Implications of the ACC/AHA risk score for prediction of heart failure: the Rotterdam Study

The Rotterdam Study. Design update and major findings between 2020 and 2024

The Rotterdam Study is a population-based cohort study, started in 1990 in the district of Ommoord in the city of Rotterdam, the Netherlands, with the aim to describe the prevalence and incidence, unravel the etiology, and identify targets for prediction, prevention or intervention of multifactorial diseases in mid-life and elderly. The study currently includes 17,931 participants (overall response rate 65%), aged 40 years and over, who are examined in-person every 3 to 5 years in a dedicated research facility, and who are followed-up continuously through automated linkage with health care providers, both regionally and nationally. Research within the Rotterdam Study is carried out along two axes. First, research lines are oriented around diseases and clinical conditions, which are reflective of medical specializations. Second, cross-cutting research lines transverse these clinical demarcations allowing for inter- and multidisciplinary research. These research lines generally reflect subdomains within epidemiology. This paper describes recent methodological updates and main findings from each of these research lines. Also, future perspective for coming years highlighted.

Predicting incident heart failure from population-based nationwide electronic health records: protocol for a model development and validation study

INTRODUCTION

Heart failure (HF) is increasingly common and associated with excess morbidity, mortality, and healthcare costs. Treatment of HF can alter the disease trajectory and reduce clinical events in HF. However, many cases of HF remain undetected until presentation with more advanced symptoms, often requiring hospitalisation. Predicting incident HF is challenging and statistical models are limited by performance and scalability in routine clinical practice. An HF prediction model implementable in nationwide electronic health records (EHRs) could enable targeted diagnostics to enable earlier identification of HF.

METHODS AND ANALYSIS

We will investigate a range of development techniques (including logistic regression and supervised machine learning methods) on routinely collected primary care EHRs to predict risk of new-onset HF over 1, 5 and 10 years prediction horizons. The Clinical Practice Research Datalink (CPRD)-GOLD dataset will be used for derivation (training and testing) and the CPRD-AURUM dataset for external validation. Both comprise large cohorts of patients, representative of the population of England in terms of age, sex and ethnicity. Primary care records are linked at patient level to secondary care and mortality data. The performance of the prediction model will be assessed by discrimination, calibration and clinical utility. We will only use variables routinely accessible in primary care.

ETHICS AND DISSEMINATION

Permissions for CPRD-GOLD and CPRD-AURUM datasets were obtained from CPRD (ref no: 21_000324). The CPRD ethical approval committee approved the study. The results will be submitted as a research paper for publication to a peer-reviewed journal and presented at peer-reviewed conferences.

TRIAL REGISTRATION DETAILS

The study was registered on Clinical Trials.gov (NCT05756127). A systematic review for the project was registered on PROSPERO (registration number: CRD42022380892).

Relationship between cumulative exposure to triglyceride-glucose index and heart failure: a prospective cohort study

BACKGROUND

High triglyceride-glucose index (TyG) is a major risk factor for heart failure, but the long-term effect of high TyG index on the risk of developing heart failure remains unclear. Therefore, we aimed to determine the relationship between the cumulative exposure to TyG index and the risk of heart failure.

METHODS

A total of 56,149 participants from the Kailuan Study, who participated in three consecutive health examinations in 2006, 2008, and 2010 and had no history of heart failure or cancer were recruited for this study. The cumulative TyG index was calculated as the weighted sum (value × time) of the mean TyG index for each time interval. The participants were placed into quartiles based on their cumulative TyG index. The study ended on December 31, 2020, and the primary outcome was new-onset heart failure during the follow-up period. In addition, a Cox proportional hazards regression model and a restricted cubic spline analysis were used to further evaluate the relationship between cumulative TyG index and the risk of heart failure.

RESULTS

During a median follow-up period of 10.04 years, a total of 1,312 new heart failure events occurred. After adjustment for potential confounding factors, the Cox regression analysis showed that the hazard ratios (95% confidence intervals) for the risk of heart failure in the Q2, Q3, and Q4 groups were 1.02 (0.83,1.25), 1.29 (1.07,1.56) and 1.40 (1.15,1.71), respectively, vs. the Q1 group. The subgroup analysis showed a significant interaction between cumulative TyG index and BMI or waist circumference, but there was no interaction between age, sex and cumulative TyG index. The restricted cubic spline analysis showed a dose-response relationship between cumulative TyG index and the risk of heart failure. In addition, the sensitivity analysis generated results that were consistent with the primary results.

