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Abstract Vaccines against COVID-19 and influenza can reduce the adverse outcomes caused by infections during pregnancy, but vaccine uptake among pregnant women has been suboptimal. We examined the COVID-19 and influenza vaccine uptake and disparities in pregnant women during the COVID-19 pandemic to inform vaccination interventions. We used data from the Oxford-Royal College of General Practitioners Research and Surveillance Centre database in England and the Secure Anonymised Information Linkage Databank in Wales. The uptake of at least one dose of vaccine was 40.2% for COVID-19 and 41.8% for influenza among eligible pregnant women. We observed disparities in COVID-19 and influenza vaccine uptake, with socioeconomically deprived and ethnic minority groups showing lower vaccination rates. The suboptimal uptake of COVID-19 and influenza vaccines, especially in those from socioeconomically deprived backgrounds and Black, mixed or other ethnic groups, underscores the necessity for interventions to reduce vaccine hesitancy and enhance acceptance in pregnant women.

Abstract Every year, there are ~100,000 hospital admissions for asthma in the UK, many of which are potentially preventable. Evidence suggests that carefully conceptualised and implemented audit and feedback (A&F) cycles have the potential to improve clinical outcomes for those with chronic conditions. We wanted to investigate the technical feasibility of developing a near-real time asthma dashboard to support A&F interventions for asthma management in primary care. We extracted cross-sectional data on asthma from 756 participating GP practices in the Oxford-Royal College of General Practitioners Research and Surveillance Centre (RCGP RSC) database in England comprising 7.6 million registered people. Summary indicators for a GP practice were compared to all participating RCGP RSC practices using practice-level data, for the week 6–12th-Mar-2023. A weekly, automated asthma dashboard with features that can support electronic-A&F cycles that compared key asthma indicators for a GP practice to RCGP RSC could be created ( https://tinyurl.com/3ydtrt85 ): 12-weeks-incidence 0.4% vs 0.4%, annual prevalence 6.1% vs 6.7%, inhaled relievers to preventer 1.2 vs 1.1, self-management plan given 83.4% vs 60.8%, annual reviews 36.8% vs 57.3%, prednisolone prescriptions 2.0% vs 3.2%, influenza vaccination 56.6% vs 55.5%, pneumococcal vaccination ever (aged ≥65 years) 90.2% vs 84.1% and current smokers 14.9% vs 14.8%. Across the RCGP RSC, the rate of hospitalisations was 0.024%; comparative data had to be suppressed for the study practice because of small numbers. We have successfully created an automated near real-time asthma dashboard that can be used to support A&F initiatives to improve asthma care and outcomes in primary care.

Summary: Background: Symptom fluctuations within and between individuals with long COVID are widely reported, but the extent to which severity varies following different types of activity and levels of exertion, and the timing of symptoms and recovery, have not previously been quantified. We aimed to characterise timing, severity, and nature of symptom fluctuations in response to effortful physical, social and cognitive activities, using Ecological Momentary Assessments. Methods: We recorded activity, effort, and severity of 8 core symptoms every 3 h for up to 24 days, in cohorts from both clinic and community settings. Symptom severities were jointly modelled using autoregressive and moving average processes. Findings: Consent was received from 376 participants providing ≥1 week's measurements (273 clinic-based, 103 community-based). Severity of all symptoms was elevated 30 min after all categories of activity. Increased effort was associated with increased symptom severity. Fatigue severity scores increased by 1.8/10 (95% CI: 1.6–1.9) following the highest physical exertions and by 1.5 (1.4–1.7) following cognitive efforts. There was evidence of only mild delayed fatigue 3 h (0.3, 0.2–0.5) or one day later (0.2, 0.0– 0.5). Fatigue severity increased as the day progressed (1.4, 1.0–1.7), and cognitive dysfunction was 0.2 lower at weekends (0.1–0.3). Interpretation: Cognitive, social, self-care and physical activities all triggered increased severity across every symptom, consistent with associated common pathways as potential therapeutic targets. Clear patterns of symptom fluctuations emerged that support more targeted self-management. Funding: National Institute for Health and Care Research.

