Cardiovascular risk prediction models for women in the general population: A systematic review

A comprehensive review on efficient artificial intelligence models for classification of abnormal cardiac rhythms using electrocardiograms

Deep learning has made many advances in data classification using electrocardiogram (ECG) waveforms. Over the past decade, data science research has focused on developing artificial intelligence (AI) based models that can analyze ECG waveforms to identify and classify abnormal cardiac rhythms accurately. However, the primary drawback of the current AI models is that most of these models are heavy, computationally intensive, and inefficient in terms of cost for real-time implementation. In this review, we first discuss the current state-of-the-art AI models utilized for ECG-based cardiac rhythm classification. Next, we present some of the upcoming modeling methodologies which have the potential to perform real-time implementation of AI-based heart rhythm diagnosis. These models hold significant promise in being lightweight and computationally efficient without compromising the accuracy. Contemporary models predominantly utilize 12-lead ECG for cardiac rhythm classification and cardiovascular status prediction, increasing the computational burden and making real-time implementation challenging. We also summarize research studies evaluating the potential of efficient data setups to reduce the number of ECG leads without affecting classification accuracy. Lastly, we present future perspectives on AI's utility in precision medicine by providing opportunities for accurate prediction and diagnostics of cardiovascular status in patients.

Incorporating reproductive system history data into cardiovascular nursing research to advance women's health

The lack of sex-specific variables, such as reproductive system history (RSH), in cardiovascular research studies is a missed opportunity to address the cardiovascular disease (CVD) burden, especially among women who face sex-specific risks of developing CVD. Collecting RSH data from women enrolled in research studies is an important step towards improving women's cardiovascular health. In this paper, we describe two approaches to collecting RSH in CVD research: extracting RSH from the medical record and participant self-report of RSH. We provide specific examples from our own research and address common data management and statistical analysis problems when dealing with RSH data in research.

The menopausal transition period and cardiovascular risk

The menopausal transition period spans, on average, 2-8 years before the final menstrual period and is associated with an increase in clinical and subclinical cardiovascular risk. In this Review, we discuss the metabolic and cardiovascular changes that occur during the menopausal transition period and the role of ovarian ageing, chronological ageing and other ageing-related risk factors in mediating these changes. Disentangling the relative contributions of chronological and reproductive ageing to cardiovascular risk is challenging, but data from longitudinal studies in women transitioning from premenopause to post-menopause have provided valuable insights. We also discuss evidence on how cardiovascular risk is altered by premature or early menopause, surgical menopause, and vasomotor and other menopausal symptoms. Whether targeted interventions can slow the progression of atherosclerosis and subclinical disease during the menopausal transition, thus delaying or preventing the onset of cardiovascular events, remains to be determined. Furthermore, we consider the recommended strategies for cardiovascular risk reduction in women undergoing menopausal transition using the framework of the American Heart Association's Life's Essential 8 key measures for improving and maintaining cardiovascular health, and discuss the cardiovascular risks and benefits of menopausal hormone therapy. Finally, we also discuss novel therapies that might benefit this population in reducing cardiovascular risk.

Major Limitations of Cardiovascular Risk Scores

Background. Epidemiological studies conducted in extensive population cohorts have led to the creation of numerous cardiovascular risk predictor models. However, these tools have certain limitations that restrict its applicability. The aim behind the following work is to summarize today's best-known limitations of cardiovascular risk assessment models through presenting the critical analyses conducted in this area, with the intention of offering practitioners a comprehensive understanding of these restrictions. Critical analyses revealed that these scales exhibit numerous limitations that could impact their performance. Most of these models evaluate cardiovascular risk based on classic risk factors and other restrictions, thereby negatively affecting their sensitivity. Scientists have made significant advancements in improving cardiovascular risk models, tailoring them to accommodate a wide range of populations and devising scales for estimating cardiovascular risks that can account for all prevailing restrictions. Better understanding these limitations could improve the cardiovascular risk stratification.

Five critical quality criteria for artificial intelligence-based prediction models

To raise the quality of clinical artificial intelligence (AI) prediction modelling studies in the cardiovascular health domain and thereby improve their impact and relevancy, the editors for digital health, innovation, and quality standards of the European Heart Journal propose five minimal quality criteria for AI-based prediction model development and validation studies: complete reporting, carefully defined intended use of the model, rigorous validation, large enough sample size, and openness of code and software.

