survey (N = 7546) was conducted. The survey used standardised measures of problematic alcohol use and mental health conditions, including the Alcohol Use Disorders Identification Test (AUDIT) and the Clinical Interview Schedule-Revised. Participants self-reported any lifetime physical health conditions. Latent class analysis considered 12 common physical illnesses to identify clusters of multimorbidity. Multinomial logistic regression (adjusting for age, gender, ethnicity, education, and occupational grade) was used to explore associations between mental health, hazardous drinking (AUDIT 8 +), and co-occurring physical illnesses. Results Five clusters were identified with statistically distinct and clinically meaningful disease patterns: ‘Physically Healthy’ (76.62%), ‘Emerging Multimorbidity’ (3.12%), ‘Hypertension & Arthritis’ (14.28%), ‘Digestive & Bowel Problems’’ (3.17%), and ‘Complex Multimorbidity’ (2.8%). Having a mental health problem was associated with increased odds of ‘Digestive & Bowel Problems’ (adjusted multinomial odds ratio (AMOR) = 1.58; 95% CI [1.15–2.17]) and ‘Complex Multimorbidity’ (AMOR = 2.02; 95% CI [1.49–2.74]). Individuals with co-occurring mental health conditions and problematic alcohol use also had higher odds of ‘Digestive & Bowel Problems’ (AMOR = 2.64; 95% CI [1.68–4.15]) and ‘Complex Multimorbidity’ (AMOR = 2.62; 95% CI [1.61–4.23]). Conclusions Individuals with a mental health condition concurrent with problematic alcohol use experience a greater burden of physical illnesses, highlighting the need for timely treatment which is likely to include better integration of alcohol and mental health services.

Abstract Background Our study examines if SARS-CoV-2 infections varied by vaccination status, if an individual had previously tested positive and by neighbourhood socioeconomic deprivation across the Delta and Omicron epidemic waves of SARS-CoV-2. Methods Population cohort study using electronic health records for 2.7 M residents in Cheshire and Merseyside, England (3rd June 2021 to 1st March 2022). Our outcome variable was registered positive test for SARS-CoV-2. Explanatory variables were vaccination status, previous registered positive test and neighbourhood socioeconomic deprivation. Cox regression models were used to analyse associations. Results Originally higher SARS-CoV-2 rates in the most socioeconomically deprived neighbourhoods changed to being higher in the least deprived neighbourhoods from the 1st September 2021, and were inconsistent during the Omicron wave. Individuals who were fully vaccinated (two doses) were associated with fewer registered positive tests (e.g., individuals engaged in testing between 1st September and 27th November 2021—Hazards Ratio (HR) = 0.48, 95% Confidence Intervals (CIs) = 0.47–0.50. Individuals with a previous registered positive test were also less likely to have a registered positive test (e.g., individuals engaged in testing between 1st September and 27th November 2021—HR = 0.16, 95% CIs = 0.15–0.18. However, the Omicron period saw smaller effect sizes for both vaccination status and previous registered positive test. Conclusions Changing patterns of SARS-CoV-2 infections during the Delta and Omicron waves reveals a dynamic pandemic that continues to affect diverse communities in sometimes unexpected ways.

Cardiovascular risk was evaluated in patients admitted to rural inpatient psychiatric services over a one-year period in a sparsely populated region of the United Kingdom. Care records were analysed for risk factor recording, and cardiovascular risk estimated using the QRISK3 calculator, which estimates 10-year risk of myocardial infarction or stroke. Of eligible patients, risk factor recording as part of routine care was completed in 86% of possible QRISK3 inputs, enabling QIRSK3 estimation in all eligible patients. QRISK3 for this group was significantly raised relative to an age, sex and ethnicity-matched population, and high risk of cardiovascular disease (QRISK3 score >10%) was detected in 28% of patients. The results demonstrate that there is significant unmet need in rural patients for cardiovascular risk reduction that could be identified as part of routine care. An opportunity exists to integrate mental and physical healthcare by routinely assessing cardiovascular risk in rural psychiatric inpatients. Resources and training are needed to produce this risk information and act on it.

Abstract Background From January to May 2021 the alpha variant (B.1.1.7) of SARS-CoV-2 was the most commonly detected variant in the UK. Following this, the Delta variant (B.1.617.2) then became the predominant variant. The UK COVID-19 vaccination programme started on 8th December 2020. Prior to the Delta variant, most vaccine effectiveness studies focused on the alpha variant. We therefore aimed to estimate the effectiveness of the BNT162b2 (Pfizer-BioNTech) and the ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines in preventing symptomatic and asymptomatic infection with respect to the Delta variant in a UK setting. Methods We used anonymised public health record data linked to infection data (PCR) using the Combined Intelligence for Population Health Action resource. We then constructed an SIR epidemic model to explain SARS-CoV-2 infection data across the Cheshire and Merseyside region of the UK. Vaccines were assumed to be effective after 21 days for 1 dose and 14 days for 2 doses. Results We determined that the effectiveness of the Oxford-AstraZeneca vaccine in reducing susceptibility to infection is 39% (95% credible interval [34, 43]) and 64% (95% credible interval [61, 67]) for a single dose and a double dose respectively. For the Pfizer-BioNTech vaccine, the effectiveness is 20% (95% credible interval [10, 28]) and 84% (95% credible interval [82, 86]) for a single-dose and a double dose respectively. Conclusion Vaccine effectiveness for reducing susceptibility to SARS-CoV-2 infection shows noticeable improvement after receiving two doses of either vaccine. Findings also suggest that a full course of the Pfizer-BioNTech provides the optimal protection against infection with the Delta variant. This reinforces the need to complete the full course programme to maximise individual protection and reduce transmission.

BackgroundPolypharmacy can be a consequence of overprescribing that is prevalent in older adults with multimorbidity. Polypharmacy can cause adverse reactions and result in hospital admission. This study predicted risks of adverse drug reaction (ADR)-related and emergency hospital admissions by medicine classes.MethodsWe used electronic health record data from general practices of Clinical Practice Research Datalink (CPRD GOLD) and Aurum. Older patients who received at least five medicines were included. Medicines were classified using the British National Formulary sections. Hospital admission cases were propensity-matched to controls by age, sex, and propensity for specific diseases. The matched data were used to develop and validate random forest (RF) models to predict the risk of ADR-related and emergency hospital admissions. Shapley Additive eXplanation (SHAP) values were calculated to explain the predictions.ResultsIn total, 89,235 cases with polypharmacy and hospitalised with an ADR-related admission were matched to 443,497 controls. There were over 112,000 different combinations of the 50 medicine classes most implicated in ADR-related hospital admission in the RF models, with the most important medicine classes being loop diuretics, domperidone and/or metoclopramide, medicines for iron-deficiency anaemias and for hypoplastic/haemolytic/renal anaemias, and sulfonamides and/or trimethoprim. The RF models strongly predicted risks of ADR-related and emergency hospital admission. The observed Odds Ratio in the highest RF decile was 7.16 (95% CI 6.65-7.72) in the validation dataset. The C-statistics for ADR-related hospital admissions were 0.58 for age and sex and 0.66 for RF probabilities.ConclusionsPolypharmacy involves a very large number of different combinations of medicines, with substantial differences in risks of ADR-related and emergency hospital admissions. Although the medicines may not be causally related to increased risks, RF model predictions may be useful in prioritising medication reviews. Simple tools based on few medicine classes may not be effective in identifying high risk patients.

