Validation and recalibration of the Framingham cardiovascular disease risk models in an Australian Indigenous cohort

Health map for HealthGap: Defining a geographical catchment to examine cardiovascular risk in Victoria, Australia

The HealthGap study aimed to understand cardiovascular risk among Indigenous Australians in Victoria using linked administrative data. A key challenge was differing spatial coverages of sources: state-level data for risk factors but cardiovascular outcomes for three hospitals. Catchments were defined based on hospital postcodes to estimate denominator populations for risk modelling: first- and second-order neighbours, and spatial distribution of outcomes ('spatial event distribution'). Catchment coverage was assessed through proportions of patients presenting to study hospitals from catchment postcodes. The spatial event distribution performed best, capturing 82% events overall (first-order:40%; second-order:64%) and 65% Indigenous (27% and 45%). No approach excluded proximal non-study hospitals. Spatial event distributions could help define denominator populations when geographic information on outcome data is available but may not avoid potential misclassification.

Ethical Challenges and Opportunities in Applying Artificial Intelligence to Cardiovascular Medicine

Much anticipation surrounds artificial intelligence's (AI) emergence as a promising tool in health care. It offers potential to revolutionise clinical practice through assistive and autonomous operation. The high prevalence of cardiac disease globally provides an opportunity for AI technology to increase health care efficiency and improve patient outcomes. This article explores the ethical considerations necessary for safe and acceptable implantation of AI within the health care space. We aim to highlight several challenges such as data privacy, consent, sustainability, and cybersecurity. In addition, we outline the future opportunities for AI use in cardiovascular medicine. Overall, we argue that AI deployment demands robust regulation, transparent algorithms, and safeguarding of patient privacy.

Impact of Race on Classification of Atherosclerotic Risk Using a National Cardiovascular Risk Prediction Tool

Introduction

The use of race in clinical risk prediction tools may exacerbate racial disparities in healthcare access and outcomes. This study quantified the number of individuals reclassified for primary prevention of cardiovascular disease owing to a change in their race alone on the basis of a commonly used risk prediction tool.

Methods

This is a cross-sectional analysis of individuals aged 40-75 years without a history of cardiovascular events, diabetes, or other high-risk features using the 2005-2018 National Health and Nutritional Examination Survey. Authors compared atherosclerotic cardiovascular disease risk scores using the American Heart Association/American College of Cardiology equation recommended for White individuals or individuals of other races with that recommended for Black individuals.

Results

A total of 2,946 White individuals; 1,361 Black individuals; and 2,495 individuals of other races were included in the analysis. Using the American Heart Association/American College of Cardiology equation, the mean 10-year atherosclerotic cardiovascular disease risk was 5.80% (95% CI=5.54, 6.06) for White individuals, 7.04% (956% CI=6.69, 7.39) for Black individuals, and 4.93% (95% CI=4.61, 5.24) for individuals of other races. When using the American Heart Association/American College of Cardiology equation designated for the opposite race (White/other race versus Black), the mean atherosclerotic cardiovascular disease risk score increased by 1.02% (95% CI=0.90, 1.13) for White individuals, decreased by 1.82% (95% CI= -1.67, -1.96) for Black individuals, and increased by 0.98% (95% CI=0.85, 1.10) for individuals of other races. When using clinical atherosclerotic cardiovascular disease categories of <7.5%, 7.5%-10%, and >10%, 16.93% of all individuals were reclassified when using the American Heart Association/American College of Cardiology's equation designated for the opposite race.

Conclusions

Changing race within a commonly used cardiovascular risk prediction tool results in significant changes in risk classification among eligible White and Black individuals in the U.S.

Recalibration of Framingham risk for a local population of Sri Lanka

BACKGROUND

Cardiovascular Diseases (CVD) account for the highest number of deaths and disability globally and within Sri Lanka. A CVD risk prediction tool is a simple means of early identification of high-risk groups which is a cost-effective preventive strategy, especially for resource-poor countries. Distribution of risk factor levels varies in different regions even within the same country, thus a common risk estimation tool for the country may give false local predictions. Since there are few published data related to Sri Lanka the aim of this study was to recalibrate the Framingham equation according to the local risk factor profile of a population in the Kurunegala region in Sri Lanka.

