Risk of severe COVID-19 outcomes associated with immune-mediated inflammatory diseases and immune-modifying therapies: a nationwide cohort study in the OpenSAFELY platform.

Background: The risk of severe COVID-19 outcomes in people with immune-mediated inflammatory diseases and on immune-modifying drugs might not be fully mediated by comorbidities and might vary by factors such as ethnicity. We aimed to assess the risk of severe COVID-19 in adults with immune-mediated inflammatory diseases and in those on immune-modifying therapies. Methods: We did a cohort study, using OpenSAFELY (an analytics platform for electronic health records) and TPP (a software provider for general practitioners), analysing routinely collected primary care data linked to hospital admission, death, and previously unavailable hospital prescription data. We included people aged 18 years or older on March 1, 2020, who were registered with TPP practices with at least 12 months of primary care records before March, 2020. We used Cox regression (adjusting for confounders and mediators) to estimate hazard ratios (HRs) comparing the risk of COVID-19-related death, critical care admission or death, and hospital admission (from March 1 to Sept 30, 2020) in people with immune-mediated inflammatory diseases compared with the general population, and in people with immune-mediated inflammatory diseases on targeted immune-modifying drugs (eg, biologics) compared with those on standard systemic treatment (eg, methotrexate). Findings: We identified 17 672 065 adults; 1 163 438 adults (640 164 [55·0%] women and 523 274 [45·0%] men, and 827 457 [71·1%] of White ethnicity) had immune-mediated inflammatory diseases, and 16 508 627 people (8 215 020 [49·8%] women and 8 293 607 [50·2%] men, and 10 614 096 [64·3%] of White ethnicity) were included as the general population. Of 1 163 438 adults with immune-mediated inflammatory diseases, 19 119 (1·6%) received targeted immune-modifying therapy and 181 694 (15·6%) received standard systemic therapy. Compared with the general population, adults with immune-mediated inflammatory diseases had an increased risk of COVID-19-related death after adjusting for confounders (age, sex, deprivation, and smoking status; HR 1·23, 95% CI 1·20-1·27) and further adjusting for mediators (body-mass index [BMI], cardiovascular disease, diabetes, and current glucocorticoid use; 1·15, 1·11-1·18). Adults with immune-mediated inflammatory diseases also had an increased risk of COVID-19-related critical care admission or death (confounder-adjusted HR 1·24, 95% CI 1·21-1·28; mediator-adjusted 1·16, 1·12-1·19) and hospital admission (confounder-adjusted 1·32, 1·29-1·35; mediator-adjusted 1·20, 1·17-1·23). In post-hoc analyses, the risk of severe COVID-19 outcomes in people with immune-mediated inflammatory diseases was higher in non-White ethnic groups than in White ethnic groups (as it was in the general population). We saw no evidence of increased COVID-19-related death in adults on targeted, compared with those on standard systemic, therapy after adjusting for confounders (age, sex, deprivation, BMI, immune-mediated inflammatory diseases [bowel, joint, and skin], cardiovascular disease, cancer [excluding non-melanoma skin cancer], stroke, and diabetes (HR 1·03, 95% CI 0·80-1·33), and after additionally adjusting for current glucocorticoid use (1·01, 0·78-1·30). There was no evidence of increased COVID-19-related death in adults prescribed tumour necrosis factor inhibitors, interleukin (IL)-12/IL­23 inhibitors, IL-17 inhibitors, IL-6 inhibitors, or Janus kinase inhibitors compared with those on standard systemic therapy. Rituximab was associated with increased COVID-19-related death (HR 1·68, 95% CI 1·11-2·56), with some attenuation after excluding people with haematological malignancies or organ transplants (1·54, 0·95-2·49). Interpretation: COVID-19 deaths and hospital admissions were higher in people with immune-mediated inflammatory diseases. We saw no increased risk of adverse COVID-19 outcomes in those on most targeted immune-modifying drugs for immune-mediated inflammatory diseases compared with those on standard systemic therapy. Funding: UK Medical Research Council, NIHR Biomedical Research Centre at King's College London and Guy's and St Thomas' NHS Foundation Trust, and Wellcome Trust.

UK prevalence of underlying conditions which increase the risk of severe COVID-19 disease: a point prevalence study using electronic health records.

BACKGROUND: Characterising the size and distribution of the population at risk of severe COVID-19 is vital for effective policy and planning. Older age, and underlying health conditions, are associated with higher risk of death from COVID-19. This study aimed to describe the population at risk of severe COVID-19 due to underlying health conditions across the United Kingdom. METHODS: We used anonymised electronic health records from the Clinical Practice Research Datalink GOLD to estimate the point prevalence on 5 March 2019 of the at-risk population following national guidance. Prevalence for any risk condition and for each individual condition is given overall and stratified by age and region with binomial exact confidence intervals. We repeated the analysis on 5 March 2014 for full regional representation and to describe prevalence of underlying health conditions in pregnancy. We additionally described the population of cancer survivors, and assessed the value of linked secondary care records for ascertaining COVID-19 at-risk status. RESULTS: On 5 March 2019, 24.4% of the UK population were at risk due to a record of at least one underlying health condition, including 8.3% of school-aged children, 19.6% of working-aged adults, and 66.2% of individuals aged 70 years or more. 7.1% of the population had multimorbidity. The size of the at-risk population was stable over time comparing 2014 to 2019, despite increases in chronic liver disease and diabetes and decreases in chronic kidney disease and current asthma. Separately, 1.6% of the population had a new diagnosis of cancer in the past 5 y. CONCLUSIONS: The population at risk of severe COVID-19 (defined as either aged ≥70 years, or younger with an underlying health condition) comprises 18.5 million individuals in the UK, including a considerable proportion of school-aged and working-aged individuals. Our national estimates broadly support the use of Global Burden of Disease modelled estimates in other countries. We provide age- and region- stratified prevalence for each condition to support effective modelling of public health interventions and planning of vaccine resource allocation. The high prevalence of health conditions among older age groups suggests that age-targeted vaccination strategies may efficiently target individuals at higher risk of severe COVID-19.

