Health outcome priorities of people with multiple long-term conditions before and during the COVID-19 pandemic: Survey data from the UK (preprint)

Background The outcome prioritisation tool (OPT) is a simple tool to ascertain the health outcome priorities of people with MLTC. Use of this tool in people aged under 65 years with MLTC has not previously been investigated. This study investigated the feasibility of using the OPT in people with MLTC aged 45 years or above, in a multi-ethnic primary-care setting, to describe the health outcome priorities of people with MLTC by age, clusters of long-term conditions and demographic factors, and to investigate any differences in prioritisation in light of the COVID-19 pandemic. Methods This was a multi-centre cross-sectional study using a questionnaire for online self-completion by people aged 45 years or above with MLTC in 19 primary care settings across the East Midlands, UK. Participants were asked to complete the OPT twice, first from their current perspective and second from their recollection of their priorities prior to COVID-19. Results The questionnaire was completed by 2,454 people with MLTC. The majority of participants agreed or strongly agreed that the OPT was easy to complete, relevant to their healthcare and will be useful in communicating priorities to their doctor. Summary scores for the whole cohort of participants showed Keeping Alive and Maintaining Independence receiving the highest scores. Statistically significant differences in prioritisation by age, clusters of long-term conditions and employment status were observed, with respondents aged over 65 most likely to prioritise Maintaining independence, and respondents aged under 65 most likely to prioritise Keeping alive. There were no differences before or after COVID-19, or by ethnicity. Conclusions The OPT is feasible and acceptable for use to elicit the health outcome priorities of people with MLTC across both middle-aged and older age groups and in a UK setting. Individual factors could influence the priorities of people with MLTC and must be considered by clinicians during consultations.

Long-term cardiovascular safety of COVID-19 vaccination according to brand, dose and combinations: Cohort study of 46 million adults in England (preprint)

Using longitudinal health records from 45.7 million adults in England followed for a year, our study compared the incidence of thrombotic and cardiovascular complications after first, second and booster doses of brands and combinations of COVID-19 vaccines used during the first two years of the UK vaccination program with the incidence before or without the corresponding vaccination. The incidence of common arterial thrombotic events (mainly acute myocardial infarction and ischaemic stroke) was generally lower after each vaccine dose, brand and combination. Similarly, the incidence of common venous thrombotic events, (mainly pulmonary embolism and lower limb deep venous thrombosis) was lower after vaccination. There was a higher incidence of previously reported rare harms after vaccination: vaccine-induced thrombotic thrombocytopenia after first ChAdOx1 vaccination, and myocarditis and pericarditis after first, second and transiently after booster mRNA vaccination (BNT-162b2 and mRNA- 1273) These findings support the wide uptake of future COVID-19 vaccination programs.

Weight trends amongst adults with diabetes or hypertension during the COVID-19 pandemic: an observational study using OpenSAFELY (preprint)

AimsTo describe patterns of weight change amongst adults living in England with Type 2 Diabetes (T2D) and/or hypertension during the COVID-19 pandemic. Design and SettingWith the approval of NHS England, we conducted an observational cohort study using the routinely collected health data of approximately 40% of adults living in England, accessed through the OpenSAFELY service inside TPP. MethodWe estimated individual rates of weight gain during the pandemic ({delta}). We then estimated associations between clinical and sociodemographic characteristics and rapid weight gain (>0.5kg/m2/year) using multivariable logistic regression. ResultsWe extracted data on adults with T2D (n=1,231,455, 44% female, 76% white British) or hypertension (n=3,558,405, 50% female, 84% white British). Adults with T2D lost weight overall (median {delta} = -0.1kg/m2/year [IQR: -0.7, 0.4]), however, rapid weight gain was common (20.7%) and associated with sex (male vs female: aOR 0.78[95%CI 0.77, 0.79]); age, older age reduced odds (e.g. 60-69-year-olds vs 18-29-year-olds: aOR 0.66[0.61, 0.71]); deprivation, (least-deprived-IMD vs most-deprived-IMD: aOR 0.87[0.85, 0.89]); white ethnicity (Black vs White: aOR 0.70[0.69, 0.71]); mental health conditions (e.g. depression: aOR 1.13 [1.12, 1.15]); and diabetes treatment (non-insulin treatment vs no pharmacological treatment: aOR 0.68[0.67, 0.69]). Adults with hypertension maintained stable weight overall (median {delta} = 0.0kg/m2/year [-0.6, 0.5]), however, rapid weight gain was common (24.7%) and associated with similar characteristics as in T2D. ConclusionAmongst adults living in England with T2D and/or hypertension, rapid pandemic weight gain was more common amongst females, younger adults, those living in more deprived areas, and those with mental health conditions. How this fits inPrevious studies, in the general population, have reported female sex, deprivation and comorbid mental health conditions increased risk of unhealthy weight gain during the pandemic, but it is not clear whether people living with hypertensions and/or type 2 diabetes experienced the same trends. We found that, during the pandemic, adults with hypertension maintained a stable weight whilst those with type 2 diabetes lost weight overall. However, underlying these overall trends, rapid weight gain was common amongst people with type 2 diabetes (20.7%) or hypertension (24.7%)), with female sex, younger age, deprivation, and comorbid mental health conditions associated with an increased odds of rapid weight gain in both populations. We have identified clinical and sociodemographic characteristics of individuals with hypertension and/or type 2 diabetes who could benefit from primary care interventions on weight and health behaviours to combat health inequalities in patterns of weight gain that were exacerbated by the pandemic.