METHOD

A cross-sectional study was conducted with the participation of 1 102 persons from the Kurunegala Regional Director of Health Services area and the data was collected using an interviewer-administered questionnaire, anthropometric, blood pressure, and biochemical measurements. CVD risk was estimated using Framingham original and recalibrated CVD risk assessment methods. Current CVD mortality and morbidity data and the recalibration method conducted by the method described by Wilson and colleagues were used for calculations.

RESULTS

Original and recalibrated Framingham CVD risk scores predicted 55.5% (N = 612) and 62.3% (N = 687) to be having less than 10% CVD risk respectively. Further, the original and recalibrated CVD Risk Scores predicted 2.2% (N = 24) and 1.8% (N = 20) to be having CVD risk more than 40% respectively.

CONCLUSION

These findings show an over prediction of the CVD risk with the original Framingham risk calculations which signifies the importance of development of a region-specific risk prediction tool using local risk factor data in Sri Lanka which will prevent unnecessary expenditure to manage people without risk of CVD.

Evidence supporting the choice of a new cardiovascular risk equation for Australia

This article reviews the risk equations recommended for use in international cardiovascular disease (CVD) primary prevention guidelines and assesses their suitability for use in Australia against a set of a priori defined selection criteria. The review and assessment were commissioned by the National Heart Foundation of Australia on behalf of the Australian Chronic Disease Prevention Alliance to inform recommendations on CVD risk estimation as part of the 2023 update of the Australian CVD risk assessment and management guidelines. Selected international risk equations were assessed against eight selection criteria: development using contemporary data; inclusion of established cardiovascular risk factors; inclusion of ethnicity and deprivation measures; prediction of a broad selection of fatal and non-fatal CVD outcomes; population representativeness; model performance; external validation in an Australian dataset; and the ability to be recalibrated or modified. Of the ten risk prediction equations reviewed, the New Zealand PREDICT equation met seven of the eight selection criteria, and met additional usability criteria aimed at assessing the ability to apply the risk equation in practice in Australia.

Erratum: Potentially preventable dementia in a First Nations population in the Torres Strait and Northern Peninsula Area of North Queensland, Australia: a cross sectional analysis using population attributable fractions

[This corrects the article DOI: 10.1016/j.lanwpc.2023.100855.][This corrects the article DOI: 10.1016/j.lanwpc.2022.100532.].

Clinical characteristics of Aboriginal and Torres Strait Islander emergency department patients with suspected acute coronary syndrome

OBJECTIVES

To describe the demographics, presentation characteristics, clinical features and cardiac outcomes for Aboriginal and Torres Strait Islander patients who present to a regional cardiac referral centre ED with suspected acute coronary syndrome (ACS).

METHODS

This was a single-centre observational study conducted at a regional referral hospital in Far North Queensland, Australia from November 2017 to September 2018 and January 2019 to December 2019. Study participants were 278 Aboriginal and Torres Strait Islander people presenting to an ED and investigated for suspected ACS. The main outcome measure was the proportion of patients with ACS at index presentation and differences in characteristics between those with and without ACS.

RESULTS

ACS at presentation was diagnosed in 38.1% of patients (n = 106). The mean age of patients with ACS was 53.5 years (SD 9.5) compared with 48.7 years (SD 12.1) in those without ACS (P = 0.001). Patients with ACS were more likely to be male (63.2% vs 39.0%, P < 0.001), smokers (70.6% vs 52.3%, P = 0.002), have diabetes (56.6% vs 38.4%, P = 0.003) and have renal impairment (24.5% vs 10.5%, P = 0.002).

CONCLUSIONS

Aboriginal and Torres Strait Islander patients with suspected ACS have a high burden of traditional cardiac risk factors, regardless of whether they are eventually diagnosed with ACS. These patients may benefit from assessment for coronary artery disease regardless of age at presentation.

