Performance of a Framingham cardiovascular risk model among Indians and Europeans in New Zealand and the role of body mass index and social deprivation

Long-term cost-effectiveness analysis of rugby fans in training-New Zealand: a body weight reduction programme for males

OBJECTIVES

We sought to extrapolate the long-term costs and clinical impacts attributed to the rugby fans in training-New Zealand (RUFIT-NZ) trial in Aotearoa, New Zealand.

DESIGN

A modelled cost-effectiveness analysis using efficacy data from RUFIT-NZ was conducted from the Aotearoa New Zealand healthcare perspective.

SETTING

A Markov cohort model was constructed with a lifetime time horizon. The model simulated events of myocardial infarction (MI), stroke and type 2 diabetes mellitus (T2DM) occurring among a hypothetical cohort of 10 000 individuals receiving either the RUFIT-NZ intervention or no intervention. Efficacy data were based on the RUFIT-NZ trial, and the latest Global Burden of Disease study was used to extrapolate the impact of body weight reduction on clinical outcomes of T2DM, MI or stroke. Cost and utility data were drawn from the RUFIT-NZ trial and published sources.

PRIMARY OUTCOME MEASURES

The incremental cost-effectiveness ratio (ICER).

RESULTS

Over a lifetime time horizon, participants in the RUFIT-NZ intervention gained 0.02 (discounted) quality-adjusted life years (QALYs) at an additional cost of NZ$863, relative to no intervention. The estimated ICER was NZ$49 515 per QALY gained (discounted), which is above the arbitrary willingness-to-pay threshold of NZ$45 000 per QALY. Sensitivity analyses supported the robustness of these findings.

CONCLUSIONS

RUFIT-NZ was associated with a reduction in cardiovascular and endocrine events for overweight and obese males. However, based on conservative assumptions, RUFIT-NZ was unlikely to be cost-effective from a healthcare system perspective.

TRIAL REGISTRATION NUMBER

ACTRN12619000069156.

Societal health and economic burden of cardiovascular diseases in the population with type 2 diabetes in Qatar. A 10-year forecasting model

AIMS

To predict the future health and economic burden of cardiovascular disease (CVD) in type 2 diabetes (T2D) in Qatar.

MATERIALS AND METHODS

A dynamic multistate model was designed to simulate the progression of fatal and non-fatal CVD events among people with T2D in Qatar aged 40-79 years. First CVD events [i.e. myocardial infarction (MI) and stroke] were calculated via the 2013 Pooled Cohort Equation, while recurrent CVD events were sourced from the REACH registry. Key model outcomes were fatal and non-fatal MI and stroke, years of life lived, quality-adjusted life years, total direct medical costs and total productivity loss costs. Utility and cost model inputs were drawn from published sources. The model adopted a Qatari societal perspective. Sensitivity analyses were performed to test the robustness of estimates.

RESULTS

Over 10 years among people with T2D, model estimates 108 195 [95% uncertainty interval (UI) 104 249-112 172] non-fatal MIs, 62 366 (95% UI 60 283-65 520) non-fatal strokes and 14 612 (95% UI 14 472-14 744) CVD deaths. The T2D population accrued 4 786 605 (95% UI 4 743 454, 4 858 705) total years of life lived and 3 781 833 (95% UI 3 724 718-3 830 669) total quality-adjusted life years. Direct costs accounted for 57.85% of the total costs, with a projection of QAR41.60 billion (US$11.40 billion) [95% UI 7.53-147.40 billion (US$2.06-40.38 billion)], while the total indirect costs were expected to exceed QAR30.31 billion (US$8.30 billion) [95% UI 1.07-162.60 billion (US$292.05 million-44.55 billion)].

CONCLUSIONS

The findings suggest a significant economic and health burden of CVD among people with T2D in Qatar and highlight the need for more enhanced preventive strategies targeting this population group.

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.

A Systematic Review and Meta-Analysis of Applying Deep Learning in the Prediction of the Risk of Cardiovascular Diseases From Retinal Images

Purpose

The purpose of this study was to perform a systematic review and meta-analysis to synthesize evidence from studies using deep learning (DL) to predict cardiovascular disease (CVD) risk from retinal images.

Methods

A systematic literature search was performed in MEDLINE, Scopus, and Web of Science up to June 2022. We extracted data pertaining to predicted outcomes, model development, and validation and model performance metrics. Included studies were graded using the Quality Assessment of Diagnostic Accuracies Studies 2 tool. Model performance was pooled across eligible studies using a random-effects meta-analysis model.

Results

A total of 26 studies were included in the analysis. There were 42 CVD risk-related outcomes predicted from retinal images were identified, including 33 CVD risk factors, 4 cardiac imaging biomarkers, 2 CVD risk scores, the presence of CVD, and incident CVD. Three studies that aimed to predict the development of future CVD events reported an area under the receiver operating curve (AUROC) between 0.68 and 0.81. Models that used retinal images as input data had a pooled mean absolute error of 3.19 years (95% confidence interval [CI] = 2.95-3.43) for age prediction; a pooled AUROC of 0.96 (95% CI = 0.95-0.97) for gender classification; a pooled AUROC of 0.80 (95% CI = 0.73-0.86) for diabetes detection; and a pooled AUROC of 0.86 (95% CI = 0.81-0.92) for the detection of chronic kidney disease. We observed a high level of heterogeneity and variation in study designs.