A nationwide study of 331 rare diseases among 58 million individuals: prevalence, demographics, and COVID-19 outcomes (preprint)

Background: The Global Burden of Disease study has provided key evidence to inform clinicians, researchers, and policy makers across common diseases, but no similar effort with single study design exists for hundreds of rare diseases. Consequently, many rare conditions lack population-level evidence including prevalence and clinical vulnerability. This has led to the absence of evidence-based care for rare diseases, prominently in the COVID-19 pandemic. Method: This study used electronic health records (EHRs) of more than 58 million people in England, linking nine National Health Service datasets spanning healthcare settings for people alive on Jan 23, 2020. Starting with all rare diseases listed in Orphanet, we quality assured and filtered down to analyse 331 conditions with ICD-10 or SNOMED-CT mappings clinically validated in our dataset. We report 1) population prevalence, clinical and demographic details of rare diseases, and 2) investigate differences in mortality with SARs-CoV-2. Findings: Among 58,162,316 individuals, we identified 894,396 with at least one rare disease. Prevalence data in Orphanet originates from various sources with varying degrees of precision. Here we present reproducible age and gender-adjusted estimates for all 331 rare diseases, including first estimates for 186 (56.2%) without any reported prevalence estimate in Orphanet. We identified 49 rare diseases significantly more frequent in females and 62 in males. Similarly we identified 47 rare diseases more frequent in Asian as compared to White ethnicity and 22 with higher Black to white ratios as compared to similar ratios in population controls. 37 rare diseases were overrepresented in the white population as compared to both Black and Asian ethnicities. In total, 7,965 of 894,396 (0.9%) of rare-disease patients died from COVID-19, as compared to 141,287 of 58,162,316 (0.2%) in the full study population. Eight rare diseases had significantly increased risks for COVID-19-related mortality in fully vaccinated individuals, with bullous pemphigoid (8.07[3.01-21.62]) being worst affected. Interpretation: Our study highlights that National-scale EHRs provide a unique resource to estimate detailed prevalence, clinical and demographic data for rare diseases. Using COVID-19-related mortality analysis, we showed the power of large-scale EHRs in providing insights to inform public health decision-making for these often neglected patient populations.

Ethnic inequalities among NHS staff in England - workplace experiences during the COVID-19 pandemic (preprint)

ObjectivesTo determine how workplace experiences of NHS staff varied by ethnic group during the COVID-19 pandemic and examine how these experiences are associated with mental and physical health at the time of the study. MethodsAn online Inequalities Survey was conducted by the TIDES study (Tackling Inequalities and Discrimination Experiences in health Services) in collaboration with NHS CHECK. This Inequalities Survey collected measures relating to workplace experiences (such as personal protective equipment (PPE), risk assessments, redeployments, and discrimination) as well as mental health, and physical health from NHS staff working in the 18 trusts participating with the NHS CHECK study between February and October 2021 (N=4622). ResultsRegression analysis revealed that staff from Black and Mixed/Other ethnic groups had greater odds of experiencing workplace harassment (adjusted odds ratio (AOR) = 2.43 [1.56-3.78] and 2.38 [1.12-5.07], respectively) and discrimination (AOR = 4.36 [2.73-6.96], and 3.94 [1.67-9.33], respectively) compared to White British staff. Staff from black ethnic groups also had greater odds than White British staff of reporting PPE unavailability (AOR = 2.16 [1.16-4.00]). Such workplace experiences were associated with negative physical and mental health outcomes, though this association varied by ethnicity. Conversely, understanding employment rights around redeployment, being informed about, and having the ability to inform redeployment decisions were associated with lower odds of poor health outcomes. ConclusionsStructural changes to the way staff from ethnically minoritised groups are supported, and how their complaints are addressed by leaders within the NHS are urgently required to address racism and inequalities in the NHS. Policy implicationsMaintaining transparency and implementing effective mechanisms for addressing poor working conditions, harassment, and discrimination is crucial in the NHS. This can be achieved through appointing a designated staff member, establishing a tracking system, and training HR managers in identifying and handling reports of racial discrimination. Incorporating diversity and inclusion considerations into professional development activities and providing staff with opportunities to actively participate in decision-making can also benefit their health. The NHS Workforce Race Equality Standard may need to broaden its scope to assess race equality effectively.

