One year health outcomes associated with systemic corticosteroids for COVID-19: a longitudinal cohort study (preprint)

BackgroundIn patients with COVID-19 requiring supplemental oxygen, dexamethasone reduces acute severity and improves survival, but longer-term effects are unknown. We hypothesised that systemic corticosteroid administration during acute COVID-19 would be associated with improved health-related quality of life (HRQoL) one year after discharge. MethodsAdults admitted to hospital between February 2020 and March 2021 for COVID-19 and meeting current guideline recommendations for dexamethasone treatment were included using two prospective UK cohort studies. HRQoL, assessed by EQ-5D-5L utility index, pre-hospital and one year after discharge were compared between those receiving corticosteroids or not after propensity weighting for treatment. Secondary outcomes included patient reported recovery, physical and mental health status, and measures of organ impairment. Sensitivity analyses were undertaken to account for survival and selection bias. FindingsIn 1,888 participants included in the primary analysis, 1,149 received corticosteroids. There was no between-group difference in EQ-5D-5L utility index at one year (mean difference 0.004, 95% CI: -0.026 to 0.034, p = 0.77). A similar reduction in EQ-5D-5L was seen at one year between corticosteroid exposed and non-exposed groups (mean (SD) change -0.12 (0.22) vs -0.11 (0.22), p = 0.32). Overall, there were no differences in secondary outcome measures. After sensitivity analyses modelled using a larger cohort of 109,318 patients admitted to hospital with COVID-19, EQ-5D-5L utility index at one year remained similar between the two groups. InterpretationSystemic corticosteroids for acute COVID-19 have no impact on the large reduction in HRQoL one year after hospital discharge. Treatments to address this are urgently needed. Take home messageSystemic corticosteroids given for acute COVID-19 do not affect health-related quality of life or other patient reported outcomes, physical and mental health outcomes, and organ function one year after hospital discharge

Risk of COVID-19 death in adults who received booster COVID-19 vaccinations: national retrospective cohort study on 14.6 million people in England (preprint)

Background: The emergence of the COVID-19 vaccination has been critical in changing the course of the COVID-19 pandemic, with estimates suggesting vaccinations have prevented millions of deaths worldwide. To ensure protection remains high in groups at high-risk, booster vaccinations in the UK have been targeted based on age and clinical vulnerabilities. We sought to identify adults at increased risk of COVID-19 death, and compared to non-COVID-19 risk, despite having received a booster dose as part of the 2022 autumn vaccination campaign in England. Methods: We undertook a national retrospective cohort study using data from the 2021 Census linked to electronic health records. We fitted cause-specific Cox regression to examine the association between a range of 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. Findings: Our total population was 14,644,570 people; there were 6,800 COVID-19 deaths (52. and 150,075 non-COVID-19 deaths. Having learning disabilities or Down Syndrome (hazard ratio=5.07;conficence 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 of these comorbidities. Interpretation: We identify groups who are at increased risk of COVID-19 death relative to non-COVID-19 deaths. Vulnerable groups should continue to be prioritised for COVID-19 booster doses to minimise the risk of COVID-19 deaths.

Patient characteristics associated with clinically coded long COVID: an OpenSAFELY study using electronic health records (preprint)

Despite reports of post-COVID-19 syndromes (long COVID) are rising, clinically coded long COVID cases are incomplete in electronic health records. It is unclear how patient characteristics may be associated with clinically coded long COVID. With the approval of NHS England, we undertook a cohort study using electronic health records within the OpenSAFELY-TPP platform in England, to study patient characteristics associated with clinically coded long COVID from 29 January 2020 to 31 March 2022. We estimated age-sex adjusted hazard ratios and fully adjusted hazard ratios for coded long COVID. Patient characteristics included demographic factors, and health behavioural and clinical factors. Among 17,986,419 adults, 36,886 (0.21%) were clinically coded with long COVID. Patient characteristics associated with coded long COVID included female sex, younger age (under 60 years), obesity, living in less deprived areas, ever smoking, greater consultation frequency, and history of diagnosed asthma, mental health conditions, pre-pandemic post-viral fatigue, or psoriasis. The strength of these associations was attenuated following two-dose vaccination compared to before vaccination. The incidence of coded long COVID was higher after hospitalised than non-hospitalised COVID-19. These results should be interpreted with caution given that long COVID was likely under-recorded in electronic health records.

