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The prevalence of multimorbidity has been growing due to the ageing population and increasingly unhealthy lifestyles. There is interest in identifying clusters of disease and how they are influenced. This systematic review aims to (i) investigate the most common clusters in the adult population with multimorbidity (ii) identify methods used to define clusters (iii) examine if clusters differ based on age, sex and socioeconomic status. We searched Medline, Embase, SCOPUS, Web of Science Core Collection, and CINAHL using concepts of multimorbidity and clustering techniques to identify relevant papers. Secondary data, including commonly reported clustering techniques, identified clusters, and other characteristics were extracted. All studies were quality assessed using the Newcastle-Ottawa Bias scale. From a total of 24,231 papers, 125 were included in the review. There was a total of 918 different clusters identified, which were categorized into 59 broad groups. A cardiometabolic cluster appeared most frequently within the identified studies and across age strata. The most common clustering technique was Latent Class Analysis (n = 51). Disease cluster prevalence appeared to differ based on age, whereas no differences could be identified by sex. Across the 125 papers identified, irrespective of clustering method, a relatively common set of clusters of disease were found. The Cardiometabolic cluster was the most frequently identified cluster across all age groups. Studies that stratified participants by age or sex identified distinct clusters within each subgroup, which differed from those observed in clusters formed from the general adult population (18+).Latent class analysis was the most common clustering technique within this review, but it was not explored if different clustering methods led to different clusters. Further work is needed to distinguish the most prevalent clusters within specific stratified cohorts of different ages, sex, and socioeconomic status; nonetheless, data strongly suggests that there are different clusters that arise dependent on stratifications. With the expected increasing burden of multimorbidity, healthcare services may need to think about the most prevalent disease combinations within certain strata and how joint-specialist services can be tailored to treat those common conditions.

The BNT162b2 mRNA (Pfizer–BioNTech) and ChAdOx1 nCoV-19 (Oxford–AstraZeneca) COVID-19 vaccines have shown high efficacy against disease in phase 3 clinical trials and are now being used in national vaccination programmes in the UK and several other countries. Studying the real-world effects of these vaccines is an urgent requirement. The aim of our study was to investigate the association between the mass roll-out of the first doses of these COVID-19 vaccines and hospital admissions for COVID-19. We did a prospective cohort study using the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19—EAVE II—database comprising linked vaccination, primary care, real-time reverse transcription-PCR testing, and hospital admission patient records for 5·4 million people in Scotland (about 99% of the population) registered at 940 general practices. Individuals who had previously tested positive were excluded from the analysis. A time-dependent Cox model and Poisson regression models with inverse propensity weights were fitted to estimate effectiveness against COVID-19 hospital admission (defined as 1–adjusted rate ratio) following the first dose of vaccine. Between Dec 8, 2020, and Feb 22, 2021, a total of 1 331 993 people were vaccinated over the study period. The mean age of those vaccinated was 65·0 years (SD 16·2). The first dose of the BNT162b2 mRNA vaccine was associated with a vaccine effect of 91% (95% CI 85–94) for reduced COVID-19 hospital admission at 28–34 days post-vaccination. Vaccine effect at the same time interval for the ChAdOx1 vaccine was 88% (95% CI 75–94). Results of combined vaccine effects against hospital admission due to COVID-19 were similar when restricting the analysis to those aged 80 years and older (83%, 95% CI 72–89 at 28–34 days post-vaccination). Mass roll-out of the first doses of the BNT162b2 mRNA and ChAdOx1 vaccines was associated with substantial reductions in the risk of hospital admission due to COVID-19 in Scotland. There remains the possibility that some of the observed effects might have been due to residual confounding. UK Research and Innovation (Medical Research Council), Research and Innovation Industrial Strategy Challenge Fund, Health Data Research UK.

