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Multimorbidity in people with cardiovascular disease (CVD) is common, but large-scale contemporary reports of patterns and trends in patients with incident CVD are limited. We investigated the burden of comorbidities in patients with incident CVD, how it changed between 2000 and 2014, and how it varied by age, sex, and socioeconomic status (SES). We used the UK Clinical Practice Research Datalink with linkage to Hospital Episode Statistics, a population-based dataset from 674 UK general practices covering approximately 7% of the current UK population. We estimated crude and age/sex-standardised (to the 2013 European Standard Population) prevalence and 95% confidence intervals for 56 major comorbidities in individuals with incident non-fatal CVD. We further assessed temporal trends and patterns by age, sex, and SES groups, between 2000 and 2014. Among a total of 4,198,039 people aged 16 to 113 years, 229,205 incident cases of non-fatal CVD, defined as first diagnosis of ischaemic heart disease, stroke, or transient ischaemic attack, were identified. Although the age/sex-standardised incidence of CVD decreased by 34% between 2000 to 2014, the proportion of CVD patients with higher numbers of comorbidities increased. The prevalence of having 5 or more comorbidities increased 4-fold, rising from 6.3% (95% CI 5.6%-17.0%) in 2000 to 24.3% (22.1%-34.8%) in 2014 in age/sex-standardised models. The most common comorbidities in age/sex-standardised models were hypertension (28.9% [95% CI 27.7%-31.4%]), depression (23.0% [21.3%-26.0%]), arthritis (20.9% [19.5%-23.5%]), asthma (17.7% [15.8%-20.8%]), and anxiety (15.0% [13.7%-17.6%]). Cardiometabolic conditions and arthritis were highly prevalent among patients aged over 40 years, and mental illnesses were highly prevalent in patients aged 30-59 years. The age-standardised prevalence of having 5 or more comorbidities was 19.1% (95% CI 17.2%-22.7%) in women and 12.5% (12.0%-13.9%) in men, and women had twice the age-standardised prevalence of depression (31.1% [28.3%-35.5%] versus 15.0% [14.3%-16.5%]) and anxiety (19.6% [17.6%-23.3%] versus 10.4% [9.8%-11.8%]). The prevalence of depression was 46% higher in the most deprived fifth of SES compared with the least deprived fifth (age/sex-standardised prevalence of 38.4% [31.2%-62.0%] versus 26.3% [23.1%-34.5%], respectively). This is a descriptive study of routine electronic health records in the UK, which might underestimate the true prevalence of diseases. The burden of multimorbidity and comorbidity in patients with incident non-fatal CVD increased between 2000 and 2014. On average, older patients, women, and socioeconomically deprived groups had higher numbers of comorbidities, but the type of comorbidities varied by age and sex. Cardiometabolic conditions contributed substantially to the burden, but 4 out of the 10 top comorbidities were non-cardiometabolic. The current single-disease paradigm in CVD management needs to broaden and incorporate the large and increasing burden of comorbidities.

ObjectiveTo systematically assess the association of circulating inflammation markers with the future risk of hypertension.MethodsWe did a systematic literature search of PubMed and Scopus, from database inception to July 10, 2018. Prospective and retrospective cohort studies evaluating the association of circulating C reactive protein (CRP), high-sensitive CRP (hs-CRP), interleukin 6 (IL-6) and IL-1β to the risk of developing hypertension in the general population were included. The relative risks (RRs) for the top versus bottom tertiles of circulating biomarkers were calculated using a fixed-effects/random-effects model. A potential non-linear dose-response association was tested.ResultsFourteen prospective cohort studies, two retrospective cohort studies and five nested case-control studies involving 142 640 participants and 20 676 cases were identified. The RR for the third versus first tertiles of circulating CRP was 1.23 (95% CI 1.11 to 1.35; I2=59%, n=12). The association remained unchanged after adjustment for body mass index. The RRs for other biomarkers were as follows: hs-CRP (RR 1.20, 95% CI 1.02 to 1.37; I2=74%, n=7), IL-6 (RR 1.51, 95% CI 1.30 to 1.71; I2=0%, n=5), and IL-1β (RR 1.22, 95% CI 0.92 to 1.51; I2=0%, n=3). A non-linear dose-response meta-analysis demonstrated that the risk of hypertension increased linearly with increasing circulating inflammation markers, even within the low-risk and intermediate-risk categories.ConclusionsHigher levels of circulating CRP, hs-CRP and IL-6, but not IL-1β, were associated with the risk of developing hypertension. The association persisted in subgroups of studies defined by major sources of heterogeneity.

