WhoishRisk - an R package to calculate WHO/ISH cardiovascular risk scores for all epidemiological subregions of the world.
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SUBMITTER: Collins D
PROVIDER: S-EPMC5345772 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Cardiovascular disease (CVD) risk in India is currently assessed using the World Health Organization/International Society for Hypertension (WHO/ISH) risk prediction charts since no population-specific models exist. The WHO/ISH risk prediction charts have two versions-one with total cholesterol as a predictor (the high information (HI) model) and the other without (the low information (LI) model). However, information on the WHO/ISH risk prediction charts including guidance on which version to use and when, as well as relative performance of the LI and HI models, is limited. This article aims to, firstly, quantify the relative performance of the LI and HI WHO/ISH risk prediction (for WHO-South East Asian Region D) using data from rural India. Secondly, we propose a pre-screening (simplified) point-of-care (POC) test to identify patients who are likely to benefit from a total cholesterol (TC) test, and subsequently when the LI model is preferential to HI model. Analysis was performed using cross-sectional data from rural Andhra Pradesh collected in 2005 with recorded blood cholesterol measurements (N = 1066). CVD risk was computed using both LI and HI models, and high risk individuals who needed treatment(THR) were subsequently identified based on clinical guidelines. Model development for the POC assessment of a TC test was performed through three machine learning techniques: Support Vector Machine (SVM), Regularised Logistic Regression (RLR), and Random Forests (RF) along with a feature selection process. Disagreement in CVD risk predicted by LI and HI WHO/ISH models was 14.5% (n = 155; p<0.01) overall and comprised 36 clinically relevant THR patients (31% of patients identified as THR by using either model). Using two patient-specific parameters (age, systolic blood pressure), our POC assessment can pre-determine the benefit of TC testing and choose the appropriate risk model (out-of-sample AUCs:RF-0.85,SVM-0.84,RLR:0.82 and maximum sensitivity-98%). The identification of patients benefitting from a TC test for CVD risk stratification can aid planning for resource-allocation and save costs for large-scale screening programmes.
| S-EPMC4545825 | biostudies-literature
Project description:Introduction and objectivesThere are no cardiovascular (CV) risk prediction models for Sri Lankans. Different risk prediction models not validated for Sri Lankans are being used to predict CV risk of Sri Lankans. We validated the WHO/ISH (SEAR-B) risk prediction charts prospectively in a population-based cohort of Sri Lankans.MethodWe selected 40-64 year-old participants from the Ragama Medical Officer of Health (MOH) area in 2007 by stratified random sampling and followed them up for 10 years. Ten-year risk predictions of a fatal/non-fatal cardiovascular event (CVE) in 2007 were calculated using WHO/ISH (SEAR-B) charts with and without cholesterol. The CVEs that occurred from 2007-2017 were ascertained. Risk predictions in 2007 were validated against observed CVEs in 2017.ResultsOf 2517 participants, the mean age was 53.7 year (SD: 6.7) and 1132 (45%) were males. Using WHO/ISH chart with cholesterol, the percentages of subjects with a 10-year CV risk <10%, 10-19%, 20%-29%, 30-39%, ≥40% were 80.7%, 9.9%, 3.8%, 2.5% and 3.1%, respectively. 142 non-fatal and 73 fatal CVEs were observed during follow-up. Among the cohort, 9.4% were predicted of having a CV risk ≥20% and 8.6% CVEs were observed in the risk category. CVEs were within the predictions of WHO/ISH charts with and without cholesterol in both high (≥20%) and low(<20%) risk males, but only in low(<20%) risk females. The predictions of WHO/ISH charts, with-and without-cholesterol were in agreement in 81% of subjects (ĸ = 0.429; p<0.001).ConclusionsWHO/ISH (SEAR B) risk prediction charts with-and without-cholesterol may be used in Sri Lanka. Risk charts are more predictive in males than in females and for lower-risk categories. The predictions when stratifying into 2 categories, low risk (<20%) and high risk (≥20%), are more appropriate in clinical practice.
