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BACKGROUND: Globally, there is a paucity of multimorbidity and comorbidity data, especially for minority ethnic groups and younger people. We estimated the frequency of common disease combinations and identified non-random disease associations for all ages in a multiethnic population. METHODS: In this population-based study, we examined multimorbidity and comorbidity patterns stratified by ethnicity or race, sex, and age for 308 health conditions using electronic health records from individuals included on the Clinical Practice Research Datalink linked with the Hospital Episode Statistics admitted patient care dataset in England. We included individuals who were older than 1 year and who had been registered for at least 1 year in a participating general practice during the study period (between April 1, 2010, and March 31, 2015). We identified the most common combinations of conditions and comorbidities for index conditions. We defined comorbidity as the accumulation of additional conditions to an index condition over an individual's lifetime. We used network analysis to identify conditions that co-occurred more often than expected by chance. We developed online interactive tools to explore multimorbidity and comorbidity patterns overall and by subgroup based on ethnicity, sex, and age. FINDINGS: We collected data for 3 872 451 eligible patients, of whom 1 955 700 (50.5%) were women and girls, 1 916 751 (49.5%) were men and boys, 2 666 234 (68.9%) were White, 155 435 (4.0%) were south Asian, and 98 815 (2.6%) were Black. We found that a higher proportion of boys aged 1-9 years (132 506 [47.8%] of 277 158) had two or more diagnosed conditions than did girls in the same age group (106 982 [40.3%] of 265 179), but more women and girls were diagnosed with multimorbidity than were boys aged 10 years and older and men (1 361 232 [80.5%] of 1 690 521 vs 1 161 308 [70.8%] of 1 639 593). White individuals (2 097 536 [78.7%] of 2 666 234) were more likely to be diagnosed with two or more conditions than were Black (59 339 [60.1%] of 98 815) or south Asian individuals (93 617 [60.2%] of 155 435). Depression commonly co-occurred with anxiety, migraine, obesity, atopic conditions, deafness, soft-tissue disorders, and gastrointestinal disorders across all subgroups. Heart failure often co-occurred with hypertension, atrial fibrillation, osteoarthritis, stable angina, myocardial infarction, chronic kidney disease, type 2 diabetes, and chronic obstructive pulmonary disease. Spinal fractures were most strongly non-randomly associated with malignancy in Black individuals, but with osteoporosis in White individuals. Hypertension was most strongly associated with kidney disorders in those aged 20-29 years, but with dyslipidaemia, obesity, and type 2 diabetes in individuals aged 40 years and older. Breast cancer was associated with different comorbidities in individuals from different ethnic groups. Asthma was associated with different comorbidities between males and females. Bipolar disorder was associated with different comorbidities in younger age groups compared with older age groups. INTERPRETATION: Our findings and interactive online tools are a resource for: patients and their clinicians, to prevent and detect comorbid conditions; research funders and policy makers, to redesign service provision, training priorities, and guideline development; and biomedical researchers and manufacturers of medicines, to provide leads for research into common or sequential pathways of disease and inform the design of clinical trials. FUNDING: UK Research and Innovation, Medical Research Council, National Institute for Health and Care Research, Department of Health and Social Care, Wellcome Trust, British Heart Foundation, and The Alan Turing Institute.

Objective To evaluate antithrombotic (AT) use in individuals with atrial fibrillation (AF) and at high risk of stroke (CHA2DS2-VASc score ≥2) and investigate whether pre-existing AT use may improve COVID-19 outcomes.Methods Individuals with AF and CHA2DS2-VASc score ≥2 on 1 January 2020 were identified using electronic health records for 56 million people in England and were followed up until 1 May 2021. Factors associated with pre-existing AT use were analysed using logistic regression. Differences in COVID-19-related hospitalisation and death were analysed using logistic and Cox regression in individuals with pre-existing AT use versus no AT use, anticoagulants (AC) versus antiplatelets (AP), and direct oral anticoagulants (DOACs) versus warfarin.Results From 972 971 individuals with AF (age 79 (±9.3), female 46.2%) and CHA2DS2-VASc score ≥2, 88.0% (n=856 336) had pre-existing AT use, 3.8% (n=37 418) had a COVID-19 hospitalisation and 2.2% (n=21 116) died, followed up to 1 May 2021. Factors associated with no AT use included comorbidities that may contraindicate AT use (liver disease and history of falls) and demographics (socioeconomic status and ethnicity). Pre-existing AT use was associated with lower odds of death (OR=0.92, 95% CI 0.87 to 0.96), but higher odds of hospitalisation (OR=1.20, 95% CI 1.15 to 1.26). AC versus AP was associated with lower odds of death (OR=0.93, 95% CI 0.87 to 0.98) and higher hospitalisation (OR=1.17, 95% CI 1.11 to 1.24). For DOACs versus warfarin, lower odds were observed for hospitalisation (OR=0.86, 95% CI 0.82 to 0.89) but not for death (OR=1.00, 95% CI 0.95 to 1.05).Conclusions Pre-existing AT use may be associated with lower odds of COVID-19 death and, while not evidence of causality, provides further incentive to improve AT coverage for eligible individuals with AF.