Validity of the models predicting 10-year risk of cardiovascular diseases in Asia: A systematic review and prediction model meta-analysis

We aimed to review the validity of existing prediction models for cardiovascular diseases (CVDs) in Asia. In this systematic review and meta-analysis, we included studies that validated prediction models for CVD risk in the general population in Asia. Various databases, including PubMed, Web of Science conference proceedings citation index, Scopus, Global Index Medicus of the World Health Organization (WHO), and Open Access Thesis and Dissertations (OATD), were searched up to November 2022. Additional studies were identified through reference lists and related reviews. The risk of bias was assessed using the PROBAST prediction model risk of bias assessment tool. Meta-analyses were performed using the random effects model, focusing on the C-statistic as a discrimination index and the observed-to-expected ratio (OE) as a calibration index. Out of 1315 initial records, 16 studies were included, with 21 external validations of six models in Asia. The validated models consisted of Framingham models, pooled cohort equations (PCEs), SCORE, Globorisk, and WHO models, combined with the results of the first four models. The pooled C-statistic for men ranged from 0.72 (95% CI 0.70 to 0.75; PCEs) to 0.76 (95% CI 0.74 to 0.78; Framingham general CVD). In women, it varied from 0.74 (95% CI 0.22 to 0.97; SCORE) to 0.79 (95% CI 0.74 to 0.83; Framingham general CVD). The pooled OE ratio for men ranged from 0.21 (95% CI 0.018 to 2.49; Framingham CHD) to 1.11 (95%CI 0.65 to 1.89; PCEs). In women, it varied from 0.28 (95%CI 0.33 to 2.33; Framingham CHD) to 1.81 (95% CI 0.90 to 3.64; PCEs). The Framingham, PCEs, and SCORE models exhibited acceptable discrimination but poor calibration in predicting the 10-year risk of CVDs in Asia. Recalibration and updates are necessary before implementing these models in the region.

Women, lipids, and atherosclerotic cardiovascular disease: a call to action from the European Atherosclerosis Society

Cardiovascular disease is the leading cause of death in women and men globally, with most due to atherosclerotic cardiovascular disease (ASCVD). Despite progress during the last 30 years, ASCVD mortality is now increasing, with the fastest relative increase in middle-aged women. Missed or delayed diagnosis and undertreatment do not fully explain this burden of disease. Sex-specific factors, such as hypertensive disorders of pregnancy, premature menopause (especially primary ovarian insufficiency), and polycystic ovary syndrome are also relevant, with good evidence that these are associated with greater cardiovascular risk. This position statement from the European Atherosclerosis Society focuses on these factors, as well as sex-specific effects on lipids, including lipoprotein(a), over the life course in women which impact ASCVD risk. Women are also disproportionately impacted (in relative terms) by diabetes, chronic kidney disease, and auto-immune inflammatory disease. All these effects are compounded by sociocultural components related to gender. This panel stresses the need to identify and treat modifiable cardiovascular risk factors earlier in women, especially for those at risk due to sex-specific conditions, to reduce the unacceptably high burden of ASCVD in women.

Added Predictive Value of Female-Specific Factors and Psychosocial Factors for the Risk of Stroke in Women Under 50

BACKGROUND AND OBJECTIVES

Female-specific factors and psychosocial factors may be important in the prediction of stroke but are not included in prediction models that are currently used. We investigated whether addition of these factors would improve the performance of prediction models for the risk of stroke in women younger than 50 years.

METHODS

We used data from the Stichting Informatievoorziening voor Zorg en Onderzoek, population-based, primary care database of women aged 20-49 years without a history of cardiovascular disease. Analyses were stratified by 10-year age intervals at cohort entry. Cox proportional hazards models to predict stroke risk were developed, including traditional cardiovascular factors, and compared with models that additionally included female-specific and psychosocial factors. We compared the risk models using the c-statistic and slope of the calibration curve at a follow-up of 10 years. We developed an age-specific stroke risk prediction tool that may help communicating the risk of stroke in clinical practice.

RESULTS

We included 409,026 women with a total of 3,990,185 person-years of follow-up. Stroke occurred in 2,751 women (incidence rate 6.9 [95% CI 6.6-7.2] per 10,000 person-years). Models with only traditional cardiovascular factors performed poorly to moderately in all age groups: 20-29 years: c-statistic: 0.617 (95% CI 0.592-0.639); 30-39 years: c-statistic: 0.615 (95% CI 0.596-0.634); and 40-49 years: c-statistic: 0.585 (95% CI 0.573-0.597). After adding the female-specific and psychosocial risk factors to the reference models, the model discrimination increased moderately, especially in the age groups 30-39 (Δc-statistic: 0.019) and 40-49 years (Δc-statistic: 0.029) compared with the reference models, respectively.