Trends in weight gain recorded in English primary care before and during the Coronavirus-19 pandemic: an observational cohort study using the OpenSAFELY platform (preprint)

Background We investigated which clinical and sociodemographic characteristics were associated with unhealthy patterns of weight gain amongst adults living in England during the pandemic. Methods With the approval of NHS England we conducted an observational cohort study of Body Mass Index (BMI) changes between March 2015 and March 2022 using the OpenSAFELY-TPP platform. We estimated individual rates of weight gain before and during the pandemic, and identified individuals with rapid weight gain (>0.5kg/m2/year) in each period. We also estimated the change in rate of weight gain between the prepandemic and pandemic period and defined extreme-accelerators as the ten percent of individuals with the greatest increase (>1.84kg/m2/year). We estimated associations with these outcomes using multivariate logistic regression. Findings We extracted data on 17,742,365 adults (50.1% female, 76.1% White British). Median BMI increased from 27.8kg/m2[IQR:24.3 to 32.1] in 2019 (March 2019 to February 2020) to 28.0kg/m2 [24.4 to 32.6] in 2021. Rapid pandemic weight gain (n=3,214,155) was associated with female sex (male vs female: aOR 0.76 [95%CI:0.76 to 0.76]); younger age (50 to 59 years vs 18 to 29 years: aOR 0.60 [0.60 to 0.61]); White British ethnicity (Black Caribbean vs White British: aOR 0.91 [0.89 to 0.94]); deprivation (least-deprived-IMD-quintile vs most-deprived:aOR 0.77 [0.77 to 0.78]); and long-term conditions, of which mental health conditions had the greatest effect (e.g. depression (aOR 1.18[1.17 to 1.18])). Similar characteristics increased risk of extreme acceleration (n=2,768,695). Interpretation We found female sex, younger age, deprivation and mental health conditions increased risk of unhealthy patterns of pandemic weight gain. This highlights the need to incorporate sociodemographic, physical, and mental health characteristics when formulating post-pandemic research, policies, and interventions targeting BMI. Funding NIHR

Employment outcomes of people with Long Covid symptoms: community-based cohort study (preprint)

Background: Evidence on the long-term employment consequences of SARS-CoV-2 infection is lacking. We used data from a large, community-based sample in the UK to estimate associations between Long Covid and subsequent employment outcomes. Methods: This was an observational, longitudinal study using a pre-post design. We included UK COVID-19 Infection Survey participants who completed questionnaires on Long Covid from 3 February 2021 to 30 September 2022 when they were aged 16 to 64 years and not in full-time education. We used conditional logit modelling to explore the time-varying relationship between Long Covid status [≥]12 weeks after a first test-confirmed SARS-CoV-2 infection (reference: pre-infection) and labour market inactivity (neither working nor looking for work) or workplace absence lasting [≥]4 weeks. Results: Of 206,299 included participants (mean age 45 years, 54% female, 92% white), 15% were ever inactive in the labour market and 10% were ever long-term absent during follow-up. Compared with pre-infection, inactivity was higher in participants reporting Long Covid 30 to <40 weeks (adjusted odds ratio (aOR): 1.45; 95% CI: 1.17 to 1.81) or 40 to <52 weeks (1.34; 1.05 to 1.72) post-infection. Compared with pre-infection, reporting Long Covid was also associated with increased odds of long-term absence 18 to <24 weeks (1.40; 1.04 to 1.90) and 24 to <30 weeks (1.45; 1.03 to 2.04) post-infection, but not beyond 30 weeks. Combining with official statistics on Long Covid prevalence, our estimates translate to 27,000 (95% CI: 6,000 to 47,000) working-age adults in the UK being inactive because of their Long Covid symptoms in July 2022. Conclusions: Long Covid is likely to have contributed to reduced levels of participation in the UK labour market, though it is unlikely to be the sole driver. Further research is required to quantify the contribution of other factors, such as indirect health effects of the pandemic.

