Background: Cardiovascular diseases(CVD) increase mortality risk from coronavirus infection(COVID-19), but there are concerns that the pandemic has affected supply and demand of acute cardiovascular care. We estimated excess mortality in specific CVDs, both direct, through infection, and indirect, through changes in healthcare. Methods: We used population-based electronic health records from 3,862,012 individuals in England to estimate pre- and post-COVID-19 mortality risk(direct effect) for people with incident and prevalent CVD. We incorporated: (i)pre-COVID-19 risk by age, sex and comorbidities, (ii)estimated population COVID-19 prevalence, and (iii)estimated relative impact of COVID-19 on mortality(relative risk, RR: 1.5, 2.0 and 3.0). For indirect effects, we analysed weekly mortality and emergency department data for England/Wales and monthly hospital data from England(n=2), China(n=5) and Italy(n=1) for CVD referral, diagnosis and treatment until 1 May 2020. Findings: CVD service activity decreased by 60-100% compared with pre-pandemic levels in eight hospitals across China, Italy and England during the pandemic. In China, activity remained below pre-COVID-19 levels for 2-3 months even after easing lockdown, and is still reduced in Italy and England. Mortality data suggest indirect effects on CVD will be delayed rather than contemporaneous(peak RR 1.4). For total CVD(incident and prevalent), at 10% population COVID-19 rate, we estimated direct impact of 31,205 and 62,410 excess deaths in England at RR 1.5 and 2.0 respectively, and indirect effect of 49932 to 99865 excess deaths. Interpretation: Supply and demand for CVD services have dramatically reduced across countries with potential for substantial, but avoidable, excess mortality during and after the COVID-19 pandemic.
Background: Obesity is a modifiable risk factor for coronavirus(COVID-19)-related mortality. We estimated excess mortality in obesity, both 'direct', through infection, and 'indirect', through changes in healthcare, and also due to potential increasing obesity during lockdown. Methods: In population-based electronic health records for 1 958 638 individuals in England, we estimated 1-year mortality risk('direct' and 'indirect' effects) for obese individuals, incorporating: (i)pre-COVID-19 risk by age, sex and comorbidities, (ii)population infection rate, and (iii)relative impact on mortality(relative risk, RR: 1.2, 1.5, 2.0 and 3.0). Using causal inference models, we estimated impact of change in body-mass index(BMI) and physical activity during 3-month lockdown on 1-year incidence for high-risk conditions(cardiovascular diseases, CVD; diabetes; chronic obstructive pulmonary disease, COPD and chronic kidney disease, CKD), accounting for confounders. Findings: For severely obese individuals (3.5% at baseline), at 10% population infection rate, we estimated direct impact of 240 and 479 excess deaths in England at RR 1.5 and 2.0 respectively, and indirect effect of 383 to 767 excess deaths, assuming 40% and 80% will be affected at RR=1.2. Due to BMI change during the lockdown, we estimated that 97 755 (5.4%: normal weight to overweight, 5.0%: overweight to obese and 1.3%: obese to severely obese) to 434 104 individuals (15%: normal weight to overweight, 15%: overweight to obese and 6%: obese to severely obese) individuals would be at higher risk for COVID-19 over one year. Interpretation: Prevention of obesity and physical activity are at least as important as physical isolation of severely obese individuals during the pandemic.
Background: Coronavirus (COVID-19) poses health system challenges in every country. As with any public health emergency, a major component of the global response is timely, effective science. However, particular factors specific to COVID-19 must be overcome to ensure that research efforts are optimised. We aimed to model the impact of COVID-19 on the clinical academic response in the UK, and to provide recommendations for COVIDrelated research. Methods:We constructed a simple stochastic model to determine clinical academic capacity in the UK in four policy approaches to COVID-19 with differing population infection rates:"Italy model" (6%), "mitigation" (10%), "relaxed mitigation" (40%) and "do-nothing" (80%) scenarios. The ability to conduct research in the COVID-19 climate is affected by the following key factors: (i) infection growth rate and population infection rate (from UK COVID-19 statistics and WHO); (ii) strain on the healthcare system (from published model); and (iii) availability of clinical academic staff with appropriate skillsets affected by frontline clinical activity and sickness (from UK statistics). Findings:In "Italy model", "mitigation", "relaxed mitigation" and "do-nothing" scenarios, from 5 March 2020 the duration (days) and peak infection rates (%) are 95(2.4%), 115(2.5%), 240(5.3%) and 240(16.7%) respectively. Near complete attrition of academia (87% reduction, <400 clinical academics) occurs 35 days after pandemic start for 11, 34, 62, 76 days respectively -with no clinical academics at all for 37 days in the "do-nothing" scenario.Restoration of normal academic workforce (80% of normal capacity) takes 11,12, 30 and 26 weeks respectively.Interpretation: Pandemic COVID-19 crushes the science needed at system level. National policies mitigate, but the academic community needs to adapt. We highlight six key strategies: radical prioritisation (eg 3-4 research ideas per institution), deep resourcing, nonstandard leadership (repurposing of key non-frontline teams), rationalisation (profoundly simple approaches), careful site selection (eg protected sites with large academic backup) and complete suspension of academic competition with collaborative approaches.
