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Cardiovascular Disease Population Risk Tool (CVDPoRT): predictive algorithm for assessing CVD risk in the community setting. A study protocol.

ABSTRACT: INTRODUCTION:Recent publications have called for substantial improvements in the design, conduct, analysis and reporting of prediction models. Publication of study protocols, with prespecification of key aspects of the analysis plan, can help to improve transparency, increase quality and protect against increased type I error. Valid population-based risk algorithms are essential for population health planning and policy decision-making. The purpose of this study is to develop, evaluate and apply cardiovascular disease (CVD) risk algorithms for the population setting. METHODS AND ANALYSIS:The Ontario sample of the Canadian Community Health Survey (2001, 2003, 2005; 77,251 respondents) will be used to assess risk factors focusing on health behaviours (physical activity, diet, smoking and alcohol use). Incident CVD outcomes will be assessed through linkage to administrative healthcare databases (619,886 person-years of follow-up until 31 December 2011). Sociodemographic factors (age, sex, immigrant status, education) and mediating factors such as presence of diabetes and hypertension will be included as predictors. Algorithms will be developed using competing risks survival analysis. The analysis plan adheres to published recommendations for the development of valid prediction models to limit the risk of overfitting and improve the quality of predictions. Key considerations are fully prespecifying the predictor variables; appropriate handling of missing data; use of flexible functions for continuous predictors; and avoiding data-driven variable selection procedures. The 2007 and 2009 surveys (approximately 50,000 respondents) will be used for validation. Calibration will be assessed overall and in predefined subgroups of importance to clinicians and policymakers. ETHICS AND DISSEMINATION:This study has been approved by the Ottawa Health Science Network Research Ethics Board. The findings will be disseminated through professional and scientific conferences, and in peer-reviewed journals. The algorithm will be accessible electronically for population and individual uses. TRIAL REGISTRATION NUMBER:ClinicalTrials.gov NCT02267447.

SUBMITTER: Taljaard M

PROVIDER: S-EPMC4208046 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Cardiovascular Disease Population Risk Tool (CVDPoRT): predictive algorithm for assessing CVD risk in the community setting. A study protocol.

Taljaard Monica M Tuna Meltem M Bennett Carol C Perez Richard R Rosella Laura L Tu Jack V JV Sanmartin Claudia C Hennessy Deirdre D Tanuseputro Peter P Lebenbaum Michael M Manuel Douglas G DG

BMJ open 20141023 10

<h4>Introduction</h4>Recent publications have called for substantial improvements in the design, conduct, analysis and reporting of prediction models. Publication of study protocols, with prespecification of key aspects of the analysis plan, can help to improve transparency, increase quality and protect against increased type I error. Valid population-based risk algorithms are essential for population health planning and policy decision-making. The purpose of this study is to develop, evaluate a ...[more]

PMID: 25341454

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Project description:BackgroundPremature mortality is an important population health indicator used to assess health system functioning and to identify areas in need of health system intervention. Predicting the future incidence of premature mortality in the population can facilitate initiatives that promote equitable health policies and effective delivery of public health services. This study protocol proposes the development and validation of the Premature Mortality Risk Prediction Tool (PreMPoRT) that will predict the incidence of premature mortality using large population-based community health surveys and multivariable modeling approaches.MethodsPreMPoRT will be developed and validated using various training, validation, and test data sets generated from the six cycles of the Canadian Community Health Survey (CCHS) linked to the Canadian Vital Statistics Database from 2000 to 2017. Population-level risk factor information on demographic characteristics, health behaviors, area level measures, and other health-related factors will be used to develop PreMPoRT and to predict the incidence of premature mortality, defined as death prior to age 75, over a 5-year period. Sex-specific Weibull accelerated failure time models will be developed using a Canadian provincial derivation cohort consisting of approximately 500,000 individuals, with approximately equal proportion of males and females, and about 12,000 events of premature mortality. External validation will be performed using separate linked files (CCHS cycles 2007-2008, 2009-2010, and 2011-2012) from the development cohort (CCHS cycles 2000-2001, 2003-2004, and 2005-2006) to check the robustness of the prediction model. Measures of overall predictive performance (e.g., Nagelkerke's R2), calibration (e.g., calibration plots), and discrimination (e.g., Harrell's concordance statistic) will be assessed, including calibration within defined subgroups of importance to knowledge users and policymakers.DiscussionUsing routinely collected risk factor information, we anticipate that PreMPoRT will produce population-based estimates of premature mortality and will be used to inform population strategies for prevention.