BackgroundEpidemiological criminology refers to health issues affecting incarcerated and nonincarcerated offender populations, a group recognized as being challenging to conduct research with. Notwithstanding this, an urgent need exists for new knowledge and interventions to improve health, justice, and social outcomes for this marginalized population. ObjectiveTo better understand research outputs in the field of epidemiological criminology, we examined the lead author’s affiliation by analyzing peer-reviewed published outputs to determine countries and organizations (eg, universities, governmental and nongovernmental organizations) responsible for peer-reviewed publications. MethodsWe used a semiautomated approach to examine the first-author affiliations of 23,904 PubMed epidemiological studies related to incarcerated and offender populations published in English between 1946 and 2021. We also mapped research outputs to the World Justice Project Rule of Law Index to better understand whether there was a relationship between research outputs and the overall standard of a country’s justice system. ResultsNordic countries (Sweden, Norway, Finland, and Denmark) had the highest research outputs proportional to their incarcerated population, followed by Australia. University-affiliated first authors comprised 73.3% of published articles, with the Karolinska Institute (Sweden) being the most published, followed by the University of New South Wales (Australia). Government-affiliated first authors were on 8.9% of published outputs, and prison-affiliated groups were on 1%. Countries with the lowest research outputs also had the lowest scores on the Rule of Law Index. ConclusionsThis study provides important information on who is publishing research in the epidemiological criminology field. This has implications for promoting research diversity, independence, funding equity, and partnerships between universities and government departments that control access to incarcerated and offending populations.

BackgroundTo better understand domestic violence, data sources from multiple sectors such as police, justice, health, and welfare are needed. Linking police data to data collections from other agencies could provide unique insights and promote an all-of-government response to domestic violence. The New South Wales Police Force attends domestic violence events and records information in the form of both structured data and a free-text narrative, with the latter shown to be a rich source of information on the mental health status of persons of interest (POIs) and victims, abuse types, and sustained injuries. ObjectiveThis study aims to examine the concordance (ie, matching) between mental illness mentions extracted from the police’s event narratives and mental health diagnoses from hospital and emergency department records. MethodsWe applied a rule-based text mining method on 416,441 domestic violence police event narratives between December 2005 and January 2016 to identify mental illness mentions for POIs and victims. Using different window periods (1, 3, 6, and 12 months) before and after a domestic violence event, we linked the extracted mental illness mentions of victims and POIs to clinical records from the Emergency Department Data Collection and the Admitted Patient Data Collection in New South Wales, Australia using a unique identifier for each individual in the same cohort. ResultsUsing a 2-year window period (ie, 12 months before and after the domestic violence event), less than 1% (3020/416,441, 0.73%) of events had a mental illness mention and also a corresponding hospital record. About 16% of domestic violence events for both POIs (382/2395, 15.95%) and victims (101/631, 16.01%) had an agreement between hospital records and police narrative mentions of mental illness. A total of 51,025/416,441 (12.25%) events for POIs and 14,802/416,441 (3.55%) events for victims had mental illness mentions in their narratives but no hospital record. Only 841 events for POIs and 919 events for victims had a documented hospital record within 48 hours of the domestic violence event. ConclusionsOur findings suggest that current surveillance systems used to report on domestic violence may be enhanced by accessing rich information (ie, mental illness) contained in police text narratives, made available for both POIs and victims through the application of text mining. Additional insights can be gained by linkage to other health and welfare data collections.

Natural environments, such as parks, woodlands and lakes, have positive impacts on health and wellbeing. Urban Green and Blue Spaces (UGBS), and the activities that take place in them, can significantly influence the health outcomes of all communities, and reduce health inequalities. Improving access and quality of UGBS needs understanding of the range of systems (e.g. planning, transport, environment, community) in which UGBS are located. UGBS offers an ideal exemplar for testing systems innovations as it reflects place-based and whole society processes, with potential to reduce non-communicable disease (NCD) risk and associated social inequalities in health. UGBS can impact multiple behavioural and environmental aetiological pathways. However, the systems which desire, design, develop, and deliver UGBS are fragmented and siloed, with ineffective mechanisms for data generation, knowledge exchange and mobilisation. Further, UGBS need to be co-designed with and by those whose health could benefit most from them, so they are appropriate, accessible, valued and used well. This paper describes a major new prevention research programme and partnership, GroundsWell, which aims to transform UGBS-related systems by improving how we plan, design, evaluate and manage UGBS so that it benefits all communities, especially those who are in poorest health. We use a broad definition of health to include physical, mental, social wellbeing and quality of life. Our objectives are to transform systems so that UGBS are planned, developed, implemented, maintained and evaluated with our communities and data systems to enhance health and reduce inequalities. GroundsWell will use interdisciplinary, problem-solving approaches to accelerate and optimise community collaborations among citizens, users, implementers, policymakers and researchers to impact research, policy, practice and active citizenship. GroundsWell will be shaped and developed in three pioneer cities (Belfast, Edinburgh, Liverpool) and their regional contexts, with embedded translational mechanisms to ensure that outputs and impact have UK-wide and international application.

It is known that SARS-CoV-2 infection can result in gastrointestinal symptoms. For some, these symptoms may persist beyond acute infection, in what is known as ‘post-COVID syndrome’. We conducted a systematic review to examine the prevalence of persistent gastrointestinal symptoms and the incidence of new gastrointestinal illnesses following acute SARS-CoV-2 infection. We searched the scientific literature using MedLine, SCOPUS, Europe PubMed Central and medRxiv from December 2019 to July 2023. Two reviewers independently identified 45 eligible articles, which followed participants for various gastrointestinal outcomes after acute SARS-CoV-2 infection. The study quality was assessed using the Joanna Briggs Institute Critical Appraisal Tools. The weighted pooled prevalence for persistent gastrointestinal symptoms of any nature and duration was 10.8% compared with 4.9% in healthy controls. For seven studies at low risk of methodological bias, the symptom prevalence ranged from 0.2% to 24.1%, with a median follow-up time of 18 weeks. We also identified a higher risk for future illnesses such as irritable bowel syndrome, dyspepsia, hepatic and biliary disease, liver disease and autoimmune-mediated illnesses such as inflammatory bowel disease and coeliac disease in historically SARS-CoV-2-exposed individuals. Our review has shown that, from a limited pool of mostly low-quality studies, previous SARS-CoV-2 exposure may be associated with ongoing gastrointestinal symptoms and the development of functional gastrointestinal illness. Furthermore, we show the need for high-quality research to better understand the SARS-CoV-2 association with gastrointestinal illness, particularly as population exposure to enteric infections returns to pre-COVID-19-restriction levels.

Summary: Background: Covid-19 test-to-release from quarantine policies affect many lives. The SMART Release pilot was the foundation of these policies and an element of the world's largest population cohort study of community-wide, SARS-CoV-2 rapid antigen testing. The objective of the study was to evaluate daily lateral flow testing (LFT) as an alternative to 10-14 days quarantine for key worker contacts of known Covid-19 (or SARS-CoV-2 infection) cases. Methods: Prospective cohort study incorporating quantitative and qualitative research methods to consider how serial LFT compares with PCR testing to detect SARS-CoV-2 infections and to understand experiences/compliance with testing and the viability of this quarantine harm-reduction strategy. Participants were residents of the Liverpool area who were key workers at participating fire, police, NHS and local government organisations in Liverpool, and who were identified as close contacts of cases between December 2020 and August 2021. Thematic qualitative analysis was used to evaluate stakeholder meetings. Findings: Compliance with the daily testing regime was good across the three main organisations in this study with 96·9%, 93·7% and 92·8% compliance for Merseyside Police, Merseyside Fire & Rescue Service and Alder Hey Children's Hospital respectively. Out of 1657 participants, 34 positive Covid-19 cases were identified and 3 undetected by the daily LFT regime. A total of 8291 workdays would have been lost to self-isolation but were prevented due to negative daily tests. Organisations reported that daily contact testing proved useful, flexible and well-tolerated initiative to sustain key worker services. Interpretation: Compliance with daily testing among key workers was high, helping sustain service continuity during periods of very high risk of staffing shortage. Services reported that the pilot was a “lifeline” and its successful delivery in Liverpool has been replicated elsewhere. Funding: This report is independent research commissioned by DHSC and part funded by DHSC and NIHR. Further funding was received from Liverpool City Council, the EPSRC and MRC.