Emergency admissions are a major source of healthcare spending. We aimed to derive, validate, and compare conventional and machine learning models for prediction of the first emergency admission. Machine learning methods are capable of capturing complex interactions that are likely to be present when predicting less specific outcomes, such as this one. We used longitudinal data from linked electronic health records of 4.6 million patients aged 18-100 years from 389 practices across England between 1985 to 2015. The population was divided into a derivation cohort (80%, 3.75 million patients from 300 general practices) and a validation cohort (20%, 0.88 million patients from 89 general practices) from geographically distinct regions with different risk levels. We first replicated a previously reported Cox proportional hazards (CPH) model for prediction of the risk of the first emergency admission up to 24 months after baseline. This reference model was then compared with 2 machine learning models, random forest (RF) and gradient boosting classifier (GBC). The initial set of predictors for all models included 43 variables, including patient demographics, lifestyle factors, laboratory tests, currently prescribed medications, selected morbidities, and previous emergency admissions. We then added 13 more variables (marital status, prior general practice visits, and 11 additional morbidities), and also enriched all variables by incorporating temporal information whenever possible (e.g., time since first diagnosis). We also varied the prediction windows to 12, 36, 48, and 60 months after baseline and compared model performances. For internal validation, we used 5-fold cross-validation. When the initial set of variables was used, GBC outperformed RF and CPH, with an area under the receiver operating characteristic curve (AUC) of 0.779 (95% CI 0.777, 0.781), compared to 0.752 (95% CI 0.751, 0.753) and 0.740 (95% CI 0.739, 0.741), respectively. In external validation, we observed an AUC of 0.796, 0.736, and 0.736 for GBC, RF, and CPH, respectively. The addition of temporal information improved AUC across all models. In internal validation, the AUC rose to 0.848 (95% CI 0.847, 0.849), 0.825 (95% CI 0.824, 0.826), and 0.805 (95% CI 0.804, 0.806) for GBC, RF, and CPH, respectively, while the AUC in external validation rose to 0.826, 0.810, and 0.788, respectively. This enhancement also resulted in robust predictions for longer time horizons, with AUC values remaining at similar levels across all models. Overall, compared to the baseline reference CPH model, the final GBC model showed a 10.8% higher AUC (0.848 compared to 0.740) for prediction of risk of emergency admission within 24 months. GBC also showed the best calibration throughout the risk spectrum. Despite the wide range of variables included in models, our study was still limited by the number of variables included; inclusion of more variables could have further improved model performances. The use of machine learning and addition of temporal information led to substantially improved discrimination and calibration for predicting the risk of emergency admission. Model performance remained stable across a range of prediction time windows and when externally validated. These findings support the potential of incorporating machine learning models into electronic health records to inform care and service planning.

