Predictors of congestive heart failure in the elderly: the Cardiovascular Health Study

Global epidemiology of heart failure

Heart failure (HF) is a heterogeneous clinical syndrome marked by substantial morbidity and mortality. The natural history of HF is well established; however, epidemiological data are continually evolving owing to demographic shifts, advances in treatment and variations in access to health care. Although the incidence of HF has stabilized or declined in high-income countries over the past decade, its prevalence continues to increase, driven by an ageing population, an increase in risk factors, the effectiveness of novel therapies and improved survival. This rise in prevalence is increasingly noted among younger adults and is accompanied by a shift towards HF with preserved ejection fraction. However, disparities exist in our epidemiological understanding of HF burden and progression in low-income and middle-income countries owing to the lack of comprehensive data in these regions. Therefore, the current epidemiological landscape of HF highlights the need for periodic surveillance and resource allocation tailored to geographically vulnerable areas. In this Review, we highlight global trends in the burden of HF, focusing on the variations across the spectrum of left ventricular ejection fraction. We also discuss evolving population-based estimates of HF incidence and prevalence, the risk factors for and aetiologies of this disease, and outcomes in different geographical regions and populations.

A normal and particularly small (<35 mm) left atrial size measured during echocardiography suggests low likelihood of moderate or severe left ventricular systolic dysfunction

INTRODUCTION

The left atrium (LA) size can change due to cardiac pathologies like heart failure and aging. While the link between LA enlargement and left ventricular (LV) dysfunction is acknowledged, this study aims to assess the negative predictive value of normal LA size concerning the severity of LV systolic function in a large cohort undergoing diagnostic echocardiography.

METHODS

This retrospective cohort study, conducted at the University of California, Irvine Medical Center from 1984 to 1998, aimed to elucidate the negative predictive value of normal LA size measured by M-mode and two-dimensional echocardiography in a large cohort undergoing diagnostic assessment.

RESULTS

In the analysis of 22,390 echocardiograms, 55.1% exhibited normal LA size (<40 mm), while 44.9% showed abnormal LA size (≥40 mm). Within the normal LA size group, only 2.4% demonstrated abnormal LV systolic function, with 1.1% mildly depressed, 0.7% moderately depressed, and 0.6% severely depressed LV function. The negative predictive value of normal LA size for abnormal LV systolic function was calculated at 97.5%, rising to 99.3% and 99.4% for moderate or severely decreased LV systolic function, respectively. In patients with small LA size (<35 mm), moderate to severely depressed LV systolic function was observed in only 0.8%, with severe LV systolic dysfunction in 0.3%, yielding an overall prevalence of 1.5% for all systolic dysfunction in the small LA size group.

CONCLUSION

Our findings underscore the clinical significance of normal LA size as a reliable indicator of preserved LV function.

A Kernel Attention-based Transformer Model for Survival Prediction of Heart Disease Patients

Survival analysis is employed to scrutinize time-to-event data, with emphasis on comprehending the duration until the occurrence of a specific event. In this article, we introduce two novel survival prediction models: CosAttnSurv and CosAttnSurv + DyACT. CosAttnSurv model leverages transformer-based architecture and a softmax-free kernel attention mechanism for survival prediction. Our second model, CosAttnSurv + DyACT, enhances CosAttnSurv with Dynamic Adaptive Computation Time (DyACT) control, optimizing computation efficiency. The proposed models are validated using two public clinical datasets related to heart disease patients. When compared to other state-of-the-art models, our models demonstrated an enhanced discriminative and calibration performance. Furthermore, in comparison to other transformer architecture-based models, our proposed models demonstrate comparable performance while exhibiting significant reduction in both time and memory requirements. Overall, our models offer significant advancements in the field of survival analysis and emphasize the importance of computationally effective time-based predictions, with promising implications for medical decision-making and patient care.

Prevalence and incidence of heart failure in type 2 diabetes patients: results from a nationwide prospective cohort-the DIABET-IC study

BACKGROUND

Type 2 diabetes (T2D) patients have an increased risk of heart failure (HF). There are limited data on the association between HF and T2D in specific healthcare settings. This study sought to analyse the prevalence and incidence of HF in a contemporary cohort of T2D patients attending cardiology and endocrinology outpatient clinics.

METHODS

We conducted an observational multicentre prospective study (DIABET-IC) that enrolled patients with a T2D diagnosis attending cardiology and endocrinology outpatient clinics in 30 centres in Spain between 2018 and 2019. The prevalence at the start of the study and the incidence of HF after a 3 year follow-up were calculated. HF was defined as the presence of typical symptoms and either: a) LVEF < 40%; or b) LVEF ≥ 40% with elevated natriuretic peptides and echocardiographic abnormalities.