Objectives Public involvement and engagement (PIE) is playing an increasingly important role in big data initiatives and projects. It is therefore important to gain a deeper understanding of the different approaches used. Approach This study explores PIE using ethnographically-informed qualitative case studies. The case studies include: three citizen juries, each one carried out over eight days and that asked jurors to consider different real-world health data initiatives; and a public panel set up by a regional databank that carries out data linking. Data collection is ongoing and I will be continuing to carry out close observations of activities, and conducting semi-structured 1:1 interviews with those that organise and have taken part in the activities. Results Data collection so far comprises completed observations at the citizen juries (~96 hours), ongoing observations of the public panel meetings (~15 hours), and thirty semi-structured 1:1 interviews with public contributors and other stakeholders about their experiences of the activities they were involved in. Early data analysis indicates key themes of: jurors feeling heard, but unsure whether anybody was listening; stakeholders being impressed by informed jurors, but raising concerns over contributors becoming too ‘expert’; how who is at the table and what information is presented impacts what is discussed; differences between online and in-person participation; and public involvement not being a substitute for informing the public about how their data is used. Conclusion ‘Who’ is involved, and ‘how’ PPIE activities are designed and run can facilitate or constrain discussion, enhancing or limiting public contributions. If public involvement is to achieve its aims, including increasing trustworthiness, deeper consideration of these factors by those who seek the public’s views in their data projects is recommended.

Objectives To analyse the impact on SARS-CoV-2 transmission of tier 3 restrictions introduced in October and December 2020 in England, compared with tier 2 restrictions. We further investigate whether these effects varied between small areas by deprivation.Design Synthetic control analysis.Setting We identified areas introducing tier 3 restrictions in October and December, constructed a synthetic control group of places under tier 2 restrictions and compared changes in weekly infections over a 4-week period. Using interaction analysis, we estimated whether this effect varied by deprivation and the prevalence of a new variant (B.1.1.7).Interventions In both October and December, no indoor between-household mixing was permitted in either tier 2 or 3. In October, no between-household mixing was permitted in private gardens and pubs and restaurants remained open only if they served a ‘substantial meal’ in tier 3, while in tier 2 meeting with up to six people in private gardens were allowed and all pubs and restaurants remained open. In December, in tier 3, pubs and restaurants were closed, while in tier 2, only those serving food remained open. The differences in restrictions between tier 2 and 3 on meeting outside remained the same as in October.Main outcome measure Weekly reported cases adjusted for changing case detection rates for neighbourhoods in England.Results Introducing tier 3 restrictions in October and December was associated with a 14% (95% CI 10% to 19%) and 20% (95% CI 13% to 29%) reduction in infections, respectively, compared with the rates expected with tier 2 restrictions only. The effects were similar across levels of deprivation and by the prevalence of the new variant.Conclusions Compared with tier 2 restrictions, additional restrictions in tier 3 areas in England had a moderate effect on transmission, which did not appear to increase socioeconomic inequalities in COVID-19 cases.

In Australia, domestic violence reports are mostly based on data from the police, courts, hospitals, and ad hoc surveys. However, gaps exist in reporting information such as victim injuries, mental health status and abuse types. The police record details of domestic violence events as structured information (e.g., gender, postcode, ethnicity), but also in text narratives describing other details such as injuries, substance use, and mental health status. However, the voluminous nature of the narratives has prevented their use for surveillance purposes. We used a validated text mining methodology on 492,393 police-attended domestic violence event narratives from 2005 to 2016 to extract mental health mentions on persons of interest (POIs) (individuals suspected/charged with a domestic violence offense) and victims, abuse types, and victim injuries. A significant increase was observed in events that recorded an injury type (28.3% in 2005 to 35.6% in 2016). The pattern of injury and abuse types differed between male and female victims with male victims more likely to be punched and to experience cuts and bleeding and female victims more likely to be grabbed and pushed and have bruises. The four most common mental illnesses (alcohol abuse, bipolar disorder, depression schizophrenia) were the same in male and female POIs. An increase from 5.0% in 2005 to 24.3% in 2016 was observed in the proportion of events with a reported mental illness with an increase between 2005 and 2016 in depression among female victims. These findings demonstrate that extracting information from police narratives can provide novel insights into domestic violence patterns including confounding factors (e.g., mental illness) and thus enable policy responses to address this significant public health problem.

Background: People with cystic fibrosis frequently have low levels of adherence to inhaled medications. Objectives: The objectives were to develop and evaluate an intervention for adults with cystic fibrosis to improve adherence to their inhaled medication. Design: We used agile software methods to develop an online platform. We used mixed methods to develop a behaviour change intervention for delivery by an interventionist. These were integrated to become the CFHealthHub intervention. We undertook a feasibility study consisting of a pilot randomised controlled trial and process evaluation in two cystic fibrosis centres. We evaluated the intervention using an open-label, parallel-group randomised controlled trial with usual care as the control. Participants were randomised in a 1 : 1 ratio to intervention or usual care. Usual care consisted of clinic visits every 3 months. We undertook a process evaluation alongside the randomised controlled trial, including a fidelity study, a qualitative interview study and a mediation analysis. We undertook a health economic analysis using both a within-trial and model-based analysis. Setting: The randomised controlled trial took place in 19 UK cystic fibrosis centres. Participants: Participants were people aged ≥ 16 years with cystic fibrosis, on the cystic fibrosis registry, not post lung transplant or on the active transplant list, who were able to consent and not using dry-powder inhalers. Intervention: People with cystic fibrosis used a nebuliser with electronic monitoring capabilities. This transferred data automatically to a digital platform. People with cystic fibrosis and clinicians could monitor adherence using these data, including through a mobile application (app). CFHealthHub displayed graphs of adherence data as well as educational and problem-solving information. A trained interventionist helped people with cystic fibrosis to address their adherence. Main outcome measures: Randomised controlled trial – adjusted incidence rate ratio of pulmonary exacerbations meeting the modified Fuchs criteria over a 12-month follow-up period (primary outcome); change in percentage adherence; and per cent predicted forced expiratory volume in 1 second (key secondary outcomes). Process evaluation – percentage fidelity to intervention delivery, and participant and interventionist perceptions of the intervention. Economic modelling – incremental cost per quality-adjusted life-year gained. Results: Randomised controlled trial – 608 participants were randomised to the intervention (n = 305) or usual care (n = 303). To our knowledge, this was the largest randomised controlled trial in cystic fibrosis undertaken in the UK. The adjusted rate of exacerbations per year (primary outcome) was 1.63 in the intervention and 1.77 in the usual-care arm (incidence rate ratio 0.96, 95% confidence interval 0.83 to 1.12; p = 0.638) after adjustment for covariates. The adjusted difference in mean weekly normative adherence was 9.5% (95% confidence interval 8.6% to 10.4%) across 1 year, favouring the intervention. Adjusted mean difference in forced expiratory volume in 1 second (per cent) predicted at 12 months was 1.4% (95% confidence interval –0.2% to 3.0%). No adverse events were related to the intervention. Process evaluation – fidelity of intervention delivery was high, the intervention was acceptable to people with cystic fibrosis, participants engaged with the intervention [287/305 (94%) attended the first intervention visit], expected mechanisms of action were identified and contextual factors varied between randomised controlled trial sites. Qualitative interviews with 22 people with cystic fibrosis and 26 interventionists identified that people with cystic fibrosis welcomed the objective adherence data as proof of actions to self and others, and valued the relationship that they built with the interventionists. Economic modelling – the within-trial analysis suggests that the intervention generated 0.01 additional quality-adjusted life-years at an additional cost of £865.91 per patient, leading to an incremental cost-effectiveness ratio of £71,136 per quality-adjusted life-year gained. This should be interpreted with caution owing to the short time horizon. The health economic model suggests that the intervention is expected to generate 0.17 additional quality-adjusted life-years and cost savings of £1790 over a lifetime (70-year) horizon; hence, the intervention is expected to dominate usual care. Assuming a willingness-to-pay threshold of £20,000 per quality-adjusted life-year gained, the probability that the intervention generates more net benefit than usual care is 0.89. The model results are dependent on assumptions regarding the duration over which costs and effects of the intervention apply, the impact of the intervention on forced expiratory volume in 1 second (per cent) predicted and the relationship between increased adherence and drug-prescribing levels. Limitations: Number of exacerbations is a sensitive and valid measure of clinical change used in many trials. However, data collection of this outcome in this context was challenging and could have been subject to bias. It was not possible to measure baseline adherence accurately. It was not possible to quantify the impact of the intervention on the number of packs of medicines prescribed. Conclusions: We developed a feasible and acceptable intervention that was delivered to fidelity in the randomised controlled trial. We observed no statistically significant difference in the primary outcome of exacerbation rates over 12 months. We observed an increase in normative adherence levels in a disease where adherence levels are low. The magnitude of the increase in adherence may not have been large enough to affect exacerbations. Future work: Given the non-significant difference in the primary outcome, further research is required to explore why an increase in objective normative adherence did not reduce exacerbations and to develop interventions that reduce exacerbations. Trial registration: Work package 3.1: Current Controlled Trials ISRCTN13076797. Work packages 3.2 and 3.3: Current Controlled Trials ISRCTN55504164. Funding: This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 9, No. 11. See the NIHR Journals Library website for further project information.