Antipsychotic prescribing and mortality in people with dementia before and during the COVID-19 pandemic: retrospective cohort study (preprint)

Background: Antipsychotic drugs have been associated with increased mortality, stroke and myocardial infarction in people with dementia. Concerns have been raised that antipsychotic prescribing may have increased during the COVID-19 pandemic due to social restrictions imposed to limit the spread of the virus. We used multisource, routinely-collected healthcare data from Wales, UK, to investigate prescribing and mortality trends in people with dementia before and during the COVID-19 pandemic. Methods: We used individual-level, anonymised, population-scale linked health data to identify adults aged >=60 years with a diagnosis of dementia in Wales, UK. We explored antipsychotic prescribing trends over 67 months between 1st January 2016 and 1st August 2021, overall and stratified by age and dementia subtype. We used time series analyses to examine all-cause, myocardial infarction (MI) and stroke mortality over the study period and identified the leading causes of death in people with dementia. Findings: Of 57,396 people with dementia, 11,929 (21%) were prescribed an antipsychotic at any point during follow-up. Accounting for seasonality, antipsychotic prescribing increased during the second half of 2019 and throughout 2020. However, the absolute difference in prescribing rates was small, ranging from 1253 to 1305 per 10,000 person-months. Prescribing in the 60-64 age group and those with Alzheimer's disease increased throughout the 5-year period. All-cause and stroke mortality increased in the second half of 2019 and throughout 2020 but MI mortality declined. From January 2020, COVID-19 was the second commonest underlying cause of death in people with dementia. Interpretation: During the COVID-19 pandemic there was a small increase in antipsychotic prescribing in people with dementia. The long-term increase in antipsychotic prescribing in younger people and in those with Alzheimer's disease warrants further investigation. Funding: British Heart Foundation (BHF) (SP/19/3/34678) via the BHF Data Science Centre led by HDR UK, and the Scottish Neurological Research Fund.

Elective Surgery Before, During and After the COVID-19 Pandemic in England 2015 - 2022: A Database Study (preprint)

Objective To track elective surgery activity before, during and after the COVID-19 pandemic in England. To examine for hypothesised differences in use of independent vs NHS hospitals, and more urgent vs less urgent operations over the pre- and post-COVID time windows. Design We extracted data from the Hospital Episodes Statistics database from 1st April 2015 to 30th April 2022. This database contains all emergency and elective patient admissions, outpatient appointments and A&E attendances funded by the NHS in England. Setting NHS and Independent hospitals in England. Participants Adult patients (over 18 years) admitted for elective surgery between April 2015 and April 2022, who were classified as being in priority groups 3 or 4. Main Outcomes Total operations, operations by hospital type, and NHS England priority ranking. Results The data show that there was a large reduction in the number of elective operations during lockdown with incomplete recovery thereafter. Also the proportion of more urgent surgeries and surgeries in independent hospitals increased in the post-COVID vs pre-COVID time windows. Conclusion Under conditions of high-demand, higher value elective surgery procedures are awarded increasing priority and the Independent sector bears a larger share of the load.

New-Onset Diabetes and COVID-19: Evidence from a Global Clinical Registry (preprint)

Background Mounting evidence shows association between COVID-19 and new diagnoses of diabetes. It is unclear, however, if COVID-19 increases detection of pre-existing diabetes or if it can induce new-onset of the disease. Methods We established a global online registry of COVID-19-related diabetes (CoviDIAB) using a web-enabled data capture system (Dendrite Clinical Systems). In this study we aimed to investigate whether COVID-19 can induce new-onset diabetes, its subtypes and clinical manifestations. To this end, we analyzed clinical and laboratory data from cases of newly-diagnosed diabetes occurring during or within four weeks from an episode of COVID-19. To exclude pre-existing hyperglycaemia, new-onset diabetes was defined as: blood sugar levels above diabetes thresholds (fasting glycaemia ≥ 126 mg/dL or non-fasting glycemia > 200 mg/dL), no prior history of the disease or use of glucose-lowering medications, and HbA1c < 6·5% at presentation. Results Between October 2020 and April 2022, 67 contributors from 61 hospitals in 25 countries entered data on 537 eligible cases of newly-diagnosed diabetes. New-onset diabetes was identified in 102 of 473 newly-diagnosed cases with recorded HbA1c (22%). Among adults, diabetes subtypes were type 2 (59%) and “not-yet known” (41%). There were two cases of new-onset type 1 diabetes among children. Hyperglycaemia persisted beyond resolution of the infection in 39 of 89 (45%) patients with new-onset diabetes who survived the episode of COVID-19. Further follow-up data beyond 3-months was available for 28 such cases, showing remission of diabetes in five and persistent diabetes in 23 cases (82%). Conclusions This study shows clinical plausibility for a diabetogenic effect of COVID-19, supporting screening for diabetes in people who contract the infection. Further investigation is warranted to confirm mechanisms of viral interference with glucose metabolism. The CoviDIAB registry is accessible online at http://covidiab.e-dendrite.com.