DISCUSSION

The addition of female-specific factors and psychosocial risk factors improves the discriminatory performance of prediction models for stroke in women younger than 50 years.

Assessment of Cardiovascular Risk in Women: Progress so Far and Progress to Come

Cardiovascular disease is the leading cause of death in women worldwide. Nonetheless, there exist several uncertainties in the prediction, diagnosis, and treatment of cardiovascular disease in women. A cornerstone in the prediction of cardiovascular disease is the implementation of risk scores. A variety of pregnancy- and reproductive-factors have been associated with lower or higher risk of cardiovascular disease. Consequently, the question has been raised, whether these female-specific factors also provide added value to cardiovascular risk prediction. In this review, we provide an overview of the existing literature on sex differences in the association of established cardiovascular risk factors with cardiovascular disease and the relation between female-specific factors and cardiovascular risk. Furthermore, we systematically reviewed the literature for studies that assessed the added value of female-specific factors beyond already established cardiovascular risk factors. Adding female-specific factors to models containing established cardiovascular risk factors has led to little or no significant improvement in the prediction of cardiovascular events. However, analyses primarily relied on data from women aged ≥40 years. Future investigations are needed to quantify whether pregnancy-related factors improve cardiovascular risk prediction in young women in order to support adequate treatment of risk factors and enhance prevention of cardiovascular disease in women.

Sex-Specific Survival Bias and Interaction Modeling in Coronary Artery Disease Risk Prediction

BACKGROUND

The 10-year Atherosclerotic Cardiovascular Disease risk score is the standard approach to predict risk of incident cardiovascular events, and recently, addition of coronary artery disease (CAD) polygenic scores has been evaluated. Although age and sex strongly predict the risk of CAD, their interaction with genetic risk prediction has not been systematically examined. This study performed an extensive evaluation of age and sex effects in genetic CAD risk prediction.

METHODS

The population-based Norwegian HUNT2 (Trøndelag Health Study 2) cohort of 51 036 individuals was used as the primary dataset. Findings were replicated in the UK Biobank (372 410 individuals). Models for 10-year CAD risk were fitted using Cox proportional hazards, and Harrell concordance index, sensitivity, and specificity were compared.

RESULTS

Inclusion of age and sex interactions of CAD polygenic score to the prediction models increased the C-index and sensitivity by accounting for nonadditive effects of CAD polygenic score and likely countering the observed survival bias in the baseline. The sensitivity for females was lower than males in all models including genetic information. We identified a total of 82.6% of incident CAD cases by using a 2-step approach: (1) Atherosclerotic Cardiovascular Disease risk score (74.1%) and (2) the CAD polygenic score interaction model for those in low clinical risk (additional 8.5%).

CONCLUSIONS

These findings highlight the importance and complexity of genetic risk in predicting CAD. There is a need for modeling age- and sex-interaction terms with polygenic scores to optimize detection of individuals at high risk, those who warrant preventive interventions. Sex-specific studies are needed to understand and estimate CAD risk with genetic information.

Protocol for development and validation of postpartum cardiovascular disease (CVD) risk prediction model incorporating reproductive and pregnancy-related candidate predictors

BACKGROUND

Cardiovascular disease (CVD) is a leading cause of death among women. CVD is associated with reduced quality of life, significant treatment and management costs, and lost productivity. Estimating the risk of CVD would help patients at a higher risk of CVD to initiate preventive measures to reduce risk of disease. The Framingham risk score and the QRISK® score are two risk prediction models used to evaluate future CVD risk in the UK. Although the algorithms perform well in the general population, they do not take into account pregnancy complications, which are well known risk factors for CVD in women and have been highlighted in a recent umbrella review. We plan to develop a robust CVD risk prediction model to assess the additional value of pregnancy risk factors in risk prediction of CVD in women postpartum.

METHODS

Using candidate predictors from QRISK®-3, the umbrella review identified from literature and from discussions with clinical experts and patient research partners, we will use time-to-event Cox proportional hazards models to develop and validate a 10-year risk prediction model for CVD postpartum using Clinical Practice Research Datalink (CPRD) primary care database for development and internal validation of the algorithm and the Secure Anonymised Information Linkage (SAIL) databank for external validation. We will then assess the value of additional candidate predictors to the QRISK®-3 in our internal and external validations.

DISCUSSION

The developed risk prediction model will incorporate pregnancy-related factors which have been shown to be associated with future risk of CVD but have not been taken into account in current risk prediction models. Our study will therefore highlight the importance of incorporating pregnancy-related risk factors into risk prediction modeling for CVD postpartum.