BackgroundTobacco control models are mathematical models predicting tobacco-related outcomes in defined populations. The policy simulation model is considered as a subcategory of tobacco control models simulating the potential outcomes of tobacco control policy options. However, we could not identify any existing tool specifically designed to assess the quality of tobacco control models. ObjectiveThe aims of this systematic methodology review are to: (1) identify best modeling practices, (2) highlight common pitfalls, and (3) develop recommendations to assess the quality of tobacco control policy simulation models. Crucially, these recommendations can empower model users to assess the quality of current and future modeling studies, potentially leading to better tobacco policy decision-making for the public. This protocol describes the planned systematic review stages, paper inclusion and exclusion criteria, data extraction, and analysis. MethodsTwo reviewers searched five databases (Embase, EconLit, PsycINFO, PubMed, and CINAHL Plus) to identify eligible studies published between July 2013 and August 2019. We included papers projecting tobacco-related outcomes with a focus on tobacco control policies in any population and setting. Eligible papers were independently screened by two reviewers. The data extraction form was designed and piloted to extract model structure, data sources, transparency, validation, and other qualities. We will use a narrative synthesis to present the results by summarizing model trends, analyzing model approaches, and reporting data input and result quality. We will propose recommendations to assess the quality of tobacco control policy simulation models using the findings from this review and related literature. ResultsData collection is in progress. Results are expected to be completed and submitted for publication by April 2021. ConclusionsThis systematic methodological review will summarize the best practices and pitfalls existing among tobacco control policy simulation models and present a recommendation list of a high-quality tobacco control simulation model. A more standardized and quality-assured tobacco control policy simulation model will benefit modelers, policymakers, and the public on both model building and decision making. Trial RegistrationPROSPERO International Prospective Register of Systematic Reviews CRD42020178146; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020178146 International Registered Report Identifier (IRRID)DERR1-10.2196/26854

Abstract Background The presence of additional chronic conditions has a significant impact on the treatment and management of type 2 diabetes (T2DM). Little is known about the patterns of comorbidities in this population. The aims of this study are to quantify comorbidity patterns in people with T2DM, to estimate the prevalence of six chronic conditions in 2027 and to identify clusters of similar conditions. Methods We used the Clinical Practice Research Datalink (CPRD) linked with the Index of Multiple Deprivation (IMD) data to identify patients diagnosed with T2DM between 2007 and 2017. 102,394 people met the study inclusion criteria. We calculated the crude and age-standardised prevalence of 18 chronic conditions present at and after the T2DM diagnosis. We analysed longitudinally the 6 most common conditions and forecasted their prevalence in 2027 using linear regression. We used agglomerative hierarchical clustering to identify comorbidity clusters. These analyses were repeated on subgroups stratified by gender and deprivation. Results More people living in the most deprived areas had ≥ 1 comorbidities present at the time of diagnosis (72% of females; 64% of males) compared to the most affluent areas (67% of females; 59% of males). Depression prevalence increased in all strata and was more common in the most deprived areas. Depression was predicted to affect 33% of females and 15% of males diagnosed with T2DM in 2027. Moderate clustering tendencies were observed, with concordant conditions grouped together and some variations between groups of different demographics. Conclusions Comorbidities are common in this population, and high between-patient variability in comorbidity patterns emphasises the need for patient-centred healthcare. Mental health is a growing concern, and there is a need for interventions that target both physical and mental health in this population.

Introduction The emergence and rapid spread of COVID-19 have caused widespread and catastrophic public health and economic impact, requiring governments to restrict societal activity to reduce the spread of the disease. The role of household transmission in the population spread of SARS-CoV-2, and of host immunity in limiting transmission, is poorly understood. This paper describes a protocol for a prospective observational study of a cohort of households in Liverpool City Region, UK, which addresses the transmission of SARS-CoV-2 between household members and how immunological response to the infection changes over time.Methods and analysis Households in the Liverpool City Region, in which members have not previously tested positive for SARS-CoV-2 with a nucleic acid amplification test, are followed up for an initial period of 12 weeks. Participants are asked to provide weekly self-throat and nasal swabs and record their activity and presence of symptoms. Incidence of infection and household secondary attack rates of COVID-19 are measured. Transmission of SARS-CoV-2 will be investigated against a range of demographic and behavioural variables. Blood and faecal samples are collected at several time points to evaluate immune responses to SARS-CoV-2 infection and prevalence and risk factors for faecal shedding of SARS-CoV-2, respectively.Ethics and dissemination The study has received approval from the National Health Service Research Ethics Committee; REC Reference: 20/HRA/2297, IRAS Number: 283 464. Results will be disseminated through scientific conferences and peer-reviewed open access publications. A report of the findings will also be shared with participants. The study will quantify the scale and determinants of household transmission of SARS-CoV-2. Additionally, immunological responses before and during the different stages of infection will be analysed, adding to the understanding of the range of immunological response by infection severity.

Objective Most current cardiovascular disease (CVD) risk stratification tools are for people without CVD, but very few are for prevalent CVD. In this study, we developed and validated a CVD severity score in people with coronary heart disease (CHD) and evaluated the association between severity and adverse outcomes.Methods Primary and secondary care data for 213 088 people with CHD in 398 practices in England between 2007 and 2017 were used. The cohort was randomly divided into training and validation datasets (80%/20%) for the severity model. Using 20 clinical severity indicators (each assigned a weight=1), baseline and longitudinal CVD severity scores were calculated as the sum of indicators. Adjusted Cox and competing-risk regression models were used to estimate risks for all-cause and cause-specific hospitalisation and mortality.Results Mean age was 64.5±12.7 years, 46% women, 16% from deprived areas, baseline severity score 1.5±1.2, with higher scores indicating a higher burden of disease. In the training dataset, 138 510 (81%) patients were hospitalised at least once, and 39 944 (23%) patients died. Each 1-unit increase in baseline severity was associated with 41% (95% CI 37% to 45%, area under the receiver operating characteristics (AUROC) curve=0.79) risk for 1 year for all-cause mortality; 59% (95% CI 52% to 67%, AUROC=0.80) for cardiovascular (CV)/diabetes mortality; 27% (95% CI 26% to 28%) for any-cause hospitalisation and 37% (95% CI 36% to 38%) for CV/diabetes hospitalisation. Findings were consistent in the validation dataset.Conclusions Higher CVD severity score is associated with higher risks for any-cause and cause-specific hospital admissions and mortality in people with CHD. Our reproducible score based on routinely collected data can help practitioners better prioritise management of people with CHD in primary care.