Impact of the Covid-19 Pandemic on Audiology Service Delivery: Observational Study of the Role of Social Media in Patient Communication (preprint)

The Covid-19 pandemic has highlighted an era in hearing health care that necessitates a comprehensive rethinking of audiology service delivery. There has been a significant increase in the number of individuals with hearing loss who seek information online. An estimated 430 million individuals worldwide suffer from hearing loss, including 11 million in the United Kingdom. The objective of this study was to identify NHS audiology service social media posts and understand how they were used to communicate service changes within audiology departments at the onset of the Covid-19 pandemic.Facebook and Twitter posts relating to audiology were extracted over a six week period (March 23 to April 30 2020) from the United Kingdom. We manually filtered the posts to remove those not directly linked to NHS audiology service communication. The extracted data was then geospatially mapped, and themes of interest were identified via a manual review. We also calculated interactions (likes, shares, comments) per post to determine the posts efficacy. A total of 981 Facebook and 291 Twitter posts were initially mined using our keywords, and following filtration, 174 posts related to NHS audiology change of service were included for analysis. The results were then analysed geographically, along with an assessment of the interactions within the included posts. NHS Trusts and Boards should consider incorporating and promoting social media to communicate service changes. Users would be notified of service modifications in real-time, and different modalities could be used (e.g. videos), resulting in a more efficient service.

Characteristics and outcomes of patients with COVID-19 at high risk of disease progression receiving sotrovimab, oral antivirals or no treatment in Scotland (preprint)

Introduction: Severe acute respiratory syndrome coronavirus 2 is constantly evolving. The clinical benefit of coronavirus disease 2019 (COVID-19) treatments against new circulating variants remains unclear. We sought to describe the real-world use of, and clinical outcomes associated with, early COVID-19 treatments among non-hospitalised patients with COVID-19 at highest risk of developing severe disease in Scotland. Methods: Retrospective cohort study of non-hospitalised patients diagnosed with COVID-19 from 1 December 2021 to 25 October 2022, using administrative health data managed by Public Health Scotland and National Records of Scotland. Patients included in the study were aged [≥]18 years, met at least one of the National Health Service highest-risk conditions criteria for early COVID-19 treatment, and had received outpatient treatment with sotrovimab, nirmatrelvir/ritonavir or molnupiravir, or no early COVID-19 treatment. Index date was defined as the earliest of either COVID-19-positive diagnosis or early COVID-19 treatment during the study period. Baseline patient characteristics and acute clinical outcomes in the 28 days following the index date were reported. To protect patient confidentiality, values of [≤]5 were suppressed. Results: A total of 2548 patients were included (492: sotrovimab, 276: nirmatrelvir/ritonavir, 71: molnupiravir, and 1709 eligible highest-risk untreated). Patients aged [≥]75 years accounted for 6.9% (n=34/492) of the sotrovimab-treated group, 21.0% (n=58/276) of those treated with nirmatrelvir/ritonavir, 16.9% (n=12/71) of those treated with molnupiravir and 13.2% (n=225/1709) of untreated patients. Advanced renal disease was reported for 6.7% (n=33/492) of sotrovimab-treated and 4.7% (n=81/1709) of untreated patients, and five or fewer patients in the nirmatrelvir/ritonavir and molnupiravir cohorts. A high proportion of treated patients did not have a highest-risk condition reported in the database (71.7% for sotrovimab [n=353/492], 85.1% for nirmatrelvir/ritonavir [n=235/276], 85.9% for molnupiravir [n=61/71]). Five or fewer patients in each treated cohort experienced COVID-19-related hospitalisations during the 28-day acute period. For untreated patients, the percentage of COVID-19-related hospitalisations was 3.0% (n=48/1622). All-cause hospitalisations were experienced by 5.3% (n=25/476) of sotrovimab-treated patients, 6.9% (n=12/175) of nirmatrelvir/ritonavir-treated patients and 13.3% (n=216/1622) of untreated patients. Five or fewer patients in the molnupiravir cohort experienced all-cause hospitalisation. There were no deaths within 28 days of index for patients in the treated cohorts. Mortality was 4.3% (n=70/1622) in untreated patients (18.6% [n=13/70] had COVID-19 as the primary cause). In our analyses of outcomes for sotrovimab-treated and untreated patients during BA.1, BA.2 and BA.5 predominance, COVID-19-related hospitalisation rates were consistent, with n[≤]5 for sotrovimab-treated patients in each period. Conclusions: Our findings indicate that sotrovimab was often used amongst patients who were aged <75 years old and had advanced renal disease. Among patients who received early COVID-19 treatment, proportions of all-cause hospitalisation and death within 28 days of treatment were low.