ObjectivesTo estimate the impact of the COVID-19 pandemic on cardiovascular disease (CVD) and CVD management using routinely collected medication data as a proxy.DesignDescriptive 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.SettingCommunity dispensed CVD medications with 100% coverage from England, Scotland and Wales, plus primary care prescribed CVD medications from England (including 98% English general practices).Participants15.8 million individuals aged 18+ years alive on 1stApril 2018 dispensed at least one CVD medicine in a year from England, Scotland and Wales.Main outcome measuresMonthly counts, percent annual change (1stApril 2018 to 31stJuly 2021) and annual rates (1stMarch 2018 to 28thFebruary 2021) of medicines dispensed by CVD/ CVD risk factor; prevalent and incident use.ResultsYear-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.ConclusionsManagement 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.

Background Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. Methods In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. Findings Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. Interpretation Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. Funding British Heart Foundation Data Science Centre, led by Health Data Research UK.

ObjectiveEvaluate antithrombotic (AT) use in individuals with atrial fibrillation (AF) and high stroke risk (CHA2DS2-VASc score>=2) and investigate whether pre-existing AT use may improve COVID-19 outcomes.MethodsIndividuals with AF and a CHA2DS2-VASc score>=2 on January 1st 2020 were identified using pseudonymised, linked electronic health records for 56 million people in England and followed-up until May 1st 2021. Factors associated with pre-existing AT use were analysed using logistic regression. Differences in COVID-19 related hospitalisation and death were analysed using logistic and Cox regression for individuals exposed to pre-existing AT use vs no AT use, anticoagulants (AC) vs antiplatelets (AP) and direct oral anticoagulants (DOACs) vs warfarin.ResultsFrom 972,971 individuals with AF and a CHA2DS2-VASc score>=2, 88.0% (n=856,336) had pre-existing AT use, 3.8% (n=37,418) had a COVID-19 related hospitalisation and 2.2% (n=21,116) died. Factors associated with no AT use included comorbidities that may contraindicate AT use (liver disease and history of falls) and demographics (socioeconomic status and ethnicity). Pre-existing AT use was associated with lower odds of death (OR=0.92 [0.87-0.96 at 95% CI]), but higher odds of hospitalisation OR=1.20 [1.15-1.26 at 95% CI]). The same pattern was observed for AC vs AP (death (OR=0.93 [0.87-0.98]), hospitalisation (OR=1.17 [1.11-1.24])) but not for DOACs vs warfarin (death (OR=1.00 [0.95-1.05]), hospitalisation (OR=0.86 [0.82-0.89]).ConclusionsPre-existing AT use may offer marginal protection against COVID-19 death, with AC offering more protection than AP. Although this association may not be causal, it provides further incentive to improve AT coverage for eligible individuals with AF.KEY QUESTIONSWhat is already known about this subject?Anticoagulants (AC), a sub-class of antithrombotics (AT), reduce the risk of stroke and are recommended for individuals with atrial fibrillation (AF) and at high risk of stroke (CHA2DS2-VASc score>=2, National Institute for Health and Care Excellence threshold). However, previous evaluations suggest that up to one third of these individuals may not be taking AC. Over estimation of bleeding and fall risk in elderly patients have been identified as potential factors in this under medicating.In response to the COVID-19 pandemic, several observational studies have observed correlations between pre-existing AT use, particularly anticoagulants (AC), and lower risk of severe COVID-19 outcomes such as hospitalisation and death. However, these correlations are inconsistent across studies and have not compared all major sub-types of AT in one study.What does this study add?This study uses datasets covering primary care, secondary care, pharmacy dispensing, death registrations, multiple COVID-19 diagnoses routes and vaccination records for 56 million people in England and is the largest scale evaluation of AT use to date. This provides the statistical power to robustly analyse targeted sub-types of AT and control for a wide range of potential confounders. All code developed for the study is opensource and an updated nationwide evaluation can be rapidly created for future time points.In 972,971 individuals with AF and a CHA2DS2-VASc score>=2, we observed 88.0% (n=856,336) with pre-existing AT use which was associated with marginal protection against COVID-19 death (OR=0.92 [0.87-0.96 at 95% CI]).How might this impact on clinical practice?These findings can help shape global AT medication policy and provide population-scale, observational analysis results alongside gold-standard randomised control trials to help assess whether a potential beneficial effect of pre-existing AT use on COVID-19 death alters risk to benefit assessments in AT prescribing decisions.

Background: The current study sought to develop a valid, reliable and unobtrusive tablet computer-based observational measure to assess engagement of people with advanced dementia. The Video Analysis Scale of Engagement (VASE) was designed to enable the rating of moment-by-moment changes in engagement during an activity, which would be useful for both future research and current residential care. Methods: An initial version of the VASE was tested. Face validity and content validity were assessed to validate an operational definition of engagement and develop an acceptable protocol for the scale. Thirty-seven non-professional and professional volunteers were recruited to view and rate level of engagement in music activities using the VASE. Results: An inter-class coefficient (ICC) test gave a high level of rating agreement across professionals and non-professionals. However, the ICC results of within-professionals were mixed. Linear mixed modelling suggested that the types of interventions (active or passive music listening), the particular intervention session being rated, time period of video and the age of raters could affect the ratings. Conclusions: Results suggested that raters used the VASE in a dynamic fashion and that the measure was able to distinguish between interventions. Further investigation and adjustments are warranted for this to be considered a valid and reliable scale in the measurement of engagement of people with advanced dementia in a residential care setting.