It has been widely observed that adult men of all ages are at higher risk of developing serious complications from COVID-19 when compared with women. This study aimed to investigate the association of COVID-19 positivity and severity with estrogen exposure in women, in a population based matched cohort study of female users of the COVID Symptom Study application in the UK. Analyses included 152,637 women for menopausal status, 295,689 women for exogenous estrogen intake in the form of the combined oral contraceptive pill (COCP), and 151,193 menopausal women for hormone replacement therapy (HRT). Data were collected using the COVID Symptom Study in May-June 2020. Analyses investigated associations between predicted or tested COVID-19 status and menopausal status, COCP use, and HRT use, adjusting for age, smoking and BMI, with follow-up age sensitivity analysis, and validation in a subset of participants from the TwinsUK cohort. Menopausal women had higher rates of predicted COVID-19 (P = 0.003). COCP-users had lower rates of predicted COVID-19 (P = 8.03E-05), with reduction in hospital attendance (P = 0.023). Menopausal women using HRT or hormonal therapies did not exhibit consistent associations, including increased rates of predicted COVID-19 (P = 2.22E-05) for HRT users alone. The findings support a protective effect of estrogen exposure on COVID-19, based on positive association between predicted COVID-19 with menopausal status, and negative association with COCP use. HRT use was positively associated with COVID-19, but the results should be considered with caution due to lack of data on HRT type, route of administration, duration of treatment, and potential unaccounted for confounders and comorbidities.

Objective To evaluate the extent to which the inter-institutional, inter-disciplinary mobilisation of data and skills in the Farr Institute contributed to establishing the emerging field of data science for health in the UK. Design and Outcome measures We evaluated evidence of six domains characterising a new field of science: • defining central scientific challenges, • demonstrating how the central challenges might be solved, • creating novel interactions among groups of scientists, • training new types of experts, • re-organising universities, • demonstrating impacts in society. We carried out citation, network and time trend analyses of publications, and a narrative review of infrastructure, methods and tools. Setting Four UK centres in London, North England, Scotland and Wales (23 university partners), 2013-2018. Results 1. The Farr Institute helped define a central scientific challenge publishing a research corpus, demonstrating insights from electronic health record (EHR) and administrative data at each stage of the translational cycle in 593 papers with at least one Farr Institute author affiliation on PubMed. 2. The Farr Institute offered some demonstrations of how these scientific challenges might be solved: it established the first four ISO27001 certified trusted research environments in the UK, and approved more than 1000 research users, published on 102 unique EHR and administrative data sources, although there was no clear evidence of an increase in novel, sustained record linkages. The Farr Institute established open platforms for the EHR phenotyping algorithms and validations (>70 diseases, CALIBER). Sample sizes showed some evidence of increase but remained less than 10% of the UK population in primary care-hospital care linked studies. 3.The Farr Institute created novel interactions among researchers: the co-author publication network expanded from 944 unique co-authors (based on 67 publications in the first 30 months) to 3839 unique co-authors (545 papers in the final 30 months). 4. Training expanded substantially with 3 new masters courses, training >400 people at masters, short-course and leadership level and 48 PhD students. 5. Universities reorganised with 4/5 Centres established 27 new faculty (tenured) positions, 3 new university institutes. 6. Emerging evidence of impacts included: > 3200 citations for the 10 most cited papers and Farr research informed eight practice-changing clinical guidelines and policies relevant to the health of millions of UK citizens. Conclusion The Farr Institute played a major role in establishing and growing the field of data science for health in the UK, with some initial evidence of benefits for health and healthcare. The Farr Institute has now expanded into Health Data Research (HDR) UK but key challenges remain including, how to network such activities internationally.

Abstract Background Patient portals are considered valuable instruments for self-management of long term conditions, however, there are concerns over how patients might interpret and act on the clinical information they access. We hypothesized that visual cues improve patients’ abilities to correctly interpret laboratory test results presented through patient portals. We also assessed, by applying eye-tracking methods, the relationship between risk interpretation and visual search behaviour. Methods We conducted a controlled study with 20 kidney transplant patients. Participants viewed three different graphical presentations in each of low, medium, and high risk clinical scenarios composed of results for 28 laboratory tests. After viewing each clinical scenario, patients were asked how they would have acted in real life if the results were their own, as a proxy of their risk interpretation. They could choose between: 1) Calling their doctor immediately (high interpreted risk); 2) Trying to arrange an appointment within the next 4 weeks (medium interpreted risk); 3) Waiting for the next appointment in 3 months (low interpreted risk). For each presentation, we assessed accuracy of patients’ risk interpretation, and employed eye tracking to assess and compare visual search behaviour. Results Misinterpretation of risk was common, with 65% of participants underestimating the need for action across all presentations at least once. Participants found it particularly difficult to interpret medium risk clinical scenarios. Participants who consistently understood when action was needed showed a higher visual search efficiency, suggesting a better strategy to cope with information overload that helped them to focus on the laboratory tests most relevant to their condition. Conclusions This study confirms patients’ difficulties in interpreting laboratories test results, with many patients underestimating the need for action, even when abnormal values were highlighted or grouped together. Our findings raise patient safety concerns and may limit the potential of patient portals to actively involve patients in their own healthcare.

Abstract Background Given the complex and progressive nature of Alzheimer’s disease (AD), a precision medicine approach for diagnosis and treatment requires the identification of patient subgroups with biomedically distinct and actionable phenotype definitions. Methods Longitudinal patient-level data for 1160 AD patients receiving placebo or no treatment with a follow-up of up to 18 months were extracted from an integrated clinical trials dataset. We used latent class mixed modelling (LCMM) to identify patient subgroups demonstrating distinct patterns of change over time in disease severity, as measured by the Alzheimer’s Disease Assessment Scale—cognitive subscale score. The optimal number of subgroups (classes) was selected by the model which had the lowest Bayesian Information Criterion. Other patient-level variables were used to define these subgroups’ distinguishing characteristics and to investigate the interactions between patient characteristics and patterns of disease progression. Results The LCMM resulted in three distinct subgroups of patients, with 10.3% in Class 1, 76.5% in Class 2 and 13.2% in Class 3. While all classes demonstrated some degree of cognitive decline, each demonstrated a different pattern of change in cognitive scores, potentially reflecting different subtypes of AD patients. Class 1 represents rapid decliners with a steep decline in cognition over time, and who tended to be younger and better educated. Class 2 represents slow decliners, while Class 3 represents severely impaired slow decliners: patients with a similar rate of decline to Class 2 but with worse baseline cognitive scores. Class 2 demonstrated a significantly higher proportion of patients with a history of statins use; Class 3 showed lower levels of blood monocytes and serum calcium, and higher blood glucose levels. Conclusions Our results, ‘learned’ from clinical data, indicate the existence of at least three subgroups of Alzheimer’s patients, each demonstrating a different trajectory of disease progression. This hypothesis-generating approach has detected distinct AD subgroups that may prove to be discrete endophenotypes linked to specific aetiologies. These findings could enable stratification within a clinical trial or study context, which may help identify new targets for intervention and guide better care.