Prognostic Value of High-Sensitivity Cardiac Troponin in Women

High-sensitivity cardiac troponin assays have become the gold standard for diagnosing acute and chronic myocardial injury. The detection of troponin levels beyond the 99th percentile is included in the fourth universal definition of myocardial infarction, specifically recommending the use of sex-specific thresholds. Measurable concentrations below the proposed diagnostic thresholds have been shown to inform prognosis in different categories of inpatients and outpatients. However, clinical investigations from the last twenty years have yielded conflicting results regarding the incremental value of using different cut-offs for men and women. While advocates of a sex-specific approach claim it may help reduce gender bias in cardiovascular medicine, particularly in acute coronary syndromes, other groups question the alleged incremental diagnostic and prognostic value of sex-specific thresholds, ultimately asserting that less is more. In the present review, we aimed to synthesize our current understanding of sex-based differences in cardiac troponin levels and to reappraise the available evidence with regard to (i) the prognostic significance of sex-specific diagnostic thresholds of high-sensitivity cardiac troponin assays compared to common cut-offs in both men and women undergoing cardiovascular disease risk assessment, and (ii) the clinical utility of high-sensitivity cardiac troponin assays for cardiovascular disease prevention in women.

Cardiovascular disease risk prediction models in the Chinese population- a systematic review and meta-analysis

Background

There is an increasing prevalence of cardiovascular disease (CVD) in China, which represents the leading cause of mortality. Precise CVD risk identification is the fundamental prevention component. This study sought to systematically review the CVD risk prediction models derived and/or validated in the Chinese population to promote primary CVD prevention.

Methods

Reports were included if they derived or validated one or more CVD risk prediction models in the Chinese population. PubMed, Embase, CINAHL, Web of Science, Scopus, China National Knowledge Infrastructure (CNKI), VIP database, etc., were searched. The risk of bias was assessed with the Prediction Model Risk of Bias Assessment Tool (PROBAST). Meta-analysis was performed in R using the package metamisc.

Results

From 55,183 records, 22 studies were included. Twelve studies derived 18 CVD risk prediction models, of which seven models were derived based on a multicentre cohort including more than two provinces of mainland China, and one was a model developed based on a New Zealand cohort including Chinese individuals. The number of predictors ranged from 6 to 22. The definitions of predicted outcomes showed considerable heterogeneity. Fourteen articles described 29 validations of 8 models. The Framingham model and pooled cohort equations (PCEs) are the most frequently validated foreign tools. Discrimination was acceptable and similar for men and women among models (0.60–0.83). The calibration estimates changed substantially from one population to another. Prediction for atherosclerotic cardiovascular disease Risk in China (China-PAR) showed good calibration [observed/expected events ratio = 0.99, 95% PI (0.57,1.70)] and female sex [1.10, 95% PI (0.23,5.16)].

Conclusions

Several models have been developed or validated in the Chinese population. The usefulness of most of the models remains unclear due to incomplete external validation and head-to-head comparison. Future research should focus on externally validating or tailoring these models to local settings.

Trail registration

This systematic review was registered at PROSPERO (International Prospective Register of Systematic Reviews, CRD42021277453).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13995-z.

Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease

The medical field has seen a rapid increase in the development of artificial intelligence (AI)-based prediction models. With the introduction of such AI-based prediction model tools and software in cardiovascular patient care, the cardiovascular researcher and healthcare professional are challenged to understand the opportunities as well as the limitations of the AI-based predictions. In this article, we present 12 critical questions for cardiovascular health professionals to ask when confronted with an AI-based prediction model. We aim to support medical professionals to distinguish the AI-based prediction models that can add value to patient care from the AI that does not.

Statins in Pregnancy: Can We Justify Early Treatment of Reproductive Aged Women?

PURPOSE OF REVIEW

Statins are the pillar of secondary prevention in reducing cardiovascular disease in high-risk adults. However, statin discontinuation is the standard recommendation in pregnant and lactating patients. This review evaluates whether we can justify the early treatment of reproductive aged women with statin therapy.

RECENT FINDINGS

Statins have several potential benefits including its antioxidant, anti-inflammatory, and anti-thrombogenic properties that may prevent the worsening of atherosclerosis in high-risk women. Nevertheless, most studies on statins and teratogenicity have a limited sample size and the effects of long-term statin use on fetal and neonatal health remain unknown. Not all statins may be safe and pravastatin's cholesterol-lowering properties may be too limited to provide much maternal benefit in pregnancy. While emerging evidence supports the use of pravastatin in pregnancy, we need to better assess the risk of early cardiovascular disease and acute progression of atherosclerosis before and during pregnancy to better understand the risks and benefits of statin use.