Developing a research ready population-scale linked data ethnicity-spine in Wales (preprint)

Introduction: Ethnicity information is recorded routinely in electronic health records (EHRs); however, to date, there is no national standard or framework for harmonisation of the existing records. Methods and analysis The national ethnicity-spine uses anonymised individual-level population-scale ethnicity data from 26 EHR available through the Secure Anonymised Information Linkage (SAIL) Databank. A total of 46 million ethnicity records for 4,297,694 individuals in Wales-UK over 22 years (between 2000 and 2021) have been compiled in a harmonised, deduplicated longitudinal research ready data asset. We serialised this data and compared distribution of records over time for four selection approaches (Latest, Mode, Weighted-Mode and Composite) across age bands, sex, deprivation quintiles, health board, and residential location, against the ONS census 2011. The distribution of the dominant group (White) is minimally affected based on the four different selection approaches. Across all other ethnicity categorisations, the Mixed group was most susceptible to variation in distribution depending on the selection approach used and varied from a 0.6% prevalence across the Latest and Mode approach to a 1.1% prevalence for the Weighted-Mode, compared to the 3.1% prevalence for the Composite approach. Substantial alignment was observed with ONS census with the Latest group method (kappa= 0.68, 95% CI [0.67,0.71]) across all sub-groups. Conclusion We provides a reproducible EHR based resource enabling the investigation and evaluation of health inequalities related to ethnic groups in Wales. This generalisable method informs opportunities for the transferability of this methodology across the UK to platforms with comparable routine data sources. Ethics and dissemination This work was supported by the Con-COV team funded by Medical Research Council, Health Data Research UK, ADR Wales funded by ADR UK through the Economic and Social Research Council, and the Wales COVID-19 Evidence Centre, funded by Health and Care Research Wales.

Digital ethnicity data in population-wide electronic health records in England: a description of completeness, coverage, and granularity of diversity (preprint)

Background The link between ethnicity and healthcare inequity, and the urgency for better data is well-recognised. This study describes ethnicity data in nation-wide electronic health records in England, UK. Methods We conducted a retrospective cohort study using de-identified person-level records for the England population available in the National Health Service (NHS) Digital trusted research environment. Primary care records (GDPPR) were linked to hospital and national mortality records. We assessed completeness, consistency, and granularity of ethnicity records using all available SNOMED-CT concepts for ethnicity and NHS ethnicity categories. Findings From 61.8 million individuals registered with a primary care practice in England, 51.5 (83.3%) had at least one ethnicity record in GDPPR, increasing to 93·9% when linked with hospital records. Approximately 12·0% had at least two conflicting ethnicity codes in primary care records. Women were more likely to have ethnicity recorded than men. Ethnicity was missing most frequently in individuals from 18 to 39 years old and in the southern regions of England. Individuals with an ethnicity record had more comorbidities recorded than those without. Of 489 SNOMED-CT ethnicity concepts available, 255 were used in primary care records. Discrepancies between SNOMED-CT and NHS ethnicity categories were observed, specifically within “Other-” ethnicity groups. Interpretation More than 250 ethnicity sub-groups may be found in health records for the English population, although commonly categorised into “White”, “Black”, “Asian”, “Mixed”, and “Other”. One in ten individuals do not have ethnicity information recorded in primary care or hospital records. SNOMED-CT codes represent more diversity in ethnicity groups than the NHS ethnicity classification. Improved recording of self-reported ethnicity at first point-of-care and consistency in ethnicity classification across healthcare settings can potentially improve the accuracy of ethnicity in research and ultimately care for all ethnicities. Funding British Heart Foundation Data Science Centre led by Health Data Research UK. Research in context Evidence before this study Ethnicity has been highlighted as a significant factor in the disproportionate impact of SARS-CoV-2 infection and mortality. Better knowledge of ethnicity data recorded in real clinical practice is required to improve health research and ultimately healthcare. We searched PubMed from database inception to 14 th July 2022 for publications using the search terms “ethnicity” and “electronic health records” or “EHR,” without language restrictions. 228 publications in 2019, before the COVID-19 pandemic, and 304 publications between 2020 and 2022 were identified. However, none of these publications used or reported any of over 400 available SNOMED-CT concepts for ethnicity to account for more granularity and diversity than captured by traditional high-level classification limited to 5 to 9 ethnicity groups. Added value of this study We provide a comprehensive study of the largest collection of ethnicity records from a national-level electronic health records trusted research environment, exploring completeness, consistency, and granularity. This work can serve as a data resource profile of ethnicity from routinely-collected EHR in England. Implications of all the available evidence To achieve equity in healthcare, we need to understand the differences between individuals, as well as the influence of ethnicity both on health status and on health interventions, including variation in the behaviour of tests and therapies. Thus, there is a need for measurements, thresholds, and risk estimates to be tailored to different ethnic groups. This study presents the different medical concepts describing ethnicity in routinely collected data that are readily available to researchers and highlights key elements for improving their accuracy in research. We aim to encourage researchers to use more granular ethnicity than the than typical approaches which aggregate ethnicity into a limited number of categories, failing to reflect the diversity of underlying populations. Accurate ethnicity data will lead to a better understanding of individual diversity, which will help to address disparities and influence policy recommendations that can translate into better, fairer health for all.