Background As populations age, frailty and the associated demand for health care increase. Evidence needed to inform planning and commissioning of services for older people living with frailty is scarce. Accurate information on incidence and prevalence of different levels of frailty and the consequences for health outcomes, service use and costs at population level is needed. Objectives To explore the incidence, prevalence, progression and impact of frailty within an ageing general practice population and model the dynamics of frailty-related healthcare demand, outcomes and costs, to inform the development of guidelines and tools to facilitate commissioning and service development. Study design and methods A retrospective observational study with statistical modelling to inform simulation (system dynamics) modelling using routine data from primary and secondary health care in England and Wales. Modelling was informed by stakeholder engagement events conducted in Hampshire, England. Data sources included the Royal College of General Practitioners Research and Surveillance Centre databank, and the Secure Anonymised Information Linkage Databank. Population prevalence, incidence and progression of frailty within an ageing cohort were estimated using the electronic Frailty Index tool, and associated service use and costs were calculated. Association of frailty with outcomes, service use and costs was explored with multistate and generalised linear models. Results informed development of a prototype system dynamics simulation model, exploring population impact of frailty and future scenarios over a 10-year time frame. Simulation model population projections were externally validated against retrospective data from Secure Anonymised Information Linkage. Study population The Royal College of General Practitioners Research and Surveillance Centre sample comprised an open cohort of the primary care population aged 50 + between 2006 and 2017 (approx. 2.1 million people). Data were linked to Hospital Episode Statistics data and Office for National Statistics death data. A comparable validation data set from Secure Anonymised Information Linkage was generated. Baseline measures Electronic Frailty Index score calculated annually and stratified into Fit, Mild, Moderate and Severe frailty categories. Other variables included age, sex, Index of Multiple Deprivation score, ethnicity and Urban/rural. Outcomes Frailty transitions, mortality, hospitalisations, emergency department attendances, general practitioner visits and costs. Findings Frailty is already present in people aged 50–64. Frailty incidence was 47 cases per 1000 person-years. Frailty prevalence increased from 26.5% (2006) to 38.9% (2017). Older age, higher deprivation, female sex, Asian ethnicity and urban location independently predict frailty onset and progression; 4.8% of ‘fit’ people aged 50–64 years experienced a transition to a higher frailty state in a year, compared to 21.4% aged 75–84. Individual healthcare use rises with frailty severity, but Mild and Moderate frailty groups have higher overall costs due to larger population numbers. Simulation projections indicate frailty will increase by 7.1%, from 41.5% to 48.7% between 2017 and 2027, and associated costs will rise by £5.8 billion (in England) over an 11-year period. Conclusions Simulation modelling indicates that frailty prevalence and associated service use and costs will continue to rise in the future. Scenario analysis indicates reduction of incidence and slowing of progression, particularly before the age of 65, has potential to substantially reduce future service use and costs, but reducing unplanned admissions in frail older people has a more modest impact. Study outputs will be collated into a commissioning toolkit, comprising guidance on drivers of frailty-related demand and simulation model outputs. Study registration This study is registered as NCT04139278 www.clinicaltrials.gov. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 16/116/43) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 44. See the NIHR Funding and Awards website for further award information. Plain language summary Why was this research needed? More people are living longer with long-term medical conditions or disabilities. They are more likely to be admitted to hospital and need health care. People with these vulnerabilities are living with ‘frailty’, which can be mild, moderate or severe. Our research is aimed to produce information on how common frailty is, how it changes over time, what can influence it getting worse, and how it will impact our future population. What did we do? We analysed two large data sets from England and Wales (2006–17) to find out the numbers of people aged 50 + living with frailty, their characteristics (e.g. age, sex, living in deprived areas) and how these influenced frailty occurring and worsening. We explored how often they used general practitioner/hospital services and how much that cost. This information was used in a computer model to predict what would happen in the future. What did we find? The proportion of people with frailty increased from 26.5% in 2006 to 38.9% in 2017, including large increases in people with mild and moderate frailty. Older age, female sex, Asian ethnicity, and living in more deprived or urban areas, all increased the risk of someone becoming frail, and of their frailty worsening. The large numbers of people with mild and moderate frailty led to the highest costs overall. The computer model predicted that the proportion of people with frailty will increase by another 7.1% between 2017 (41.5%) and 2027 (48.7%), and associated costs will rise by £5.8 billion over an 11-year period. What does this mean? We have estimated how the number of people with frailty and their use of services will continue to rise in the future. Taking action to reduce people’s risk of becoming frail, particularly before age 65, and slowing frailty progression can reduce the need for services. We will report this information to people who plan health care so they can provide more effective care for people with frailty. Scientific summary Background As the population ages, prevalence of frailty and associated demand for health care in both primary and secondary care settings will rise. Identification and clinical management of frailty are a priority, but capacity and resources for delivery remain limited. There is an evidence gap in relation to the planning, commissioning and delivery of services for older people living with frailty and questions remain about the incidence and prevalence of different levels of frailty and the consequences for health outcomes, service use and costs. Objectives The overarching aim of this study was to explore the incidence, prevalence, progression and impact of frailty within the ageing population. The specific study objectives were to: identify incidence and prevalence of frailty states in an ageing population; identify frailty trajectories and transitions in severity in the older population over time; explore drivers of progression of frailty, including clinical, socio-economic and demographic factors; examine the impact of frailty on service use, costs and pathways of care; explore the relationship between frailty status, socioeconomic factors, practice factors and service use and outcomes (mortality, unplanned admissions, residential care use); and predict trends in frailty, modelling of health and care demand and costs over time and in different service contexts. The final aim of these analyses was to inform the development of guidelines and tools to facilitate commissioning and service development, thus providing an evidence-based approach to planning primary and secondary care services for patients aged 50 and over with different levels of frailty. Study design and methods This study used a retrospective observational study design with statistical modelling to inform simulation (system dynamics) modelling using routine healthcare data from primary and secondary care. Retrospective data were used to determine population prevalence, incidence and progression of frailty within an ageing cohort using the electronic Frailty Index (eFI) tool and data from the English Royal College of General Practitioners Research and Surveillance Centre (RCGP RSC) databank, with additional data from the Welsh Secure Anonymised Information Linkage (SAIL) Databank. Associated service use and costs were determined from linked routine data. Statistical analysis of the RCGP RSC data involved both descriptive summaries as well as multistate modelling to identify key socioeconomic variables (e.g. age, gender, deprivation, ethnicity) that are independently associated with frailty. A cost analysis of both primary and secondary care data was also conducted using generalised linear models to identify factors associated with costs and provide estimates of adjusted mean costs, by frailty and age categories. Five stakeholder engagement group (SEG) sessions were held at appropriate times throughout the study period to seek input from a broad range of health and care professionals and commissioners, members of the general public, patients and carers. These sessions focused on different aspects of the research as the project evolved, starting with the type of services available for people living with frailty and who would use them, to gaining feedback on ongoing analyses and ways of presenting the results, to informing and appraising the developing simulation model and suggesting scenarios that could be applied. Information from the statistical modelling as well as that gathered during patient and professional stakeholder events was used to inform the development of a system dynamics simulation model which could be used to examine the incidence, and progression of frailty in the 50 and over population. An initial model was developed and validated with the RCGP RSC data before further external validation against a comparable large data set from SAIL. The simulation was further adapted to use Office for National Statistics (ONS) population estimates for England, thus allowing exploration of future population trends in frailty prevalence and health service impact over a 10-year period following 2017. As one of the benefits of simulation modelling is to consider ‘what-if’ scenarios, the baseline simulation model was used to explore future trends in frailty prevalence and the associated primary and secondary care demand if present trends continue. Further ‘what-if’ scenarios exploring the impact of reduced frailty incidence, slowed frailty progression and reduced unplanned hospitalisation were carried out. Study population The primary data source for the study was the RCGP RSC, providing primary care data from England. The sample comprised an open cohort of the primary care population aged 50 and over (approx. 1.1 million people) during the year 2006, rising to 1,491,954 in 2017, with a total of 2.1 million people included overall and 15.5 million person-years of data. The data were linked to Hospital Episode Statistics (HES) secondary care data and ONS death registry data. A comparable data set from Wales, provided by SAIL, was used for external validation of the simulation model and included approximately 1.3 million people and 11 million person-years of data. Baseline measures The eFI score was calculated for all adults aged 50 +, with scores recalculated at 12-month intervals for the study period. The population was stratified into Fit, Mild, Moderate and Severe frailty groups according to their eFI score [Fit: (0–0.12); Mild: (0.13–0.24); Moderate: (0.25–0.36); Severe: (> 0.36)]. Other variables included age, sex, Index of Multiple Deprivation (IMD) score, ethnicity, long-term condition diagnoses, urban/rural indicators, practice size. Outcomes Frailty transitions, mortality, primary care [general practice surgery and home visits, telephone and electronic consultations, and individual medicines], secondary care [ambulance calls, emergency department (ED) attendances, critical care admissions, hospitalisations (unplanned and elective) and outpatient appointments] and care home residence. Costs were estimated for primary and secondary care and total care service use for the different frailty categories over 12 years. The influence of frailty on outcomes, service use and costs was explored using the RCGP RSC databank and via multistate and generalised linear models. These analyses along with information gathered during stakeholder events were used to inform the development of a prototype system dynamics simulation model (implemented in AnyLogic software) to explore the development and impact of frailty in the population and likely future scenarios over a 10-year time frame. The simulation model population projections were externally validated against retrospective data from the SAIL data set. The prototype simulation model was further adapted to use ONS population estimates for England, thus enabling population level projections of frailty in those aged 50 and over for a 10-year period following 2017. Baseline (‘no service changes’) projections of both the prevalence of frailty in the population and the associated primary, secondary and residential care use were examined over the period 2017–27. ‘What-if’ scenarios exploring the impact of reduced frailty incidence, slowed frailty progression and reduced unplanned hospitalisations were carried out. Findings Frailty is already present in those aged 50–64, with approximately 10% of this age group having mild, moderate or severe frailty at baseline. The overall incidence of frailty in people aged 50 + was 47 cases per 1000 person-years at risk (PYAR). Mortality increased with age and frailty severity. The overall prevalence of frailty increased from 26.5% to 38.9% over the 12-year study period, with the greatest change in prevalence in the mild and moderate frailty categories. At least one transition between frailty categories was observed in 32.7% (n = 709,377) of the cohort over a median follow-up of 7 years. The average age of transition from fit to mild was 69 years, fit/mild to moderate was 77 years and any category to severe was 81 years. In order of impact, older age, higher deprivation, female sex, Asian ethnicity and urban location are independent predictors of frailty onset and progression. For example, 4.8% of people aged 50–64 in the Fit category will experience a transition to a higher frailty state in a 12-month period, as compared to 21.4% in people aged 75–84. Trends in primary and secondary care service use were observed within frailty categories and age groups. Mean face-to-face appointments were generally similar within frailty categories across age groups, but with a notable decrease in appointments with older age in the severe category. Prescriptions increased with increasing age in both Fit and Mild frailty categories but decreased in moderate and severe categories. When stratified by age, mean annual outpatient appointments, ED attendances and hospital admissions (both elective and unplanned) were similar across age groups within the Fit and Mild categories, and decreased with increasing age in the moderate and severe categories. Individual annual total use of primary and secondary care services rise with frailty severity, but overall costs for people living with frailty are highest in the mild and moderate frailty groups due to their larger population numbers. An approximate doubling in costs was observed between fit and mild frailty categories, a trebling for moderate frailty, and quadrupling for severe frailty. Stakeholder engagement established that in addition to core primary and secondary care services, future work will need to consider additional community health care and social care services to provide a more complete overview of total care use and costs, while acknowledging that data on these services is more difficult to obtain. A focus on having the right services at the right time, for example preventative and well-being services for middle-aged adults to reduce onset of frailty, and supportive services for older adults to slow frailty progression and enable continued independence and hospital avoidance were discussed. The role of health inequalities and deprivation as demonstrated by the analyses was considered key to diversify service planning according to local needs. Simulation modelling has provided a useful means of capturing both the statistical modelling and cost analysis elements of the study along with the suggestions from both the patient and professional members involved in the stakeholder events. The development of the model with 16 connected subgroups and connected flows in and out of the groups has been an iterative approach and has benefited from the information contained in the two large data sets (RCGO RSC and SAIL) as well as ONS population estimates and projections. The system dynamics (SD) model has been extensively validated against summary descriptive data from the RCGP RSC cohort (with a 6.9% error) and externally against a similar data set from SAIL (9.3% error) before being scaled up (using ONS estimates for the number of people entering the 50 + population and those turning 65, 75 or 85 in a given year) to consider how frailty incidence and prevalence at a national population level could be represented over the period of the cohort study (2006–17) and 10 years into the future. The prototype simulation model is therefore able to consider the estimated frailty dynamics for England as well as the associated service use and costs in both baseline and ‘what-if’ scenarios. A baseline (no service changes) scenario experiment suggests what might happen if there is no change to current service provision and interventions caring for the population aged 50 and over (which is projected to increase from 20,045,766 to 21,755,097 between 2017 and 2027). Preliminary results suggest a projected increase in primary care service use and medication use with the cost for providing GP services and individual medicines in England rising by £3.1 billion for people with frailty. For secondary care, the rise in costs is estimated to be £2.7 billion for patients with frailty. The simulation predicted that the proportion of people with frailty will increase by another 7.1% between 2017 (41.5%) and 2027 (48.7%), and associated costs will rise by £5.8 billion over an 11-year period. A scenario experiment exploring reducing frailty incidence by 5% indicates that almost 180,000 people remain fit each year rather than becoming frail (121,000 fewer mildly frail people, 27,500 fewer moderately frail and 12,800 fewer severely frail), which in turn could result in almost 300,000 fewer GP consultations (in the first year of the intervention) among the mildly frail and 14,000 fewer would be needed by those with moderate and severe frailty. In relation to secondary care services, there would be 114,000 fewer events among those that are mildly frail and an extra 57,000 among those that are fit. This would result in 5.3 million fewer secondary care service events in those with some degree of frailty over the projected 10-year period. Reducing frailty incidence could result in 26,418 fewer unplanned admissions and 47,506 fewer elective admissions. The cost savings from all these service use changes could amount to £266 million per annum by 2027. A scenario experiment exploring a reduction in frailty progression indicates that almost 222,000 people remain mildly frail each year rather than becoming moderately or severely frail (68,200 fewer moderately frail and 110,000 fewer severely frail). The corresponding impact on primary care service use is projected to be 623,700 fewer GP consultations (face-to-face, telephone, home visits and e-consultations) per annum in 2027. In relation to secondary care services there could be 64,111 fewer Accident and Emergency (A&E) attendances, 1540 fewer admissions to critical care and 350,762 fewer outpatient appointments as well as 53,162 fewer unplanned admissions and 54,283 fewer elective admissions. The cost savings from all these service use changes could amount to £298.9 million per annum by 2027. A scenario experiment considering reducing the number of unplanned hospital admissions among patients with frailty by 5% indicates 89,000 fewer hospital admissions. The cost saving from this service use change could amount to £153.8 million per annum by 2027. Findings will be used to inform guidelines and recommendations for service providers and commissioners. Conclusions This study provides new and robust evidence on incidence, prevalence and progression of frailty in an ageing population, in particular highlighting that frailty is already present in those aged 50–64 and that healthcare use and costs related to older people with frailty are substantial. The statistical modelling suggests that age, sex, deprivation, ethnicity and urban/rural location are all independently associated with frailty onset and progression and costs. The large increases in individual costs with more severe frailty need to be considered together with overall population prevalence of frailty categories, and the larger overall total costs of care for people with mild or moderate frailty need to be taken into account when deciding which services would be most cost-effective. The simulation model provides projections of frailty prevalence and associated service use and costs over 10 years. Frailty prevalence, service use and costs will continue to rise in the future due in part to the ageing population. Scenario analyses indicate that reduction of incidence and slowing of progression, particularly before the age of 65, has potential to reduce future service demand in both primary and secondary care settings. For example, in relation to primary care, reducing frailty incidence in all age groups could result in reduced GP consultations and home visits as well as fewer medicines used. In secondary care settings, there could also be reductions in ED attendances, hospital admissions and outpatient appointments. Reducing unplanned hospitalisations in older people with frailty would have a more modest impact on costs. The outputs and findings from each element of the study will be collated into a commissioning toolkit, comprising guidance on drivers of frailty-related demand and simulation model outputs that can be used for prediction of future demand and exploration of different service scenarios. Study registration This study is registered as NCT04139278 www.clinicaltrials.gov. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 16/116/43) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 44. See the NIHR Funding and Awards website for further award information.

Background and Objectives SARS-CoV-2 infection in children and young people (CYP) can lead to life threatening conditions including COVID-19, transmission to more vulnerable individuals, or even long COVID. Vaccination against COVID-19 reduces the chance of infection and transmission of the virus, but vaccine uptake in the UK has been shown to decrease with age. Approach We undertook a multistate-model approach to estimate hazard ratios on national cohorts constructed from linked health and administrative data, adjusting for several demographic factors. The models were applied to 3,433,483 CYP aged 5-17 years between 4th August 2021 and 31st May 2022. The results were combined in a random effects meta-analysis. Results Uptake of the first COVID-19 vaccine in CYP was lower compared to older age groups in the UK, and diminished further with subsequent doses (34%, 20% and 2% for 1st, 2nd, and booster dose respectively). Age of the CYP and vaccination status of the adults in the household were identified as important risk factors. For example, 5-11-year-olds were less likely to receive their first vaccine compared to 16-17-year-olds (adjusted Hazard Ratio [aHR]: 0.10 (95%CI: 0.06-0.19), and CYP in unvaccinated households were less likely to receive their first vaccine compared to partially vaccinated households (aHR: 0.19, 95%CI 0.13-0.29). Conclusions and Implications Our work highlights the need for targeted strategies to increase COVID-19 vaccine acceptance and uptake among CYP, especially considering the influence of parental consent and household factors. Further research could help identify risk factors in household types to investigate more direct associations, which may be influenced by factors such as living with vulnerable people, familial structure, or deprivation.

Abstract SARS-CoV-2 infection in children and young people (CYP) can lead to life-threatening COVID-19, transmission within households and schools, and the development of long COVID. Using linked health and administrative data, we investigated vaccine uptake among 3,433,483 CYP aged 5–17 years across all UK nations between 4th August 2021 and 31st May 2022. We constructed national cohorts and undertook multi-state modelling and meta-analysis to identify associations between demographic variables and vaccine uptake. We found that uptake of the first COVID-19 vaccine among CYP was low across all four nations compared to other age groups and diminished with subsequent doses. Age and vaccination status of adults living in the same household were identified as important risk factors associated with vaccine uptake in CYP. For example, 5–11 year-olds were less likely to receive their first vaccine compared to 16–17 year-olds (adjusted Hazard Ratio [aHR]: 0.10 (95%CI: 0.06–0.19)), and CYP in unvaccinated households were less likely to receive their first vaccine compared to CYP in partially vaccinated households (aHR: 0.19, 95%CI 0.13–0.29).

BackgroundNo single multimorbidity measure is validated for use in NHS (National Health Service) England’s General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR), the nationwide primary care data set created for COVID-19 pandemic research. The Cambridge Multimorbidity Score (CMMS) is a validated tool for predicting mortality risk, with 37 conditions defined by Read Codes. The GDPPR uses the more internationally used Systematized Nomenclature of Medicine clinical terms (SNOMED CT). We previously developed a modified version of the CMMS using SNOMED CT, but the number of terms for the GDPPR data set is limited making it impossible to use this version. ObjectiveWe aimed to develop and validate a modified version of CMMS using the clinical terms available for the GDPPR. MethodsWe used pseudonymized data from the Oxford-Royal College of General Practitioners Research and Surveillance Centre (RSC), which has an extensive SNOMED CT list. From the 37 conditions in the original CMMS model, we selected conditions either with (1) high prevalence ratio (≥85%), calculated as the prevalence in the RSC data set but using the GDPPR set of SNOMED CT codes, divided by the prevalence included in the RSC SNOMED CT codes or (2) conditions with lower prevalence ratios but with high predictive value. The resulting set of conditions was included in Cox proportional hazard models to determine the 1-year mortality risk in a development data set (n=500,000) and construct a new CMMS model, following the methods for the original CMMS study, with variable reduction and parsimony, achieved by backward elimination and the Akaike information stopping criterion. Model validation involved obtaining 1-year mortality estimates for a synchronous data set (n=250,000) and 1-year and 5-year mortality estimates for an asynchronous data set (n=250,000). We compared the performance with that of the original CMMS and the modified CMMS that we previously developed using RSC data. ResultsThe initial model contained 22 conditions and our final model included 17 conditions. The conditions overlapped with those of the modified CMMS using the more extensive SNOMED CT list. For 1-year mortality, discrimination was high in both the derivation and validation data sets (Harrell C=0.92) and 5-year mortality was slightly lower (Harrell C=0.90). Calibration was reasonable following an adjustment for overfitting. The performance was similar to that of both the original and previous modified CMMS models. ConclusionsThe new modified version of the CMMS can be used on the GDPPR, a nationwide primary care data set of 54 million people, to enable adjustment for multimorbidity in predicting mortality in people in real-world vaccine effectiveness, pandemic planning, and other research studies. It requires 17 variables to produce a comparable performance with our previous modification of CMMS to enable it to be used in routine data using SNOMED CT.