Derivation, internal validation, and recalibration of a cardiovascular risk score for Latin America and the Caribbean (Globorisk-LAC): A pooled analysis of cohort studies

Background

Risk stratification is a cornerstone of cardiovascular disease (CVD) prevention and a main strategy proposed to achieve global goals of reducing premature CVD deaths. There are no cardiovascular risk scores based on data from Latin America and the Caribbean (LAC) and it is unknown how well risk scores based on European and North American cohorts represent true risk among LAC populations.

Methods

We developed a CVD (including coronary heart disease and stroke) risk score for fatal/non-fatal events using pooled data from 9 prospective cohorts with 21,378 participants and 1,202 events. We developed laboratory-based (systolic blood pressure, total cholesterol, diabetes, and smoking), and office-based (body mass index replaced total cholesterol and diabetes) models. We used Cox proportional hazards and held back a subset of participants to internally validate our models by estimating Harrell's C-statistic and calibration slopes.

Findings

The C-statistic for the laboratory-based model was 72% (70-74%), the calibration slope was 0.994 (0.934-1.055) among men and 0.852 (0.761-0.942) among women; for the office-based model the C-statistic was 71% (69-72%) and the calibration slope was 1.028 (0.980-1.076) among men and 0.811 (0.663-0.958) among women. In the pooled sample, using a 20% risk threshold, the laboratory-based model had sensitivity of 21.9% and specificity of 94.2%. Lowering the threshold to 10% increased sensitivity to 52.3% and reduced specificity to 78.7%.

Interpretation

The cardiovascular risk score herein developed had adequate discrimination and calibration. The Globorisk-LAC would be more appropriate for LAC than the current global or regional risk scores. This work provides a tool to strengthen risk-based cardiovascular prevention in LAC.

Funding

Wellcome Trust (214185/Z/18/Z).

Accuracy of approximations to recover incompletely reported logistic regression models depended on other available information

OBJECTIVE

To provide approximations to recover the full regression equation across different scenarios of incompletely reported prediction models that were developed from binary logistic regression.

STUDY DESIGN AND SETTING

In a case study, we considered four common scenarios and illustrated their corresponding approximations: (A) Missing: the intercept, Available: the regression coefficients of predictors, overall frequency of the outcome and descriptive statistics of the predictors; (B) Missing: regression coefficients and the intercept, Available: a simplified score; (C) Missing: regression coefficients and the intercept, Available: a nomogram; (D) Missing: regression coefficients and the intercept, Available: a web calculator.

RESULTS

In the scenario A, a simplified approach based on the predicted probability corresponding to the average linear predictor was inaccurate. An approximation based on the overall outcome frequency and an approximation of the linear predictor distribution was more accurate, however, the appropriateness of the underlying assumptions cannot be verified in practice. In the scenario B, the recovered equation was inaccurate due to rounding and categorization of risk scores. In the scenarios C and D, the full regression equation could be recovered with minimal error.

CONCLUSION

The accuracy of the approximations in recovering the regression equation varied depending on the available information.

Polygenic risk score and coronary artery disease: A meta-analysis of 979,286 participant data

BACKGROUND AND AIMS

Coronary artery disease (CAD) is a complex disease with a strong genetic basis. While previous studies have combined common single-nucleotide polymorphisms (SNPs) into a polygenic risk score (PRS) to predict CAD risk, this association is poorly characterised. We performed a meta-analysis to estimate the effect of PRS on the risk of CAD.

METHODS

Online databases were searched for studies reporting PRS and CAD. PRS computation was based on log-odds (PRS_LN), pruning or clumping and thresholding (PRS_P/C + T), Lassosum regression (PRS_Lassosum), LDpred (PRS_LDpred), or metaGRS (PRS_metaGRS). The reported odds ratio (OR), hazard ratio (HR), C-indexes and their corresponding 95% confidence interval (95% CI) were pooled in a random-effects meta-analysis.

RESULTS

Forty-nine studies were included (979,286 individuals). There was a significant association between 1-standard deviation [SD] increment in PRS and adjusted risks of both incident and prevalent CAD (OR [95% CI]: 1.67 [1.57-1.77] for PRS_metaGRS, 1.46 [1.26-1.68] for PRS_LDpred). The risk of incident CAD was highest for PRS_P/C + T (HR [95% CI]: 1.49 [1.26-1.78]), PRS_metaGRS (1.37 [1.27-1.47]), and PRS_LDpred (1.36 [1.31-1.42]). Analysis of model performance demonstrated that PRS predicted incident CAD with C-index of up to 0.71. Importantly, addition of PRS to clinical risk scores resulted in modest but statistically significant improvements in CAD risk prediction, with 1.5% observed for PRS_P/C + T (p < 0.001) and 1.6% for PRS_LDpred (p < 0.001).

