The Antidepressant Advisor (ADeSS): A Decision Support System for Antidepressant Treatment for Depression in UK primary care – a feasibility study (preprint)

Objectives To develop and probe the first computerised decision-support tool to provide antidepressant treatment guidance to GPs in UK primary care. Design A parallel group, cluster-randomised controlled feasibility trial, where individual participants were blind to treatment allocation. Setting South London NHS GP practices. Participants Ten practices and eighteen patients with treatment-resistant current major depressive disorder (MDD). Interventions Practices were randomised to two treatment arms: 1) treatment-as-usual, 2) computerised decision support tool. Results Ten GP practices participated in the trial, which was within our target range (8-20). However, practice and patient recruitment were slower than anticipated and only 18 of 86 intended patients were recruited. This was due to fewer than expected patients being eligible for the study, as well as disruption resulting from the Covid-19 pandemic. Only one patient was lost to follow-up. There were no serious or medically important adverse events during the trial. GPs in the ‘Decision tool’ arm indicated moderate support for the tool. A minority of patients fully engaged with the mobile app-based tracking of symptoms, medication adherence and side effects. Conclusions Overall, the trial is not feasible in the current form and would need to be modified as follows to overcome its limitations: 1) inclusion of patients who have only tried one SSRI, rather than two, to improve recruitment and pragmatic relevance of the study, 2) approaching community pharmacists to implement tool recommendations rather than GPs, 3) further funding to directly interface between the decision support tool and self-reported symptom app, 4) increasing the geographic reach by not requiring detailed diagnostic assessments and replacing this with supported remote self-report. Ethics and dissemination The study has received NHS ethical approval from the London - Camberwell St Giles Research Ethics Committee (ref:17/LO/2074). Trial registration number ClinicalTrials.gov Identifier: NCT03628027 Strengths and limitations of this study The Antidepressant Advisor tool was incorporated into an existing GP healthcare record system for ease of use by GPs We were unable to recruit a sufficient number of participants to estimate effect sizes for future trials The eligibility criteria for participants to have tried two antidepressants before entering the study limited the number of eligible participants

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.

The adverse impact of COVID-19 pandemic on cardiovascular disease prevention and management in England, Scotland and Wales: A population-scale descriptive analysis of trends in medication data (preprint)

Objectives: To estimate the impact of the COVID-19 pandemic on cardiovascular disease (CVD) and CVD management using routinely collected medication data as a proxy. Design: Descriptive and interrupted time series analysis using anonymised individual-level population-scale data for 1.32 billion records of dispensed CVD medications across 15.8 million individuals in England, Scotland and Wales. Setting: Community dispensed CVD medications with 100% coverage from England, Scotland and Wales, plus primary care prescribed CVD medications from England (including 98% English general practices). Participants: 15.8 million individuals aged 18+ years alive on 1st April 2018 dispensed at least one CVD medicine in a year from England, Scotland and Wales. Main outcome measures: Monthly counts, percent annual change (1st April 2018 to 31st July 2021) and annual rates (1st March 2018 to 28th February 2021) of medicines dispensed by CVD/ CVD risk factor; prevalent and incident use. Results: Year-on-year change in dispensed CVD medicines by month were observed, with notable uplifts ahead of the first (11.8% higher in March 2020) but not subsequent national lockdowns. Using hypertension as one example of the indirect impact of the pandemic, we observed 491,203 fewer individuals initiated antihypertensive treatment across England, Scotland and Wales during the period March 2020 to end May 2021 than would have been expected compared to 2019. We estimated that this missed antihypertension treatment could result in 13,659 additional CVD events should individuals remain untreated, including 2,281 additional myocardial infarctions (MIs) and 3,474 additional strokes. Incident use of lipid-lowering medicines decreased by an average 14,793 per month in early 2021 compared with the equivalent months prior to the pandemic in 2019. In contrast, the use of incident medicines to treat type-2 diabetes (T2DM) increased by approximately 1,642 patients per month. Conclusions: Management of key CVD risk factors as proxied by incident use of CVD medicines has not returned to pre-pandemic levels in the UK. Novel methods to identify and treat individuals who have missed treatment are urgently required to avoid large numbers of additional future CVD events, further adding indirect cost of the COVID-19 pandemic.