Potentially preventable dementia in a First Nations population in the Torres Strait and Northern Peninsula Area of North Queensland, Australia: A cross sectional analysis using population attributable fractions

Background

Dementia is highly prevalent among Australia's First Nations peoples, including Torres Strait Islander and Aboriginal peoples in Far North Queensland (FNQ). It is likely that historically recent exposure to modifiable risk factors underlies these rates, and a large proportion of dementia may be potentially preventable.

Methods

Data from two adult community health checks (2015-2018) were analyzed to determine the prevalence of 11 modifiable dementia risk factors among the First Nations residents of the Torres Strait and Northern Peninsula Area of FNQ. Population attributable fractions (PAF%) for dementia were calculated using age-standardized prevalence estimates derived from these health checks and relative risks obtained from previous meta-analyses in other populations. PAF% estimates were weighted for communality to account for overlap of risk factors.

Findings

Half (52·1%) of the dementia burden in this population may be attributed to 11 potentially modifiable risk factors. Hypertension (9·4%), diabetes mellitus (9·0%), obesity (8·0%), and smoking (5·3%) were the highest contributing risk factors. The contribution of depression (2·0%) and alcohol (0·3%) was lower than other global and national estimates. While the adjusted PAF% for social isolation was low based on the adult community health check data (1·6%), it was higher (4·2%) when official census data were analyzed.

Interpretation

These results suggest that a substantial proportion of dementia in FNQ First Nations peoples could potentially be prevented. Government investment in preventative health now is essential to reduce the future burden of dementia.

Funding

National Health and Medical Research Council (NHMRC, GNT1107140, GNT1191144, GNT1106175, GNT0631947).

Predicted cardiovascular disease risk and prescribing of antihypertensive therapy among patients with hypertension in Australia using MedicineInsight

Hypertension guidelines recommend that absolute cardiovascular disease (CVD) risk guide the management of hypertensive patients. This study aimed to assess the proportion of patients with diagnosed hypertension with sufficient data to calculate absolute CVD risk and determine whether CVD risk is associated with prescribing of antihypertensive therapies. This was a cross-sectional study using a large national database of electronic medical records of patients attending general practice in 2018 (MedicineInsight). Of 571,492 patients aged 45-74 years without a history of CVD, 251,733 [40.6% (95% CI: 39.8-41.2)] had a recorded hypertension diagnosis. The proportion of patients with sufficient recorded data available to calculate CVD risk was higher for patients diagnosed with hypertension [51.0% (95% CI: 48.0-53.9)] than for patients without a diagnosis of hypertension [38.7% (95% CI: 36.5-41.0)]. Of those patients with sufficient data to calculate CVD risk, 29.3% (95% CI: 28.1-30.6) were at high risk clinically, 6.0% (95% CI: 5.8-6.3) were at high risk based on their CVD risk score, 12.8% (95% CI: 12.5-13.2) at moderate risk and 51.8% (95% CI: 50.8-52.9) at low risk. The overall prevalence of antihypertensive therapy was 60.9% (95% CI: 59.3-62.5). Prescribing was slightly lower in patients at high risk based on their CVD risk score [57.4% (95% CI: 55.4-59.4)] compared with those at low [63.3% (95% CI: 61.9-64.8)] or moderate risk [61.8% (95% CI: 60.2-63.4)] or at high risk clinically [64.1% (95% CI: 61.9-66.3)]. Guideline adherence is suboptimal, and many patients miss out on treatments that may prevent future CVD events.

The Oral, Gut Microbiota and Cardiometabolic Health of Indigenous Orang Asli Communities