RESULTS

A total of 1249 T2D patients were included in the present analysis (67.6 ± 10.1 years, 31.7% female). HF was present in 490 participants at baseline (prevalence 39.2%), 150 (30.6%) of whom had a preserved ejection fraction. The presence of adverse social determinants and chronic conditions such as chronic kidney disease and atherosclerotic cardiovascular disease were more frequent in HF patients. During the study period, there were 58 new diagnoses of HF (incidence 7.6%) among those without baseline HF. The incidence rate was 3.0 per 100 person-years. Independent predictors of incident HF were smoking, left ventricular ejection fraction, NT-ProBNP, history of tachyarrhythmia and treatment with pioglitazone, oral anticoagulants, or diuretics. Despite an average suboptimal glycaemic control, the use of antidiabetic drugs with cardiovascular benefits was low (30.4% for sodium-glucose cotransporter-2 inhibitors and 12.5% for glucagon-like peptide-1 receptor agonists).

CONCLUSIONS

In this contemporary cohort of T2D patients attending cardiology and endocrinology outpatient clinics, the prevalence and incidence of HF were high, comorbidities were frequent, and the use of antidiabetic agents with cardiovascular benefit was low. Outpatient care seems to be a unique opportunity for a comprehensive T2D approach that encompasses HF prevention, diagnosis, and treatment.

Prognostic Implications of Insulin Resistance in Heart Failure in Japan

Diabetes mellitus (DM) is a major risk and prognostic factor for heart failure (HF). Insulin resistance (IR) is an important component of DM, but the relationship between IR and HF prognosis has not yet been established across a wide variety of HF populations. We retrospectively evaluated the relationship between IR and clinical outcomes of HF patients at our hospital between 2017 and 2021. IR was defined as a homeostatic model assessment of IR (HOMA-IR) index ≥ 2.5, calculated from fasting blood glucose and insulin concentrations. The primary outcome was a composite of all-cause death and hospitalisation for HF (HHF). Among 682 patients included in the analyses, 337 (49.4%) had IR. The median age was 70 [interquartile range (IQR): 59-77] years old, and 66% of the patients were men. Among the patients, 41% had a left ventricular ejection fraction below 40%, and 32% had DM. The median follow-up period was 16.5 [IQR: 4.4-37.3] months. IR was independently associated with the primary outcome (HR: 1.91, 95% CI: 1.39-2.62, p < 0.0001), death (hazard ratio [HR]: 1.86, 95% confidence interval [CI]: 1.28-2.83, p < 0.01), and HHF (HR: 1.91, 95% CI: 1.28-2.83, p < 0.01). HOMA-IR is an independent prognostic factor of HF in a wide variety of HF populations.

Temporal trends on the prevalence of renal disease and outcomes among patients with diabetes mellitus hospitalized by heart failure: findings from INCAex

BACKGROUND

To assess 20-year time trends in the prevalence of diabetes mellitus (DM) among inpatients with heart failure (HF) and the influence of coexisting DM and kidney disease (KD) on outcomes.

RESEARCH DESIGN AND METHODS

A retrospective study of patients was admitted due to HF, during the period 2000/2019. The period of follow-up was divided into three intervals according to the European Medical Agency approval of newer hypoglycemic drugs. We analyzed in-hospital mortality and outcomes during the follow-up period.

RESULTS

A total of 4959 patients were included. Over time, prevalence of DM was significantly raising among women with HF (50 to 53.2%) and descending among men (50% to 46.8%, p = 0.02). Total mortality and readmissions were higher in patients with DM during the and second periods. However, no significant differences were found in the third-one (HR 1.14, 95% CI 0.94-1.39, p = 0.181). A protector role of oral hypoglycemic medications was observed in this last period. According to the presence of KD, the patients with both DM and KD were who presented most of the events.

CONCLUSIONS

Over the time analyzed, the prevalence of DM raised among women and decreased among men. DM influenced the prognosis of HF except in the third period when more protective hypoglycemic drugs started to be used.

Sex and age significantly modulate cardiovascular disease presentation in type 2 diabetes: a large population-based cohort study

Aims

We aimed to describe and compare the incidence of the first cardiovascular event and its major subtypes, coronary heart disease (CHD), cerebrovascular disease, heart failure (HF), or peripheral artery disease (PAD), according to age and sex in a population-based cohort of individuals with type 2 diabetes (T2D) from a Mediterranean region.

Material and methods

We used linked primary care electronic medical reports, pharmacy-invoicing data, and hospital admission disease registry records from the SIDIAP database, which contains linked data for 74% of the Catalonian population. We selected individuals with T2D aged 30 to 89 years free of cardiovascular disease (CVD). The primary outcome was the first presentation of CVD.