A case-control and cohort study to determine the relationship between ethnic background and severe COVID-19 (preprint)

BackgroundPeople of minority ethnic background may be disproportionately affected by severe COVID-19 for reasons that are unclear. We sought to examine the relationship between ethnic background and (1) hospital admission for severe COVID-19; (2) in-hospital mortality. MethodsWe conducted a case-control study of 872 inner city adult residents admitted to hospital with confirmed COVID-19 (cases) and 3,488 matched controls randomly sampled from a primary healthcare database comprising 344,083 people resident in the same region. To examine in-hospital mortality, we conducted a cohort study of 1827 adults consecutively admitted with COVID-19. Data collected included hospital admission for COVID-19, demographics, comorbidities, in-hospital mortality. The primary exposure variable was self-defined ethnicity. ResultsThe 872 cases comprised 48.1% Black, 33.7% White, 12.6% Mixed/Other and 5.6% Asian patients. In conditional logistic regression analyses, Black and Mixed/Other ethnicity were associated with higher admission risk than white (OR 3.12 [95% CI 2.63-3.71] and 2.97 [2.30-3.85] respectively). Adjustment for comorbidities and deprivation modestly attenuated the association (OR 2.28 [1.87-2.79] for Black, 2.66 [2.01-3.52] for Mixed/Other). Asian ethnicity was not associated with higher admission risk (OR 1.20 [0.86-1.66]). In the cohort study of 1827 patients, 455 (28.9%) died over a median (IQR) of 8 (4-16) days. Age and male sex, but not Black (adjusted HR 0.84 [0.63-1.11]) or Mixed/Other ethnicity (adjusted HR 0.69 [0.43-1.10]), were associated with in-hospital mortality. Asian ethnicity was associated with higher in-hospital mortality (adjusted HR 1.54 [0.98-2.41]). ConclusionsBlack and Mixed ethnicity are independently associated with greater admission risk with COVID-19 and may be risk factors for development of severe disease. Comorbidities and socioeconomic factors only partly account for this and additional ethnicity-related factors may play a large role. The impact of COVID-19 may be different in Asians. Funding sourcesBritish Heart Foundation (CH/1999001/11735 and RE/18/2/34213 to AMS); the National Institute for Health Research Biomedical Research Centre (NIHR BRC) at Guys & St Thomas NHS Foundation Trust and Kings College London (IS-BRC-1215-20006); and the NIHR BRC at South London and Maudsley NHS Foundation Trust and Kings College London (IS-BRC-1215-20018).

Suspected COVID-19 in primary care: how GP records contribute to understanding differences in prevalence by ethnicity. (preprint)

Abstract Background The first wave of the London COVID-19 epidemic peaked in April 2020. Attention initially focussed on severe presentations, intensive care capacity, and the timely supply of equipment. General practice has seen a rapid take up of technology to allow virtual consultations, enabling the management of mild and moderate community cases. Aim To quantify the prevalence and time-course of suspected COVID-19 presenting to general practices during the London epidemic. To report disease prevalence by ethnic group, and explore how far differences by ethnicity can be explained by data in the electronic health record (EHR). Design and Setting Cross-sectional study using anonymised data from the primary care records of 1.3 million people registered with 157 practices in four adjacent east London clinical commissioning groups (CCGs). The study area includes 48% of people from ethnic minorities and is in the top decile of social deprivation in England. Method Suspected COVID-19 cases were identified using SNOMED codes. Explanatory variables included age, gender, self-reported ethnicity and measures of social deprivation. Clinical factors included 16 long-term conditions, latest body mass index and smoking status. Results There were 8,985 suspected COVID-19 cases. Ethnicity recording was 78% complete. Univariate analysis showed a two-fold increase in odds of infection for South Asian and Black adults compared to White. In a fully adjusted analysis, including clinical factors, the odds were: South Asian OR 1.93 (95% CI = 1.83 to 2.04) Black OR 1.47 (95% CI 1.38 to 1.57) Conclusions Using data in GP records Black and south Asian ethnicity remain as predictors of community cases of COVID-19, with levels of risk similar to hospital admission cases. Further understanding of these differences requires social and occupational data.