| S-EPMC8183983 | biostudies-literature
Project description:ObjectivesAlthough cardiovascular disease (CVD) is of growing importance in low- and middle-income countries (LMICs), there are conflicting views regarding CVD as a major public health problem for the urban poor, including those living in slums. We examine multivariable risk prediction in a slum population and assess the number of cardiovascular related deaths within 10 years of application of the tool.SettingWe use data from the Nairobi Urban Health and Demographic Surveillance System (NUHDSS) population (residents of two slum communities) between May 2008 and April 2009.DesignThis is a secondary data analysis from a cross-sectional survey. We use the WHO/International Society of Hypertension (WHO/ISH) cardiovascular risk prediction tool to examine 10-year risk of major CVD events in a slum population. CVD deaths in the cohort, reported up until June 2018 and identified through verbal autopsy are also presented.Participants3063 men and women aged over 40 years with complete data for variables needed for the WHO/ISH risk prediction tool were eligible to take part.ResultsThe majority of study members (2895, 94.5%) were predicted to have 'low' risk (<10%) of a cardiovascular event over the next 10 years and just 51 (1.7%) to have 'high' CVD risk (≥20%). 91 CVD deaths were reported for the cohort up until June 2018. Of individuals classified as low risk, 74 (2.6%) were identified as having died of CVD. Nine (7.7%) individuals classified at 10% to 20% risk and eight (15.9%) classified at >20% were identified as dying of CVD.ConclusionsThis study shows that there is a low risk profile of CVD in this slum population in Nairobi, Kenya, in comparison to results from application of multivariable risk prediction tools in other LMIC populations. This has implications for health service planning in these contexts.
| S-EPMC6731939 | biostudies-literature
Project description:Credit scores are the most widely used instruments to assess whether or not a person is a financial risk. Credit scoring has been so successful that it has expanded beyond lending and into our everyday lives, even to inform how insurers evaluate our health. The pervasive application of credit scoring has outpaced knowledge about why credit scores are such useful indicators of individual behavior. Here we test if the same factors that lead to poor credit scores also lead to poor health. Following the Dunedin (New Zealand) Longitudinal Study cohort of 1,037 study members, we examined the association between credit scores and cardiovascular disease risk and the underlying factors that account for this association. We find that credit scores are negatively correlated with cardiovascular disease risk. Variation in household income was not sufficient to account for this association. Rather, individual differences in human capital factors—educational attainment, cognitive ability, and self-control—predicted both credit scores and cardiovascular disease risk and accounted for ∼45% of the correlation between credit scores and cardiovascular disease risk. Tracing human capital factors back to their childhood antecedents revealed that the characteristic attitudes, behaviors, and competencies children develop in their first decade of life account for a significant portion (∼22%) of the link between credit scores and cardiovascular disease risk at midlife. We discuss the implications of these findings for policy debates about data privacy, financial literacy, and early childhood interventions.
| S-EPMC4260546 | biostudies-literature
Project description:BackgroundMultivariable cardiovascular disease (CVD) risk calculators, such as the Framingham risk equations, can be used to identify populations most likely to benefit from treatments to decrease risk.PurposeTo determine the proportion of adults within an electronic health record (EHR) for whom Framingham CVD risk scores could be calculated using cholesterol (lab-based) and/or BMI (BMI-based) formulae.MethodsEHR data were used to identify patients aged 30-74 years with no CVD and at least 2 years continuous enrollment before April 1, 2010, and relevant data from the preceding 5-year time frame. Analyses were conducted between 2010 and 2011 to determine the proportion of patients with a lab- or BMI-based risk score, the data missing, and the concordance between scores.ResultsOf 122,270 eligible patients, 59.7% (n=73,023) had sufficient data to calculate the lab-based risk score and 84.1% (102,795) the BMI-based risk score. Risk categories were concordant in 78.2% of patients. When risk categories differed, BMI-based risk was almost always in a higher category, with 20.3% having a higher and 1.4% a lower BMI- than lab-based risk score. Concordance between lab- and BMI-based risk was greatest among those at lower estimated risk, including people who were younger, female, without diabetes, not obese, and those not on blood pressure- or lipid-lowering medications.ConclusionsEHR data can be used to classify CVD risk for most adults aged 30-74 years. In the population for the current study, CVD risk scores based on BMI could be used to identify those at low risk for CVD and potentially reduce unnecessary laboratory cholesterol testing.Trial registrationThis study is registered at clinicaltrials.gov NCT01077388.