Project description:IntroductionOlder adults living in the community often have multiple, chronic conditions and functional impairments. A challenge for healthcare providers working in the community is the lack of a predictive tool that can be applied to the broad spectrum of mortality risks observed and may be used to inform care planning.ObjectiveTo predict survival time for older adults in the home care setting. The final mortality risk algorithm will be implemented as a web-based calculator that can be used by older adults needing care and by their caregivers.DesignOpen cohort study using the Resident Assessment Instrument for Home Care (RAI-HC) data in Ontario, Canada, from 1 January 2007 to 31 December 2013.ParticipantsThe derivation cohort will consist of ∼437 000 older adults who had an RAI-HC assessment between 1 January 2007 and 31 December 2012. A split sample validation cohort will include ∼122 000 older adults with an RAI-HC assessment between 1 January and 31 December 2013.Main outcome measuresPredicted survival from the time of an RAI-HC assessment. All deaths (n≈245 000) will be ascertained through linkage to a population-based registry that is maintained by the Ministry of Health in Ontario.Statistical analysisProportional hazards regression will be estimated after assessment of assumptions. Predictors will include sociodemographic factors, social support, health conditions, functional status, cognition, symptoms of decline and prior healthcare use. Model performance will be evaluated for 6-month and 12-month predicted risks, including measures of calibration (eg, calibration plots) and discrimination (eg, c-statistics). The final algorithm will use combined development and validation data.Ethics and disseminationResearch ethics approval has been granted by the Sunnybrook Health Sciences Centre Review Board. Findings will be disseminated through presentations at conferences and in peer-reviewed journals.Trial registration numberNCT02779309, Pre-results.

Project description:BackgroundCardiovascular disease (CVD) is the leading cause of death globally. Community pharmacist intervention studies have demonstrated clinical effectiveness for improving several leading individual CVD risk factors. Primary prevention strategies increasingly emphasise the need for consideration of overall cardiovascular risk and concurrent management of multiple risk factors. It is therefore important to demonstrate the feasibility of multiple risk factor management by community pharmacists to ensure continued currency of their role.Methods/designThis study will be a longitudinal pre- and post-test pilot study with a single cohort of up to 100 patients in ten pharmacies. Patients aged 50-74 years with no history of heart disease or diabetes, and taking antihypertensive or lipid-lowering medicines, will be approached for participation. Assessment of cardiovascular risk, medicines use and health behaviours will be undertaken by a research assistant at baseline and following the intervention (6 months). Validated interview scales will be used where available. Baseline data will be used by accredited medicines management pharmacists to generate a report for the treating community pharmacist. This report will highlight individual patients' overall CVD risk and individual risk factors, as well as identifying modifiable health behaviours for risk improvement and suggesting treatment and behavioural goals. The treating community pharmacist will use this information to finalise and implement a treatment plan in conjunction with the patient and their doctor. Community pharmacists will facilitate patient improvements in lifestyle, medicines adherence, and medicines management over the course of five counselling sessions with monthly intervals. The primary outcome will be the change to average overall cardiovascular risk, assessed using the Framingham risk equation.DiscussionThis study will assess the feasibility of implementing holistic primary CVD prevention programs into community pharmacy, one of the most accessible health services in most developed countries.Trial registrationAustralia and New Zealand Clinical Trial Registry Number: ACTRN12609000677202.