Indirect acute effects of the COVID-19 pandemic on physical and mental health in the UK: a population-based study.

BACKGROUND: There are concerns that the response to the COVID-19 pandemic in the UK might have worsened physical and mental health, and reduced use of health services. However, the scale of the problem is unquantified, impeding development of effective mitigations. We aimed to ascertain what has happened to general practice contacts for acute physical and mental health outcomes during the pandemic. METHODS: Using de-identified electronic health records from the Clinical Research Practice Datalink (CPRD) Aurum (covering 13% of the UK population), between 2017 and 2020, we calculated weekly primary care contacts for selected acute physical and mental health conditions: anxiety, depression, self-harm (fatal and non-fatal), severe mental illness, eating disorder, obsessive-compulsive disorder, acute alcohol-related events, asthma exacerbation, chronic obstructive pulmonary disease exacerbation, acute cardiovascular events (cerebrovascular accident, heart failure, myocardial infarction, transient ischaemic attacks, unstable angina, and venous thromboembolism), and diabetic emergency. Primary care contacts included remote and face-to-face consultations, diagnoses from hospital discharge letters, and secondary care referrals, and conditions were identified through primary care records for diagnoses, symptoms, and prescribing. Our overall study population included individuals aged 11 years or older who had at least 1 year of registration with practices contributing to CPRD Aurum in the specified period, but denominator populations varied depending on the condition being analysed. We used an interrupted time-series analysis to formally quantify changes in conditions after the introduction of population-wide restrictions (defined as March 29, 2020) compared with the period before their introduction (defined as Jan 1, 2017 to March 7, 2020), with data excluded for an adjustment-to-restrictions period (March 8-28). FINDINGS: The overall population included 9 863 903 individuals on Jan 1, 2017, and increased to 10 226 939 by Jan 1, 2020. Primary care contacts for almost all conditions dropped considerably after the introduction of population-wide restrictions. The largest reductions were observed for contacts for diabetic emergencies (odds ratio 0·35 [95% CI 0·25-0·50]), depression (0·53 [0·52-0·53]), and self-harm (0·56 [0·54-0·58]). In the interrupted time-series analysis, with the exception of acute alcohol-related events (0·98 [0·89-1·10]), there was evidence of a reduction in contacts for all conditions (anxiety 0·67 [0·66-0·67], eating disorders 0·62 [0·59-0·66], obsessive-compulsive disorder [0·69 [0·64-0·74]], self-harm 0·56 [0·54-0·58], severe mental illness 0·80 [0·78-0·83], stroke 0·59 [0·56-0·62], transient ischaemic attack 0·63 [0·58-0·67], heart failure 0·62 [0·60-0·64], myocardial infarction 0·72 [0·68-0·77], unstable angina 0·72 [0·60-0·87], venous thromboembolism 0·94 [0·90-0·99], and asthma exacerbation 0·88 [0·86-0·90]). By July, 2020, except for unstable angina and acute alcohol-related events, contacts for all conditions had not recovered to pre-lockdown levels. INTERPRETATION: There were substantial reductions in primary care contacts for acute physical and mental conditions following the introduction of restrictions, with limited recovery by July, 2020. Further research is needed to ascertain whether these reductions reflect changes in disease frequency or missed opportunities for care. Maintaining health-care access should be a key priority in future public health planning, including further restrictions. The conditions we studied are sufficiently severe that any unmet need will have substantial ramifications for the people with the conditions as well as health-care provision. FUNDING: Wellcome Trust Senior Fellowship, Health Data Research UK.

Comparisons of Staphylococcus aureus infection and other outcomes between users of angiotensin-converting-enzyme inhibitors and angiotensin II receptor blockers: lessons for COVID-19 from a nationwide cohort study.

Background: Mice receiving angiotensin converting enzyme inhibitor (ACEI) drugs show increased susceptibility to infection by Staphylococcus aureus ( S. aureus). We sought to investigate whether humans using ACEI were at increased risk of S. aureus infection, comparing them to users of Angiotensin II Receptor Blockers (ARB) with multiple control outcomes to assess the potential for residual confounding. Methods: Using the UK Clinical Practice Research Datalink linked to Hospital Episode Statistics between 1997 and 2017, we identified adults starting ACEI or ARB (as an active comparator drug). We regarded prescription of ACEI or ARB as time-dependent exposure and used a Cox regression model to compare incidence of first hospitalisation with infection due to S. aureus in periods with ACEI to periods with ARB prescriptions. We repeated the analysis using control outcomes that we did not expect to be associated with use of ACEI versus ARB (Gram-negative sepsis, hip fracture and herpes zoster) and one that we did (dry cough). Results: We identified 445,341 new users of ACEI (mean age 64.0±14.0, male 51.7%) and 41,824 new users of ARB (mean age 64.1±14.0, male 45.5%). The fully adjusted hazard ratio for S. aureus infection (ACEI vs. ARB) was 1.18 (95% CI 1.10-1.27), consistent across sensitivity analyses. However, we also found associations with all control outcomes; rates of Gram-negative sepsis, hip fracture and dry cough were also increased during periods of time treated with ACEI compared to ARB while herpes zoster was more common during time treated with ARB. Conclusions: Our results suggest that although ARB users appear an ideal control for analyses of ACEI effects, there is residual confounding even after multivariable adjustment. This has implications for observational analyses comparing users of these drug classes, in particular the effect of these drugs in relation to COVID-19 infection.