CONCLUSIONS

Polygenic risk score is strongly associated with increased risks of CAD. Future prospective studies should explore the usefulness of polygenic risk scores for identifying individuals at a high risk of developing CAD.

External validation of the European and American equations for calculating cardiovascular risk in a Spanish working population

INTRODUCTION AND OBJECTIVE

This work aims to externally validate the European and American models for calculating cardiovascular risk in the primary prevention.

METHODS

This is a cross-sectional study of a nation-wide cohort of individuals who are active in the work force. Workers without a medical history cardiovascular disease who attended occupational health check-ups between 2004 and 2007 were included. They were followed-up on until December 2017.

RESULTS

A total of 244,236 subjects participated. Of them, 24.5% were women and the mean age was 48.10 years (SD 6.26). According to the European SCORE risk chart, the mean risk was 1.70 (SD 1.81) for men and 0.37 (SD 0.53) for women. According to the North American PCE model, the mean risk was 6.98 (SD 5.66) for men and 1.97 (SD 1.96) for women. A total of 1177 events (0.51%) were registered according to the SCORE tool and 2,330 events (1.00%) were registered according to the PCE tool. The Harrell's C-statistic was 0.746 for SCORE and 0.725 for PCE. Sensitivity and specificity for the SCORE'S 5% cut-off point were 17.59% (95%CI 15.52%-19.87%) and 95.68% (95%CI 95.59%-95.76%). Sensitivity and specificity for the PCE's 20% cut-off point were 9.06% (95%CI 7.96%-10.29%) and 97.55% (95%CI 97.48%-97.61%), respectively.

CONCLUSIONS

The European SCORE and North American PCE models overestimate the risk in our population but with an acceptable discrimination. SCORE showed better validity indices than the PCE. The population's risk is continuously changing; therefore, it is important continue updating the equations to include information on current populations.

Gestational Diabetes History and Glucose Tolerance After Pregnancy Associated With Coronary Artery Calcium in Women During Midlife: The CARDIA Study

BACKGROUND

Gestational diabetes (GD) leads to earlier onset and heightened risk of type 2 diabetes, a strong risk factor for cardiovascular disease (CVD). However, it is unclear whether attaining normoglycemia can ameliorate the excess CVD risk associated with GD history. This study sought to evaluate GD history and glucose tolerance after pregnancy associated with coronary artery calcification (CAC) in women, a manifestation of atherosclerotic CVD and a predictor of CVD clinical events.

METHODS

Data were obtained from the CARDIA study (Coronary Artery Risk Development in Young Adults), a US multicenter, community-based prospective cohort of young Black (50%) and White adults aged 18 to 30 years at baseline (1985-1986). The sample included 1133 women without diabetes at baseline, who had ≥1 singleton births (n=2066) during follow-up, glucose tolerance testing at baseline and up to 5 times during 25 years (1986-2011), GD status, and CAC measurements obtained from 1 or more follow up examinations at years 15, 20, and 25 (2001-2011). CAC was measured by noncontrast cardiac computed tomography; dichotomized as Any CAC (score>0) or No CAC (score=0). Complementary log-log models for interval-censored data estimated adjusted hazard ratios of CAC and 95% confidence intervals for GD history and subsequent glucose tolerance groups (normoglycemia, prediabetes, or incident diabetes) on average 14.7 years after the last birth adjusted for prepregnancy and follow-up covariates.

RESULTS

Of 1133 women, 139 (12.3%) reported GD and were 47.6 years of age (4.8 SD) at follow-up. CAC was present in 25% (34/139) of women with GD and 15% (149/994) of women with no GD. In comparison with no GD/normoglycemia, adjusted hazard ratios (95% CIs) were 1.54 (1.06-2.24) for no GD/prediabetes and 2.17 (1.30-3.62) for no GD/incident diabetes, and 2.34 (1.34-4.09), 2.13 (1.09-4.17), and 2.02 (0.98-4.19) for GD/normoglycemia, GD/prediabetes, and GD/incident diabetes, respectively (overall P=0.003).

CONCLUSIONS

Women without previous GD showed a graded increase in the risk of CAC associated with worsening glucose tolerance. Women with a history of GD had a 2-fold higher risk of CAC across all subsequent levels of glucose tolerance. Midlife atherosclerotic CVD risk among women with previous GD is not diminished by attaining normoglycemia.