Abstract Background Understanding the distribution and determinants of disease in animal populations must be underpinned by knowledge of animal demographics. For companion animals, these data have been difficult to collect because of the distributed nature of the companion animal veterinary industry. Here we describe key demographic features of a large veterinary-visiting pet population in Great Britain as recorded in electronic health records, and explore the association between a range of animal’s characteristics and socioeconomic factors. Results Electronic health records were captured by the Small Animal Veterinary Surveillance Network (SAVSNET), from 143 practices (329 sites) in Great Britain. Mixed logistic regression models were used to assess the association between socioeconomic factors and species and breed ownership, and preventative health care interventions. Dogs made up 64.8% of the veterinary-visiting population, with cats, rabbits and other species making up 30.3, 2.0 and 1.6% respectively. Compared to cats, dogs and rabbits were more likely to be purebred and younger. Neutering was more common in cats (77.0%) compared to dogs (57.1%) and rabbits (45.8%). The insurance and microchipping relative frequency was highest in dogs (27.9 and 53.1%, respectively). Dogs in the veterinary-visiting population belonging to owners living in least-deprived areas of Great Britain were more likely to be purebred, neutered, insured and microchipped. The same association was found for cats in England and for certain parameters in Wales and Scotland. Conclusions The differences we observed within these populations are likely to impact on the clinical diseases observed within individual veterinary practices that care for them. Based on this descriptive study, there is an indication that the population structures of companion animals co-vary with human and environmental factors such as the predicted socioeconomic level linked to the owner’s address. This ‘co-demographic’ information suggests that further studies of the relationship between human demographics and pet ownership are warranted.

Abstract Background Clinical prediction models (CPMs) are increasingly deployed to support healthcare decisions but they are derived inconsistently, in part due to limited data. An emerging alternative is to aggregate existing CPMs developed for similar settings and outcomes. This simulation study aimed to investigate the impact of between-population-heterogeneity and sample size on aggregating existing CPMs in a defined population, compared with developing a model de novo. Methods Simulations were designed to mimic a scenario in which multiple CPMs for a binary outcome had been derived in distinct, heterogeneous populations, with potentially different predictors available in each. We then generated a new ‘local’ population and compared the performance of CPMs developed for this population by aggregation, using stacked regression, principal component analysis or partial least squares, with redevelopment from scratch using backwards selection and penalised regression. Results While redevelopment approaches resulted in models that were miscalibrated for local datasets of less than 500 observations, model aggregation methods were well calibrated across all simulation scenarios. When the size of local data was less than 1000 observations and between-population-heterogeneity was small, aggregating existing CPMs gave better discrimination and had the lowest mean square error in the predicted risks compared with deriving a new model. Conversely, given greater than 1000 observations and significant between-population-heterogeneity, then redevelopment outperformed the aggregation approaches. In all other scenarios, both aggregation and de novo derivation resulted in similar predictive performance. Conclusion This study demonstrates a pragmatic approach to contextualising CPMs to defined populations. When aiming to develop models in defined populations, modellers should consider existing CPMs, with aggregation approaches being a suitable modelling strategy particularly with sparse data on the local population.

Abstract Background Multiple imputation is frequently used to deal with missing data in healthcare research. Although it is known that the outcome should be included in the imputation model when imputing missing covariate values, it is not known whether it should be imputed. Similarly no clear recommendations exist on: the utility of incorporating a secondary outcome, if available, in the imputation model; the level of protection offered when data are missing not-at-random; the implications of the dataset size and missingness levels. Methods We used realistic assumptions to generate thousands of datasets across a broad spectrum of contexts: three mechanisms of missingness (completely at random; at random; not at random); varying extents of missingness (20–80% missing data); and different sample sizes (1,000 or 10,000 cases). For each context we quantified the performance of a complete case analysis and seven multiple imputation methods which deleted cases with missing outcome before imputation, after imputation or not at all; included or did not include the outcome in the imputation models; and included or did not include a secondary outcome in the imputation models. Methods were compared on mean absolute error, bias, coverage and power over 1,000 datasets for each scenario. Results Overall, there was very little to separate multiple imputation methods which included the outcome in the imputation model. Even when missingness was quite extensive, all multiple imputation approaches performed well. Incorporating a secondary outcome, moderately correlated with the outcome of interest, made very little difference. The dataset size and the extent of missingness affected performance, as expected. Multiple imputation methods protected less well against missingness not at random, but did offer some protection. Conclusions As long as the outcome is included in the imputation model, there are very small performance differences between the possible multiple imputation approaches: no outcome imputation, imputation or imputation and deletion. All informative covariates, even with very high levels of missingness, should be included in the multiple imputation model. Multiple imputation offers some protection against a simple missing not at random mechanism.

Children's body mass index (BMI) growth trajectories are associated with adult health outcomes, and vary by geography and epoch. Understanding these trajectories could help to identify high risk children and thus support improved health outcomes. In this review, we compare and quantitatively analyse BMI level and trajectory data published since 2010. We characterise recent growth in children aged 4–11 years, an age range most frequently targeted for BMI intervention, yet less studied than young childhood or infancy.Through searches in OVID, we identified 54 relevant texts which describe either post-2000 summary BMI values by age and gender in cohorts with sample sizes of over 1000 children, or the results of latent class analyses of BMI trajectories within the 4–11 year age range. Population level median growth curves were projected and visualised as weighted means. These BMI curves, based on data from 729,692 children, can be visually clustered into ‘high’ and ‘low’ charting groups with extreme outlying values. Within populations, latent class analyses converge on 3–4 individual child trajectories, two of which predispose adult overweight. These growth pathways diverge early in childhood, yet are not effectively distinguished via isolated BMI measurements taken between 4 and 11 years, meaning some high risk children may currently be poorly identified. Keywords: Body mass index, Pediatric obesity, Child development, Obesity

Summary: Background: Since the mid-1990s, excess mortality has increased markedly for adults aged 25–44 years in the north compared with the south of England. We examined the underlying causes of this excess mortality and the contribution of socioeconomic deprivation. Methods: Mortality data from the Office of National Statistics for adults aged 25–44 years were aggregated and compared between England's five most northern versus five most southern government office regions between Jan 1, 1981, and Dec 31, 2016. Poisson regression models, adjusted for age and sex, were used to quantify excess mortality in the north compared with the south by underlying cause of death (accidents, alcohol related, cardiovascular disease and diabetes, drug related, suicide, cancer, and other causes). The role of socioeconomic deprivation, as measured by the 2015 Index of Multiple Deprivation, in explaining the excess and regional variability was also explored. Findings: A mortality divide between the north and south appeared in the mid-1990s and rapidly expanded thereafter for deaths attributed to accidents, alcohol misuse, and drug misuse. In the 2014–16 period, the northern excess was incidence rate ratio (IRR) 1·47 (95% CI 1·39–1·54) for cardiovascular reasons, 2·09 (1·94–2·25) for alcohol misuse, and 1·60 (1·51–1·70) for drug misuse, across both men and women aged 25–44 years. National mortality rates for cardiovascular deaths declined over the study period but a longstanding gap between north and south persisted (from 33·3 [95% CI 31·8–34·8] in 1981 to 15·0 [14·0–15·9] in 2016 in the north vs from 23·5 [22·3–24·8] to 9·9 [9·2–10·5] in the south). Between 2014 and 2016, estimated excess numbers of death in the north versus the south for those aged 25–44 years were 1881 (95% CI 726–2627) for women and 3530 (2216–4511) for men. Socioeconomic deprivation explained up to two-thirds of the excess mortality in the north (IRR for northern effect reduced from 1·15 [95% CI 1·14–1·15; unadjusted] to 1·05 [1·04–1·05; adjusted for Index of Multiple Deprivation]). By 2016, in addition to the persistent north–south gap, mortality rates in London were lower than in all other regions, with IRRs ranging from IRR 1·13 (95% CI 1·12–1·15) for the East England to 1·22 (1·20–1·24) for the North East, even after adjusting for deprivation. Interpretation: Sharp relative rises in deaths from cardiovascular reasons, alcohol misuse and drug misuse in the north compared with the south seem to have created new health divisions between England's regions. This gap might be due to exacerbation of existing social and health inequalities that have been experienced for many years. These divisions might suggest increasing psychological distress, despair, and risk taking among young and middle-aged adults, particularly outside of London. Funding: Medical Research Council and Wellcome Trust.