Conclusions

Although DL models appear to have reasonably good performance when it comes to predicting CVD risk, further work is necessary to evaluate the real-world applicability and predictive accuracy.

Translational Relevance

DL-based CVD risk assessment from retinal images holds great promise to be translated to clinical practice as a novel approach for CVD risk assessment, given its simple, quick, and noninvasive nature.

Contemporary Review of Risk Scores in Prediction of Coronary and Cardiovascular Deaths

PURPOSE OF REVIEW

Explore the current literature supporting risk stratification scores for prediction of coronary and cardiovascular disease deaths.

RECENT FINDINGS

Accurate risk prediction remains the foundation of management choice in primary prevention. When applied to new populations, the calibration of a predictive model will deteriorate, although discrimination changes minimally. One of the approaches with better performance and validation is the initial use of pooled cohort equation to identify low and high-risk patients, followed by coronary artery calcium scoring in those with borderline to intermediate risk. It is important to utilize a risk stratification tool that has been validated in a patient population that resembles the one used to develop the original tool to maintain adequate calibration. It is likely that the future of mortality risk prediction will develop in combined clinical risk predictors and cardiovascular imaging, such coronary artery calcium (CAC) scoring that renders the highest predictive accuracy.

Educational Level, but Not Income or Area Deprivation, is Related to Macrovascular Disease: Results From Two Population-Based Cohorts in Germany

Objectives: An inverse relationship between education and cardiovascular risk has been described, however, the combined association of education, income, and neighborhood socioeconomic status with macrovascular disease is less clear. The aim of this study was to evaluate the association of educational level, equivalent household income and area deprivation with macrovascular disease in Germany.

Methods: Cross-sectional data from two representative German population-based studies, SHIP-TREND (n = 3,731) and KORA-F4 (n = 2,870), were analyzed. Multivariable logistic regression models were applied to estimate odds ratios and 95% confidence intervals for the association between socioeconomic determinants and macrovascular disease (defined as self-reported myocardial infarction or stroke).

Results: The study showed a higher odds of prevalent macrovascular disease in men with low and middle educational level compared to men with high education. Area deprivation and equivalent income were not related to myocardial infarction or stroke in any of the models.

Conclusion: Educational level, but not income or area deprivation, is significantly related to the macrovascular disease in men. Effective prevention of macrovascular disease should therefore start with investing in individual education.

Use of Coronary Computed Tomography Angiography to Screen Hospital Employees with Cardiovascular Risk Factors

The objective of this study was to determine how coronary computed tomography angiography (CCTA) can be employed to detect coronary artery disease in hospital employees, enabling early treatment and minimizing damage. All employees of our hospital were assessed using the Framingham Risk Score. Those with a 10-year risk of myocardial infarction or death of >10% were offered CCTA; the Coronary Artery Disease Reporting and Data System (CAD-RADS) score was the outcome. A total of 3923 hospital employees were included, and the number who had received CCTA was 309. Among these 309, 31 (10.0%) had a CAD-RADS score of 3-5, with 10 of the 31 (32.3%) requiring further cardiac catheterization; 161 (52.1%) had a score of 1-2; and 117 (37.9%) had a score of 0. In the multivariate logistic regression, only age of ≥ 55 years (p < 0.05), hypertension (p < 0.05), and hyperlipidemia (p < 0.05) were discovered to be significant risk factors for a CAD-RADS score of 3-5. Thus, regular and adequate control of chronic diseases is critical for patients, and more studies are required to be confirmed if there are more significant risk factors.

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.

Validation of the cardiovascular risk model NORRISK 2 in South Asians and people with diabetes

OBJECTIVES

To evaluate the predictive ability of the previously published NORRISK 2 cardiovascular risk model in Norwegian-born and immigrants born in South Asia living in Norway, and to add information about diabetes and ethnicity in an updated model for South Asians and diabetics (NORRISK 2-SADia). Design. We included participants (30-74 years) born in Norway (n = 13,885) or South Asia (n = 1942) from health surveys conducted in Oslo 2000-2003. Cardiovascular disease (CVD) risk factor information including self-reported diabetes was linked with information on subsequent acute myocardial infarction (AMI) and acute cerebral stroke in hospital and mortality registry data throughout 2014 from the nationwide CVDNOR project. We developed an updated model using Cox regression with diabetes and South Asian ethnicity as additional predictors. We assessed model performance by Harrell's C and calibration plots. Results. The NORRISK 2 model underestimated the risk in South Asians in all quintiles of predicted risk. The mean predicted 13-year risk by the NORRISK 2 model was 3.9% (95% CI 3.7-4.2) versus observed 7.3% (95% CI 5.9-9.1) in South Asian men and 1.1% (95% CI 1.0-1.2) versus 2.7% (95% CI 1.7-4.2) observed risk in South Asian women. The mean predictions from the NORRISK 2-SADia model were 7.2% (95% CI 6.7-7.6) in South Asian men and 2.7% (95% CI 2.4-3.0) in South Asian women. Conclusions. The NORRISK 2-SADia model improved predictions of CVD substantially in South Asians, whose risks were underestimated by the NORRISK 2 model. The NORRISK 2-SADia model may facilitate more intense preventive measures in this high-risk population.