Cohort Profile: Post-hospitalisation COVID-19 study (PHOSP-COVID) (preprint)

Abstract [bullet] PHOSP-COVID is a national UK multi-centre cohort study of patients who were hospitalised for COVID-19 and subsequently discharged. [bullet] PHOSP-COVID was established to investigate the medium- and long-term sequelae of severe COVID-19 requiring hospitalisation, understand the underlying mechanisms of these sequelae, evaluate the medium- and long-term effects of COVID-19 treatments, and to serve as a platform to enable future studies, including clinical trials. [bullet] Data collected covered a wide range of physical measures, biological samples, and Patient Reported Outcome Measures (PROMs). [bullet] Participants could join the cohort either in Tier 1 only with remote data collection using hospital records, a PROMs app and postal saliva sample for DNA, or in Tier 2 where they were invited to attend two specific research visits for further data collection and biological research sampling. These research visits occurred at five (range 2-7) months and 12 (range 10-14) months post-discharge. Participants could also participate in specific nested studies (Tier 3) at selected sites. [bullet] All participants were asked to consent to further follow-up for 25 years via linkage to their electronic healthcare records and to be re-contacted for further research. [bullet] In total, 7935 participants were recruited from 83 UK sites: 5238 to Tier 1 and 2697 to Tier 2, between August 2020 and March 2022. [bullet] Cohort data are held in a Trusted Research Environment and samples stored in a central biobank. Data and samples can be accessed upon request and subject to approvals.

Association between antibody responses post-vaccination and severe COVID-19 outcomes: national population-based cohort study in Scotland (preprint)

Several population-level studies have described individual clinical risk factors associated with suboptimal antibody responses following COVID-19 vaccination, but none have examined multimorbidity. Others have shown that suboptimal post-vaccination responses offer reduced protection to subsequent SARS-CoV-2 infection; however, the level of protection from COVID-19 hospitalisation/death remains unconfirmed. We use national Scottish datasets to investigate the association between multimorbidity and testing antibody-negative, examining the correlation between antibody levels and subsequent COVID-19 hospitalisation/death among double-vaccinated individuals. We found that individuals with multimorbidity (≥five conditions) were more likely to test antibody-negative post-vaccination and 13.37 [6.05 - 29.53] times more likely to be hospitalised/die from COVID-19 than individuals without conditions. We also show a dose-dependent association between post-vaccination antibody levels and COVID-19 hospitalisation or death, with those with undetectable antibody levels at a significantly higher risk (HR 9.21 [95% CI 4.63 - 18.29]) of these serious outcomes compared to those with high antibody levels.