The original article [1] contains an omitted grant acknowledgement and affiliation as relates to the contribution of co-author, Rafael Perera-Salazar. As such, the following two amendments should apply to the original article:

Background: The Salford Integrated Care Programme (SICP) was a large-scale transformation project to improve care for older people with long-term conditions and social care needs. We report an evaluation of the ability of the SICP to deliver an enhanced experience of care, improved quality of life, reduced costs of care and improved cost-effectiveness. Objectives: To explore the process of implementation of the SICP and the impact on patient outcomes and costs. Design: Qualitative methods (interviews and observations) to explore implementation, a cohort multiple randomised controlled trial to assess patient outcomes through quasi-experiments and a formal trial, and an analysis of routine data sets and appropriate comparators using non-randomised methodologies. Setting: Salford in the north-west of England. Participants: Older people aged ≥ 65 years, carers, and health and social care professionals. Interventions: A large-scale integrated care project with three core mechanisms of integration (community assets, multidisciplinary groups and an ‘integrated contact centre’). Main outcome measures: Patient self-management, care experience and quality of life, and health-care utilisation and costs. Data sources: Professional and patient interviews, patient self-report measures, and routine quantitative data on service utilisation. Results: The SICP and subsequent developments have been sustained by strong partnerships between organisations. The SICP achieved ‘functional integration’ through the pooling of health and social care budgets, the development of the Alliance Agreement between four organisations and the development of the shared care record. ‘Service-level’ integration was slow and engagement with general practice was a challenge. We saw only minor changes in patient experience measures over the period of the evaluation (both improvements and reductions), with some increase in the use of community assets and care plans. Compared with other sites, the difference in the rates of admissions showed an increase in emergency admissions. Patient experience of health coaching was largely positive, although the effects of health coaching on activation and depression were not statistically significant. Economic analyses suggested that coaching was likely to be cost-effective, generating improvements in quality of life [mean incremental quality-adjusted life-year gain of 0.019, 95% confidence interval (CI) –0.006 to 0.043] at increased cost (mean incremental total cost increase of £150.58, 95% CI –£470.611 to £711.776). Limitations: The Comprehensive Longitudinal Assessment of Salford Integrated Care study represents a single site evaluation, with consequent limits on external validity. Patient response rates to the cohort survey were

BackgroundTranscatheter aortic valve implantation (TAVI) is indicated for patients with aortic stenosis who are intermediate‐high surgical risk. Although all‐cause mortality rates after TAVI are established, survival attributable to the procedure is unclear because of competing causes of mortality. The aim was to report relative survival (RS) after TAVI, which accounts for background mortality risks in a matched general population. Methods and ResultsNational cohort data (n=6420) from the 2007 to 2014 UK TAVI registry were matched by age, sex, and year to mortality rates for England and Wales (population, 57.9 million). The Ederer II method related observed patient survival to that expected from the matched general population. We modelled RS using a flexible parametric approach that modelled the log cumulative hazard using restricted cubic splines. RS of the TAVI cohort was 95.4%, 90.2%, and 83.8% at 30 days, 1 year, and 3 years, respectively. By 1‐year follow‐up, mortality hazards in the >85 years age group were not significantly different from those of the matched general population; by 3 years, survival rates were comparable. The flexible parametric RS model indicated that increasing age was associated with significantly lower excess hazards after the procedure; for example, by 2 years, a 5‐year increase in age was associated with 20% lower excess mortality over the general population. ConclusionsRS after TAVI was high, and survival rates in those aged >85 years approximated those of a matched general population within 3 years. High rates of RS indicate that patients selected for TAVI tolerate the risks of the procedure well.

BackgroundAortic valve predilation with balloon aortic valvuloplasty (BAV) is recommended before transcatheter aortic valve implantation (TAVI), despite limited data around the requirement of this preprocedural step and the potential risks of embolization. This study aimed to investigate the trends in practice and associations of BAV on short‐term outcomes in the UK TAVI registry. Methods and ResultsEleven clinical endpoints were investigated, including 30‐day mortality, myocardial infarction, aortic regurgitation, valve dysfunction, and composite early safety. All endpoints were defined as per the VARC‐2 definitions. Odd ratios of each endpoint were estimated using logistic regression, with data analyzed in balloon‐ and self‐expandable valve subgroups. Propensity scores were calculated using patient demographics and procedural variables, which were included in the models of each endpoint to adjust for measured confounding. Between 2007 and 2014, 5887 patients met the study inclusion criteria, 1421 (24.1%) of whom had no BAV before TAVI valve deployment. We observed heterogeneity in the use of BAV nationally, both temporally and by center experience; rates of BAV in pre‐TAVI workup varied between 30% and 97% across TAVI centers. All endpoints were similar between treatment groups in SAPIEN (Edwards Lifesciences Inc., Irvine, CA) valve patients. After correction for multiple testing, none of the endpoints in CoreValve (Medtronic, Minneapolis, MN) patients were significantly different between patients with or without predilation. ConclusionsPerforming TAVI without predilation was not associated with adverse short‐term outcomes post procedure, especially when using a balloon‐expandable prosthesis. Randomized trials including different valve types are required to provide conclusive evidence regarding the utility of predilation before‐TAVI.

BackgroundWe aim to determine the prevalence of anemia in acute coronary syndrome (ACS) patients and compare their clinical characteristics, management, and clinical outcomes to those without anemia in an unselected national ACS cohort. Methods and ResultsThe Myocardial Ischemia National Audit Project (MINAP) registry collects data on all adults admitted to hospital trusts in England and Wales with diagnosis of an ACS. We conducted a retrospective cohort study by analyzing patients in this registry between January 2006 and December 2010 and followed them up until August 2011. Multiple logistic regressions were used to determine factors associated with anemia and the adjusted odds of 30‐day mortality with 1 g/dL incremental hemoglobin increase and the 30‐day and 1‐year mortality for anemic compared to nonanemic groups. Analyses were adjusted for covariates. Our analysis of 422 855 patients with ACS showed that 27.7% of patients presenting with ACS are anemic and that these patients are older, have a greater prevalence of renal disease, peripheral vascular disease, diabetes mellitus, and previous acute myocardial infarction, and are less likely to receive evidence‐based therapies shown to improve clinical outcomes. Finally, our analysis suggests that anemia is independently associated with 30‐day (OR 1.28, 95% CI 1.22‐1.35) and 1‐year mortality (OR 1.31, 95% CI 1.27‐1.35), and we observed a reverse J‐shaped relationship between hemoglobin levels and mortality outcomes. ConclusionsThe prevalence of anemia in a contemporary national ACS cohort is clinically significant. Patients with anemia are older and multimorbid and less likely to receive evidence‐based therapies shown to improve clinical outcomes, with the presence of anemia independently associated with mortality outcomes.