Summary: Background: There were substantial reductions in asthma exacerbations during the COVID-19 pandemic for reasons that remain poorly understood. We investigated changes in modifiable risk factors which might help explain the reductions in asthma exacerbations. Methods: Multilevel generalised linear mixed models were fitted to examine changes in modifiable risk factors for asthma exacerbations during 2020–2022, compared to pre-pandemic year (2019), using observational, routine data from general practices in the Oxford-Royal College of General Practitioners Research and Surveillance Centre. Asthma exacerbations were defined as any of GP recorded: asthma exacerbations, prescriptions of prednisolone, accident and emergency department attendance or hospitalisation for asthma. Modifiable risk factors of interest were ownership of asthma self-management plan, asthma annual review, inhaled-corticosteroid (ICS) prescriptions, influenza vaccinations and respiratory-tract-infections (RTI). Findings: Compared with 2019 (n = 550,995), in 2020 (n = 565,956) and 2022 (n = 562,167) (p

ObjectivesThe majority of patients with respiratory illness are seen in primary care settings. Given COVID-19 is predominantly a respiratory illness, the INTernational ConsoRtium of Primary Care BIg Data Researchers (INTRePID), assessed the pandemic impact on primary care visits for respiratory illnesses.DesignDefinitions for respiratory illness types were agreed on collectively. Monthly visit counts with diagnosis were shared centrally for analysis.SettingPrimary care settings in Argentina, Australia, Canada, China, Norway, Peru, Singapore, Sweden and the United States.ParticipantsOver 38 million patients seen in primary care settings in INTRePID countries before and during the pandemic, from January 1st, 2018, to December 31st, 2021.Main outcome measuresRelative change in the monthly mean number of visits before and after the onset of the pandemic for acute infectious respiratory disease visits including influenza, upper and lower respiratory tract infections and chronic respiratory disease visits including asthma, chronic obstructive pulmonary disease, respiratory allergies, and other respiratory diseases.ResultsINTRePID countries reported a marked decrease in the average monthly visits for respiratory illness. Changes in visits varied from −10.9% [95% confidence interval (CI): −33.1 to +11.3%] in Norway to −79.9% (95% CI: −86.4% to −73.4%) in China for acute infectious respiratory disease visits and − 2.1% (95% CI: −12.1 to +7.8%) in Peru to −59.9% (95% CI: −68.6% to −51.3%) in China for chronic respiratory illness visits. While seasonal variation in allergic respiratory illness continued during the pandemic, there was essentially no spike in influenza illness during the first 2 years of the pandemic.ConclusionThe COVID-19 pandemic had a major impact on primary care visits for respiratory presentations. Primary care continued to provide services for respiratory illness, although there was a decrease in infectious illness during the COVID pandemic. Understanding the role of primary care may provide valuable information for COVID-19 recovery efforts and planning for future global emergencies.

BackgroundGlobally, there are marked inconsistencies in how immunosuppression is characterized and subdivided into clinical risk groups. This is detrimental to the precision and comparability of disease surveillance efforts—which has negative implications for the care of those who are immunosuppressed and their health outcomes. This was particularly apparent during the COVID-19 pandemic; despite collective motivation to protect these patients, conflicting clinical definitions created international rifts in how those who were immunosuppressed were monitored and managed during this period. We propose that international clinical consensus be built around the conditions that lead to immunosuppression and their gradations of severity concerning COVID-19. Such information can then be formalized into a digital phenotype to enhance disease surveillance and provide much-needed intelligence on risk-prioritizing these patients. ObjectiveWe aim to demonstrate how electronic Delphi objectives, methodology, and statistical approaches will help address this lack of consensus internationally and deliver a COVID-19 risk-stratified phenotype for “adult immunosuppression.” MethodsLeveraging existing evidence for heterogeneous COVID-19 outcomes in adults who are immunosuppressed, this work will recruit over 50 world-leading clinical, research, or policy experts in the area of immunology or clinical risk prioritization. After 2 rounds of clinical consensus building and 1 round of concluding debate, these panelists will confirm the medical conditions that should be classed as immunosuppressed and their differential vulnerability to COVID-19. Consensus statements on the time and dose dependencies of these risks will also be presented. This work will be conducted iteratively, with opportunities for panelists to ask clarifying questions between rounds and provide ongoing feedback to improve questionnaire items. Statistical analysis will focus on levels of agreement between responses. ResultsThis protocol outlines a robust method for improving consensus on the definition and meaningful subdivision of adult immunosuppression concerning COVID-19. Panelist recruitment took place between April and May of 2024; the target set for over 50 panelists was achieved. The study launched at the end of May and data collection is projected to end in July 2024. ConclusionsThis protocol, if fully implemented, will deliver a universally acceptable, clinically relevant, and electronic health record–compatible phenotype for adult immunosuppression. As well as having immediate value for COVID-19 resource prioritization, this exercise and its output hold prospective value for clinical decision-making across all diseases that disproportionately affect those who are immunosuppressed. International Registered Report Identifier (IRRID)PRR1-10.2196/56271

Abstract The emergence of the COVID-19 vaccination has been critical in changing the course of the COVID-19 pandemic. To ensure protection remains high in vulnerable groups booster vaccinations in the UK have been targeted based on age and clinical vulnerabilities. We undertook a national retrospective cohort study using data from the 2021 Census linked to electronic health records. We fitted cause-specific Cox models to examine the association between health conditions and the risk of COVID-19 death and all-other-cause death for adults aged 50-100-years in England vaccinated with a booster in autumn 2022. Here we show, having learning disabilities or Down Syndrome (hazard ratio=5.07;95% confidence interval=3.69-6.98), pulmonary hypertension or fibrosis (2.88;2.43-3.40), motor neuron disease, multiple sclerosis, myasthenia or Huntington’s disease (2.94, 1.82-4.74), cancer of blood and bone marrow (3.11;2.72-3.56), Parkinson’s disease (2.74;2.34-3.20), lung or oral cancer (2.57;2.04 to 3.24), dementia (2.64;2.46 to 2.83) or liver cirrhosis (2.65;1.95 to 3.59) was associated with an increased risk of COVID-19 death. Individuals with cancer of the blood or bone marrow, chronic kidney disease, cystic fibrosis, pulmonary hypotension or fibrosis, or rheumatoid arthritis or systemic lupus erythematosus had a significantly higher risk of COVID-19 death relative to other causes of death compared with individuals who did not have diagnoses. Policy makers should continue to priorities vulnerable groups for subsequent COVID-19 booster doses to minimise the risk of COVID-19 death.

BackgroundInnovation in seasonal influenza vaccine development has resulted in a wider range of formulations becoming available. Understanding vaccine coverage across populations including the timing of administration is important when evaluating vaccine benefits and risks. ObjectiveThis study aims to report the representativeness, uptake of influenza vaccines, different formulations of influenza vaccines, and timing of administration within the English Primary Care Sentinel Cohort (PCSC). MethodsWe used the PCSC of the Oxford-Royal College of General Practitioners Research and Surveillance Centre. We included patients of all ages registered with PCSC member general practices, reporting influenza vaccine coverage between September 1, 2019, and January 29, 2020. We identified influenza vaccination recipients and characterized them by age, clinical risk groups, and vaccine type. We reported the date of influenza vaccination within the PCSC by International Standard Organization (ISO) week. The representativeness of the PCSC population was compared with population data provided by the Office for National Statistics. PCSC influenza vaccine coverage was compared with published UK Health Security Agency’s national data. We used paired t tests to compare populations, reported with 95% CI. ResultsThe PCSC comprised 7,010,627 people from 693 general practices. The study population included a greater proportion of people aged 18-49 years (2,982,390/7,010,627, 42.5%; 95% CI 42.5%-42.6%) compared with the Office for National Statistics 2019 midyear population estimates (23,219,730/56,286,961, 41.3%; 95% CI 4.12%-41.3%; P

Background: Recent policy initiatives seeking to address the workforce crisis in general practice have promoted greater multidisciplinarity. Evidence is lacking on how changes in staffing and the relational climate in practice teams affect the experiences of staff and patients. Aim: To synthesise evidence on how the composition of the practice workforce and team climate affect staff job satisfaction and burnout, and the processes and quality of care for patients. Design & setting: A systematic literature review of international evidence. Method: Four different searches were carried out using MEDLINE, Embase, Cochrane Library, CINAHL, PsycINFO, and Web of Science. Evidence from English language articles from 2012–2022 was identified, with no restriction on study design. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed and data were synthesised thematically. Results: In total, 11 studies in primary healthcare settings were included, 10 from US integrated healthcare systems, one from Canada. Findings indicated that when teams are understaffed and work environments are stressful, patient care and staff wellbeing suffer. However, a good relational climate can buffer against burnout and protect patient care quality in situations of high workload. Good team dynamics and stable team membership are important for patient care coordination and job satisfaction. Female physicians are at greater risk of burnout. Conclusion: Evidence regarding team composition and team climate in relation to staff and patient outcomes in general practice remains limited. Challenges exist when drawing conclusions across different team compositions and definitions of team climate. Further research is needed to explore the conditions that generate a ‘good’ climate.

BackgroundPrepandemic sentinel surveillance focused on improved management of winter pressures, with influenza-like illness (ILI) being the key clinical indicator. The World Health Organization (WHO) global standards for influenza surveillance include monitoring acute respiratory infection (ARI) and ILI. The WHO’s mosaic framework recommends that the surveillance strategies of countries include the virological monitoring of respiratory viruses with pandemic potential such as influenza. The Oxford-Royal College of General Practitioner Research and Surveillance Centre (RSC) in collaboration with the UK Health Security Agency (UKHSA) has provided sentinel surveillance since 1967, including virology since 1993. ObjectiveWe aim to describe the RSC’s plans for sentinel surveillance in the 2023-2024 season and evaluate these plans against the WHO mosaic framework. MethodsOur approach, which includes patient and public involvement, contributes to surveillance objectives across all 3 domains of the mosaic framework. We will generate an ARI phenotype to enable reporting of this indicator in addition to ILI. These data will support UKHSA’s sentinel surveillance, including vaccine effectiveness and burden of disease studies. The panel of virology tests analyzed in UKHSA’s reference laboratory will remain unchanged, with additional plans for point-of-care testing, pneumococcus testing, and asymptomatic screening. Our sampling framework for serological surveillance will provide greater representativeness and more samples from younger people. We will create a biomedical resource that enables linkage between clinical data held in the RSC and virology data, including sequencing data, held by the UKHSA. We describe the governance framework for the RSC. ResultsWe are co-designing our communication about data sharing and sampling, contextualized by the mosaic framework, with national and general practice patient and public involvement groups. We present our ARI digital phenotype and the key data RSC network members are requested to include in computerized medical records. We will share data with the UKHSA to report vaccine effectiveness for COVID-19 and influenza, assess the disease burden of respiratory syncytial virus, and perform syndromic surveillance. Virological surveillance will include COVID-19, influenza, respiratory syncytial virus, and other common respiratory viruses. We plan to pilot point-of-care testing for group A streptococcus, urine tests for pneumococcus, and asymptomatic testing. We will integrate test requests and results with the laboratory-computerized medical record system. A biomedical resource will enable research linking clinical data to virology data. The legal basis for the RSC’s pseudonymized data extract is The Health Service (Control of Patient Information) Regulations 2002, and all nonsurveillance uses require research ethics approval. ConclusionsThe RSC extended its surveillance activities to meet more but not all of the mosaic framework’s objectives. We have introduced an ARI indicator. We seek to expand our surveillance scope and could do more around transmissibility and the benefits and risks of nonvaccine therapies.