Project description:BackgroundAvailability and accessibility of nutritious foods can vary according to the food outlets present within a neighbourhood or community. There is increasing evidence that community food environments influence food choice, diet and the risk of diet-related chronic disease, however contemporary community food environments assessments (e.g. unhealthy fast food outlets versus healthy supermarkets or fruit and vegetable shops) may be too simplistic to accurately summarise the complexities of their impacts on food choice. This study protocol describes the development of the Food Outlets Dietary Risk (FODR) assessment tool for use by local government in Perth, Western Australia.MethodsSimilar to food safety risk assessment, the FODR assessment tool rates the potential harmful public health nutrition impact of food outlets by identifying and characterising the issues, and assessing the risk of exposure. Scores are attributed to six public health nutrition attributes: 1) availability of nutrient-poor foods; 2) availability of nutritious foods; 3) acceptability and appeal; 4) accessibility; 5) type of business operation; and 6) complex food outlet considerations. Food retail outlets are then classified as having a low, medium, high or very high dietary risk based on their total score.DiscussionA local government administered tool to rate the public health nutrition risk of food outlets requires data which can be collected during routine assessments or sourced from the internet. The ongoing categorical classification of foods available within food outlets as either unhealthy or nutritious will require nutrition scientists' input. An objective risk assessment of the dietary impact of food retail outlets can guide local government planning, policies and interventions to create supportive community food environments. It is intended that locally relevant data can be sourced throughout Australia and in other countries to apply the local context to the FODR assessment tool. Utility and acceptability of the tool will be tested, and consultation with environmental health officers and public health practitioners will inform future iterations.

Project description:BackgroundDuring the pandemic, remote consultations have become the norm for assessing patients with signs and symptoms of COVID-19 to decrease the risk of transmission. This has intensified the clinical uncertainty already experienced by primary care clinicians when assessing patients with suspected COVID-19 and has prompted the use of risk prediction scores, such as the National Early Warning Score (NEWS2), to assess severity and guide treatment. However, the risk prediction tools available have not been validated in a community setting and are not designed to capture the idiosyncrasies of COVID-19 infection.ObjectiveThe objective of this study is to produce a multivariate risk prediction tool, RECAP-V1 (Remote COVID-19 Assessment in Primary Care), to support primary care clinicians in the identification of those patients with COVID-19 that are at higher risk of deterioration and facilitate the early escalation of their treatment with the aim of improving patient outcomes.MethodsThe study follows a prospective cohort observational design, whereby patients presenting in primary care with signs and symptoms suggestive of COVID-19 will be followed and their data linked to hospital outcomes (hospital admission and death). Data collection will be carried out by primary care clinicians in four arms: North West London Clinical Commissioning Groups (NWL CCGs), Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), Covid Clinical Assessment Service (CCAS), and South East London CCGs (Doctaly platform). The study involves the use of an electronic template that incorporates a list of items (known as RECAP-V0) thought to be associated with disease outcome according to previous qualitative work. Data collected will be linked to patient outcomes in highly secure environments. We will then use multivariate logistic regression analyses for model development and validation.ResultsRecruitment of participants started in October 2020. Initially, only the NWL CCGs and RCGP RSC arms were active. As of March 24, 2021, we have recruited a combined sample of 3827 participants in these two arms. CCAS and Doctaly joined the study in February 2021, with CCAS starting the recruitment process on March 15, 2021. The first part of the analysis (RECAP-V1 model development) is planned to start in April 2021 using the first half of the NWL CCGs and RCGP RSC combined data set. Posteriorly, the model will be validated with the rest of the NWL CCGs and RCGP RSC data as well as the CCAS and Doctaly data sets. The study was approved by the Research Ethics Committee on May 27, 2020 (Integrated Research Application System number: 283024, Research Ethics Committee reference number: 20/NW/0266) and badged as National Institute of Health Research Urgent Public Health Study on October 14, 2020.ConclusionsWe believe the validated RECAP-V1 early warning score will be a valuable tool for the assessment of severity in patients with suspected COVID-19 in the community, either in face-to-face or remote consultations, and will facilitate the timely escalation of treatment with the potential to improve patient outcomes.Trial registrationISRCTN registry ISRCTN13953727; https://www.isrctn.com/ISRCTN13953727.International registered report identifier (irrid)DERR1-10.2196/29072.