Background The present study was conducted to investigate the association of dietary insulin index(II), insulin load(IL), glycemic index(GI), and glycemic load(GL) with the risk of cardiovascular disease(CVD). Methods This cohort study was conducted within the framework of the Tehran Lipid and Glucose Study on 2198 subjects, aged≥19 years old, who were followed-up for a median (IQR) 6.7 (6.1–7.1) years. Dietary GI, GL, II, and IL were calculated using a food frequency questionnaire at the baseline. Multivariate Cox proportional hazard regression models were used to estimate the risk of CVD across quartiles of dietary insulin and glycemic indices. Results Mean ± SD age of the subjects(44.9% men) was 38.3 ± 13.4 years. During a mean of 2406 ± 417 person-years of follow-up, 76(3.5%) new cases of the CVD were ascertained. The mean ± SD of II, IL, GI, and GL of participants were 51.7 ± 6.5, 235.8 ± 90.2, 61.9 ± 7.8, and 202.2 ± 78.1, respectively. After adjusting for the variables of age, sex, smoking, physical activity, daily energy intake, body mass index, diabetes, and hypertension, the hazard ratio (HR) of the highest quartile of dietary GL was 2.77(95%CI:1.00–7.69,P for trend:0.033) compared to the lowest one. Also, each one SD increase in the GL score was associated with a higher risk of CVD[(RR:1.46;CI:1.00–2.16), P -value = 0.047]. However, there was no significant association between the dietary GI, II, and IL and risk for CVD incidence. Conclusions Our results suggested that a high GL diet can increase the incidence of CVD, whereas high dietary II and IL were not associated with the risk of CVD among adults.

Previous randomised studies have provided compelling evidence for the efficacy of blood pressure and lipid-lowering treatments in reducing the risk of CVD, suggesting unique opportunities for the prevention of this chronic and prevalent disease through affordable and accessible pharmacological treatment approaches.1 2 Although reports from some western countries show gradual, yet suboptimal, improvements in the CVD burden, the situation in the rest of the world remains challenging.3 This indicates an unmet need for effective, accessible and cost-effective strategies to address this global health issue. Specifically, a significant knowledge gap remains concerning the efficacy of polypill across diverse communities characterised by varying levels of risk factors and lifestyles, differential access to healthcare resources and the balance between benefits and risks when interventions are implemented for primary prevention at the population level. [...]integrated pharmacological strategies that concurrently target multiple risk factors may prove beneficial. Blood pressure lowering treatment trialists collaboration. pharmacological blood pressure lowering for primary and secondary prevention of cardiovascular disease across different levels of blood pressure: an individual participant-level data meta-analysis.

There are currently no approved pharmacological treatment options for aortic stenosis (AS), and there are limited identified drug targets for this chronic condition. It remains unclear whether inflammation plays a role in AS pathogenesis and whether immunomodulation could become a therapeutic target. We evaluated the potentially causal association between inflammation and AS by investigating the genetically proxied effects of tocilizumab (IL6 receptor, IL6R, inhibitor), canakinumab (IL1β inhibitor) and colchicine (β-tubulin inhibitor) through a Mendelian randomisation (MR) approach. Genetic proxies for these drugs were identified as single nucleotide polymorphisms (SNPs) in the gene, enhancer or promoter regions of IL6R , IL1β or β-tubulin gene isoforms, respectively, that were significantly associated with serum C-reactive protein (CRP) in a large European genome-wide association study (GWAS; 575,531 participants). These were paired with summary statistics from a large GWAS of AS in European patients (653,867 participants) to then perform primary inverse-variance weighted random effect and sensitivity MR analyses for each exposure. This analysis showed that genetically proxied tocilizumab was associated with reduced risk of AS (OR 0.56, 95% CI 0.45–0.70 per unit decrease in genetically predicted log-transformed CRP). Genetically proxied canakinumab was not associated with risk of AS (OR 0.80, 95% CI 0.51–1.26), and only one suitable SNP was identified to proxy the effect of colchicine (OR 34.37, 95% CI 1.99–592.89). The finding that genetically proxied tocilizumab was associated with reduced risk of AS is concordant with an inflammatory hypothesis of AS pathogenesis. Inhibition of IL6R may be a promising therapeutic target for AS management.