ABSTRACTPrevention of respiratory syncytial virus (RSV) infection is now a global health priority, with a long-acting monoclonal antibody and two RSV vaccines recently licenced for clinical use. Most licenced and candidate interventions target the RSV fusion (RSV-F) protein. New interventions may be associated with the spread of mutations, reducing susceptibility to antibody neutralization in RSV-F. There is a need for ongoing longitudinal global surveillance of circulating RSV strains. To achieve this large-scale genomic surveillance, a reliable, high-throughput RSV sequencing assay is required. Here we report an improved high-throughput RSV whole-genome sequencing (WGS) assay performed directly on clinical samples without additional enrichment, using a 4-primer-pool, short-amplicon PCR-tiling approach that is suitable for short-read sequencing platforms. Using upper respiratory tract (URT) RSV-positive clinical samples obtained from a sentinel network of primary care providers and from hospital patients (29.7% and 70.2%, respectively; n = 1,037), collected over the period 2019 to 2023, this assay had a threshold of approximately 4 × 103 to 8 × 103 copies/mL (RSV-B and RSV-A sub-types, respectively) as the lowest amount of virus needed in the sample to achieve >96% of whole-genome coverage at a high-quality level. Using a Ct value of 31 as an empirical cut-off, the overall assay success rate of obtaining >90% genome coverage at a read depth minimum of 20 was 96.83% for clinical specimens successfully sequenced from a total of 1,071. The RSV WGS approach described in this study has increased sensitivity compared to previous approaches and can be applied to clinical specimens without the requirement for enrichment. The updated approach produces sequences of high quality consistently and cost-effectively, suitable for implementation to underpin national programs for the surveillance of RSV genomic variation.IMPORTANCEIn this paper, we report an improved high-throughput respiratory syncytial virus (RSV) whole-genome sequencing (WGS) assay performed directly on clinical samples, using a 4-primer-pool, short-amplicon PCR-tiling approach that is suitable for short-read sequencing platforms. The RSV WGS approach described in this study has increased sensitivity compared to previous approaches and can be applied to clinical specimens without the requirement for enrichment. The updated approach produces sequences of high quality consistently and cost-effectively, suitable for implementation to underpin national and global programs for the surveillance of RSV genomic variation. The quality of sequence produced is essential for preparedness for new interventions in monitoring antigenic escape, where a single point mutation might lead to a reduction in antibody binding effectiveness and neutralizing activity, or indeed in the monitoring of retaining susceptibility to neutralization by existing and new interventions.

Summary: Background: The COVID-19 pandemic impacted mental health disorders, affecting both individuals with pre-existing conditions and those with no prior history. However, there is limited evidence regarding the pandemic's impact on mental health visits to primary care physicians. The International Consortium of Primary Care Big Data Researchers (INTRePID) explored primary care visit trends related to mental health conditions in Argentina, Australia, Canada, China, Norway, Peru, Singapore, Sweden, and the USA. Methods: We conducted an interrupted time series analysis in nine countries to examine changes in rates of monthly mental health visits to primary care settings from January 1st, 2018, to December 31st, 2021. Sub-group analysis considered service type (in-person/virtual) and six categories of mental health conditions (anxiety/depression, bipolar/schizophrenia/other psychotic disorders, sleep disorders, dementia, ADHD/eating disorders, and substance use disorder). Findings: Mental health visit rates increased after the onset of the pandemic in most countries. In Argentina, Canada, China, Norway, Peru, and Singapore, this increase was immediate ranged from an incidence rate ratio of 1·118 [95% CI 1.053–1.187] to 2.240 [95% CI 2.057–2.439] when comparing the first month of pandemic with the pre-pandemic trend. Increases in the following months varied across countries. Anxiety/depression was the leading reason for mental health visits in most countries. Virtual visits were reported in Australia, Canada, Norway, Peru, Sweden, and the USA, accounting for up to 40% of the total mental health visits. Interpretation: Findings suggest an overall increase in mental health visits, driven largely by anxiety/depression. During the COVID-19 pandemic, many of the studied countries adopted virtual care in particular for mental health visits. Primary care plays a crucial role in addressing mental ill-health in times of crisis. Funding: Canadian Institutes of Health Research grant #173094 and the Rathlyn Foundation Primary Care EMR Research and Discovery Fund.

Summary: Background: The cardiovascular and kidney benefits of sodium-glucose co-transporter-2 (SGLT2) inhibitors in people with chronic kidney disease (CKD) are well established. The implementation of updated SGLT2 inhibitor guidelines and prescribing in the real-world CKD population remains largely unknown. Methods: A cross-sectional study of adults with CKD registered with UK primary care practices in the Oxford-Royal College of General Practitioners Research and Surveillance Centre network on the 31st December 2022 was undertaken. Pseudonymised data from electronic health records held securely within the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub (ORCHID) were extracted. An update to a previously described ontological approach was used to identify the study population, using a combination of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) indicating a diagnosis of CKD and laboratory confirmed CKD based on Kidney Disease: Improving Global Outcomes (KDIGO) diagnostic criteria. We examined the extent to which SGLT2 inhibitor guidelines apply to and are then implemented in adults with CKD. A logistic regression model was used to identify factors associated with SGLT2 inhibitor prescribing, reported as odds ratios (ORs) with 95% confidence intervals (CI). The four guidelines under investigation were the United Kingdom Kidney Association (UKKA) Clinical Practice Guideline SGLT2 Inhibition in Adults with Kidney Disease (October 2021), American Diabetes Association (ADA) and KDIGO Consensus Report on Diabetes Management in CKD (October 2022), National Institute for Health and Care Excellence (NICE) Guideline Type 2 Diabetes in Adults: Management (June 2022), and NICE Technology Appraisal Dapagliflozin for Treating CKD (March 2022). Findings: Of 6,670,829 adults, we identified 516,491 (7.7%) with CKD, including 32.8% (n = 169,443) who had co-existing type 2 diabetes (T2D). 26.8% (n = 138,183) of the overall CKD population had a guideline directed indication for SGLT2 inhibitor treatment. A higher proportion of people with CKD and co-existing T2D were indicated for treatment, compared to those without T2D (62.8% [n = 106,468] vs. 9.1% [n = 31,715]). SGLT2 inhibitors were prescribed to 17.0% (n = 23,466) of those with an indication for treatment, and prescriptions were predominantly in those with co-existing T2D; 22.0% (n = 23,464) in those with T2D, and

Summary: Background: UK COVID-19 vaccination policy has evolved to offering COVID-19 booster doses to individuals at increased risk of severe Illness from COVID-19. Building on our analyses of vaccine effectiveness of first, second and initial booster doses, we aimed to identify individuals at increased risk of severe outcomes (i.e., COVID-19 related hospitalisation or death) post the autumn 2022 booster dose. Methods: We undertook a national population-based cohort analysis across all four UK nations through linked primary care, vaccination, hospitalisation and mortality data. We included individuals who received autumn 2022 booster doses of BNT162b2 (Comirnaty) or mRNA-1273 (Spikevax) during the period September 1, 2022 to December 31, 2022 to investigate the risk of severe COVID-19 outcomes. Cox proportional hazard models were used to estimate adjusted hazard ratios (aHR) and 95% confidence intervals (CIs) for the association between demographic and clinical factors and severe COVID-19 outcomes after the autumn booster dose. Analyses were adjusted for age, sex, body mass index (BMI), deprivation, urban/rural areas and comorbidities. Stratified analyses were conducted by vaccine type. We then conducted a fixed-effect meta-analysis to combine results across the four UK nations. Findings: Between September 1, 2022 and December 31, 2022, 7,451,890 individuals ≥18 years received an autumn booster dose. 3500 had severe COVID-19 outcomes (2.9 events per 1000 person-years). Being male (male vs female, aHR 1.41 (1.32–1.51)), older adults (≥80 years vs 18–49 years; 10.43 (8.06–13.50)), underweight (BMI

BackgroundThe COVID-19 pandemic has reshaped healthcare delivery worldwide.ObjectiveTo explore potential changes in the reasons for visits and modality of care in primary care settings through the International Consortium of Primary Care Big Data Researchers (INTRePID).MethodsWe conducted a cross-sectional, retrospective study from 2018-2021. We examined visit volume, modality, and reasons for visits to primary care in Argentina, Australia, Canada, China, Peru, Norway, Singapore, Sweden, and the USA. The analysis involved a comparison between the pre-pandemic and pandemic periods.ResultsThere were more than 215 million visits from over 38 million patients during the study period in INTRePID primary care settings. Most INTRePID countries experienced a decline in monthly visit rates during the first year of the pandemic, with rate ratios (RR) and 95% confidence intervals (CI) ranging from RR:0.57 (95%CI:0.49-0.66) to RR:0.90 (95%CI:0.83-0.98), except for in Canada (RR:0.99, 95%CI:0.94-1.05) and Norway (RR:1.00, 95%CI:0.92-1.10), where rates remained stable and in Australia where rates increased (RR:1.19, 95%CI:1.11-1.28). Argentina, China, and Singapore had limited or no adoption of virtual care, whereas the remaining INTRePID countries varied in the extent of virtual care utilization. In Peru, virtual visits accounted for 7.34% (95%CI:7.33%-7.35%) of all interactions in the initial year of the pandemic, dipping to 5.22% (95%CI:5.21%-5.23%) in the subsequent year. However, in Canada 75.30% (95%CI:75.20%-75.40%) of the visits in the first year were virtual, decreasing to 62.77% (95%CI:62.66%-62.88%) in the second year. Diabetes, hypertension and/or hyperlipidemia and general health exams were in the top 10 reasons for visits in 2019 for all countries. Anxiety, depression and/or other mental health related reasons were among the top 10 reasons for virtual visits in all countries that had virtual care.ConclusionsThe pandemic resulted in changes in reasons for visits to primary care, with virtual care mitigating visit volume disruptions in many countries.

Introduction Worldwide, pancreatic cancer has a poor prognosis. Early diagnosis may improve survival by enabling curative treatment. Statistical and machine learning diagnostic prediction models using risk factors such as patient demographics and blood tests are being developed for clinical use to improve early diagnosis. One example is the Enriching New-onset Diabetes for Pancreatic Cancer (ENDPAC) model, which employs patients’ age, blood glucose and weight changes to provide pancreatic cancer risk scores. These values are routinely collected in primary care in the UK. Primary care’s central role in cancer diagnosis makes it an ideal setting to implement ENDPAC but it has yet to be used in clinical settings. This study aims to determine the feasibility of applying ENDPAC to data held by UK primary care practices.Methods and analysis This will be a multicentre observational study with a cohort design, determining the feasibility of applying ENDPAC in UK primary care. We will develop software to search, extract and process anonymised data from 20 primary care providers’ electronic patient record management systems on participants aged 50+ years, with a glycated haemoglobin (HbA1c) test result of ≥48 mmol/mol (6.5%) and no previous abnormal HbA1c results. Software to calculate ENDPAC scores will be developed, and descriptive statistics used to summarise the cohort’s demographics and assess data quality. Findings will inform the development of a future UK clinical trial to test ENDPAC’s effectiveness for the early detection of pancreatic cancer.Ethics and dissemination This project has been reviewed by the University of Surrey University Ethics Committee and received a favourable ethical opinion (FHMS 22-23151 EGA). Study findings will be presented at scientific meetings and published in international peer-reviewed journals. Participating primary care practices, clinical leads and policy makers will be provided with summaries of the findings.