Background: Abdominal aortic aneurysm (AAA) repair aims to prevent premature death from AAA rupture. Elective repair is currently recommended when AAA diameter reaches 5.5 cm (men) and 5.0 cm (women). Applying population-based indications may not be appropriate for individual patient decisions, as the optimal indication is likely to differ between patients based on age and comorbidities. Objective: To develop an Aneurysm Repair Decision Aid (ARDA) to indicate when elective AAA repair optimises survival for individual patients and to assess the cost-effectiveness and associated uncertainty of elective repair at the aneurysm diameter recommended by the ARDA compared with current practice. Data sources: The UK Vascular Governance North West and National Vascular Database provided individual patient data to develop predictive models for perioperative mortality and survival. Data from published literature were used to model AAA growth and risk of rupture. The cost-effectiveness analysis used data from published literature and from local and national databases. Methods: A combination of systematic review methods and clinical registries were used to provide data to populate models and inform the structure of the ARDA. Discrete event simulation (DES) was used to model the patient journey from diagnosis to death and synthesised data were used to estimate patient outcomes and costs for elective repair at alternative aneurysm diameters. Eight patient clinical scenarios (vignettes) were used as exemplars. The DES structure was validated by clinical and statistical experts. The economic evaluation estimated costs, quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs) from the NHS, social care provider and patient perspective over a lifetime horizon. Cost-effectiveness acceptability analyses and probabilistic sensitivity analyses explored uncertainty in the data and the value for money of ARDA-based decisions. The ARDA outcome measures include perioperative mortality risk, annual risk of rupture, 1-, 5- and 10-year survival, postoperative long-term survival, median life expectancy and predicted time to current threshold for aneurysm repair. The primary economic measure was the ICER using the QALY as the measure of health benefit. Results: The analysis demonstrated it is feasible to build and run a complex clinical decision aid using DES. The model results support current guidelines for most vignettes but suggest that earlier repair may be effective in younger, fitter patients and ongoing surveillance may be effective in elderly patients with comorbidities. The model adds information to support decisions for patients with aneurysms outside current indications. The economic evaluation suggests that using the ARDA compared with current guidelines could be cost-effective but there is a high level of uncertainty. Limitations: Lack of high-quality long-term data to populate all sections of the model meant that there is high uncertainty about the long-term clinical and economic consequences of repair. Modelling assumptions were necessary and the developed survival models require external validation. Conclusions: The ARDA provides detailed information on the potential consequences of AAA repair or a decision not to repair that may be helpful to vascular surgeons and their patients in reaching informed decisions. Further research is required to reduce uncertainty about key data, including reintervention following AAA repair, and assess the acceptability and feasibility of the ARDA for use in routine clinical practice. Funding: The National Institute for Health Research Health Technology Assessment programme.

BACKGROUND:Serum total cholesterol is one of the major targets for cardiovascular disease prevention. Statins are effective for cholesterol control in individual patients. At the population level, however, their contribution to total cholesterol decline remains unclear. The aim of this study was to quantify the contribution of statins to the observed fall in population mean cholesterol levels in England over the past two decades, and explore any differences between socioeconomic groups. METHODS AND FINDINGS:This is a modelling study based on data from the Health Survey for England. We analysed changes in observed mean total cholesterol levels in the adult England population between 1991-92 (baseline) and 2011-12. We then compared the observed changes with a counterfactual 'no statins' scenario, where the impact of statins on population total cholesterol was estimated and removed. We estimated uncertainty intervals (UI) using Monte Carlo simulation, where confidence intervals (CI) were impractical. In 2011-12, 13.2% (95% CI: 12.5-14.0%) of the English adult population used statins at least once per week, compared with 1991-92 when the proportion was just 0.5% (95% CI: 0.3-1.0%). Between 1991-92 and 2011-12, mean total cholesterol declined from 5.86 mmol/L (95% CI: 5.82-5.90) to 5.17 mmol/L (95% CI: 5.14-5.20). For 2011-12, mean total cholesterol was lower in more deprived groups. In our 'no statins' scenario we predicted a mean total cholesterol of 5.36 mmol/L (95% CI: 5.33-5.40) for 2011-12. Statins were responsible for approximately 33.7% (95% UI: 28.9-38.8%) of the total cholesterol reduction since 1991-92. The statin contribution to cholesterol reduction was greater among the more deprived groups of women, while showing little socio-economic gradient among men. CONCLUSIONS:Our model suggests that statins explained around a third of the substantial falls in total cholesterol observed in England since 1991. Approximately two thirds of the cholesterol decrease can reasonably be attributed non-pharmacological determinants.

The term "atopic march" has been used to imply a natural progression of a cascade of symptoms from eczema to asthma and rhinitis through childhood. We hypothesize that this expression does not adequately describe the natural history of eczema, wheeze, and rhinitis during childhood. We propose that this paradigm arose from cross-sectional analyses of longitudinal studies, and may reflect a population pattern that may not predominate at the individual level.Data from 9,801 children in two population-based birth cohorts were used to determine individual profiles of eczema, wheeze, and rhinitis and whether the manifestations of these symptoms followed an atopic march pattern. Children were assessed at ages 1, 3, 5, 8, and 11 y. We used Bayesian machine learning methods to identify distinct latent classes based on individual profiles of eczema, wheeze, and rhinitis. This approach allowed us to identify groups of children with similar patterns of eczema, wheeze, and rhinitis over time. Using a latent disease profile model, the data were best described by eight latent classes: no disease (51.3%), atopic march (3.1%), persistent eczema and wheeze (2.7%), persistent eczema with later-onset rhinitis (4.7%), persistent wheeze with later-onset rhinitis (5.7%), transient wheeze (7.7%), eczema only (15.3%), and rhinitis only (9.6%). When latent variable modelling was carried out separately for the two cohorts, similar results were obtained. Highly concordant patterns of sensitisation were associated with different profiles of eczema, rhinitis, and wheeze. The main limitation of this study was the difference in wording of the questions used to ascertain the presence of eczema, wheeze, and rhinitis in the two cohorts.The developmental profiles of eczema, wheeze, and rhinitis are heterogeneous; only a small proportion of children (∼ 7% of those with symptoms) follow trajectory profiles resembling the atopic march. Please see later in the article for the Editors' Summary.

Adherence to highly active antiretroviral therapy (HAART) medication is the greatest patient-enabled predictor of treatment success and mortality for those who have access to drugs. We systematically reviewed the literature to determine patient-reported barriers and facilitators to adhering to antiretroviral therapy.We examined both developed and developing nations. We searched the following databases: AMED (inception to June 2005), Campbell Collaboration (inception to June 2005), CinAhl (inception to June 2005), Cochrane Library (inception to June 2005), Embase (inception to June 2005), ERIC (inception to June 2005), MedLine (inception to June 2005), and NHS EED (inception to June 2005). We retrieved studies conducted in both developed and developing nation settings that examined barriers and facilitators addressing adherence. Both qualitative and quantitative studies were included. We independently, in duplicate, extracted data reported in qualitative studies addressing adherence. We then examined all quantitative studies addressing barriers and facilitators noted from the qualitative studies. In order to place the findings of the qualitative studies in a generalizable context, we meta-analyzed the surveys to determine a best estimate of the overall prevalence of issues. We included 37 qualitative studies and 47 studies using a quantitative methodology (surveys). Seventy-two studies (35 qualitative) were conducted in developed nations, while the remaining 12 (two qualitative) were conducted in developing nations. Important barriers reported in both economic settings included fear of disclosure, concomitant substance abuse, forgetfulness, suspicions of treatment, regimens that are too complicated, number of pills required, decreased quality of life, work and family responsibilities, falling asleep, and access to medication. Important facilitators reported by patients in developed nation settings included having a sense of self-worth, seeing positive effects of antiretrovirals, accepting their seropositivity, understanding the need for strict adherence, making use of reminder tools, and having a simple regimen. Among 37 separate meta-analyses examining the generalizability of these findings, we found large heterogeneity.We found that important barriers to adherence are consistent across multiple settings and countries. Research is urgently needed to determine patient-important factors for adherence in developing world settings. Clinicians should use this information to engage in open discussion with patients to promote adherence and identify barriers and facilitators within their own populations.