Risk of cardiovascular events following COVID-19 in people with and without pre-existing chronic respiratory disease (preprint)

Background COVID-19 is associated with a higher risk of cardiovascular outcomes in the general population. People with chronic respiratory disease have a higher risk of cardiovascular disease than the general population therefore, we investigated the association between pre-existing chronic respiratory disease and risk of cardiovascular events following COVID-19 using routinely collected data from 56 million people in England. Methods Primary and secondary care data from the English National Health Service and COVID-19-specific linked data were used to define a population of adults with COVID-19 between 01/01/2020-30/11/2021. Start of follow-up was from first COVID-19 diagnosis. Pre-existing chronic respiratory disease included asthma, chronic obstructive pulmonary disease, bronchiectasis, cystic fibrosis, or pulmonary fibrosis prior to COVID-19 diagnosis. Adjusted Cox Proportional Hazard regression was used to investigate the association between pre-existing chronic respiratory disease and risk of cardiovascular events. Secondary objectives investigated the impact of COVID-19 hospitalisation and vaccine dose on risk of cardiovascular outcomes. Findings A total of 3,670,455 people were included. People with pre-existing respiratory disease had a higher risk of cardiovascular events (adjusted HR 1.11, 95% confidence intervals 1.07-1.14), heart failure (1.15, 1.09-1.21), and pulmonary embolism (1.20, 1.11-1.30) compared with those without pre-existing respiratory disease. Regardless of pre-existing respiratory disease, the risk of cardiovascular events was lower with increasing COVID-19 vaccine dose. Interpretation People with chronic respiratory disease have a higher risk of some cardiovascular outcomes but the risk might be explained by the underlying respiratory condition. Risk of cardiovascular events was lower with increasing COVID-19 vaccine doses regardless of pre-existing chronic respiratory disease. Funding This work was funded by the British Heart Foundation Data Science Centre.

Analysis of uptake, effectiveness and safety of COVID-19 vaccinations in pregnancy using the QResearch database: research protocol and statistical analysis plan (preprint)

Background The COVID-19 pandemic has affected millions of people globally with major health, social and economic consequences, prompting development of vaccines for use in the general population. However, vaccination uptake is lower in some groups, including in pregnant women, because of concerns regarding vaccine safety. There is evidence of increased risk of adverse pregnancy and neonatal outcomes associated with SARS-CoV-2 infection, but fear of vaccine-associated adverse events on the baby both in short and longer term is one of the main drivers of low uptake for this group. Other vaccines commonly used in pregnancy include influenza and pertussis. These both have reportedly higher uptake compared with COVID-19 vaccination, which may be because they are perceived to be safer. In this study, we will undertake an independent evaluation of the uptake, effectiveness and safety of COVID-19 vaccinations in pregnant women using the QResearch primary care database in England. Objectives A. To determine COVID-19 vaccine uptake in pregnant women compared to uptake of influenza and pertussis vaccinations. B. To estimate COVID-19 vaccine effectiveness in pregnant women by evaluating the risk of severe COVID-19 outcomes following vaccination. C. To assess the safety of COVID-19 vaccination in pregnancy by evaluating the risks of adverse pregnancy and perinatal outcomes and adverse events of special interest for vaccine safety after COVID-19 vaccination compared with influenza and pertussis vaccinations. Methods This population-based study uses the QResearch database of primary health care records, linked to individual-level data on hospital admissions, mortality, COVID-19 vaccination, SARS-CoV-2 testing data and congenital anomalies. We will include women aged 16 to 49 years with at least one pregnancy during the study period of 30th December 2020 to the latest date available. Babies born during the study period will be identified and linked to the mothers record, where possible. We will describe vaccine uptake in pregnant women by trimester and population subgroups defined by demographics and other characteristics. Cox proportional hazards multivariable regression will be used to identify factors associated with vaccine uptake. The effectiveness of COVID-19 vaccines in pregnant women will be assessed using time varying Royston-Palmar regression analyses to determine unadjusted and adjusted hazard ratios for the occurrence of severe COVID-19 outcomes after each vaccine dose compared with unvaccinated individuals. For the safety analysis, we will we use logistic regression analyses to determine unadjusted and adjusted odds ratios for the occurrence of maternal (e.g. miscarriage, ectopic pregnancy and gestational diabetes) and perinatal outcomes (e.g. stillbirth, small for gestational age and congenital anomalies) by vaccination status compared to unvaccinated individuals. For the adverse events of special interest for vaccine safety (e.g. venous thromboembolism, myocarditis and Guillain Barre syndrome), we will use time varying Royston-Palmar regression analyses to determine unadjusted and adjusted hazard ratios for the occurrence of each outcome by vaccination status to unvaccinated individuals. Ethics and dissemination QResearch is a Research Ethics Approved Research Database with ongoing approval from the East Midlands Multi-Centre Research Ethics Committee (Ref: 18/EM/0400). This study was approved by the QResearch Scientific Committee on 9th June 2022. This research protocol has been developed with support from a patient and public involvement panel, who will continue to provide input throughout the duration of the study. Research findings will be submitted to pre-print servers such as MedRxIv, academic publication and disseminated more broadly through media releases and community groups and conference presentations.