Introduction Smoking is harmful, and its cessation is recommended to prevent chronic kidney disease, which often begins with abnormal leakage of albumin in the urine, called albuminuria. Smoking cessation’s effect on albuminuria depends on the pack-years smoked, length of abstinence, body mass index (BMI) and glycosylated haemoglobin (HbA1c). Using the UK Biobank data, we examined the relationship between these cardiorenal variables and albuminuria.Methods For this study, we selected a UK Biobank cohort with urinary albumin concentration (UAC) in the first and second visits. Participants were divided into progressor and regressor groups, where progressors were defined as those with increased UAC value, and regressors were those with decreased UAC value. Three different logistic regression models were fitted. In model 1, with a cohort design, we explored the impact of a change in age, HbA1c and BMI between the first and second visits and the UAC. In model 2 and 3, in a cross-sectional design, we explored which cardiorenal risk factors were associated with a rise or fall of UAC at the time point of the second visit. Results are expressed in OR and 95% CI.Results The prevalence of albuminuria was highest in ex-smokers who started smoking between the ages of 13 and 18. With a mean duration of 51 months, there was no statistically significant relationship between smoking status and BMI with albuminuria. Each year of ageing and each unit of increase in HbA1c (mmol/mol) increased the odds of progression of albuminuria by 20% and 3%, respectively. In ex-smokers, at the time point of the second visit, each year of smoking increased, and each year of abstinence decreased the odds by 4% and 6%, respectively.Conclusion Smokers should be supported to stop smoking and remain abstinent despite short-term weight gain. Childhood smoking should be actively discouraged.

Abstract Understanding the connection between physical and mental health with evidence-based research is important to inform and support targeted screening and early treatment. The objective of this study was to document the co-occurrence of physical and mental health conditions during and after the experience of symptomatic SARS-CoV-2 illness episodes. Drawing from a national symptoms' surveillance survey conducted in the UK in 2020, this study shows that individuals with symptomatic forms of SARS-CoV-2 (identified by anosmia with either fever, breathlessness or cough) presented significantly higher odds of experiencing moderate and severe anxiety (2.41, CI 2.01–2.90) and depression (3.64, CI 3.06–4.32). Respondents who recovered from physical SARS-CoV-2 symptoms also experienced higher odds of anxiety and depression in comparison to respondents who never experienced symptoms. The findings are robust to alternative estimation models that compare individuals with the same socioeconomic and demographic characteristics and who experienced the same local and contextual factors such as mobility and social restrictions. The findings have important implications for the screening and detection of mental health disorders in primary care settings. They also suggest the need to design and test interventions to address mental health during and after physical illness episodes.

Background Chronic kidney disease (CKD) and atrial fibrillation (AF) are increasing in prevalence globally and share common risk factors.Our aim was to characterise real-world evidence on direct oral anticoagulant (DOAC) prescribing for people with AF and CKD, in terms of adherence, persistence and renal dose titration.Methods PubMed, EMBASE and CINAHL were searched from inception to June 2022. Our search terms included a combination of Medical Subject Headings (MeSH) terms and keywords including ‘atrial fibrillation’, ‘chronic kidney disease’, ‘adherence’, ‘persistence’, ‘direct oral anticoagulants’ and ‘dosing’. Data extraction and quality assessment were undertaken by two reviewers independently. Meta-analyses for pooled estimates were performed using DerSimonian and Laird random-effects models. Age, sex, diabetes, hypertension and heart failure were chosen as variables of interest.Results From 19 studies, a total of 252 117 patients were included with CKD and AF. Meta-analysis was only possible in seven studies with 128 406 patients, five on DOAC dose titration and two on adherence. There were insufficient studies on persistence. Our meta-analysis of dosing showed that 68% of patients with CKD and AF had correct dosing. There was no evidence to show any association between correct DOAC dosing and variables of interest. Overall, 67% of patients were DOAC adherent.Conclusion Adherence and correct dosing of DOACs were suboptimal compared with other medications in the pooled studies with respect to CKD and AF. Thus, further research is required as the lack of generalisation of findings is a rate-limiting factor for improved DOAC management in AF and CKD.PROSPERO registration number CRD;42022344491.

BackgroundHepatitis A outbreaks in the United Kingdom are uncommon. Most people develop mild to moderate symptoms that resolve, without sequelae, within months. However, in high-risk groups, including those with underlying chronic liver disease (CLD), hepatitis A infection can be severe, with a higher risk of mortality and morbidity. The Health Security Agency and the National Institute of Health and Care Excellence recommend preexposure hepatitis A vaccination given in 2 doses to people with CLD, regardless of its cause. There are currently no published reports of vaccination coverage for people with CLD in England or internationally. ObjectiveThis study aims to describe hepatitis A vaccination coverage in adults with CLD in a UK primary care setting and compare liver disease etiology, sociodemographic characteristics, and comorbidities in people who are and are not exposed to the hepatitis A vaccine. MethodsWe will conduct a retrospective cohort study with data from the Primary Care Sentinel Cohort of the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub database, which is nationally representative of the English population. We will include people aged 18 years and older who have been registered in general practices in the Research and Surveillance Centre network and have a record of CLD between January 1, 2012, and December 31, 2022, including those with alcohol-related liver disease, chronic hepatitis B, chronic hepatitis C, nonalcohol fatty liver disease, Wilson disease, hemochromatosis, and autoimmune hepatitis. We will carefully curate variables using the Systematized Nomenclature of Medicine Clinical Terms. We will report the sociodemographic characteristics of those who are vaccinated. These include age, gender, ethnicity, population density, region, socioeconomic status (measured using the index of multiple deprivation), obesity, alcohol consumption, and smoking. Hepatitis A vaccination coverage for 1 and 2 doses will be calculated using an estimate of the CLD population as the denominator. We will analyze the baseline characteristics using descriptive statistics, including measures of dispersion. Pairwise comparisons of case-mix characteristics, comorbidities, and complications will be reported according to vaccination status. A multistate survival model will be fitted to estimate the transition probabilities among four states: (1) diagnosed with CLD, (2) first dose of hepatitis A vaccination, (3) second dose of hepatitis A vaccination, and (4) death. This will identify any potential disparities in how people with CLD get vaccinated. ResultsThe Research and Surveillance Centre population comprises over 8 million people. The reported incidence of CLD is 20.7 cases per 100,000. International estimates of hepatitis A vaccine coverage vary between 10% and 50% in this group. ConclusionsThis study will describe the uptake of the hepatitis A vaccine in people with CLD and report any disparities or differences in the characteristics of the vaccinated population. International Registered Report Identifier (IRRID)PRR1-10.2196/51861

Abstract There is a need for better understanding of the risk of thrombocytopenic, haemorrhagic, thromboembolic disorders following first, second and booster vaccination doses and testing positive for SARS-CoV-2. Self-controlled cases series analysis of 2.1 million linked patient records in Wales between 7th December 2020 and 31st December 2021. Outcomes were the first diagnosis of thrombocytopenic, haemorrhagic and thromboembolic events in primary or secondary care datasets, exposure was defined as 0–28 days post-vaccination or a positive reverse transcription polymerase chain reaction test for SARS-CoV-2. 36,136 individuals experienced either a thrombocytopenic, haemorrhagic or thromboembolic event during the study period. Relative to baseline, our observations show greater risk of outcomes in the periods post-first dose of BNT162b2 for haemorrhagic (IRR 1.47, 95%CI: 1.04–2.08) and idiopathic thrombocytopenic purpura (IRR 2.80, 95%CI: 1.21–6.49) events; post-second dose of ChAdOx1 for arterial thrombosis (IRR 1.14, 95%CI: 1.01–1.29); post-booster greater risk of venous thromboembolic (VTE) (IRR-Moderna 3.62, 95%CI: 0.99–13.17) (IRR-BNT162b2 1.39, 95%CI: 1.04–1.87) and arterial thrombosis (IRR-Moderna 3.14, 95%CI: 1.14–8.64) (IRR-BNT162b2 1.34, 95%CI: 1.15–1.58). Similarly, post SARS-CoV-2 infection the risk was increased for haemorrhagic (IRR 1.49, 95%CI: 1.15–1.92), VTE (IRR 5.63, 95%CI: 4.91, 6.4), arterial thrombosis (IRR 2.46, 95%CI: 2.22–2.71). We found that there was a measurable risk of thrombocytopenic, haemorrhagic, thromboembolic events after COVID-19 vaccination and infection.

Introduction A substantial proportion of COVID-19 survivors continue to have symptoms more than 3 months after infection, especially of those who required medical intervention. Lasting symptoms are wide-ranging, and presentation varies between individuals and fluctuates within an individual. Improved understanding of undulation in symptoms and triggers may improve efficacy of healthcare providers and enable individuals to better self-manage their Long Covid. We present a protocol where we aim to develop and examine the feasibility and usability of digital home monitoring for capturing daily fluctuation of symptoms in individuals with Long Covid and provide data to facilitate a personalised approach to the classification and management of Long Covid symptoms.Methods and analysis This study is a longitudinal prospective cohort study of adults with Long Covid accessing 10 National Health Service (NHS) rehabilitation services in the UK. We aim to recruit 400 people from participating NHS sites. At referral to study, 6 weeks and 12 weeks, participants will complete demographic data (referral to study) and clinical outcome measures, including ecological momentary assessment (EMA) using personal mobile devices. EMA items are adapted from the COVID-19 Yorkshire Rehabilitation Scale items and include self-reported activities, symptoms and psychological factors. Passive activity data will be collected through wrist-worn sensors. We will use latent class growth models to identify trajectories of experience, potential phenotypes defined by co-occurrence of symptoms and inter-relationships between stressors, symptoms and participation in daily activities. We anticipate that n=300 participants provide 80% power to detect a 20% improvement in fatigue over 12 weeks in one class of patients relative to another.Ethics and dissemination The study was approved by the Yorkshire & The Humber—Bradford Leeds Research Ethics Committee (ref: 21/YH/0276). Findings will be disseminated in peer-reviewed publications and presented at conferences.Trial registration number ISRCTN15022307.

IntroductionDevelopment of Robust and Innovative Vaccine Effectiveness (DRIVE) was a European public–private partnership (PPP) that aimed to provide annual, brand-specific estimates of influenza vaccine effectiveness (IVE) for regulatory and public health purposes. DRIVE was launched in 2017 under the umbrella of the Innovative Medicines Initiative (IMI) and conducted IVE studies from its pilot season in 2017–2018 to its final season in 2021–2022.MethodsIn 2021–2022, DRIVE conducted four primary care-based test-negative design (TND) studies (Austria, Italy, Iceland, and England; involving >1,000 general practitioners), nine hospital-based TND studies (France, Iceland, Italy, Romania, and Spain, for a total of 21 hospitals), and one population-based cohort study in Finland. In the TND studies, patients with influenza-like illness (primary care) or severe acute respiratory infection (hospital) were enrolled, and laboratory tested for influenza using RT-PCR. Study contributor-specific IVE was calculated using logistic regression, adjusting for age, sex, and calendar time, and pooled by meta-analysis.ResultsIn 2021–2022, pooled confounder-adjusted influenza vaccine effectiveness (IVE) estimates against laboratory-confirmed influenza (LCI) overall and per type and subtype/lineage was produced, albeit with wide confidence intervals (CI). The limited circulation of influenza in Europe did not allow the network to reach the optimal sample size to produce precise IVE estimates for all the brands included. The most significant IVE estimates were 76% (95% CI 23%−93%) for any vaccine and 81% (22%−95%) for Vaxigrip Tetra in adults ≥65 years old and 64% (25%−83%) for Fluenz Tetra in children (TND primary care setting), 85% (12%−97%) for any vaccine in adults 18–64 years (TND hospital setting), and 38% (1%−62%) in children 6 months−6 years (population-based cohort, mixed setting).DiscussionOver five seasons, DRIVE collected data on >35,000 patients, more than 60 variables, and 13 influenza vaccines. DRIVE demonstrated that estimating brand-specific IVE across Europe is possible, but achieving sufficient sample size to obtain precise estimates for all relevant stratifications remains a challenge. Finally, DRIVE's network of study contributors and lessons learned have greatly contributed to the development of the COVID-19 vaccine effectiveness platform COVIDRIVE.