Socioeconomic inequalities of Long COVID: findings from a population-based survey in the United Kingdom (preprint)

Objective To estimate the risk of Long COVID by socioeconomic deprivation and to further examine the socioeconomic inequalities in Long COVID by sex and occupational groups. Design We analysed data from the COVID-19 Infection Survey conducted by the Office for National Statistics between 26/04/2020 and 31/01/2022. This is the largest and nationally representative survey of COVID-19 in the UK and provides uniquely rich, contemporaneous, and longitudinal data on occupation, health status, COVID-19 exposure, and Long COVID symptoms. Setting Community-based longitudinal survey of COVID-19 in the UK. Participants We included 201,799 participants in our analysis who were aged between 16 and 64 years and had a confirmed SARS-CoV-2 infection. Main outcome measures We used multivariable logistic regression models to estimate the risk of Long COVID at least 4 weeks after acute SARS-CoV-2 infection by deciles of index of multiple deprivation (IMD) and adjusted for a range of demographic and spatiotemporal factors. We further examined the modifying effects of socioeconomic deprivation by sex and occupational groups. Results A total of 19,315 (9.6%) participants reported having Long COVID symptoms. Compared to the least deprived IMD decile, participants in the most deprived decile had a higher adjusted risk of Long COVID (11.4% vs 8.2%; adjusted OR: 1.45; 95% confidence interval [CI]: 1.33, 1.57). There were particularly significantly higher inequalities (most vs least deprived decile) of Long COVID in healthcare and patient facing roles (aOR: 1.76; 1.27, 2.44), and in the education sector (aOR: 1.62; 1.26, 2.08). The inequality of Long COVID was higher in females (aOR: 1.54; 1.38, 1.71) than males (OR: 1.32; 1.15, 1.51). Conclusions Participants living in the most socioeconomically deprived areas had a higher risk of Long COVID. The inequality gap was wider in females and certain public facing occupations (e.g., healthcare and education). These findings will help inform public health policies and interventions in adopting a social justice and health inequality lens.

Indirect effects of the first two years of the COVID-19 pandemic on secondary care for cardiovascular disease in the UK: an electronic health record analysis across three countries. (preprint)

BackgroundAlthough morbidity and mortality from COVID-19 have been widely reported, the indirect effects of the pandemic beyond 2020 on other major diseases and health service activity have not been well described. MethodsAnalyses used national administrative electronic hospital records in England, Scotland and Wales for 2016-2021. Admissions and procedures during the pandemic (2020-2021) related to six major cardiovascular conditions (acute coronary syndrome, heart failure, stroke/transient ischaemic attack, peripheral arterial disease, aortic aneurysm, and venous thromboembolism) were compared to the annual average in the pre-pandemic period (2016-2019). Differences were assessed by time period and urgency of care. ResultsIn 2020, there were 31,064 (-6%) fewer hospital admissions (14,506 [-4%] fewer emergencies, 16,560 [-23%] fewer elective admissions) compared to 2016-2019 for the six major cardiovascular diseases combined. The proportional reduction in admissions was similar in all three countries. Overall, hospital admissions returned to pre-pandemic levels in 2021. Elective admissions remained substantially below expected levels for almost all conditions in all three countries (-10,996 [-15%] fewer admissions). However, these reductions were offset by higher than expected total emergency admissions (+25,878 [+6%] higher admissions), notably for heart failure and stroke in England, and for venous thromboembolism in all three countries. Analyses for procedures showed similar temporal variations to admissions. ConclusionThis study highlights increasing emergency cardiovascular admissions as a result of the pandemic, in the context of a substantial and sustained reduction in elective admissions and procedures. This is likely to increase further the demands on cardiovascular services over the coming years. Key QuestionWhat is the impact in 2020 and 2021 of the COVID-19 pandemic on hospital admissions and procedures for six major cardiovascular diseases in England, Scotland and Wales? Key FindingIn 2020, there were 6% fewer hospital admissions (emergency: -4%, elective: -23%) compared to 2016-2019 for six major cardiovascular diseases, across three UK countries. Overall, admissions returned to pre-pandemic levels in 2021, but elective admissions remained below expected levels. Take-home MessageThere was increasing emergency cardiovascular admissions as a result of the pandemic, with substantial and sustained reduction in elective admissions and procedures. This is likely to increase further the demands on cardiovascular services over the coming years.