Costs and effects of cardiovascular risk reclassification using the ankle-brachial index (ABI) in addition to the Framingham risk scoring in women

BACKGROUND AND AIMS

Ankle brachial index (ABI) is a simple and cheap parameter to assess the presence of atherosclerosis. It could also help correctly reclassify the cardiovascular risk when added to the Framingham risk score (FRS). Recent evidence has demonstrated improvement in prediction performance of ABI when added to FRS, particularly in women. However, no studies have been published yet evaluating the cost-effectiveness of this approach. This study attempts to fill in this gap by assessing the cost-effectiveness of ABI measurements in primary prevention in women.

METHODS

We developed a Markov model to compare two different strategies for assessing the cardiovascular risk (low, intermediate and high) among women in the general population: 1) FRS strategy, and 2) FRS + ABI strategy; and the relative impact associated with interventions for preventing CV events in intermediate and high-risk categories.

RESULTS

In the base-case analysis, FRS + ABI reported an additional cost of € 110 and a gain of 0.0039 QALYs per patient, resulting in an ICER of € 27.986/QALY, when compared to FRS alone. The ICER improved to €1.641/QALY when using a lifetime horizon. The effectiveness of preventive CV disease interventions reported also a significant impact. A 32% reduction of CV events was the minimum value estimated to maintain FRS + ABI as a cost-effective strategy.

CONCLUSIONS

The addition of ABI to FRS is a cost-effective approach in women classified at low and intermediate risk with FRS only. This new approach gives the possibility to reclassify and allocate them into the appropriate risk group and treatment.

Development and Internal Validation of a Model Predicting Premature Cardiovascular Disease Among Women With Hypertensive Disorders of Pregnancy: A Population-Based Study in Quebec, Canada

Background

Hypertensive disorders of pregnancy (HDP) are associated with an increased risk of premature cardiovascular disease (CVD), but existing cardiovascular prediction models do not adequately capture risks in young women. We developed a model to predict the 10‐year risk of premature CVD and mortality among women who have HDP.

Methods and Results

Using a population‐based cohort of women with HDP who delivered between April 1989 and March 2017 in Quebec, Canada, we developed a 10‐year CVD risk model using Cox proportional hazards regression. Women aged 18 to 45 years were followed from their first HDP‐complicated delivery until March 2018. We assessed performance of the model based on discrimination, calibration, and risk stratification ability. Internal validity was assessed using the bootstrap method. The cohort included 95 537 women who contributed 1 401 084 person‐years follow‐up. In total, 4024 (4.2%) of women were hospitalized for CVD, of which 1585 events (1.6%) occurred within 10 years of follow‐up. The final model had modest discriminatory performance (area under the receiver operating characteristic curve, 0.66; 95% CI, 0.65–0.67) and good calibration with slope of 0.95 and intercept of −0.19. There was moderate classification accuracy (likelihood ratio+: 5.90; 95% CI, 5.01–6.95) in the highest‐risk group upon risk stratification.

Conclusions

Overall, our model had modest performance in predicting the 10‐year risk of premature CVD for women with HDP. We recommend the addition of clinical variables, and external validation, before consideration for clinical use.

Association between the reproductive health of young women and cardiovascular disease in later life: umbrella review

OBJECTIVE

To consolidate evidence from systematic reviews and meta-analyses investigating the association between reproductive factors in women of reproductive age and their subsequent risk of cardiovascular disease.

DESIGN

Umbrella review.

DATA SOURCES

Medline, Embase, and Cochrane databases for systematic reviews and meta-analyses from inception until 31 August 2019.

REVIEW METHODS

Two independent reviewers undertook screening, data extraction, and quality appraisal. The population was women of reproductive age. Exposures were fertility related factors and adverse pregnancy outcomes. Outcome was cardiovascular diseases in women, including ischaemic heart disease, heart failure, peripheral arterial disease, and stroke.