BackgroundMolecular point-of-care testing (POCT) used in primary care can inform whether a patient presenting with an acute respiratory infection has influenza. A confirmed clinical diagnosis, particularly early in the disease, could inform better antimicrobial stewardship. Social distancing and lockdowns during the COVID-19 pandemic have disturbed previous patterns of influenza infections in 2021. However, data from samples taken in the last quarter of 2022 suggest that influenza represents 36% of sentinel network positive virology, compared with 24% for respiratory syncytial virus. Problems with integration into the clinical workflow is a known barrier to incorporating technology into routine care. ObjectiveThis study aims to report the impact of POCT for influenza on antimicrobial prescribing in primary care. We will additionally describe severe outcomes of infection (hospitalization and mortality) and how POCT is integrated into primary care workflows. MethodsThe impact of POCT for influenza on antimicrobial stewardship (PIAMS) in UK primary care is an observational study being conducted between December 2022 and May 2023 and involving 10 practices that contribute data to the English sentinel network. Up to 1000 people who present to participating practices with respiratory symptoms will be swabbed and tested with a rapid molecular POCT analyzer in the practice. Antimicrobial prescribing and other study outcomes will be collected by linking information from the POCT analyzer with data from the patient’s computerized medical record. We will collect data on how POCT is incorporated into practice using data flow diagrams, unified modeling language use case diagrams, and Business Process Modeling Notation. ResultsWe will present the crude and adjusted odds of antimicrobial prescribing (all antibiotics and antivirals) given a POCT diagnosis of influenza, stratifying by whether individuals have a respiratory or other relevant diagnosis (eg, bronchiectasis). We will also present the rates of hospital referrals and deaths related to influenza infection in PIAMS study practices compared with a set of matched practices in the sentinel network and the rest of the network. We will describe any difference in implementation models in terms of staff involved and workflow. ConclusionsThis study will generate data on the impact of POCT testing for influenza in primary care as well as help to inform about the feasibility of incorporating POCT into primary care workflows. It will inform the design of future larger studies about the effectiveness and cost-effectiveness of POCT to improve antimicrobial stewardship and any impact on severe outcomes. International Registered Report Identifier (IRRID)DERR1-10.2196/46938

Here, Simpson et al. analyze data from 3.6 million COVID-19 vaccine second doses (ChAdOx1 and BNT162b2) in Scotland for risk of thrombocytopenic, thromboembolic and hemorrhagic events. Borderline increased risks of immune thrombocytopenic purpura and cerebral venous sinus thrombosis were found for the ChAdOx1 vaccine. These events were rare and usually short-lived.

Abstract Background Influenza surveillance systems vary widely between countries and there is no framework to evaluate national surveillance systems in terms of data generation and dissemination. This study aimed to develop and test a comparative framework for European influenza surveillance. Methods Surveillance systems were evaluated qualitatively in five European countries (France, Germany, Italy, Spain, and the United Kingdom) by a panel of influenza experts and researchers from each country. Seven surveillance sub-systems were defined: non-medically attended community surveillance, virological surveillance, community surveillance, outbreak surveillance, primary care surveillance, hospital surveillance, mortality surveillance). These covered a total of 19 comparable outcomes of increasing severity, ranging from non-medically attended cases to deaths, which were evaluated using 5 comparison criteria based on WHO guidance (granularity, timing, representativeness, sampling strategy, communication) to produce a framework to compare the five countries. Results France and the United Kingdom showed the widest range of surveillance sub-systems, particularly for hospital surveillance, followed by Germany, Spain, and Italy. In all countries, virological, primary care and hospital surveillance were well developed, but non-medically attended events, influenza cases in the community, outbreaks in closed settings and mortality estimates were not consistently reported or published. The framework also allowed the comparison of variations in data granularity, timing, representativeness, sampling strategy, and communication between countries. For data granularity, breakdown per risk condition were available in France and Spain, but not in the United Kingdom, Germany and Italy. For data communication, there were disparities in the timeliness and accessibility of surveillance data. Conclusions This new framework can be used to compare influenza surveillance systems qualitatively between countries to allow the identification of structural differences as well as to evaluate adherence to WHO guidance. The framework may be adapted for other infectious respiratory diseases.

Chickenpox is a common childhood disease caused by varicella-zoster virus (VZV). VZV vaccination is not part of the UK childhood immunisation programme, but its potential inclusion is regularly assessed. It is therefore important to understand the ongoing burden of VZV in the community to inform vaccine policy decisions. General practitioner (GP) chickenpox consultations were studied from 1 September 2016 to 9 December 2022. Over the study period, the mean weekly chickenpox consultation rate per 100,000 population in England was 3.4, with a regular peak occurring between weeks 13 and 15. Overall, rates decreased over time, from a mean weekly rate of 5.5 in 2017 to 4.2 in 2019. The highest mean weekly rates were among children aged 1–4 years. There was no typical epidemic peak during the COVID-19 pandemic, but in 2022, rates were proportionally higher among children aged < 1 year old compared to pre-pandemic years. Chickenpox GP consultation rates decreased in England, continuing a longer-term decline in the community. The COVID-19 pandemic impacted rates, likely caused by the introduction of non-pharmaceutical interventions to prevent SARS-CoV-2 transmission. The lasting impact of the interruption of typical disease transmission remains to be seen, but it is important to monitor the chickenpox burden to inform decisions on vaccine programmes.

Abstract Background Frailty is a common condition in older adults and has a major impact on patient outcomes and service use. Information on the prevalence in middle-aged adults and the patterns of progression of frailty at an individual and population level is scarce. To address this, a cohort was defined from a large primary care database in England to describe the epidemiology of frailty and understand the dynamics of frailty within individuals and across the population. This article describes the structure of the dataset, cohort characteristics and planned analyses. Methods Retrospective cohort study using electronic health records. Participants were aged ≥50 years registered in practices contributing to the Oxford Royal College of General Practitioners Research and Surveillance Centre between 2006 to 2017. Data include GP practice details, patient sociodemographic and clinical characteristics, twice-yearly electronic Frailty Index (eFI), deaths, medication use and primary and secondary care health service use. Participants in each cohort year by age group, GP and patient characteristics at cohort entry are described. Results The cohort includes 2,177,656 patients, contributing 15,552,946 person-years, registered at 419 primary care practices in England. The mean age was 61 years, 52.1% of the cohort was female, and 77.6% lived in urban environments. Frailty increased with age, affecting 10% of adults aged 50–64 and 43.7% of adults aged ≥65. The prevalence of long-term conditions and specific frailty deficits increased with age, as did the eFI and the severity of frailty categories. Conclusion A comprehensive understanding of frailty dynamics will inform predictions of current and future care needs to facilitate timely planning of appropriate interventions, service configurations and workforce requirements. Analysis of this large, nationally representative cohort including participants aged ≥50 will capture earlier transitions to frailty and enable a detailed understanding of progression and impact. These results will inform novel simulation models which predict future health and service needs of older people living with frailty. Study registration Registered on www.clinicaltrials.gov October 25th 2019, NCT04139278 .

Abstract Background Valproate is a teratogenic drug that should be avoided during the preconception period and pregnancy. The aim was to explore general practitioners’ (GPs) prescription patterns over time, describe trends, and explore inter-practice variation within primary care. Methods We identified women of childbearing age (12–46 years old) in the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) sentinel network. We performed repeated cross-sectional analyses from 2004 to 2018 to determine rates of prescription and a retrospective cohort estimated the prevalence of use of valproate during pregnancy. Results In 2004, 0.31% (95% Confidence Interval (95%CI):0.18 to 0.44%) women were prescribed valproate, decreasing to 0.16% (95%CI:0.07 to 0.24%) by 2018. Among women with epilepsy, the rate fell from 15.2% (95%CI:14.4 to 16.0%) to 8.8% (95% CI:8.2 to 9.7%) over the same period. In 2018, almost two thirds (62.2%) of women who were prescribed valproate had epilepsy only, whereas bipolar disorder and migraine accounted for 15.8% and 7.4% respectively. Contraceptive prescriptions did not increase over time, and only in 2018 was there greater odds of being prescribed contraception (OR 1.41, 95%CI:1.08 to 1.45). Just under a fifth (19.7%) of women were prescribed valproate during their pregnancy; two out of three of these pregnancies were preceded by folic acid prescription (5 mg). While some practices reduced their rate of valproate prescription, others did not. Conclusions Regulatory guidelines have changed GPs' prescription patterns in women of childbearing potential for valproate but not for contraception. Further research is needed to identify the barriers of GPs and women of childbearing potential to undertaking contraception.

Introduction: Anemia is common in chronic kidney disease (CKD) and is associated with increased cardiovascular risk and reduced quality of life, but is often sub-optimally managed. Most patients are managed in primary care alongside other comorbidities. Interventions to improve the management of anemia in CKD in this setting are needed. Methods: We conducted a qualitative study to evaluate how an audit-based education (ABE) intervention might improve the management of anemia in CKD. We explored outcomes that would be relevant to practitioners and patients, that exposed variation of practice from National Institute for Health and Care Excellence (NICE) guidelines, and whether the intervention was feasible and acceptable. Results: Practitioners (n = 5 groups) and patients (n = 7) from 4 London general practices participated in discussions. Practitioners welcomed the evidence-based step-wise intervention. However, prescribing erythropoiesis-stimulating agents (ESAs) was felt to be outside of their scope of practice. There was a gap between NICE guidance and clinical practice in primary care. Iron studies were not well understood and anemia management was often conservative or delayed. Patients were often unaware of having CKD, and were more concerned about their other comorbidities, but largely trusted their GPs to manage them appropriately. Conclusions: The first steps of the intervention were welcomed by practitioners, but they expressed concerns about independently prescribing ESAs. Renal physicians and GPs could develop shared care protocols for ESA use in primary care. There is scope to improve awareness of renal anemia, and enhance knowledge of guideline recommendations; and our intervention should be modified accordingly.

BackgroundThe Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) is one of Europe’s oldest sentinel systems, working with the UK Health Security Agency (UKHSA) and its predecessor bodies for 55 years. Its surveillance report now runs twice weekly, supplemented by online observatories. In addition to conducting sentinel surveillance from a nationally representative group of practices, the RSC is now also providing data for syndromic surveillance. ObjectiveThe aim of this study was to describe the cohort profile at the start of the 2021-2022 surveillance season and recent changes to our surveillance practice. MethodsThe RSC’s pseudonymized primary care data, linked to hospital and other data, are held in the Oxford-RCGP Clinical Informatics Digital Hub, a Trusted Research Environment. We describe the RSC’s cohort profile as of September 2021, divided into a Primary Care Sentinel Cohort (PCSC)—collecting virological and serological specimens—and a larger group of syndromic surveillance general practices (SSGPs). We report changes to our sampling strategy that brings the RSC into alignment with European Centre for Disease Control guidance and then compare our cohort’s sociodemographic characteristics with Office for National Statistics data. We further describe influenza and COVID-19 vaccine coverage for the 2020-2021 season (week 40 of 2020 to week 39 of 2021), with the latter differentiated by vaccine brand. Finally, we report COVID-19–related outcomes in terms of hospitalization, intensive care unit (ICU) admission, and death. ResultsAs a response to COVID-19, the RSC grew from just over 500 PCSC practices in 2019 to 1879 practices in 2021 (PCSC, n=938; SSGP, n=1203). This represents 28.6% of English general practices and 30.59% (17,299,780/56,550,136) of the population. In the reporting period, the PCSC collected >8000 virology and >23,000 serology samples. The RSC population was broadly representative of the national population in terms of age, gender, ethnicity, National Health Service Region, socioeconomic status, obesity, and smoking habit. The RSC captured vaccine coverage data for influenza (n=5.4 million) and COVID-19, reporting dose one (n=11.9 million), two (n=11 million), and three (n=0.4 million) for the latter as well as brand-specific uptake data (AstraZeneca vaccine, n=11.6 million; Pfizer, n=10.8 million; and Moderna, n=0.7 million). The median (IQR) number of COVID-19 hospitalizations and ICU admissions was 1181 (559-1559) and 115 (50-174) per week, respectively. ConclusionsThe RSC is broadly representative of the national population; its PCSC is geographically representative and its SSGPs are newly supporting UKHSA syndromic surveillance efforts. The network captures vaccine coverage and has expanded from reporting primary care attendances to providing data on onward hospital outcomes and deaths. The challenge remains to increase virological and serological sampling to monitor the effectiveness and waning of all vaccines available in a timely manner.