Mitral regurgitation in people without prior cardiac disease is considered a degenerative disease with no established risk factors for its prevention. We aimed to test the hypothesis that elevated systolic blood pressure (SBP) across its usual spectrum is associated with higher risk of mitral regurgitation. We used linked electronic health records from the United Kingdom Clinical Practice Research Datalink (CPRD) from 1 January 1990 to 31 December 2015. CPRD covers approximately 7% of the current UK population and is broadly representative of the population by age, sex, and ethnicity. About 5.5 million UK patients with no known cardiovascular or valve disease at baseline were included in this cohort study. We investigated the relationship between blood pressure (BP) and risk of mitral regurgitation using Cox regression models. Our primary exposure variable was SBP and our primary outcome was incident reports of mitral regurgitation, which were identified from hospital discharge reports or primary care records. Of the 5,553,984 patients in the CPRD that met our inclusion criteria, during the 10-year follow-up period, 28,655 (0.52%) were diagnosed with mitral regurgitation and a further 1,262 (0.02%) were diagnosed with mitral stenosis. SBP was continuously related to the risk of mitral regurgitation with no evidence of a nadir down to 115 mmHg (p < 0.001). Each 20 mmHg increment in SBP was associated with a 26% higher risk of mitral regurgitation (hazard ratio [HR] 1.26; CI 1.23, 1.29). The observed association was partially mediated by diseases affecting the left ventricle during follow-up (myocardial infarction [MI], ischaemic heart disease [IHD], cardiomyopathy, and heart failure). However, the percentage of excess risk mediated (PERM) by these proximate causes of secondary mitral regurgitation was only 13% (CI 6.1%, 20%), and accounting for them had little effect on the long-term association between SBP and mitral regurgitation (mediator-adjusted HR 1.22; CI 1.20, 1.25; p < 0.001). Associations were similar for each 10 mmHg increment in diastolic blood pressure (DBP) (p < 0.001) or each 15 mmHg increment in pulse pressure (PP) (p < 0.001). By contrast, there was no association between SBP and risk of mitral stenosis (HR per 20 mmHg higher SBP 1.03; CI 0.93, 1.14; p = 0.58). These analyses are based on routinely collected data from health records which may be sensitive to measurement errors, and the observed associations may not be generalizable to less severe and subclinical cases of mitral regurgitation. Long-term exposure to elevated BP across its whole spectrum is associated with an increased risk of primary and secondary mitral regurgitation. These findings suggest that BP control may be of importance in the prevention of mitral regurgitation.

Randomised evidence on the efficacy of blood pressure (BP)-lowering treatment to reduce cardiovascular risk in patients with atrial fibrillation (AF) is limited. Therefore, this study aimed to compare the effects of BP-lowering drugs in patients with and without AF at baseline. The study was based on the resource provided by the Blood Pressure Lowering Treatment Trialists' Collaboration (BPLTTC), in which individual participant data (IPD) were extracted from trials with over 1,000 patient-years of follow-up in each arm, and that had randomly assigned patients to different classes of BP-lowering drugs, BP-lowering drugs versus placebo, or more versus less intensive BP-lowering regimens. For this study, only trials that had collected information on AF status at baseline were included. The effects of BP-lowering treatment on a composite endpoint of major cardiovascular events (stroke, ischaemic heart disease or heart failure) according to AF status at baseline were estimated using fixed-effect one-stage IPD meta-analyses based on Cox proportional hazards models stratified by trial. Furthermore, to assess whether the associations between the intensity of BP reduction and cardiovascular outcomes are similar in those with and without AF at baseline, we used a meta-regression. From the full BPLTTC database, 28 trials (145,653 participants) were excluded because AF status at baseline was uncertain or unavailable. A total of 22 trials were included with 188,570 patients, of whom 13,266 (7%) had AF at baseline. Risk of bias assessment showed that 20 trials were at low risk of bias and 2 trials at moderate risk. Meta-regression showed that relative risk reductions were proportional to trial-level intensity of BP lowering in patients with and without AF at baseline. Over 4.5 years of median follow-up, a 5-mm Hg systolic BP (SBP) reduction lowered the risk of major cardiovascular events both in patients with AF (hazard ratio [HR] 0.91, 95% confidence interval [CI] 0.83 to 1.00) and in patients without AF at baseline (HR 0.91, 95% CI 0.88 to 0.93), with no difference between subgroups. There was no evidence for heterogeneity of treatment effects by baseline SBP or drug class in patients with AF at baseline. The findings of this study need to be interpreted in light of its potential limitations, such as the limited number of trials, limitation in ascertaining AF cases due to the nature of the arrhythmia and measuring BP in patients with AF. In this meta-analysis, we found that BP-lowering treatment reduces the risk of major cardiovascular events similarly in individuals with and without AF. Pharmacological BP lowering for prevention of cardiovascular events should be recommended in patients with AF.