CONCLUSIONS

High cumulative TyG index is associated with a higher risk of heart failure. Thus, the TyG index may be useful for the identification of individuals at high risk of heart failure. The present findings emphasize the importance of the long-term monitoring of the TyG index in clinical practice.

Duration of Diabetes, Glycemic Control, and Risk of Heart Failure Among Adults With Diabetes: A Cohort Study

CONTEXT

The influences of diabetes duration and glycemic control and their potential interplays on the risk of heart failure (HF) remain unclear.

OBJECTIVE

This work aimed to investigate the association of diabetes duration and glycemic control with the risk of HF.

METHODS

A total of 23 754 individuals with diabetes but without HF during the baseline recruitment of UK Biobank were included in this study. Duration of diabetes was self-reported, and the status of glycemic control was reflected by glycated hemoglobin A1c (HbA1c) levels. Their associations with incident HF were assessed using multivariate Cox models adjusting for traditional risk factors.

RESULTS

Duration of diabetes and HbA1c levels both were positively associated with the risk of HF. The hazard ratios (HRs) (95% CI) for diabetes durations of 5 to less than 10, 10 to less than 15, and 15 years or more were 1.09 (0.97-1.23), 1.13 (0.97-1.30), and 1.32 (1.15-1.53), respectively (vs < 5 years); and the HRs for HbA1c of 53.0 to less than 58.5 mmol/mol (7.0% to < 7.5%), 58.5 to less than 63.9 mmol/mol (7.5% to < 8.0%), and 63.9 mmol/mol or greater (8.0%) were 1.15 (1.02-1.31), 1.07 (0.91-1.26), and 1.46 (1.30-1.65), respectively (vs < 53.0 mmol/mol [7.0%]). Individuals with the longest disease duration (≥ 15 years) and poorer glycemic control (HbA1c  ≥ 63.9 mmol/mol [8.0%]) had a particularly higher risk of HF (P for interaction = .026).

CONCLUSION

The risk of HF among individuals with diabetes increases with a longer duration of diabetes and increasing HbA1c levels. This finding may contribute to the individualized prevention of HF in patients with diabetes if being considered in clinical practices and policy-making.

Coronary Artery Computed Tomography Angiography for Preventing Cardio-Cerebrovascular Disease: Observational Cohort Study Using the Observational Health Data Sciences and Informatics' Common Data Model

Background

Cardio-cerebrovascular diseases (CVDs) result in 17.5 million deaths annually worldwide, accounting for 46.2% of noncommunicable causes of death, and are the leading cause of death, followed by cancer, respiratory disease, and diabetes mellitus. Coronary artery computed tomography angiography (CCTA), which detects calcification in the coronary arteries, can be used to detect asymptomatic but serious vascular disease. It allows for noninvasive and quick testing despite involving radiation exposure.

Objective

The objective of our study was to investigate the effectiveness of CCTA screening on CVD outcomes by using the Observational Health Data Sciences and Informatics’ Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) data and the population-level estimation method.

Methods

Using electronic health record–based OMOP-CDM data, including health questionnaire responses, adults (aged 30-74 years) without a history of CVD were selected, and 5-year CVD outcomes were compared between patients undergoing CCTA (target group) and a comparison group via 1:1 propensity score matching. Participants were stratified into low-risk and high-risk groups based on the American College of Cardiology/American Heart Association atherosclerotic cardiovascular disease (ASCVD) risk score and Framingham risk score (FRS) for subgroup analyses.

Results

The 2-year and 5-year risk scores were compared as secondary outcomes between the two groups. In total, 8787 participants were included in both the target group and comparison group. No significant differences (calibration P=.37) were found between the hazard ratios of the groups at 5 years. The subgroup analysis also revealed no significant differences between the ASCVD risk scores and FRSs of the groups at 5 years (ASCVD risk score: P=.97; FRS: P=.85). However, the CCTA group showed a significantly lower increase in risk scores at 2 years (ASCVD risk score: P=.03; FRS: P=.02).