The Orang Asli (OA) of Malaysia have been relatively understudied where little is known about their oral and gut microbiomes. As human health is closely intertwined with the human microbiome, this study first assessed the cardiometabolic health in four OA communities ranging from urban, rural to semi-nomadic hunter-gatherers. The urban Temuan suffered from poorer cardiometabolic health while rural OA communities were undergoing epidemiological transition. The oral microbiota of the OA were characterised by sequencing the V4 region of the 16S rRNA gene. The OA oral microbiota were unexpectedly homogenous, with comparably low alpha diversity across all four communities. The rural Jehai and Temiar PP oral microbiota were enriched for uncharacterised bacteria, exhibiting potential for discoveries. This finding also highlights the importance of including under-represented populations in large cohort studies. The Temuan oral microbiota were also elevated in opportunistic pathogens such as Corynebacterium, Prevotella, and Mogibacterium, suggesting possible oral dysbiosis in these urban settlers. The semi-nomadic Jehai gut microbiota had the highest alpha diversity, while urban Temuan exhibited the lowest. Rural OA gut microbiota were distinct from urban-like microbiota and were elevated in bacteria genera such as Prevotella 2, Prevotella 9, Lachnospiraceae ND3007, and Solobacterium. Urban Temuan microbiota were enriched in Odoribacter, Blautia, Parabacetroides, Bacteroides and Ruminococcacecae UCG-013. This study brings to light the current health trend of these indigenous people who have minimal access to healthcare and lays the groundwork for future, in-depth studies in these populations.

Using Health Check Data to Understand Risks for Dementia and Cognitive Impairment Among Torres Strait Islander and Aboriginal Peoples in Northern Queensland—A Data Linkage Study

Objective

High rates of dementia are evident in First Nations populations, and modifiable risk factors may be contributing to this increased risk. This study aimed to use a longitudinal dataset to gain insights into the long-term risk and protective factors for dementia and cognitive impairment not dementia (CIND) in a Torres Strait Islander and Aboriginal population in Far North Queensland, Australia.

Study Design and Setting

Probabilistic data linkage was used to combine baseline health check data obtained in 1998/2000 and 2006/2007 for 64 residents in remote communities with their results on a single dementia assessment 10–20 years later (2015–2018). The relationship between earlier measures and later CIND/dementia status was examined using generalized linear modeling with risk ratios (RRs). Due to the small sample size, bootstrapping was used to inform variable selection during multivariable modeling.

Results

One third of participants (n = 21, 32.8%) were diagnosed with dementia (n = 6) or CIND (n = 15) at follow-up. Secondary school or further education (RR = 0.38, 95% CI 0.19–0.76, p = 0.006) and adequate levels of self-reported physical activity (RR = 0.26, 95% CI 0.13–0.52, p < 0.001) were repeatedly selected in bootstrapping and showed some evidence of protection against later CIND/dementia in final multivariate models, although these had moderate collinearity. Vascular risk measures showed inconclusive or unexpected associations with later CIND/dementia risk.

Conclusions

The preliminary findings from this small study highlighted two potential protective factors for dementia that may be present in this population. A tentative risk profile for later CIND/dementia risk is suggested, although the small sample size limits the applicability of these findings.

Risk prediction models for atherosclerotic cardiovascular disease: A systematic assessment with particular reference to Qatar

Background: Atherosclerotic cardiovascular disease (ASCVD) is a common disease in the State of Qatar and results in considerable morbidity, impairment of quality of life and mortality. The American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) is currently used in Qatar to identify those at high risk of ASCVD. However, it is unclear if this is the optimal ASCVD risk prediction model for use in Qatar's ethnically diverse population.

Aims: This systematic review aimed to identify, assess the methodological quality of and compare the properties of established ASCVD risk prediction models for the Qatari population.

Methods: Two reviewers performed head-to-head comparisons of established ASCVD risk calculators systematically. Studies were independently screened according to predefined eligibility criteria and critically appraised using Prediction Model Risk Of Bias Assessment Tool. Data were descriptively summarized and narratively synthesized with reporting of key statistical properties of the models.

Results: We identified 20,487 studies, of which 41 studies met our eligibility criteria. We identified 16 unique risk prediction models. Overall, 50% (n = 8) of the risk prediction models were judged to be at low risk of bias. Only 13% of the studies (n = 2) were judged at low risk of bias for applicability, namely, PREDICT and QRISK3.Only the PREDICT risk calculator scored low risk in both domains.

Conclusions: There is no existing ASCVD risk calculator particularly well suited for use in Qatar's ethnically diverse population. Of the available models, PREDICT and QRISK3 appear most appropriate because of their inclusion of ethnicity. In the absence of a locally derived ASCVD for Qatar, there is merit in a formal head-to-head comparison between PCE, which is currently in use, and PREDICT and QRISK3.