Cardiovascular risk assessment in South and Middle-East Asians living in the Western countries

Nearly a quarter of the world population lives in the South Asian region (India, Pakistan, Bangladesh, Sri Lanka, Nepal, Bhutan, and the Maldives). Due to rapid demographic and epidemiological transition in these countries, the burden of non-communicable diseases is growing, which is a serious public health concern. Particularly, the prevalence of pre-diabetes, diabetes and atherosclerotic cardiovascular disease (CVD) is increasing. South Asians living in the West have also substantially higher risk of CVD and mortality compared with white Europeans and Americans. Further, as a result of global displacement over the past three decades, Middle-Eastern immigrants now represent the largest group of non-European immigrants in Northern Europe. This vulnerable population has been less studied. Hence, the aim of the present review was to address cardiovascular risk assessment in South Asians (primarily people from India, Pakistan and Bangladesh), and Middle-East Asians living in Western countries compared with whites (Caucasians) and present results from some major intervention studies. A systematic search was conducted in PubMed to identify major cardiovascular health studies of South Asian and Middle-Eastern populations living in the West, relevant for this review. Results indicated an increased risk of CVD. In conclusion, both South Asian and Middle-Eastern populations living in the West carry significantly higher risk of diabetes and CVD compared with native white Europeans. Lifestyle interventions have been shown to have beneficial effects in terms of reduction in the risk of diabetes by increasing insulin sensitivity, weight loss as well as better glycemic and lipid control.

Is the History of Erectile Dysfunction a Reliable Risk Factor for New Onset Acute Myocardial Infarction? A Systematic Review and Meta-Analysis

Acute myocardial infarction (AMI) occurs as a manifestation of coronary atherosclerotic disease. The occurrence of erectile dysfunction (ED) following AMI is well documented and this association and pathophysiology is often interrelated. Few studies have objectively assessed the diagnostic value of ED as a risk factor for AMI, in general. In this review, we aimed to better outline the diagnostic predictability of ED as a precursor for 'first/new onset' AMI. This review was performed using selective search terms, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines. The Cochrane, Embase, PubMed, Scopus and Web of Science databases were searched (September 2018). Selected studies were further assessed for relevance and quality (Critical Appraisal Skills Program tool-Oxford). Four studies [573 participants; mean 143 (SD ± 76.3604) and median 141 participants] were eligible for analysis. Meta-analysis of the studies resulted in a pooled sensitivity of 51.36% (95% CI: 47.37-55.33%). For the single study which reported true negative and false positive cases, a specificity of 76.53% (95% CI: 68.57-83.00%) was calculated. The results of this systematic review and meta-analysis suggest that a history of ED should be used as a risk factor for new onset AMI.

Evaluating Cardiovascular Disease (CVD) risk scores for participants with known CVD and non-CVD in a multiracial/ethnic Caribbean sample

Background

Cardiovascular Disease (CVD) risk prediction models have been useful in estimating if individuals are at low, intermediate, or high risk, of experiencing a CVD event within some established time frame, usually 10 years. Central to this is the concern in Trinidad and Tobago of using pre-existing CVD risk prediction methods, based on populations in the developed world (e.g. ASSIGN, Framingham and QRISK^®2), to establish risk for its multiracial/ethnic Caribbean population. The aim of this study was to determine which pre-existing CVD risk method is best suited for predicting CVD risk for individuals in this population.

Method

A survey was completed by 778 participants, 526 persons with no prior CVD, and 252 who previously reported a CVD event. Lifestyle and biometric data was collected from non-CVD participants, while for CVD participants, medical records were used to collect data at the first instance of CVD. The performances of three CVD risk prediction models (ASSIGN, Framingham and QRISK^®2) were evaluated using their calculated risk scores.

Results

All three models (ASSIGN, Framingham and QRISK^®2) identified less than 62% of cases (CVD participants) with a high proportion of false-positive predictions to true predictions as can be seen by positive predictabilities ranging from 78% (ASSIGN and Framingham) to 87% (QRISK^®2). Further, for all three models, individuals whose scores fell into the misclassification range were 2X more likely to be individuals who had experienced a prior CVD event as opposed to healthy individuals.

Conclusion

The ASSIGN, Framingham and QRISK^®2 models should be utilised with caution on a Trinidad and Tobago population of intermediate and high risk for CVD since these models were found to have underestimated the risk for individuals with CVD up to 2.5 times more often than they overestimated the risk for healthy persons.