Summary: Background: Smoking is attributed to both micro- and macrovascular complications at any stage of metabolic deregulation including prediabetes. Current global diabetes prevention programmes appear to be glucocentric, and do not fully acknowledge the ramifications of cardiorenal risk factors in smokers and ex-smokers. A more holistic approach is needed to prevent vascular complications in people with prediabetes and diabetes before and after quitting. Methods: A cross-sectional study was carried out on participants who agreed to take part in the UK Biobank dataset at the time of their first attendances between March 01, 2006, and December 31, 2010. Those who had their urinary albumin concentration (UAC) data available were included, and those who did not have this data, were excluded. A logistic regression model was fitted to explore the relationship between cardiorenal risk factors and albuminuria in people with prediabetes and diabetes, based on smoking status. Findings: A total of 502,490 participants were included in the UK Biobank dataset. Of them, 30.4% (n=152,896) had their UAC level recorded. Compared with non-smokers, the odds of albuminuria in smokers with prediabetes and diabetes were 1.21 (95% CI 1.05 – 1.39, p=0.009), and 1.26 (95% CI 1.10 – 1.44, p=0.001), respectively. The odds declined after quitting in both groups, but it was not statistically significant (p>0.05). Each unit increase in HbA1c was associated with equivalent increased odds of albuminuria in current and ex-smokers, OR 1.035 (95% CI 1.030 – 1.039, p

Introduction As new vaccines are developed more vaccine coadministrations vaccines are being offered to make delivery more practical for health systems and patients. We compared the safety of coadministered vaccines with separate vaccination for 20 coadministrations by considering nine types of adverse events following immunisation (AEFI).Methods Real-life immunisation and adverse event data for this observational cohort study were extracted from the Oxford-Royal College of General Practitioners Research and Surveillance Centre for children registered in the database between 2008 and 2018. We applied the self-controlled case series method to calculate relative incidence ratios (RIR) for AEFI. These RIRs compare the RI of AEFI following coadministration with the RI following separate administration of the same vaccines.Results We assessed 3 518 047 adverse events and included 5 993 290 vaccine doses given to 958 591 children. 17% of AEFI occurred less and 11% more frequently following coadministration than would have been expected based on the RIs following separate vaccinations, while there was no significant difference for 72% of AEFI. We found amplifying interaction effects for AEFI after five coadministrations comprising three vaccines: for fever (RIR 1.93 (95% CI 1.63 to 2.29)), rash (RIR 1.49 (95% CI 1.29 to 1.74)), gastrointestinal events (RIR 1.31 (95% CI 1.14 to 1.49)) and respiratory events (RIR 1.27 (1.17–1.38)) following DTaP/IPV/Hib+MenC+ PCV; gastrointestinal events (RIR 1.65 (95% CI 1.35 to 2.02)) following DTaP/IPV/Hib+MenC+ RV; fever (RIR 1.44 (95% CI 1.09 to 1.90)) and respiratory events (RIR 1.40 (95% CI 1.25 to 1.57)) following DTaP/IPV/Hib+PCV+ RV; gastrointestinal (RIR 1.48 (95% CI 1.20 to 1.82)) and respiratory events (RIR 1.43 (95% CI 1.26 to 1.63)) following MMR+Hib/MenC+PCV; gastrointestinal events (RIR 1.68 (95% CI 1.07 to 2.64)) and general symptoms (RIR 11.83 (95% CI 1.28 to 109.01)) following MMR+MenC+PCV. Coadministration of MMR+PCV led to more fever (RIR 1.91 (95% CI 1.83 to 1.99)), neurological events (RIR 2.04 (95% CI 1.67 to 2.49)) and rash (RIR 1.06 (95% CI 1.01 to 1.11)) compared with separate administration, DTaP/IPV/Hib+MMR to more musculoskeletal events (RIR 3.56 (95% CI 1.21 to 10.50)) and MMR+MenC to more fever (RIR 1.58 (95% CI 1.37 to 1.82)). There was no indication that unscheduled coadministrations are less safe than scheduled coadministrations.Conclusion Real-life RIRs of AEFI justify coadministering routine childhood vaccines according to the immunisation schedule. Further research into the severity of AEFI following coadministration is required for a complete understanding of the burden of these AEFI.

Abstract Background Sodium-glucose co-transporter-2 inhibitors (SGLT-2is) are licenced for initiation for glucose lowering in people with type 2 diabetes (T2DM) with an estimated glomerular filtration rate (eGFR) ≥ 60 mL/min/1.73m2). However, recent trial data have shown that these medications have renal and cardio-protective effects, even for impaired kidney function. The extent to which trial evidence and updated guidelines have influenced real-world prescribing of SGLT-2is is not known, particularly with co-administration of diuretics. Methods We performed a cross-sectional analysis of people with T2DM registered with practices in the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) database on the 31st July 2019. We calculated the percentage of people prescribed SGLT-2is according to eGFR categories (

BackgroundThe COVID-19 pandemic has resulted in an unprecedented impact on the day-to-day lives of people, with several features potentially adversely affecting mental health. There is growing evidence of the size of the impact of COVID-19 on mental health, but much of this is from ongoing population surveys using validated mental health scores. ObjectiveThis study investigated the impact of the pandemic and control measures on mental health conditions presenting to a spectrum of national health care services monitored using real-time syndromic surveillance in England. MethodsWe conducted a retrospective observational descriptive study of mental health presentations (those calling the national medical helpline, National Health Service [NHS] 111; consulting general practitioners [GPs] in and out-of-hours; calling ambulance services; and attending emergency departments) from January 1, 2019, to September 30, 2020. Estimates for the impact of lockdown measures were provided using an interrupted time series analysis. ResultsMental health presentations showed a marked decrease during the early stages of the pandemic. Postlockdown, attendances for mental health conditions reached higher than prepandemic levels across most systems—a rise of 10% compared to that expected for NHS 111 and 21% for GP out-of-hours service—while the number of consultations to GP in-hours service was 13% lower compared to the same time previous year. Increases were observed in calls to NHS 111 for sleep problems. ConclusionsThese analyses showed marked changes in the health care attendances and prescribing for common mental health conditions across a spectrum of health care provision, with some of these changes persisting. The reasons for such changes are likely to be complex and multifactorial. The impact of the pandemic on mental health may not be fully understood for some time, and therefore, these syndromic indicators should continue to be monitored.

BackgroundFollowing COVID-19, up to 40% of people have ongoing health problems, referred to as postacute COVID-19 or long COVID (LC). LC varies from a single persisting symptom to a complex multisystem disease. Research has flagged that this condition is underrecorded in primary care records, and seeks to better define its clinical characteristics and management. Phenotypes provide a standard method for case definition and identification from routine data and are usually machine-processable. An LC phenotype can underpin research into this condition. ObjectiveThis study aims to develop a phenotype for LC to inform the epidemiology and future research into this condition. We compared clinical symptoms in people with LC before and after their index infection, recorded from March 1, 2020, to April 1, 2021. We also compared people recorded as having acute infection with those with LC who were hospitalized and those who were not. MethodsWe used data from the Primary Care Sentinel Cohort (PCSC) of the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) database. This network was recruited to be nationally representative of the English population. We developed an LC phenotype using our established 3-step ontological method: (1) ontological step (defining the reasoning process underpinning the phenotype, (2) coding step (exploring what clinical terms are available, and (3) logical extract model (testing performance). We created a version of this phenotype using Protégé in the ontology web language for BioPortal and using PhenoFlow. Next, we used the phenotype to compare people with LC (1) with regard to their symptoms in the year prior to acquiring COVID-19 and (2) with people with acute COVID-19. We also compared hospitalized people with LC with those not hospitalized. We compared sociodemographic details, comorbidities, and Office of National Statistics–defined LC symptoms between groups. We used descriptive statistics and logistic regression. ResultsThe long-COVID phenotype differentiated people hospitalized with LC from people who were not and where no index infection was identified. The PCSC (N=7.4 million) includes 428,479 patients with acute COVID-19 diagnosis confirmed by a laboratory test and 10,772 patients with clinically diagnosed COVID-19. A total of 7471 (1.74%, 95% CI 1.70-1.78) people were coded as having LC, 1009 (13.5%, 95% CI 12.7-14.3) had a hospital admission related to acute COVID-19, and 6462 (86.5%, 95% CI 85.7-87.3) were not hospitalized, of whom 2728 (42.2%) had no COVID-19 index date recorded. In addition, 1009 (13.5%, 95% CI 12.73-14.28) people with LC were hospitalized compared to 17,993 (4.5%, 95% CI 4.48-4.61; P

BackgroundMost studies of long COVID (symptoms of COVID-19 infection beyond 4 weeks) have focused on people hospitalized in their initial illness. Long COVID is thought to be underrecorded in UK primary care electronic records. ObjectiveWe sought to determine which symptoms people present to primary care after COVID-19 infection and whether presentation differs in people who were not hospitalized, as well as post–long COVID mortality rates. MethodsWe used routine data from the nationally representative primary care sentinel cohort of the Oxford–Royal College of General Practitioners Research and Surveillance Centre (N=7,396,702), applying a predefined long COVID phenotype and grouped by whether the index infection occurred in hospital or in the community. We included COVID-19 infection cases from March 1, 2020, to April 1, 2021. We conducted a before-and-after analysis of long COVID symptoms prespecified by the Office of National Statistics, comparing symptoms presented between 1 and 6 months after the index infection matched with the same months 1 year previously. We conducted logistic regression analysis, quoting odds ratios (ORs) with 95% CIs. ResultsIn total, 5.63% (416,505/7,396,702) and 1.83% (7623/416,505) of the patients had received a coded diagnosis of COVID-19 infection and diagnosis of, or referral for, long COVID, respectively. People with diagnosis or referral of long COVID had higher odds of presenting the prespecified symptoms after versus before COVID-19 infection (OR 2.66, 95% CI 2.46-2.88, for those with index community infection and OR 2.42, 95% CI 2.03-2.89, for those hospitalized). After an index community infection, patients were more likely to present with nonspecific symptoms (OR 3.44, 95% CI 3.00-3.95; P

BackgroundThe Data and Connectivity COVID-19 Vaccines Pharmacovigilance (DaC-VaP) UK-wide collaboration was created to monitor vaccine uptake and effectiveness and provide pharmacovigilance using routine clinical and administrative data. To monitor these, pooled analyses may be needed. However, variation in terminologies present a barrier as England uses the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), while the rest of the United Kingdom uses the Read v2 terminology in primary care. The availability of data sources is not uniform across the United Kingdom. ObjectiveThis study aims to use the concept mappings in the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) to identify common concepts recorded and to report these in a repeated cross-sectional study. We planned to do this for vaccine coverage and 2 adverse events of interest (AEIs), cerebral venous sinus thrombosis (CVST) and anaphylaxis. We identified concept mappings to SNOMED CT, Read v2, the World Health Organization’s International Classification of Disease Tenth Revision (ICD-10) terminology, and the UK Dictionary of Medicines and Devices (dm+d). MethodsExposures and outcomes of interest to DaC-VaP for pharmacovigilance studies were selected. Mappings of these variables to different terminologies used across the United Kingdom’s devolved nations’ health services were identified from the Observational Health Data Sciences and Informatics (OHDSI) Automated Terminology Harmonization, Extraction, and Normalization for Analytics (ATHENA) online browser. Lead analysts from each nation then confirmed or added to the mappings identified. These mappings were then used to report AEIs in a common format. We reported rates for windows of 0-2 and 3-28 days postvaccine every 28 days. ResultsWe listed the mappings between Read v2, SNOMED CT, ICD-10, and dm+d. For vaccine exposure, we found clear mapping from OMOP to our clinical terminologies, though dm+d had codes not listed by OMOP at the time of searching. We found a list of CVST and anaphylaxis codes. For CVST, we had to use a broader cerebral venous thrombosis conceptual approach to include Read v2. We identified 56 SNOMED CT codes, of which we selected 47 (84%), and 15 Read v2 codes. For anaphylaxis, our refined search identified 60 SNOMED CT codes and 9 Read v2 codes, of which we selected 10 (17%) and 4 (44%), respectively, to include in our repeated cross-sectional studies. ConclusionsThis approach enables the use of mappings to different terminologies within the OMOP CDM without the need to catalogue an entire database. However, Read v2 has less granular concepts than some terminologies, such as SNOMED CT. Additionally, the OMOP CDM cannot compensate for limitations in the clinical coding system. Neither Read v2 nor ICD-10 is sufficiently granular to enable CVST to be specifically flagged. Hence, any pooled analysis will have to be at the less specific level of cerebrovascular venous thrombosis. Overall, the mappings within this CDM are useful, and our method could be used for rapid collaborations where there are only a limited number of concepts to pool.