The role of multiple metabolic genes in predicting the overall survival of colorectal cancer: A study based on TCGA and GEO databases

The recent advances in gene chip technology have led to the identification of multiple metabolism-related genes that are closely associated with colorectal cancer (CRC). Nevertheless, none of these genes could accurately diagnose or predict CRC. The prognosis of CRC has been made by previous prognostic models constructed by using multiple genes, however, the predictive function of multi-gene prognostic models using metabolic genes for the CRC prognosis remains unexplored. In this study, we used the TCGA-CRC cohort as the test dataset and the GSE39582 cohort as the experimental dataset. Firstly, we constructed a prognostic model using metabolic genes from the TCGA-CRC cohort, which were also associated with CRC prognosis. We analyzed the advantages of the prognostic model in the prognosis of CRC and its regulatory mechanism of the genes associated with the model. Secondly, the outcome of the TCGA-CRC cohort analysis was validated using the GSE39582 cohort. We found that the prognostic model can be employed as an independent prognostic risk factor for estimating the CRC survival rate. Besides, compared with traditional clinical pathology, it can precisely predict CRC prognosis as well. The high-risk group of the prognostic model showed a substantially lower survival rate as compared to the low-risk group. In addition, gene enrichment analysis of metabolic genes showed that genes in the prognostic model are enriched in metabolism and cancer-related pathways, which may explain its underlying mechanism. Our study identified a novel metabolic profile containing 11 genes for prognostic prediction of CRC. The prognostic model may unravel the imbalanced metabolic microenvironment, and it might promote the development of biomarkers for predicting treatment response and streamlining metabolic therapy in CRC.

Predictive Ability of a Clinical-Genetic Risk Score for Venous Thromboembolism in Northern and Southern European Populations

Venous thromboembolism (VTE) is a complex, multifactorial problem, the development of which depends on a combination of genetic and acqfiguired risk factors. In a Spanish population, the Thrombo inCode score (or TiC score), which combines clinical and genetic risk components, was recently proven better at determining the risk of VTE than the commonly used model involving the analysis of two genetic variants associated with thrombophilia: the Factor V Leiden (F5 rs6025) and the G20210A prothrombin (F2 rs1799963). The aim of the present case-control study was to validate the VTE risk predictive capacity of the TiC score in a Northern European population (from Sweden). The study included 173 subjects with VTE and 196 controls. All were analyzed for the genetic risk variants included in the TiC gene panel. Standard measures -receiver operating characteristic (ROC) area under the curve (AUC), sensitivity, specificity, and odds ratio (OR)-were calculated. The TiC score returned an AUC value of 0.673, a sensitivity of 72.25%, a specificity of 60.62%, and an OR of 4.11. These AUC, sensitivity, and OR values are all greater than those associated with the currently used combination of genetic variants. A TiC version adjusted for the allelic frequencies of the Swedish population significantly improved its AUC value (0.783). In summary, the TiC score returned more reliable risk estimates for the studied Northern European population than did the analysis of the Factor V Leiden and the G20210A genetic variations in combination. Thus, the TiC score can be reliably used with European populations, despite differences in allelic frequencies.

National Heart Foundation of Australia: position statement on coronary artery calcium scoring for the primary prevention of cardiovascular disease in Australia

Introduction

This position statement considers the evolving evidence on the use of coronary artery calcium scoring (CAC) for defining cardiovascular risk in the context of Australian practice and provides advice to health professionals regarding the use of CAC scoring in primary prevention of cardiovascular disease in Australia.

Main recommendations:

CAC scoring could be considered for selected people with moderate absolute cardiovascular risk, as assessed by the National Vascular Disease Prevention Alliance (NVDPA) absolute cardiovascular risk algorithm, and for whom the findings are likely to influence the intensity of risk management. (GRADE evidence certainty: Low. GRADE recommendation strength: Conditional.)