Trends in inequalities in avoidable hospitalisations across the COVID-19 pandemic: A cohort study of 23.5 million people in England (preprint)

Background: The COVID-19 pandemic and associated national lockdowns created unprecedented disruption to healthcare, with reduced access to services and planned clinical encounters postponed or cancelled. It was widely anticipated that failure to obtain timely treatment would cause progression of illness and increased hospital admissions. Additional concerns were that social and spatial inequalities would widen given the disproportionate impacts of COVID-19 directly. The aim of our study is to determine whether this was observable in England. Methods: With the approval of NHS England we utilised individual-level electronic health records from OpenSAFELY, which covered ~40% of general practices in England (mean monthly population size 23.5 million people). We estimated crude and directly age-standardised rates for potentially preventable unplanned hospital admissions: ambulatory care sensitive conditions and urgent emergency sensitive conditions. We considered how trends in these outcomes varied by three measures of social and spatial inequality: neighbourhood socioeconomic deprivation, ethnicity, and geographical region. Findings: There were large declines in avoidable hospitalisations during the first national lockdown, which then reversed post-lockdown albeit never reaching pre-pandemic levels. While trends were consistent by each measure of inequality, absolute levels of inequalities narrowed throughout 2020 (especially during the first national lockdown) and remained lower than pre-pandemic trends. While the scale of inequalities remained similar into 2021 for deprivation and ethnicity, we found evidence of widening absolute and relative inequalities by geographic region in 2021 and 2022. Interpretation: The anticipation that healthcare disruption from the COVID-19 pandemic and lockdowns would result in more (avoidable) hospitalisations and widening social inequalities was wrong. However, the recent growing gap between geographic regions suggests that the effects of the pandemic has reinforced spatial inequalities.

The protection gap under a social health protection initiative in the COVID-19 pandemic: A case study from Khyber Pakhtunkhwa, Pakistan. (preprint)

Background Sehat Sahulat Programme (SSP) is a Social Health Protection (SHP) initiative by the Government of Khyber Pakhtunkhwa (GoKP), covering inpatient services for 100% of the provinces population. In this paper, we describe SSPs role in GoKPs COVID-19 response and draw inferences for similar programmes in Pakistan. Methodology and methods We conceptualised SSP as an instrumental case study and collected three complementary data sources. First, we studied GoKPs official documents to understand SSPs benefits package. Then we undertook in-depth interviews and collected non-participant observations at the SSP policy and implementation levels. We recruited participants through direct (verbal and email) and indirect (invitation posters) methods. Use of maximum variation sampling enabled us to understand contrasting views from various stakeholders on SSPs policy dimensions (i.e., coverage and financing), tensions between the policy directions (i.e., whether or not to cover COVID-19) and how policy decisions were made and implemented. We collected data from March 2021 to December 2021. Thematic analysis was conducted with the help of Nvivo12. Findings Throughout 2020, SSP did not cover COVID-19 treatment. The insurer and GoKP officials considered the pandemic a standard exclusion to insurance coverage. One SSP official said: "COVID-19 is not covered and not relevant to us". GoKP had stopped non-emergency services at all hospitals. When routine services restarted, the insurer did not cover COVID-19 screening tests, which were mandatory prior to hospital admission. In 2021, GoKP engaged 10 private SSP hospitals for COVID-19 treatment. The SSP Reserve Fund, rather than insurance pooled money, was used. The Reserve Fund was originally meant to cover high-cost organ transplants. In 2021, SSP had 1,002 COVID-19-related admissions, which represented 0.2% of all hospital admissions (N=544,841). An advocacy group representative called the COVID-19 care under SSP "too little too late". In contrast, SSP officials suggested their insurance database and funds flow mechanism could help GoKP in future health emergencies. Conclusion The commercially focused interpretation of SHP arrangements led to a protection gap in the context of COVID-19. SSP and similar programmes in other provinces of Pakistan should emphasise the notion of protection and not let commercial interests lead to protection gaps.