Project description:Chronic kidney disease (CKD) is currently defined as the presence of proteinuria and/or an eGFR < 60 mL/min/1.73m2 on the basis of the renal diagnosis. The global dimension of CKD is relevant, since its prevalence and incidence have doubled in the past three decades worldwide. A major complication that occurs in CKD patients is the development of cardiovascular (CV) disease, being the incidence rate of fatal/nonfatal CV events similar to the rate of ESKD in CKD. Moreover, CKD is a multifactorial disease where multiple mechanisms contribute to the individual prognosis. The correct development of novel biomarkers of CV risk may help clinicians to ameliorate the management of CKD patients. Biomarkers of CV risk in CKD patients are classifiable as prognostic, which help to improve CV risk prediction regardless of treatment, and predictive, which allow the selection of individuals who are likely to respond to a specific treatment. Several prognostic (cystatin C, cardiac troponins, markers of inflammation, and fibrosis) and predictive (genes, metalloproteinases, and complex classifiers) biomarkers have been developed. Despite previous biomarkers providing information on the pathophysiological mechanisms of CV risk in CKD beyond proteinuria and eGFR, only a minority have been adopted in clinical use. This mainly depends on heterogeneous results and lack of validation of biomarkers. The purpose of this review is to present an update on the already assessed biomarkers of CV risk in CKD and examine the strategies for a correct development of biomarkers in clinical practice. Development of both predictive and prognostic biomarkers is an important task for nephrologists. Predictive biomarkers are useful for designing novel clinical trials (enrichment design) and for better understanding of the variability in response to the current available treatments for CV risk. Prognostic biomarkers could help to improve risk stratification and anticipate diagnosis of CV disease, such as heart failure and coronary heart disease.

Project description:UnlabelledRisk factors for cardiovascular disease including diabetes have seen a large rise in prevalence in recent years. This has prompted interest in prevention through the identifying individuals at risk of both diabetes and cardiovascular disease and has seen increased investment in screening interventions taking place in primary care. Community pharmacies have become increasingly involved in the provision of such interventions and this systematic review and meta-analysis aims to gather and analyse the existing literature assessing community pharmacy based screening for risk factors for diabetes and those with a high cardiovascular disease risk.MethodsWe conducted systematic searches of electronic databases using MeSH and free text terms from 1950 to March 2012. For our analysis two outcomes were assessed. They were the percentage of those screened who were referred for further assessment by primary care and the uptake of this referral.ResultsSixteen studies fulfilled our inclusion criteria comprising 108,414 participants screened. There was significant heterogeneity for all included outcomes. Consequently we have not presented summary statistics and present forest plots with I2 and p values to describe heterogeneity. We found that all included studies suffered from high rates of attrition between pharmacy screening and follow up. We have also identified a strong trend towards higher rates for referral in more recent studies.ConclusionsOur results show that pharmacies are feasible sites for screening for diabetes and those at risk of cardiovascular disease. A significant number of previously unknown cases of cardiovascular disease risk factors such as hypertension, hypercholesterolemia and diabetes are identified, however a significant number of referred participants at high risk do not attend their practitioner for follow up. Research priorities should include methods of increasing uptake to follow up testing and early intervention, to maximise the efficacy of screening interventions based in community pharmacies.

Dataset Information

Cardiovascular Disease Population Risk Tool (CVDPoRT): predictive algorithm for assessing CVD risk in the community setting. A study protocol.

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Cardiovascular Disease Population Risk Tool (CVDPoRT): predictive algorithm for assessing CVD risk in the community setting. A study protocol.

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