Background: Cross sectional measures of body mass index (BMI) are associated with cardiovascular disease (CVD) incidence, but less is known about whether weight change affects the risk of CVD. Methods: We estimated the effect of 2 year weight change interventions on 7 year risk of CVD, by emulating hypothetical target trials using electronic health records. We identified 138.567 individuals in England between 1998 and 2016, aged 45-69 years old, free of chronic diseases at baseline. We performed pooled logistic regression, using inverse-probability weighting to adjust for baseline and time-varying variables. Each individual was classified into a weight loss, maintenance, or gain group. Findings: In the normal weight, both weight loss and gain were associated with increased risk for CVD [HR vs weight maintenance=1.53 (1.18 to 1.98) and 1.43 (1.19 to 1.71 respectively)]. Among overweight individuals, both weight loss and gain groups, compared to weight maintenance, had a moderately higher risk of CVD [HR=1.20 (0.99 to 1.44) and 1.17 (0.99 to 1.38), respectively]. In the obese, weight loss had a lower risk lower risk of CHD [HR =0.66 (0.49 to 0.89)] and a moderately lower risk of CVD [HR =0.90 (0.72 to 1.13)]. When we assumed that a chronic disease occurred 1-3 years before the recorded date, estimates for weight loss and gain were attenuated among overweight individuals and estimates for weight loss were stronger among individuals with obesity. Interpretation: Among individuals with obesity, the weight loss group had a lower risk of CHD and moderately lower risk of CVD. Weight gain increased the risk of CVD across BMI groups.
ObjectivesWe used data from UK-Biobank that were linked with Hospital Episode Statistics and Office for National Statistics to assess the relationship between low-density lipoprotein cholesterol (LDL-C) and atrial fibrillation (AF). In this study, we applied Mendelian randomization in order to find out whether there is a causal effect of LDL-C to AF. ApproachWe used data from the UK Biobank (˜500,000 subjects) which is linked with electronic health records. At baseline (2006)(2007)(2008)(2009)(2010), participants from across the UK took part in this project. They have undergone measures, provided blood, urine and saliva samples for future analysis, detailed information about themselves and agreed to have their health followed. Information in relation to the development of atrial fibrillation was derived from a) the enrollment of the participants (self-reported events), b) their hospitalization before and after their recruitment to UKBiobank (confirmed events from Hospital Episode Statistics) and c) the death certificates [confirmed events from Office for National Statistics]. We also used genetic data from the analyses of the participants' blood sample that have been stored. We used Mendelian randomization to capture the effect of LDL-C to AF. As instruments, we used a genetic predisposition risk score (GPRs) for LDL-C, which was created as a weighted sum of the 18 most significant SNPs related to LDL-C, as there were documented in Global Lipid Consortium, in 18 out of 22 chromosomes. We ran a logistic regression model, using AF as outcome and GPRs as exposure. ResultsOur final sample consisted of 144,092 individuals, for which we have valid information for their genetic data. The AF cases in this sample were 3207, most of which were identified from Hospital Episode Statistics (hospitalization of the participants). From the Mendelian randomization study, from our preliminary results, we found a weak positive relationship between GPRs and AF, when we did not adjust for any covariate [OR per one unit increase of GPRs=1.08, 95% CI= (0.95-1.22)] and results remained practically the same when we adjusted for age and sex [OR=1.09, 95% CI= (0.96-1.24 )]. ConclusionsWe observed a weak positive association between LDL-C and AF in this study. This is the first Mendelian randomization approach that focuses on this relationship. More Mendelian randomization studies should be performed in order to identify the causal effect of LDL-C to AF. The use of electronic health records will facilitate the conduction of similar studies. * Corresponding Author: Email Address: m.katsoulis@ucl.ac.uk (M. Katsoulis) http://dx
Wstęp: Wraz ze starzeniem się populacji w najbliższych latach należy spodziewać się wzrostu częstości występowania osteoporozy i chorób układu oddechowego. Kortykosteroidy—leki zwiększające ryzyko osteoporozy, są stosowane w różnych postaciach u chorych na schorzenia układu oddechowego, bez względu na zaawansowany wiek i zwiększone ryzyko złamań. Celem badania była ocena ryzyka złamania szyjki kości udowej u osób w wieku podeszłym, leczonych kortykosteroidami ze wskazań pulmonologicznych, z uwzględnieniem leków wziewnych. Materiał i metody: Dane na temat nowych złamań szyjki kości udowej zbierano za pomocą aktywnej obserwacji prospektywnej uczestników greckiego segmentu badania EPIC-Greece (EPIC-Greece, European Prospective Investigation into Cancer and Nutrition), którzy w momencie rekrutacji osiągnęli wiek co najmniej 60 lat i deklarowali chorobę układu oddechowego rozpoznaną przez lekarza. Dane na temat statusu socjoekonomicznego, stylu życia, stanu zdrowia oraz stosowania kortykosteroidów gromadzono za pomocą kwestionariuszy na początku i końcu badania. W celu oceny współczynnika ryzyka (HR) zastosowano model regresji Coxa, z uwzględnieniem czynników zakłócających. Wyniki: Stwierdzono wzrost ryzyka złamania szyjki kości udowej związany ze stosowaniem kortykosteroidów (HR: 1.68; 95% CI: 0.85–3.34). Zwiększone ryzyko utrzymywało się, gdy analizę ograniczono do osób przyjmujących jakiekolwiek kortykosteroidy z powodu chorób obturacyjnych (HR: 1.40; 95% CI: 0.64–3.06) oraz do osób przyjmujących wyłącznie leki wziewne (HR: 1.58; 95% CI: 0.71–3.50). Ta pozytywna zależność nie osiągnęła jednak poziomu istotności statystycznej, prawdopodobnie z powodu małej liczby osób ze złamaniami. Wnioski: Ryzyko złamania szyjki kości udowej powinno być brane pod uwagę w sytuacji, gdy zaleca się stosowanie kortykosteroidów ze wskazań pulmonologicznych osobom w podeszłym wieku. Problem ten dotyczy również leków wziewnych.
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