Multicollinearity refers to the presence of collinearity between multiple variables and renders the results of statistical inference erroneous (Type II error). This is particularly important in environmental health research where multicollinearity can hinder inference. To address this, correlated variables are often excluded from the analysis, limiting the discovery of new associations. An alternative approach to address this problem is the use of principal component analysis. This method, combines and projects a group of correlated variables onto a new orthogonal space. While this resolves the multicollinearity problem, it poses another challenge in relation to interpretability of results. Standard hypothesis testing methods can be used to evaluate the association of projected predictors, called principal components, with the outcomes of interest, however, there is no established way to trace the significance of principal components back to individual variables. To address this problem, we investigated the use of sparse principal component analysis which enforces a parsimonious projection. We hypothesise that this parsimony could facilitate the interpretability of findings. To this end, we investigated the association of 20 environmental predictors with all-cause mortality adjusting for demographic, socioeconomic, physiological, and behavioural factors. The study was conducted in a cohort of 379,690 individuals in the UK. During an average follow-up of 8.05 years (3,055,166 total person-years), 14,996 deaths were observed. We used Cox regression models to estimate the hazard ratio (HR) and 95% confidence intervals (CI). The Cox models were fitted to the standardised environmental predictors (a) without any transformation (b) transformed with PCA, and (c) transformed with SPCA. The comparison of findings underlined the potential of SPCA for conducting inference in scenarios where multicollinearity can increase the risk of Type II error. Our analysis unravelled a significant association between average noise pollution and increased risk of all-cause mortality. Specifically, those in the upper deciles of noise exposure have between 5 and 10% increased risk of all-cause mortality compared to the lowest decile.

Background and objective: Heart failure (HF) is associated with high morbidity, mortality, and healthcare costs. Its prevalence continues to rise, particularly in the context of ageing populations and increasing rates of metabolic comorbidities such as type 2 diabetes and obesity. We aimed to assess the therapeutic potential of repurposing PPARα agonists for the treatment of HF. Method: We conducted a comprehensive literature review to evaluate preclinical and clinical evidence investigating the potential of PPARα agonist drugs in reducing HF. We did not apply any restrictions on the study design. Results: The current body of evidence consists of preclinical mechanistic studies, emerging pharmacogenetic data, and post hoc analyses of large randomised clinical trials (RCTs) that included HF endpoints. No dedicated, HF-specific RCTs of PPARα agonists were identified. These studies support the hypothesis that PPARα agonists may link metabolic modulation with cardiac remodelling. Preclinical models demonstrate potential therapeutic benefits, such as enhanced myocardial energy metabolism and attenuation of fibrosis and inflammation, as well as context-dependent risks, including possible deleterious effects in advanced HF or off-target mechanisms. Prior failures of fibrates to improve cardiovascular outcomes in some trials and concerns in PPARα-deficient states underscore the complexity of metabolic therapies in HF. These findings support a more stratified, phenotype-driven approach to therapy. RCTs specifically designed to evaluate HF outcomes are essential to clarify whether PPARα agonists can complement established neurohormonal treatments, particularly in the context of the rising burden of HFpEF associated with obesity and type 2 diabetes. Conclusions: PPARα agonists represent a promising class within the emerging therapeutic framework of metabolic heart failure. They are inexpensive, generally well tolerated, and address several pathophysiological mechanisms of HF. Preliminary evidence suggests that fenofibrate may delay or prevent HF in high-risk diabetic populations. However, rigorous, dedicated trials are needed to establish their clinical utility.