CAC scoring could be considered for selected people with low absolute cardiovascular risk, as assessed by the NVDPA absolute cardiovascular risk algorithm, and who have additional risk-enhancing factors that may result in the underestimation of risk. (GRADE evidence certainty: Low. GRADE recommendation strength: Conditional.)

If CAC scoring is undertaken, a CAC score of 0 AU could reclassify a person to a low absolute cardiovascular risk status, with subsequent management to be informed by patient–clinician discussion and follow contemporary recommendations for low absolute cardiovascular risk. (GRADE evidence certainty: Very low. GRADE recommendation strength: Conditional.)

If CAC scoring is undertaken, a CAC score > 99 AU or ≥ 75th percentile for age and sex could reclassify a person to a high absolute cardiovascular risk status, with subsequent management to be informed by patient–clinician discussion and follow contemporary recommendations for high absolute cardiovascular risk. (GRADE evidence certainty: Very low. GRADE recommendation strength: Conditional.)

Changes in management as a result of this statement

CAC scoring can have a role in reclassification of absolute cardiovascular risk for selected patients in Australia, in conjunction with traditional absolute risk assessment and as part of a shared decision‐making approach that considers the preferences and values of individual patients.

External validation and clinical usefulness of three commonly used cardiovascular risk prediction scores in an Emirati population: a retrospective longitudinal cohort study

OBJECTIVES

Cardiovascular disease (CVD) risk prediction models are useful tools for identifying those at high risk of cardiovascular events in a population. No studies have evaluated the performance of such risk models in an Arab population. Therefore, in this study, the accuracy and clinical usefulness of two commonly used Framingham-based risk models and the 2013 Pooled Cohort Risk Equation (PCE) were assessed in a United Arab Emirates (UAE) national population.

DESIGN

A 10-year retrospective cohort study.

SETTING

Outpatient clinics at a tertiary care hospital, Al-Ain, UAE.

PARTICIPANTS

The study cohort included 1041 UAE nationals aged 30-79 who had no history of CVD at baseline. Patients were followed until 31 December 2019. Eligible patients were grouped into the PCE and the Framingham validation cohorts.

EXPOSURE

The 10-year predicted risk for CVD for each patient was calculated using the 2008 Framingham risk model, the 2008 office-based Framingham risk model, and the 2013 PCE model.

PRIMARY OUTCOME MEASURE

The discrimination, calibration and clinical usefulness of the three models for predicting 10-year cardiovascular risk were assessed.

RESULTS

In women, the 2013 PCE model showed marginally better discrimination (C-statistic: 0.77) than the 2008 Framingham models (C-statistic: 0.74-0.75), whereas all three models showed moderate discrimination in men (C-statistic: 0.69‒0.70). All three models overestimated CVD risk in both men and women, with higher levels of predicted risk. The 2008 Framingham risk model (high-risk threshold of 20%) classified only 46% of women who subsequently developed incident CVD within 10 years as high risk. The 2013 PCE risk model (high-risk threshold of 7.5%) classified 74% of men who did not develop a cardiovascular event as high risk.

CONCLUSIONS

None of the three models is accurate for predicting cardiovascular risk in UAE nationals. The performance of the models could potentially be improved by recalibration.

Cardiovascular disease risk assessment in an Aboriginal community-controlled health service: comparing algorithms

Aboriginal and Torres Strait Islander people have high rates of cardiovascular disease (CVD). The National Vascular Disease Prevention Alliance (NVDPA) CVD risk assessment algorithm is used for all Australians. The Central Australian Rural Practitioners Association (CARPA) algorithm used in the Northern Territory adds five percentage points to all NVDPA risk scores for Indigenous Australians. Information was extracted from an Aboriginal Community-Controlled Health Service for all Aboriginal and Torres Strait Islander regular clients aged 35-74 years without known CVD (n=1057). CVD risk scores were calculated using both algorithms. Prescription of lipid-lowering medications was assessed. Clients with high-risk scores were reviewed and recalled if required. CVD risk scores were calculated for 362 (34.4%) clients. Clients with high CVD risk comprised 17.7% (NVDPA) or 23.8% (CARPA), with most determined clinically. Clients with low CVD risk comprised 73.7% (NVDPA) or 47.2% (CARPA). More than 30% of those with high risk were not on lipid-lowering medications. Significant health and social issues affected treatment uptake. It is unclear which algorithm is most applicable; however, this service has decided to continue to use the NVDPA algorithm. Use of CVD risk assessment and management of high-risk clients could be increased in primary care.