COVID-19 vaccination and SARS-CoV-2 infection in early pregnancy and the risk of major congenital anomalies: a national population-based cohort study (preprint)

Evidence on associations between COVID-19 vaccination or SARS-CoV-2 infection and the risk of congenital anomalies is limited. We conducted a national, population-based, matched cohort study to estimate the association between COVID-19 vaccination and, separately, SARS-CoV-2 infection between six weeks pre-conception and 19 weeks and six days gestation and the risk of [1] any congenital anomaly and; [2] non-genetic anomalies. Mothers vaccinated in this pregnancy exposure period mostly received an mRNA vaccine (73.7% Pfizer-BioNTech BNT162b2 and 7.9% Moderna mRNA-1273). Of the 6,731 babies whose mothers were vaccinated in the pregnancy exposure period, 153 had any congenital anomaly and 120 had a non-genetic anomaly. Primary analyses found no association between vaccination and any anomaly (adjusted Odds Ratio [aOR] = 1.01, 95% Confidence Interval [CI] = 0.83–1.24) or non-genetic anomalies (aOR = 1.00, 95% CI = 0.81–1.22). Primary analyses also found no association between SARS-CoV-2 infection and any anomaly (aOR = 1.02, 95% CI = 0.66–1.60) or non-genetic anomalies (aOR = 0.94, 95% CI = 0.57–1.54). Findings were robust to sensitivity analyses. These data provide reassurance on the safety of vaccination, in particular mRNA vaccines, just before or in early pregnancy.

Rebound in asthma exacerbations following relaxation of COVID-19 restrictions: a longitudinal population-based study (COVIDENCE UK) (preprint)

BackgroundThe imposition of restrictions on social mixing early in the COVID-19 pandemic was followed by a reduction in asthma exacerbations in multiple settings internationally. Temporal trends in social mixing, incident acute respiratory infections (ARI) and asthma exacerbations following relaxation of COVID-19 restrictions have not yet been described. MethodsWe conducted a population-based longitudinal study in 2,312 UK adults with asthma between November 2020 and April 2022. Details of face covering use, social mixing, incident ARI and moderate/severe asthma exacerbations were collected via monthly on-line questionnaires. Temporal changes in these parameters were visualised using Poisson generalised additive models. Multilevel logistic regression was used to test for associations between incident ARI and risk of asthma exacerbations, adjusting for potential confounders. ResultsRelaxation of COVID-19 restrictions from April 2021 coincided with reduced face covering use (p<0.001), increased frequency of indoor visits to public places and other households (p<0.001) and rising incidence of COVID-19 (p<0.001), non-COVID-19 ARI (p<0.001) and moderate/severe asthma exacerbations (p=0.007). Incident non-COVID-19 ARI associated independently with increased risk of asthma exacerbation (adjusted odds ratio 5.75, 95% CI 4.75 to 6.97) as did incident COVID-19, both prior to emergence of the omicron variant of SARS-CoV-2 (5.89, 3.45 to 10.04) and subsequently (5.69, 3.89 to 8.31). ConclusionsRelaxation of COVID-19 restrictions coincided with decreased face covering use, increased social mixing and a rebound in ARI and asthma exacerbations. Associations between incident ARI and risk of moderate/severe asthma exacerbation were similar for non-COVID-19 ARI and COVID-19, both before and after emergence of the SARS-CoV-2 omicron variant. FundingBarts Charity, UKRI