Population-level data on COVID-19 vaccine uptake in pregnancy and SARS-CoV-2 infection outcomes are lacking. We describe COVID-19 vaccine uptake and SARS-CoV-2 infection in pregnant women in Scotland, using whole-population data from a national, prospective cohort. Between the start of a COVID-19 vaccine program in Scotland, on 8 December 2020 and 31 October 2021, 25,917 COVID-19 vaccinations were given to 18,457 pregnant women. Vaccine coverage was substantially lower in pregnant women than in the general female population of 18−44 years; 32.3% of women giving birth in October 2021 had two doses of vaccine compared to 77.4% in all women. The extended perinatal mortality rate for women who gave birth within 28 d of a COVID-19 diagnosis was 22.6 per 1,000 births (95% CI 12.9−38.5; pandemic background rate 5.6 per 1,000 births; 452 out of 80,456; 95% CI 5.1−6.2). Overall, 77.4% (3,833 out of 4,950; 95% CI 76.2−78.6) of SARS-CoV-2 infections, 90.9% (748 out of 823; 95% CI 88.7−92.7) of SARS-CoV-2 associated with hospital admission and 98% (102 out of 104; 95% CI 92.5−99.7) of SARS-CoV-2 associated with critical care admission, as well as all baby deaths, occurred in pregnant women who were unvaccinated at the time of COVID-19 diagnosis. Addressing low vaccine uptake rates in pregnant women is imperative to protect the health of women and babies in the ongoing pandemic. Findings from the COVID-19 in Pregnancy in Scotland (COPS) study reveals low levels of vaccination uptake by pregnant women compared to women in the general population and that not being vaccinated is associated with increased risk of severe complications of COVID-19 in pregnancy, including perinatal mortality.

Current UK vaccination policy is to offer future COVID-19 booster doses to individuals at high risk of serious illness from COVID-19, but it is still uncertain which groups of the population could benefit most. In response to an urgent request from the UK Joint Committee on Vaccination and Immunisation, we aimed to identify risk factors for severe COVID-19 outcomes (ie, COVID-19-related hospitalisation or death) in individuals who had completed their primary COVID-19 vaccination schedule and had received the first booster vaccine. We constructed prospective cohorts across all four UK nations through linkages of primary care, RT-PCR testing, vaccination, hospitalisation, and mortality data on 30 million people. We included individuals who received primary vaccine doses of BNT162b2 (tozinameran; Pfizer–BioNTech) or ChAdOx1 nCoV-19 (Oxford–AstraZeneca) vaccines in our initial analyses. We then restricted analyses to those given a BNT162b2 or mRNA-1273 (elasomeran; Moderna) booster and had a severe COVID-19 outcome between Dec 20, 2021, and Feb 28, 2022 (when the omicron (B.1.1.529) variant was dominant). We fitted time-dependent Poisson regression models and calculated adjusted rate ratios (aRRs) and 95% CIs for the associations between risk factors and COVID-19-related hospitalisation or death. We adjusted for a range of potential covariates, including age, sex, comorbidities, and previous SARS-CoV-2 infection. Stratified analyses were conducted by vaccine type. We then did pooled analyses across UK nations using fixed-effect meta-analyses. Between Dec 8, 2020, and Feb 28, 2022, 17 337 580 individuals completed their primary vaccine schedule and 14 698 030 individuals received a booster dose. Between Dec 20, 2021, and Feb 28, 2022, 59 510 (0·3%) of the primary vaccine group and 26 100 (0·2%) of those who received their booster had severe COVID-19 outcomes. The risk of severe COVID-19 outcomes reduced after receiving the booster (rate change: 8·8 events per 1000 person-years to 7·6 events per 1000 person-years). Older adults (≥80 years vs 18–49 years; aRR 3·60 [95% CI 3·45–3·75]), those with comorbidities (≥5 comorbidities vs none; 9·51 [9·07–9·97]), being male (male vs female; 1·23 [1·20–1·26]), and those with certain underlying health conditions—in particular, individuals receiving immunosuppressants (yes vs no; 5·80 [5·53–6·09])—and those with chronic kidney disease (stage 5 vs no; 3·71 [2·90–4·74]) remained at high risk despite the initial booster. Individuals with a history of COVID-19 infection were at reduced risk (infected ≥9 months before booster dose vs no previous infection; aRR 0·41 [95% CI 0·29–0·58]). Older people, those with multimorbidity, and those with specific underlying health conditions remain at increased risk of COVID-19 hospitalisation and death after the initial vaccine booster and should, therefore, be prioritised for additional boosters, including novel optimised versions, and the increasing array of COVID-19 therapeutics. National Core Studies–Immunity, UK Research and Innovation (Medical Research Council), Health Data Research UK, the Scottish Government, and the University of Edinburgh.