Conclusions

Although we could not confirm a significant difference in the preventive effects of CCTA screening for CVDs over a long period of 5 years, it may have a beneficial effect on risk score management over 2 years.

Serum Levels of Irisin Predict Cumulative Clinical Outcomes in Heart Failure Patients With Type 2 Diabetes Mellitus

Background: The aim of this study was to investigate the role of serum irisin level in predicting clinical outcome in heart failure (HF) patients with type 2 diabetes mellitus (T2DM).

Methods: 153 T2DM patients with HF aged 41–62 years were prospectively recruited for the study. Serum levels of irisin and NT-proBNP were measured by ELISA. Laboratory tests including HbA1c, fasting glucose, blood creatinine, insulin, lipids and creatinine with estimation of GFR were performed along with echocardiography at baseline. The observation period was 56 weeks.

Results: We identified 76 composite cardiovascular (CV) outcomes, which included CV death and death from all causes, resuscitated cardiac death, non-fatal/fatal acute myocardial infarction or stroke, and HF hospitalization. Therefore, the entire patient cohort was divided into 2 groups with (n = 76) and without (n = 77) composite CV outcomes. We found that the concentrations of NT-proBNP were higher in HF patients with T2DM who had a CV composite outcome than in patients without CV composite outcome (p = 0.001). In contrast, the relationship was exactly reversed for irisin, as HF and T2DM patients with CV composite outcome had significantly lower irisin levels (p = 0.001). Unadjusted multivariate Cox regression analyses showed that LVEF &lt; 40%, LAVI &gt; 39 ml/m2, NT-proBNP &gt; 2,250 pmol/ml, and irisin &lt; 6.50 ng/ml were the strongest predictors of CV outcomes in HF patients with T2DM. After adjustment for LVEF, serum levels of NT-proBNP and irisin remained independent predictors of end points. Furthermore, divergence of Kaplan-Meier curves pointed out that patients with NT-proBNP &gt; 2,250 pmol/ml and irisin &lt; 6.50 ng/ml had worse prognosis than those with any other compartment of the bomarkers’ levels.

Conclusion: Adding irisin to NT-proBNP significantly improved discriminative value of the whole model. HF patients with T2DM had significantly worse clinical outcomes when showing the constellation NT-proBNP &gt; 2,250 pmol/ml and irisin &lt; 6.50 ng/ml, respectively, in comparison to patients with opposite trends for both biomarkers.

Systemic Inflammation and Cognitive Decrements in Patients With Stage B Heart Failure

OBJECTIVE

This study aimed to investigate the role of systemic inflammation in reduced cognitive functioning in patients with early-stage heart failure (HF) while determining associations with other cardiovascular risk factors.

METHODS

Patients with stage B HF (n = 270; mean [standard deviation] age = 66.1 [10.1] years) were examined cross-sectionally for relationships among cardiovascular disease (CVD) and psychological risk factors, C-reactive protein (CRP), and Montreal Cognitive Assessment (MoCA) scores. A subsample (n = 83) at high risk for stage C HF (B-type natriuretic peptide levels ≥65 pg/ml) were followed up for 12 months for relationships between CRP levels and cognitive function.

RESULTS

Baseline smoking (χ2 = 6.33), unmarried (χ2 = 12.0), hypertension (χ2 = 5.72), greater body mass index (d = 0.45), and physical fatigue (d = 0.25) were related to higher CRP levels (p values < .05). Cross-sectionally, CRP levels were negatively related to MoCA scores, beyond CVD (ΔR2 = 0.022, β = -0.170, p < .010) and psychological risk factors (ΔR2 = 0.016, β = 0.145, p < .027), and related to mild cognitive impairment criteria (odds ratio = 1.35, 95% confidence interval [CI] = 1.00-1.81, p = .046). Across 12 months, B-type natriuretic peptide high-risk patients with CRP levels ≥3 mg/L had lower MoCA scores (23.6; 95% CI = 22.4-24.8) than did patients with CRP levels <3 mg/L (25.4; 95% CI = 24.4-26.5; p = .024).

CONCLUSIONS

Patients with stage B HF and heightened CRP levels had greater cognitive impairment at baseline and follow-up, independent of CVD and potentially psychological risk factors. Low-grade systemic inflammation may be one mechanism involved in cognitive dysfunction at early stages of HF.