| S-EPMC3308122 | biostudies-literature
Project description:People with type 2 diabetes have an increased risk of cardiovascular disease (CVD). Multivariate cardiovascular risk scores have been used in many countries to identify individuals who are at high risk of CVD. These risk scores include those originally developed in individuals with diabetes and those developed in a general population. This article reviews the published evidence for the performance of CVD risk scores in diabetic patients by: (1) examining the overall rationale for using risk scores; (2) systematically reviewing the literature on available scores; and (3) exploring methodological issues surrounding the development, validation and comparison of risk scores. The predictive performance of cardiovascular risk scores varies substantially between different populations. There is little evidence to suggest that risk scores developed in individuals with diabetes estimate cardiovascular risk more accurately than those developed in the general population. The inconsistency in the methods used in evaluation studies makes it difficult to compare and summarise the predictive ability of risk scores. Overall, CVD risk scores rank individuals reasonably accurately and are therefore useful in the management of diabetes with regard to targeting therapy to patients at highest risk. However, due to the uncertainty in estimation of true risk, care is needed when using scores to communicate absolute CVD risk to individuals.
| S-EPMC2744770 | biostudies-other
Project description:BackgroundCardiovascular disease (CVD) is the major cause of death after renal transplantation. Not only conventional CVD risk factors, but also transplant-specific risk factors can influence the development of CVD in kidney transplant recipients. The main objective of this study will be to determine the incidence of post-transplant CVD after renal transplantation and related factors. A secondary objective will be to examine the ability of standard cardiovascular risk scores (Framingham, REGICOR, SCORE, and DORICA) to predict post-transplantation cardiovascular events in renal transplant recipients, and to develop a new score for predicting the risk of CVD after kidney transplantation.Methods/designObservational prospective cohort study of all kidney transplant recipients in the A Coruna Hospital (Spain) in the period 1981-2008 (2059 transplants corresponding to 1794 patients). The variables included will be: donor and recipient characteristics, chronic kidney disease-related risk factors, pre-transplant and post-transplant cardiovascular risk factors, routine biochemistry, and immunosuppressive, antihypertensive and lipid-lowering treatment. The events studied in the follow-up will be: patient and graft survival, acute rejection episodes and cardiovascular events (myocardial infarction, invasive coronary artery therapy, cerebral vascular events, new-onset angina, congestive heart failure, rhythm disturbances and peripheral vascular disease). Four cardiovascular risk scores were calculated at the time of transplantation: the Framingham score, the European Systematic Coronary Risk Evaluation (SCORE) equation, and the REGICOR (Registre Gironi del COR (Gerona Heart Registry)), and DORICA (Dyslipidemia, Obesity, and Cardiovascular Risk) functions. The cumulative incidence of cardiovascular events will be analyzed by competing risk survival methods. The clinical relevance of different variables will be calculated using the ARR (Absolute Risk Reduction), RRR (Relative Risk Reduction) and NNT (Number Needed to Treat). The ability of different cardiovascular risk scores to predict cardiovascular events will be analyzed by using the c index and the area under ROC curves. Based on the competing risks analysis, a nomogram to predict the probability of cardiovascular events after kidney transplantation will be developed.DiscussionThis study will make it possible to determine the post-transplant incidence of cardiovascular events in a large cohort of renal transplant recipients in Spain, to confirm the relationship between traditional and transplant-specific cardiovascular risk factors and CVD, and to develop a score to predict the risk of CVD in these patients.