Primary care practices in Scotland were randomly assigned to various start dates for an intervention with financial incentives to review patients at high risk for adverse effects from antiplatelet agents or NSAIDs. The intervention was associated with reduced high-risk prescribing. High-risk prescribing and preventable drug-related complications in primary care are major concerns for health care systems internationally. 1 – 7 Up to 4% of emergency hospital admissions are caused by preventable adverse drug events, 8 – 10 and in the United States, the cost of avoidable drug-related hospital admissions, emergency department attendances, and outpatient visits was estimated at $19.6 billion in 2013. 11 The majority of drug-related emergency admissions are caused by commonly prescribed drugs, with substantial contributions from nonsteroidal antiinflammatory drugs (NSAIDs) and antiplatelet medications because of gastrointestinal, cardiovascular, and renal adverse drug events. 4 , 5 , 7 , 8 Despite routine public reporting of a number . . .

Objective(1) To estimate the pooled prevalence of multimorbidity in all age groups, globally. (2) To examine how measurement of multimorbidity impacted the estimated prevalence.MethodsIn this systematic review and meta-analysis, we conducted searches in nine bibliographic databases (PsycINFO, Embase, Global Health, Medline, Scopus, Web of Science, Cochrane Library, CINAHL and ProQuest Dissertations and Theses Global) for prevalence studies published between database inception and 21 January 2020. Studies reporting the prevalence of multimorbidity (in all age groups and in community, primary care, care home and hospital settings) were included. Studies with an index condition or those that did not include people with no long-term conditions in the denominator were excluded. Retrieved studies were independently reviewed by two reviewers, and relevant data were extracted using predesigned pro forma. We used meta-analysis to pool the estimated prevalence of multimorbidity across studies, and used random-effects meta-regression and subgroup analysis to examine the association of heterogeneous prevalence estimates with study and measure characteristics.Results13 807 titles were screened, of which 193 met inclusion criteria for meta-analysis. The pooled prevalence of multimorbidity was 42.4% (95% CI 38.9% to 46.0%) with high heterogeneity (I2 >99%). In adjusted meta-regression models, participant mean age and the number of conditions included in a measure accounted for 47.8% of heterogeneity in effect sizes. The estimated prevalence of multimorbidity was significantly higher in studies with older adults and those that included larger numbers of conditions. There was no significant difference in estimated prevalence between low-income or middle-income countries (36.8%) and high-income countries (44.3%), or between self-report (40.0%) and administrative/clinical databases (52.7%).ConclusionsThe pooled prevalence of multimorbidity was significantly higher in older populations and when studies included a larger number of baseline conditions. The findings suggest that, to improve study comparability and quality of reporting, future studies should use a common core conditions set for multimorbidity measurement and report multimorbidity prevalence stratified by sociodemographics. PROSPERO registration number CRD42020172409.

Background General and preventive health checks are a key feature of contemporary policies of anticipatory care. Ensuring high and equitable uptake of such general health checks is essential to ensuring health gain and preventing health inequalities. This literature review explores the socio-demographic, clinical and social cognitive characteristics of those who do and do not engage with general health checks or preventive health checks for cardiovascular disease. Methods An exploratory scoping study approach was employed. Databases searched included the British Nursing Index and Archive, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Database of Systematic Reviews (CDSR) and Database of Abstracts of Reviews of Effects (DARE), EMBASE, MEDLINE, PsycINFO and the Social Sciences Citation Index (SSCI). Titles and abstracts of 17463 papers were screened; 1171 papers were then independently assessed by two researchers. A review of full text was carried out by two of the authors resulting in 39 being included in the final review. Results Those least likely to attend health checks were men on low incomes, low socio-economic status, unemployed or less well educated. In general, attenders were older than non-attenders. An individual’s marital status was found to affect attendance rates with non-attenders more likely to be single. In general, white individuals were more likely to engage with services than individuals from other ethnic backgrounds. Non-attenders had a greater proportion of cardiovascular risk factors than attenders, and smokers were less likely to attend than non-smokers. The relationship between health beliefs and health behaviours appeared complex. Non-attenders were shown to value health less strongly, have low self-efficacy, feel less in control of their health and be less likely to believe in the efficacy of health checks. Conclusion Routine health check-ups appear to be taken up inequitably, with gender, age, socio-demographic status and ethnicity all associated with differential service use. Furthermore, non-attenders appeared to have greater clinical need or risk factors suggesting that differential uptake may lead to sub-optimal health gain and contribute to inequalities via the inverse care law. Appropriate service redesign and interventions to encourage increased uptake among these groups is required.