Re-estimation improved the performance of two Framingham cardiovascular risk equations and the Pooled Cohort equations: A nationwide registry analysis

Equations predicting the risk of occurrence of cardiovascular disease (CVD) are used in primary care to identify high-risk individuals among the general population. To improve the predictive performance of such equations, we updated the Framingham general CVD 1991 and 2008 equations and the Pooled Cohort equations for atherosclerotic CVD within five years in a contemporary cohort of individuals who participated in the Austrian health-screening program from 2009-2014. The cohort comprised 1.7 M individuals aged 30-79 without documented CVD history. CVD was defined by hospitalization or death from cardiovascular cause. Using baseline and follow-up data, we recalibrated and re-estimated the equations. We evaluated the gain in discrimination and calibration and assessed explained variation. A five-year general CVD risk of 4.61% was observed. As expected, discrimination c-statistics increased only slightly and ranged from 0.73-0.79. The two original Framingham equations overestimated the CVD risk, whereas the original Pooled Cohort equations underestimated it. Re-estimation improved calibration of all equations adequately, especially for high-risk individuals. Half of the individuals were reclassified into another risk category using the re-estimated equations. Predictors in the re-estimated Framingham equations explained 7.37% of the variation, whereas the Pooled Cohort equations explained 5.81%. Age was the most important predictor.

Cardiovascular disease risk assessment for Aboriginal and Torres Strait Islander adults aged under 35 years: a consensus statement

Cardiovascular disease (CVD) is a leading cause of preventable morbidity and mortality in Aboriginal and Torres Strait Islander peoples. This statement from the Australian Chronic Disease Prevention Alliance, the Royal Australian College of General Practitioners, the National Aboriginal Community Controlled Health Organisation and the Editorial Committee for Remote Primary Health Care Manuals communicates the latest consensus advice of guideline developers, aligning recommendations on the age to commence Aboriginal and Torres Strait Islander CVD risk assessment across three guidelines. MAIN RECOMMENDATIONS: In Aboriginal and Torres Strait Islander peoples without existing CVD: CVD risk factor screening should commence from the age of 18 years at the latest, including for blood glucose level or glycated haemoglobin, estimated glomerular filtration rate, serum lipids, urine albumin to creatinine ratio, and other risk factors such as blood pressure, history of familial hypercholesterolaemia, and smoking status. Individuals aged 18-29 years with the following clinical conditions are automatically conferred high CVD risk: ▶type 2 diabetes and microalbuminuria; ▶moderate to severe chronic kidney disease; ▶systolic blood pressure ≥ 180 mmHg or diastolic blood pressure ≥ 110 mmHg; ▶familial hypercholesterolaemia; or ▶serum total cholesterol > 7.5 mmol/L. Assessment using the National Vascular Disease Prevention Alliance absolute CVD risk algorithm should commence from the age of 30 years at the latest - consider upward adjustment of calculated CVD risk score, accounting for local guideline use, risk factor and CVD epidemiology, and clinical discretion. Assessment should occur as part of an annual health check or opportunistically. Subsequent review should be conducted according to level of risk. CHANGES IN MANAGEMENT AS A RESULT OF THIS STATEMENT: From age 18 years (at the latest), Aboriginal and Torres Strait Islander adults should undergo CVD risk factor screening, and from age 30 years (at the latest), they should undergo absolute CVD risk assessment using the NVDPA risk algorithm.

Performance of cardiovascular risk prediction equations in Indigenous Australians

OBJECTIVE

To assess the performance of cardiovascular disease (CVD) risk equations in Indigenous Australians.