RESULTS

32 reviews were included, evaluating multiple risk factors over an average follow-up period of 7-10 years. All except three reviews were of moderate quality. A narrative evidence synthesis with forest plots and tabular presentations was performed. Associations for composite cardiovascular disease were: twofold for pre-eclampsia, stillbirth, and preterm birth; 1.5-1.9-fold for gestational hypertension, placental abruption, gestational diabetes, and premature ovarian insufficiency; and less than 1.5-fold for early menarche, polycystic ovary syndrome, ever parity, and early menopause. A longer length of breastfeeding was associated with a reduced risk of cardiovascular disease. The associations for ischaemic heart disease were twofold or greater for pre-eclampsia, recurrent pre-eclampsia, gestational diabetes, and preterm birth; 1.5-1.9-fold for current use of combined oral contraceptives (oestrogen and progesterone), recurrent miscarriage, premature ovarian insufficiency, and early menopause; and less than 1.5-fold for miscarriage, polycystic ovary syndrome, and menopausal symptoms. For stroke outcomes, the associations were twofold or more for current use of any oral contraceptive (combined oral contraceptives or progesterone only pill), pre-eclampsia, and recurrent pre-eclampsia; 1.5-1.9-fold for current use of combined oral contraceptives, gestational diabetes, and preterm birth; and less than 1.5-fold for polycystic ovary syndrome. The association for heart failure was fourfold for pre-eclampsia. No association was found between cardiovascular disease outcomes and current use of progesterone only contraceptives, use of non-oral hormonal contraceptive agents, or fertility treatment.

CONCLUSIONS

From menarche to menopause, reproductive factors were associated with cardiovascular disease in women. In this review, presenting absolute numbers on the scale of the problem was not feasible; however, if these associations are causal, they could account for a large proportion of unexplained risk of cardiovascular disease in women, and the risk might be modifiable. Identifying reproductive risk factors at an early stage in the life of women might facilitate the initiation of strategies to modify potential risks. Policy makers should consider incorporating reproductive risk factors as part of the assessment of cardiovascular risk in clinical guidelines.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42019120076.

Variations between women and men in risk factors, treatments, cardiovascular disease incidence, and death in 27 high-income, middle-income, and low-income countries (PURE): a prospective cohort study

BACKGROUND

Some studies, mainly from high-income countries (HICs), report that women receive less care (investigations and treatments) for cardiovascular disease than do men and might have a higher risk of death. However, very few studies systematically report risk factors, use of primary or secondary prevention medications, incidence of cardiovascular disease, or death in populations drawn from the community. Given that most cardiovascular disease occurs in low-income and middle-income countries (LMICs), there is a need for comprehensive information comparing treatments and outcomes between women and men in HICs, middle-income countries, and low-income countries from community-based population studies.

METHODS

In the Prospective Urban Rural Epidemiological study (PURE), individuals aged 35-70 years from urban and rural communities in 27 countries were considered for inclusion. We recorded information on participants' sociodemographic characteristics, risk factors, medication use, cardiac investigations, and interventions. 168 490 participants who enrolled in the first two of the three phases of PURE were followed up prospectively for incident cardiovascular disease and death.

FINDINGS

From Jan 6, 2005 to May 6, 2019, 202 072 individuals were recruited to the study. The mean age of women included in the study was 50·8 (SD 9·9) years compared with 51·7 (10) years for men. Participants were followed up for a median of 9·5 (IQR 8·5-10·9) years. Women had a lower cardiovascular disease risk factor burden using two different risk scores (INTERHEART and Framingham). Primary prevention strategies, such as adoption of several healthy lifestyle behaviours and use of proven medicines, were more frequent in women than men. Incidence of cardiovascular disease (4·1 [95% CI 4·0-4·2] for women vs 6·4 [6·2-6·6] for men per 1000 person-years; adjusted hazard ratio [aHR] 0·75 [95% CI 0·72-0·79]) and all-cause death (4·5 [95% CI 4·4-4·7] for women vs 7·4 [7·2-7·7] for men per 1000 person-years; aHR 0·62 [95% CI 0·60-0·65]) were also lower in women. By contrast, secondary prevention treatments, cardiac investigations, and coronary revascularisation were less frequent in women than men with coronary artery disease in all groups of countries. Despite this, women had lower risk of recurrent cardiovascular disease events (20·0 [95% CI 18·2-21·7] versus 27·7 [95% CI 25·6-29·8] per 1000 person-years in men, adjusted hazard ratio 0·73 [95% CI 0·64-0·83]) and women had lower 30-day mortality after a new cardiovascular disease event compared with men (22% in women versus 28% in men; p<0·0001). Differences between women and men in treatments and outcomes were more marked in LMICs with little differences in HICs in those with or without previous cardiovascular disease.

INTERPRETATION

Treatments for cardiovascular disease are more common in women than men in primary prevention, but the reverse is seen in secondary prevention. However, consistently better outcomes are observed in women than in men, both in those with and without previous cardiovascular disease. Improving cardiovascular disease prevention and treatment, especially in LMICs, should be vigorously pursued in both women and men.

FUNDING

Full funding sources are listed at the end of the paper (see Acknowledgments).