Vaccine effectiveness for preventing COVID-19 hospital admission during pregnancy: a population-based cohort study in England during the Alpha and Delta waves of the SARS-CoV-2 pandemic (preprint)

Objective: To estimate vaccine effectiveness (VE) for preventing COVID-19 hospital admission in women first infected with SARS-CoV-2 during pregnancy, and assess how this compares to VE among women of reproductive age who were not pregnant when first infected. Design: Population-based cohort study using national, linked Census and administrative data. Setting: England, United Kingdom, from 8th December 2020 to 31st August 2021. Participants: 815,4777 women aged 18 to 45 years (mean age, 30.4 years) who had documented evidence of a first SARS-CoV-2 infection in NHS Test and Trace data or Hospital Episode Statistics. Main outcome measures: A hospital inpatient episode where COVID-19 was recorded as the primary diagnosis. Cox proportional hazards models, adjusted for calendar time of infection and sociodemographic factors related to vaccine uptake and risk of severe COVID-19, were used to estimate VE as the complement of the hazard ratio for COVID-19 hospital admission. Results: Compared with unvaccinated pregnant women, the adjusted rate of COVID-19 hospital admission was 76% (95% confidence interval 69% to 82%) lower for single-vaccinated pregnant women and 83% (75% to 88%) lower for double-vaccinated pregnant women. These estimates were similar to those found for non-pregnant women: 79% (76% to 81%) for single-vaccinated and 82% (80% to 83%) for double-vaccinated. Among those vaccinated more than 90 days before infection, being double-vaccinated was associated with a greater reduction in risk than being single-vaccinated. Conclusions: COVID-19 vaccination is associated with reduced rates of severe illness in pregnant women infected with SARS-CoV-2, and the reduction in risk is similar to that for non-pregnant women. Waning of vaccine effectiveness occurs more quickly after one dose of a vaccine than two doses.

Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration (preprint)

Background The CVD-COVID-UK consortium was formed to understand the relationship between COVID-19 and cardiovascular diseases through analyses of harmonised electronic health records (EHRs) across the four UK nations. Beyond COVID-19, data harmonisation and common approaches enables analysis within and across independent Trusted Research Environments. Here we describe the reproducible harmonisation method developed using large-scale EHRs in Wales to accommodate the fast and efficient implementation of cross-nation analysis in England and Wales as part of the CVD-COVID-UK programme. We characterise current challenges and share lessons learnt.Methods Serving the scope and scalability of multiple study protocols, we used linked, anonymised individual-level EHR, demographic and administrative data held within the SAIL Databank for the population of Wales. The harmonisation method was implemented as a four-layer reproducible process, starting from raw data in the first layer. Then each of the layers two to four is framed by, but not limited to, the characterised challenges and lessons learnt. We achieved curated data as part of our second layer, followed by extracting phenotyped data in the third layer. We captured any project-specific requirements in the fourth layer.Results Using the implemented four-layer harmonisation method, we retrieved approximately 100 health-related variables for the 3.2 million individuals in Wales, which are harmonised with corresponding variables for > 56 million individuals in England. We processed 13 data sources into the first layer of our harmonisation method: five of these are updated daily or weekly, and the rest at various frequencies providing sufficient data flow updates for frequent capturing of up-to-date demographic, administrative and clinical information.Conclusions We implemented an efficient, transparent, scalable, and reproducible harmonisation method that enables multi-nation collaborative research. With a current focus on COVID-19 and its relationship with cardiovascular outcomes, the harmonised data has supported a wide range of research activities across the UK.

QCovid 4 - Predicting risk of death or hospitalisation from COVID-19 in adults testing positive for SARS-CoV-2 infection during the Omicron wave in England (preprint)