| S-EPMC3022886 | biostudies-literature
Project description:BackgroundPolygenic risk scores (PRSs) can stratify populations into cardiovascular disease (CVD) risk groups. We aimed to quantify the potential advantage of adding information on PRSs to conventional risk factors in the primary prevention of CVD.Methods and findingsUsing data from UK Biobank on 306,654 individuals without a history of CVD and not on lipid-lowering treatments (mean age [SD]: 56.0 [8.0] years; females: 57%; median follow-up: 8.1 years), we calculated measures of risk discrimination and reclassification upon addition of PRSs to risk factors in a conventional risk prediction model (i.e., age, sex, systolic blood pressure, smoking status, history of diabetes, and total and high-density lipoprotein cholesterol). We then modelled the implications of initiating guideline-recommended statin therapy in a primary care setting using incidence rates from 2.1 million individuals from the Clinical Practice Research Datalink. The C-index, a measure of risk discrimination, was 0.710 (95% CI 0.703-0.717) for a CVD prediction model containing conventional risk predictors alone. Addition of information on PRSs increased the C-index by 0.012 (95% CI 0.009-0.015), and resulted in continuous net reclassification improvements of about 10% and 12% in cases and non-cases, respectively. If a PRS were assessed in the entire UK primary care population aged 40-75 years, assuming that statin therapy would be initiated in accordance with the UK National Institute for Health and Care Excellence guidelines (i.e., for persons with a predicted risk of ≥10% and for those with certain other risk factors, such as diabetes, irrespective of their 10-year predicted risk), then it could help prevent 1 additional CVD event for approximately every 5,750 individuals screened. By contrast, targeted assessment only among people at intermediate (i.e., 5% to <10%) 10-year CVD risk could help prevent 1 additional CVD event for approximately every 340 individuals screened. Such a targeted strategy could help prevent 7% more CVD events than conventional risk prediction alone. Potential gains afforded by assessment of PRSs on top of conventional risk factors would be about 1.5-fold greater than those provided by assessment of C-reactive protein, a plasma biomarker included in some risk prediction guidelines. Potential limitations of this study include its restriction to European ancestry participants and a lack of health economic evaluation.ConclusionsOur results suggest that addition of PRSs to conventional risk factors can modestly enhance prediction of first-onset CVD and could translate into population health benefits if used at scale.
| S-EPMC7808664 | biostudies-literature
Project description:Clinical implementation of new prediction models requires evaluation of their utility in a broad range of intended use populations. Here we develop and validate ancestry-specific Polygenic Risk Scores (PRSs) for Coronary Artery Disease (CAD) using 29,389 individuals from diverse cohorts and genetic ancestry groups. The CAD PRSs outperform published scores with an average Odds Ratio per Standard Deviation of 1.57 (SD = 0.14) and identify between 12% and 24% of individuals with high genetic risk. Using this risk factor to reclassify borderline or intermediate 10 year Atherosclerotic Cardiovascular Disease (ASCVD) risk improves assessments for both CAD (Net Reclassification Improvement (NRI) = 13.14% (95% CI 9.23-17.06%)) and ASCVD (NRI = 10.70 (95% CI 7.35-14.05)) in an independent cohort of 9,691 individuals. Our analyses demonstrate that using PRSs as Risk Enhancers improves ASCVD risk assessments outlining an approach for guiding ASCVD prevention with genetic information.
| S-EPMC10625612 | biostudies-literature
Project description:BACKGROUND:The brunt of cardiovascular disease (CVD) burden globally now resides within low- and middle-income countries, including Indonesia. However, little is known regarding cardiovascular health in Indonesia. This study aimed to estimate the prevalence of elevated CVD risk in a specific region of Indonesia. METHODS:We conducted full household screening for cardiovascular risk factors among adults aged 40 years and older in 8 villages in Malang District, East Java Province, Indonesia, in 2016-2017. 10-year cardiovascular risk scores were calculated based on the World Health Organization/International Society of Hypertension's region-specific charts that use age, sex, blood pressure, diabetes status and smoking behaviour. RESULTS:Among 22,093 participants, 6,455 (29.2%) had high cardiovascular risk, defined as the presence of coronary heart disease, stroke or other atherosclerotic disease; estimated 10-year CVD risk of ? 30%; or estimated 10-year CVD risk between 10% to 29% combined with a systolic blood pressure of > 140 mmHg. The prevalence of high CVD risk was greater in urban (31.6%, CI 30.7-32.5%) than in semi-urban (28.7%, CI 27.3-30.1%) and rural areas (26.2%, CI 25.2-27.2%). Only 11% and 1% of all the respondents with high CVD risk were on blood pressure lowering and statins treatment, respectively. CONCLUSIONS:High cardiovascular risk is common among Indonesian adults aged ?40 years, and rates of preventive treatment are low. Population-based and clinical approaches to preventing CVD should be a priority in both urban and rural areas.
| S-EPMC6490907 | biostudies-literature