BackgroundRespiratory syncytial virus (RSV) commonly causes lower respiratory tract infections and hospitalization in children. In 2019-2020, the Europe-wide RSV ComNet standardized study protocol was developed to measure the clinical and socioeconomic disease burden of RSV infections among children aged

BackgroundSodium-glucose cotransporter-2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1RAs) are both considered to be part of standard care in the management of glycemia in type 2 diabetes. Recent trial evidence has indicated benefits on primary kidney end points for individual drugs within each medication class. Despite the potential benefits of combining SGLT2is and GLP-1RAs for glycemia management, according to national and international guideline recommendations, there is currently limited data on kidney end points for this drug combination. ObjectiveThe aims of the study are to assess the real-world effects of combination SGLT2i and GLP-1RA therapies for diabetes management on kidney end points, glycemic control, and weight in people with type 2 diabetes who are being treated with renin-angiotensin system blockade medication. MethodsThis retrospective cohort study will use the electronic health records of people with type 2 diabetes that are registered with general practices covering over 15 million people in England and Wales and are included in the Oxford-Royal College of General Practitioners Research and Surveillance Centre network. A propensity score–matched cohort of prevalent new users of SGLT2is and GLP-1RAs and those who have been prescribed SGLT2is and GLP-1RAs in combination will be identified. They will be matched based on drug histories, comorbidities, and demographics. A repeated-measures, multilevel, linear regression analysis will be performed to compare the mean change (from baseline) in estimated glomerular filtration rate at 12 and 24 months between those who switched to combined therapy and those continuing monotherapy with an SGLT2i or GLP-1RA. The secondary end points will be albuminuria, serum creatinine level, glycated hemoglobin level, and BMI. These will also be assessed for change at the 12- and 24-month follow-ups. ResultsThe study is due to commence in March 2022 and is expected to be complete by September 2022. ConclusionsOur study will be the first to assess the impact of combination SGLT2i and GLP-1RA therapy in type 2 diabetes on primary kidney end points from a real-world perspective. International Registered Report Identifier (IRRID)PRR1-10.2196/34206

BackgroundGeneral Practitioners (GPs) report high levels of burnout, job dissatisfaction, and turnover intention. The complexity of presenting problems to general practice makes diagnostic uncertainty a common occurrence that has been linked to burnout. The interrelationship between diagnostic uncertainty with other factors such as burnout, job satisfaction and turnover intention have not been previously examined.ObjectivesTo examine associations between diagnostic uncertainty, emotional exhaustion (EE), depersonalization (DP), job satisfaction, and turnover intention in GPs.MethodsSeventy general practices in England were randomly selected through the Oxford-Royal College of General Practitioners Research and Surveillance Centre (RCGP-RSC). A total of 348 GPs within 67 these practices completed a 10-item online questionnaire which included questions on GP characteristics, work-life balance, job satisfaction, sickness presenteeism, diagnostic uncertainty, turnover intention as well as EE and DP. Associations between diagnostic uncertainty and each of EE, DP, job satisfaction, and turnover intention were evaluated in multivariate mixed-effect ordinal logistic regressions whilst adjusting for covariates, to account for the correlation in the three outcomes of interest.ResultsAlmost one-third of GPs (n = 101; 29%) reported experiencing >10% of diagnostic uncertainty in their day-to-day practice over the past year. GPs reporting greater diagnostic uncertainty had higher levels of EE [OR = 3.90; 95% CI = (2.54, 5.99)], job dissatisfaction [OR = 2.01; 95% CI = (1.30, 3.13)] and turnover intention [OR = 4.51; 95% CI = (2.86, 7.11)]. GPs with no sickness presenteeism had lower levels of EE [OR = 0.53; 95% CI = (0.35, 0.82)], job dissatisfaction [OR = 0.56; 95% CI = (0.35, 0.88)], and turnover intention [OR = 0.61; 95% CI = (0.41, 0.91)].ConclusionDiagnostic uncertainty may not only negatively impact on the wellbeing of GPs, but could also have adverse implications on workforce retention in primary care.

Abstract Background The aim of RApid community Point-of-care Testing fOR COVID-19 (RAPTOR-C19) is to assess the diagnostic accuracy of multiple current and emerging point-of-care tests (POCTs) for active and past SARS-CoV2 infection in the community setting. RAPTOR-C19 will provide the community testbed to the COVID-19 National DiagnOstic Research and Evaluation Platform (CONDOR). Methods RAPTOR-C19 incorporates a series of prospective observational parallel diagnostic accuracy studies of SARS-CoV2 POCTs against laboratory and composite reference standards in patients with suspected current or past SARS-CoV2 infection attending community settings. Adults and children with suspected current SARS-CoV2 infection who are having an oropharyngeal/nasopharyngeal (OP/NP) swab for laboratory SARS-CoV2 reverse transcriptase Digital/Real-Time Polymerase Chain Reaction (d/rRT-PCR) as part of clinical care or community-based testing will be invited to participate. Adults (≥ 16 years) with suspected past symptomatic infection will also be recruited. Asymptomatic individuals will not be eligible. At the baseline visit, all participants will be asked to submit samples for at least one candidate point-of-care test (POCT) being evaluated (index test/s) as well as an OP/NP swab for laboratory SARS-CoV2 RT-PCR performed by Public Health England (PHE) (reference standard for current infection). Adults will also be asked for a blood sample for laboratory SARS-CoV-2 antibody testing by PHE (reference standard for past infection), where feasible adults will be invited to attend a second visit at 28 days for repeat antibody testing. Additional study data (e.g. demographics, symptoms, observations, household contacts) will be captured electronically. Sensitivity, specificity, positive, and negative predictive values for each POCT will be calculated with exact 95% confidence intervals when compared to the reference standard. POCTs will also be compared to composite reference standards constructed using paired antibody test results, patient reported outcomes, linked electronic health records for outcomes related to COVID-19 such as hospitalisation or death, and other test results. Discussion High-performing POCTs for community use could be transformational. Real-time results could lead to personal and public health impacts such as reducing onward household transmission of SARS-CoV2 infection, improving surveillance of health and social care staff, contributing to accurate prevalence estimates, and understanding of SARS-CoV2 transmission dynamics in the population. In contrast, poorly performing POCTs could have negative effects, so it is necessary to undertake community-based diagnostic accuracy evaluations before rolling these out. Trial registration ISRCTN, ISRCTN14226970

Introduction Through the INTernational ConsoRtium of Primary Care BIg Data Researchers (INTRePID), we compared the pandemic impact on the volume of primary care visits and uptake of virtual care in Australia, Canada, China, Norway, Singapore, South Korea, Sweden, the UK and the USA.Methods Visit definitions were agreed on centrally, implemented locally across the various settings in INTRePID countries, and weekly visit counts were shared centrally for analysis. We evaluated the weekly rate of primary care physician visits during 2019 and 2020. Rate ratios (RRs) of total weekly visit volume and the proportion of weekly visits that were virtual in the pandemic period in 2020 compared with the same prepandemic period in 2019 were calculated.Results In 2019 and 2020, there were 80 889 386 primary care physician visits across INTRePID. During the pandemic, average weekly visit volume dropped in China, Singapore, South Korea, and the USA but was stable overall in Australia (RR 0.98 (95% CI 0.92 to 1.05, p=0.59)), Canada (RR 0.96 (95% CI 0.89 to 1.03, p=0.24)), Norway (RR 1.01 (95% CI 0.88 to 1.17, p=0.85)), Sweden (RR 0.91 (95% CI 0.79 to 1.06, p=0.22)) and the UK (RR 0.86 (95% CI 0.72 to 1.03, p=0.11)). In countries that had negligible virtual care prepandemic, the proportion of visits that were virtual were highest in Canada (77.0%) and Australia (41.8%). In Norway (RR 8.23 (95% CI 5.30 to 12.78, p

Introduction Long COVID, a new condition whose origins and natural history are not yet fully established, currently affects 1.5 million people in the UK. Most do not have access to specialist long COVID services. We seek to optimise long COVID care both within and outside specialist clinics, including improving access, reducing inequalities, helping self-management and providing guidance and decision support for primary care. We aim to establish a ‘gold standard’ of care by systematically analysing current practices, iteratively improving pathways and systems of care.Methods and analysis This mixed-methods, multisite study is informed by the principles of applied health services research, quality improvement, co-design, outcome measurement and learning health systems. It was developed in close partnership with patients (whose stated priorities are prompt clinical assessment; evidence-based advice and treatment and help with returning to work and other roles) and with front-line clinicians. Workstreams and tasks to optimise assessment, treatment and monitoring are based in three contrasting settings: workstream 1 (qualitative research, up to 100 participants), specialist management in 10 long COVID clinics across the UK, via a quality improvement collaborative, experience-based co-design and targeted efforts to reduce inequalities of access, return to work and peer support; workstream 2 (quantitative research, up to 5000 participants), patient self-management at home, technology-supported monitoring and validation of condition-specific outcome measures and workstream 3 (quantitative research, up to 5000 participants), generalist management in primary care, harnessing electronic record data to study population phenotypes and develop evidence-based decision support, referral pathways and analysis of costs. Study governance includes an active patient advisory group.Ethics and dissemination LOng COvid Multidisciplinary consortium Optimising Treatments and servIces acrOss the NHS study is sponsored by the University of Leeds and approved by Yorkshire & The Humber—Bradford Leeds Research Ethics Committee (ref: 21/YH/0276). Participants will provide informed consent. Dissemination plans include academic and lay publications, and partnerships with national and regional policymakers.Trial registration number NCT05057260, ISRCTN15022307.

BackgroundSocial distancing and other nonpharmaceutical interventions to reduce the spread of COVID-19 infection in the United Kingdom have led to substantial changes in delivering ongoing care for patients with chronic conditions, including type 2 diabetes mellitus (T2DM). Clinical guidelines for the management and prevention of complications for people with T2DM delivered in primary care services advise routine annual reviews and were developed when face-to-face consultations were the norm. The shift in consultations from face-to-face to remote consultations caused a reduction in direct clinical contact and may impact the process of care for people with T2DM. ObjectiveThe aim of this study is to explore the impact of the COVID-19 pandemic’s first year on the monitoring of people with T2DM using routine annual reviews from a national primary care perspective in England. MethodsA retrospective cohort study of adults with T2DM will be performed using routinely collected primary care data from the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC). We will describe the change in the rate of monitoring of hemoglobin A1c (HbA1c) between the first year of the COVID-19 pandemic (2020) and the preceding year (2019). We will also report any change in the eight checks that make up the components of these reviews. The change in HbA1c monitoring rates will be determined using a multilevel logistic regression model, adjusting for patient and practice characteristics, and similarly, the change in a composite measure of the completeness of all eight checks will be modeled using ordinal regression. The models will be adjusted for the following patient-level variables: age, gender, socioeconomic status, ethnicity, COVID-19 shielding status, duration of diabetes, and comorbidities. The model will also be adjusted for the following practice-level variables: urban versus rural, practice size, Quality and Outcomes Framework achievement, the National Health Service region, and the proportion of face-to-face consultations. Ethical approval was provided by the University of Oxford Medical Sciences Interdivisional Research Ethics Committee (September 2, 2021, reference R77306/RE001). ResultsThe analysis of the data extract will include 3.96 million patients with T2DM across 700 practices, which is 6% of the available Oxford-RCGP RSC adult population. The preliminary results will be submitted to a conference under the domain of primary care. The resulting publication will be submitted to a peer-reviewed journal on diabetes and endocrinology. ConclusionsThe COVID-19 pandemic has impacted the delivery of care, but little is known about the process of caring for people with T2DM. This study will report the impact of the COVID-19 pandemic on these processes of care. International Registered Report Identifier (IRRID)DERR1-10.2196/35971