To (a) derive and validate risk prediction algorithms (QCovid4) to estimate risk of COVID-19 mortality and hospitalisation in UK adults with a SARS-CoV-2 positive test during the Omicron pandemic wave and (b) evaluate performance with earlier versions of algorithms developed in previous pandemic waves and the high-risk cohort identified by NHS Digital in England. Design Population-based cohort study using the QResearch database linked to national data on COVID-19 vaccination, high risk patients prioritised for COVID-19 therapeutics, SARS-CoV-2 results, hospitalisation, cancer registry, systemic anticancer treatment, radiotherapy and the national death registry. Settings and study period 1.3 million adults in the derivation cohort and 0.15 million adults in the validation cohort aged 18-100 years with a SARS-CoV-2 positive test between 11th December 2021 and 31st March 2022 with follow up to 30th June 2022. Main outcome measures Our primary outcome was COVID-19 death. The secondary outcome of interest was COVID-19 hospital admission. Models fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance evaluated in a separate validation cohort. Results Of 1,297,984 people with a SARS-CoV-2 positive test in the derivation cohort, 18,756 (1.45%) had a COVID-19 related hospital admission and 3,878 (0.3%) had a COVID-19 death during follow-up. Of the 145,404 people in the validation cohort, there were 2,124 (1.46%) COVID-19 admissions and 461 (0.3%) COVID-19 deaths. The COVID-19 mortality rate in men increased with age and deprivation. In the QCovid4 model in men hazard ratios were highest for those with the following conditions- kidney transplant (6.1-fold increase), Downs syndrome (4.9-fold); radiotherapy (3.1-fold); type 1 diabetes (3.4-fold), chemotherapy grade A (3.8-fold), grade B (5.8-fold), grade C (10.9-fold), solid organ transplant ever (2.4-fold), dementia (1.62-fold), Parkinsons disease (2.2-fold), liver cirrhosis (2.5-fold). Other conditions associated with increased COVID-19 mortality included learning disability, chronic kidney disease (stages 4 and 5), blood cancer, respiratory cancer, immunosuppressants, oral steroids, COPD, coronary heart disease, stroke, atrial fibrillation, heart failure, thromboembolism, rheumatoid or SLE, schizophrenia or bipolar disease sickle cell or HIV or SCID, type 2 diabetes. Results were similar in the model in women. COVID-19 mortality risk was lower among those who had received COVID-19 vaccination compared with unvaccinated individuals with evidence of a dose response relationship. The reduced mortality rates associated with prior SARS-CoV-2 infection were similar in men (adjusted hazard ratio (HR) 0.51 (95% CI 0.40, 0.64)) and women (adjusted HR 0.55 (95%CI 0.45, 0.67)). The QCOVID4 algorithm explained 76.6% (95%CI 74.4 to 78.8) of the variation in time to COVID-19 death (R2) in women. The D statistic was 3.70 (95%CI 3.48 to 3.93) and the Harrells C statistic was 0.965 (95%CI 0.951 to 0.978). The corresponding results for COVID-19 death in men were similar with R2 76.0% (95% 73.9 to 78.2); D statistic 3.65 (95%CI 3.43 to 3.86) and C statistic of 0.970 (95%CI 0.962 to 0.979). QCOVID4 discrimination for mortality was slightly higher than that for QCOVID1 and QCOVID2, but calibration was much improved. Conclusion The QCovid4 risk algorithm modelled from data during the UK Omicron wave now includes vaccination dose and prior SARS-CoV-2 infection and predicts COVID-19 mortality among people with a positive test. It has excellent performance and could be used for targeting COVID-19 vaccination and therapeutics. Although large disparities in risks of severe COVID-19 outcomes among ethnic minority groups were observed during the early waves of the pandemic, these are much reduced now with no increased risk of mortality by ethnic group.

Non-pharmacological therapies for post-viral syndromes, including Long COVID: A systematic review (preprint)

Background: Post-viral syndromes (PVS), including Long COVID, are symptoms sustained from weeks to years following an acute viral infection. Non-pharmacological treatments for these symptoms are poorly understood. This review summarises evidence for the effectiveness of non-pharmacological treatments for symptoms of PVS. It also summarises the symptoms and health impacts of PVS in individuals recruited to studies evaluating treatments. Methods and findings: We conducted a systematic review to evaluate the effectiveness of non-pharmacological interventions for PVS, as compared to either standard care, alternative non-pharmacological therapy, or placebo. The outcomes of interest were changes in symptoms, exercise capacity, quality of life (including mental health and wellbeing), and work capability. We searched five databases (Embase, MEDLINE, PsycINFO, CINAHL, MedRxiv) for randomised controlled trials (RCTs) published between 1st January 2001 to 29th October 2021. We anticipated that there would be few RCTs specifically pertaining to Long COVID, so we also included observational studies only if they assessed interventions in individuals where the viral pathogen was SARS-COV-2. Relevant outcome data were extracted, study quality appraised using the Cochrane Risk of Bias tool, and the findings were synthesised narratively. Quantitative synthesis was not planned due to substantial heterogeneity between the studies. Overall, five studies of five different interventions (Pilates, music therapy, telerehabilitation, resistance exercise, neuromodulation) met the inclusion criteria. Aside from music-based intervention, all other selected interventions demonstrated some support in the management of PVS in some patients. Conclusions: In this study, we observed a lack of robust evidence evaluating non-pharmacological treatments for PVS, including Long COVID. Considering the prevalence of prolonged symptoms following acute viral infections, there is an urgent need for clinical trials evaluating the effectiveness and cost-effectiveness of non-pharmacological treatments for patients with PVS as well as what may work for certain sub-groups of patients with differential symptom presentation. Registration: The study protocol was registered with PROSPERO [CRD42021282074] in October 2021 and published in BMJ Open in 2022. Keywords: Post-viral syndromes, PVS, COVID-19, Long COVID, post-COVID-19 condition, post-acute sequelae of SARS-CoV-2 infection (PASC), rehabilitation, systematic review, non-pharmacological intervention