METHODS

We conducted an individual participant meta-analysis using longitudinal data of 3618 Indigenous Australians (55% women) aged 30-74 years without CVD from population-based cohorts of the Cardiovascular Risk in IndigenouS People(CRISP) consortium. Predicted risk was calculated using: 1991 and 2008 Framingham Heart Study (FHS), the Pooled Cohorts (PC), GloboRisk and the Central Australian Rural Practitioners Association (CARPA) modification of the FHS equation. Calibration, discrimination and diagnostic accuracy were evaluated. Risks were calculated with and without the use of clinical criteria to identify high-risk individuals.

RESULTS

When applied without clinical criteria, all equations, except the CARPA-adjusted FHS, underestimated CVD risk (range of percentage difference between observed and predicted CVD risks: -55% to -14%), with underestimation greater in women (-63% to -13%) than men (-47% to -18%) and in younger age groups. Discrimination ranged from 0.66 to 0.72. The CARPA-adjusted FHS equation showed good calibration but overestimated risk in younger people, those without diabetes and those not at high clinical risk. When clinical criteria were used with risk equations, the CARPA-adjusted FHS algorithm scored 64% of those who had CVD events as high risk; corresponding figures for the 1991-FHS were 58% and were 87% for the PC equation for non-Hispanic whites. However, specificity fell.

CONCLUSION

The CARPA-adjusted FHS CVD risk equation and clinical criteria performed the best, achieving higher combined sensitivity and specificity than other equations. However, future research should investigate whether modifications to this algorithm combination might lead to improved risk prediction.

Economic Modelling of Chronic Kidney Disease: A Systematic Literature Review to Inform Conceptual Model Design

BACKGROUND

Chronic kidney disease (CKD) is a progressive condition that leads to irreversible damage to the kidneys and is associated with an increased incidence of cardiovascular events and mortality. As novel interventions become available, estimates of economic and clinical outcomes are needed to guide payer reimbursement decisions.

OBJECTIVE

The aim of the present study was to systematically review published economic models that simulated long-term outcomes of kidney disease to inform cost-effectiveness evaluations of CKD treatments.

METHODS

The review was conducted across four databases (MEDLINE, Embase, the Cochrane library and EconLit) and health technology assessment agency websites. Relevant information on each model was extracted. Transition and mortality rates were also extracted to assess the choice of model parameterisation on disease progression by simulating patient's time with end-stage renal disease (ESRD) and time to ESRD/death. The incorporation of cardiovascular disease in a population with CKD was qualitatively assessed across identified models.

RESULTS

The search identified 101 models that met the criteria for inclusion. Models were classified into CKD models (n = 13), diabetes models with nephropathy (n = 48), ESRD-only models (n = 33) and cardiovascular models with CKD components (n = 7). Typically, published models utilised frameworks based on either (estimated or measured) glomerular filtration rate (GFR) or albuminuria, in line with clinical guideline recommendations for the diagnosis and monitoring of CKD. Generally, two core structures were identified, either a microsimulation model involving albuminuria or a Markov model utilising CKD stages and a linear GFR decline (although further variations on these model structures were also identified). Analysis of parameter variability in CKD disease progression suggested that mean time to ESRD/death was relatively consistent across model types (CKD models 28.2 years; diabetes models with nephropathy 24.6 years). When evaluating time with ESRD, CKD models predicted extended ESRD survival over diabetes models with nephropathy (mean time with ESRD 8.0 vs. 3.8 years).

DISCUSSION

This review provides an overview of how CKD is typically modelled. While common frameworks were identified, model structure varied, and no single model type was used for the modelling of patients with CKD. In addition, many of the current methods did not explicitly consider patient heterogeneity or underlying disease aetiology, except for diabetes. However, the variability of individual patients' GFR and albuminuria trajectories perhaps provides rationale for a model structure designed around the prediction of individual patients' GFR trajectories. Frameworks of future CKD models should be informed and justified based on clinical rationale and availability of data to ensure validity of model results. In addition, further clinical and observational research is warranted to provide a better understanding of prognostic factors and data sources to improve economic modelling accuracy in CKD.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP)

Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP)

Risk assessment have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP)

Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of – usually interactive and online available – tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.