ObjectiveTo develop international consensus on the definition and measurement of multimorbidity in research.DesignDelphi consensus study.SettingInternational consensus; data collected in three online rounds from participants between 30 November 2020 and 18 May 2021.ParticipantsProfessionals interested in multimorbidity and people with long term conditions were recruited to professional and public panels.Results150 professional and 25 public participants completed the first survey round. Response rates for rounds 2/3 were 83%/92% for professionals and 88%/93% in the public panel, respectively. Across both panels, the consensus was that multimorbidity should be defined as two or more long term conditions. Complex multimorbidity was perceived to be a useful concept, but the panels were unable to agree on how to define it. Both panels agreed that conditions should be included in a multimorbidity measure if they were one or more of the following: currently active; permanent in their effects; requiring current treatment, care, or therapy; requiring surveillance; or relapsing-remitting conditions requiring ongoing care. Consensus was reached for 24 conditions to always include in multimorbidity measures, and 35 conditions to usually include unless a good reason not to existed. Simple counts were preferred for estimating prevalence and examining clustering or trajectories, and weighted measures were preferred for risk adjustment and outcome prediction.ConclusionsPrevious multimorbidity research is limited by inconsistent definitions and approaches to measuring multimorbidity. This Delphi study identifies professional and public panel consensus guidance to facilitate consistency of definition and measurement, and to improve study comparability and reproducibility.

Understanding the impact of SARS-CoV-2 infection and COVID-19 vaccination in pregnancy on neonatal and maternal outcomes informs clinical decision-making. Here we report a national, population-based, matched cohort study to investigate associations between SARS-CoV-2 infection and, separately, COVID-19 vaccination just before or during pregnancy and the risk of adverse neonatal and maternal outcomes among women in Scotland with a singleton pregnancy ending at ≥20 weeks gestation. Neonatal outcomes are stillbirth, neonatal death, extended perinatal mortality, preterm birth (overall, spontaneous, and provider-initiated), small-for-gestational age, and low Apgar score. Maternal outcomes are admission to critical care or death, venous thromboembolism, hypertensive disorders of pregnancy, and pregnancy-related bleeding. We use conditional logistic regression to derive odds ratios adjusted for socio-demographic and clinical characteristics (aORs). We find that infection is associated with an increased risk of preterm (aOR=1.36, 95% Confidence Interval [CI] = 1.16–1.59) and very preterm birth (aOR = 1.90, 95% CI 1.20–3.02), maternal admission to critical care or death (aOR=1.72, 95% CI = 1.39–2.12), and venous thromboembolism (aOR = 2.53, 95% CI = 1.47–4.35). We find no evidence of increased risk for any of our outcomes following vaccination. These data suggest SARS-CoV-2 infection during pregnancy is associated with adverse neonatal and maternal outcomes, and COVID-19 vaccination remains a safe way for pregnant women to protect themselves and their babies against infection. The impacts of SARS-CoV-2 infection and COVID-19 vaccination in pregnancy are not fully understood. Here, the authors perform a cohort study using data from Scotland and find that infection was associated with increased risk of preterm birth and some adverse maternal outcomes, but there was no evidence of adverse outcomes associated with vaccination.

Data on the safety of COVID-19 vaccines in early pregnancy are limited. We conducted a national, population-based, matched cohort study assessing associations between COVID-19 vaccination and miscarriage prior to 20 weeks gestation and, separately, ectopic pregnancy. We identified women in Scotland 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). Matched, unvaccinated women from the pre-pandemic and, separately, pandemic periods were used as controls. Here we show no association between vaccination and miscarriage (adjusted Odds Ratio [aOR], pre-pandemic controls = 1.02, 95% Confidence Interval [CI] = 0.96–1.09) or ectopic pregnancy (aOR = 1.13, 95% CI = 0.92–1.38). We undertook additional analyses examining confirmed SARS-CoV-2 infection as the exposure and similarly found no association with miscarriage or ectopic pregnancy. Our findings support current recommendations that vaccination remains the safest way for pregnant women to protect themselves and their babies from COVID-19. Data on the safety of COVD-19 vaccines in early pregnancy are limited. Here, the authors assess the rates of miscarriage and ectopic pregnancy following vaccination using electronic health record data from Scotland, and find no evidence of increased risks.