Early pregnancy outcomes following COVID-19 vaccination and SARS-CoV-2 infection: a national population-based matched cohort study (preprint)

There are limited data regarding the safety of COVID-19 vaccines in early pregnancy. This may contribute to vaccine hesitancy in people who are pregnant, or who are planning pregnancy. We conducted a population-level matched cohort study assessing associations between COVID-19 vaccination and miscarriage (pregnancy loss prior to 20 weeks gestation) and ectopic pregnancy. We used electronic health records of all female residents in Scotland who were vaccinated between 6 weeks preconception and 19 weeks 6 days gestation (for miscarriage; n = 18,780) or 2 weeks 6 days gestation (for ectopic; n = 10,570). Primary analyses used unvaccinated women from the pre-pandemic period as controls (historical controls) matched (3:1) on maternal age, gestational age at vaccination, and season of conception; with adjustment for maternal deprivation level, rural/urban status and clinical vulnerability. Supplementary analyses used unvaccinated women from the pandemic period as controls (contemporary controls). Analyses of outcomes following SARS-CoV-2 infection were undertaken with infection rather than vaccination as the exposure. Following COVID-19 vaccination, the rate of miscarriage was 9.1% (n = 1,716) and ectopic pregnancy 1.2% (n = 126). Primary analyses found no association between vaccination and miscarriage (adjusted Odds Ratio [aOR] = 1.02, 95% Confidence Interval [CI] = 0.96–1.09) or ectopic pregnancy (aOR = 1.13, 95% CI = 0.92–1.38). Primary analyses also found no association between SARS-CoV-2 infection and miscarriage or ectopic pregnancy. Results of supplementary analyses were similar to primary analyses. Given that SARS-CoV-2 infection in later pregnancy carries substantial risks to women and babies, our findings support current recommendations that vaccination remains the safest way for pregnant women to protect themselves and their babies from COVID-19.

Uptake of Sotrovimab for prevention of severe COVID-19 and its safety in the community in England (preprint)

Sotrovimab is a neutralising monoclonal antibody (nMAB), currently administrated in England to treat extremely clinically vulnerable COVID-19 patients. Trials have shown it to have mild or moderate side effects, however safety in real-world settings has not been yet evaluated. We used national databases to investigate its uptake and safety in community patients across England. We used a cohort study to describe uptake and a self-controlled case series design to evaluate the risks of 49 pre-specified suspected adverse events in the 2-28 days post-treatment. Between December 11, 2021 and May 24, 2022, there were 172,860 COVID-19 patients eligible for treatment. Of the 22,815 people who received Sotrovimab, 21,487 (94.2%) had a positive SARS-CoV-2 test and 5,999 (26.3%) were not on the eligible list. Between treated and untreated eligible individuals, the mean age (54.6, SD: 16.1 vs 54.1, SD: 18.3) and sex distribution (women: 60.9% vs 58.1%; men: 38.9% vs 41.1%) were similar. There were marked variations in uptake between ethnic groups, which was higher amongst Indian (15.0%; 95%CI 13.8, 16.3), Other Asian (13.7%; 95%CI 11.9, 15.8), White (13.4%; 95%CI 13.3, 13.6), and Bangladeshi (11.4%; 95%CI 8.8, 14.6); and lower amongst Black Caribbean individuals (6.4%; 95%CI 5.4, 7.5) and Black Africans (4.7%; 95%CI 4.1, 5.4). We found no increased risk of any of the suspected adverse events in the overall period of 2-28 days post-treatment, but an increased risk of rheumatoid arthritis (IRR 3.08, 95% CI 1.44, 6.58) and of systematic lupus erythematosus (IRR 5.15, 95% CI 1.60, 16.60) in the 2-3 days post-treatment, when we narrowed the risk period. FundingNational Institute of Health Research (Grant reference 135561)

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.