Results

The study cohort included 247,751 individuals (48.6% women, 66.8 ± 11.9 years). During a 6.99-year follow-up, the cumulative incidence of the first cardiovascular event was 23.4%. Men were at higher risk for CVD (hazard ratio [HR]: 1.47 95%CI: 1.45-1.50), CHD (HR: 1.52 95%CI: 1.47-1.57), cerebrovascular disease (HR:1.07 95%CI: 1.03-1.10) and PAD (HR: 2.30 95%CI: 2.21-2.39) than women but at a lower risk for HF (HR:0.70 95%CI: 0.68-0.73). CHD and PAD were the most frequent CVD presentations among men (28.1% and 27.5%) and HF (40.1%) in women. CHD predominated among young participants of both sexes, while HF predominated among women older than 65 and men older than 75.

Conclusions

In individuals with T2D, the overall risk and the type of first CVD manifestation largely varied by sex and age. This epidemiological evidence should be considered in clinical practice.

Blood pressure, hypertension, and the risk of heart failure: a systematic review and meta-analysis of cohort studies

AIMS

Several observational studies have investigated the association between hypertension or elevated systolic blood pressure and diastolic blood pressure and risk of heart failure, but not all the studies have been consistent. This systematic review and meta-analysis aimed to summarize the available data from cohort studies on the association between hypertension, systolic and diastolic blood pressure, and the risk of heart failure.

METHODS AND RESULTS

PubMed and Embase databases were searched for relevant articles from inception to 10 June 2022. Cohort studies on hypertension or blood pressure and heart failure were included. Random effect models were used to calculate summary relative risks (RRs) and 95% confidence intervals (CIs) for the association between hypertension or blood pressure and heart failure. Forty-seven cohort studies were included. The summary RR was 1.71 (95% CI: 1.53-1.90, I2 = 98.4%) for hypertension vs. no hypertension (n = 43 studies, 166 798 cases, 20 359 997 participants), 1.28 (95% CI: 1.22-1.35, I2 = 90.3%) per 20 mmHg of systolic blood pressure (24 studies, 31 639 cases and 2 557 975 participants), and 1.12 (95% CI: 1.04-1.21, I2 = 92.6%) per 10 mmHg of diastolic blood pressure (16 studies, 23 127 cases and 2 419 972 participants). There was a steeper increase in heart failure risk at higher blood pressure levels and a three- to five-fold increase in RR at around 180/120 mmHg of systolic and diastolic blood pressure compared with 100/60 mmHg, respectively. There was little indication of publication bias across analyses.

CONCLUSION

This meta-analysis suggests a strong positive association between hypertension and systolic and diastolic blood pressure and the risk of heart failure. These results support efforts to reduce blood pressure in the general population to reduce the risk of heart failure.

Optimal Screening for Predicting and Preventing the Risk of Heart Failure Among Adults With Diabetes Without Atherosclerotic Cardiovascular Disease: A Pooled Cohort Analysis

BACKGROUND

The optimal approach to identify individuals with diabetes who are at a high risk for developing heart failure (HF) to inform implementation of preventive therapies is unknown, especially in those without atherosclerotic cardiovascular disease (ASCVD).

METHODS

Adults with diabetes and no HF at baseline from 7 community-based cohorts were included. Participants without ASCVD who were at high risk for developing HF were identified using 1-step screening strategies: risk score (WATCH-DM [Weight, Age, Hypertension, Creatinine, HDL-C, Diabetes Control, QRS Duration, MI, and CABG] ≥12), NT-proBNP (N-terminal pro-B-type natriuretic peptide ≥125 pg/mL), hs-cTn (high-sensitivity cardiac troponin T ≥14 ng/L; hs-cTnI ≥31 ng/L), and echocardiography-based diabetic cardiomyopathy (echo-DbCM; left atrial enlargement, left ventricular hypertrophy, or diastolic dysfunction). High-risk participants were also identified using 2-step screening strategies with a second test to identify residual risk among those deemed low risk by the first test: WATCH-DM/NT-proBNP, NT-proBNP/hs-cTn, NT-proBNP/echo-DbCM. Across screening strategies, the proportion of HF events identified, 5-year number needed to treat and number needed to screen to prevent 1 HF event with an SGLT2i (sodium-glucose cotransporter 2 inhibitor) among high-risk participants, and cost of screening were estimated.

RESULTS

The initial study cohort included 6293 participants (48.2% women), of whom 77.7% without prevalent ASCVD were evaluated with different HF screening strategies. At 5-year follow-up, 6.2% of participants without ASCVD developed incident HF. The 5-year number needed to treat to prevent 1 HF event with an SGLT2i among participants without ASCVD was 43 (95% CI, 29-72). In the cohort without ASCVD, high-risk participants identified using 1-step screening strategies had a low 5-year number needed to treat (22 for NT-proBNP to 37 for echo-DbCM). However, a substantial proportion of HF events occurred among participants identified as low risk using 1-step screening approaches (29% for echo-DbCM to 47% for hs-cTn). Two-step screening strategies captured most HF events (75-89%) in the high-risk subgroup with a comparable 5-year number needed to treat as the 1-step screening approaches (30-32). The 5-year number needed to screen to prevent 1 HF event was similar across 2-step screening strategies (45-61). However, the number of tests and associated costs were lowest for WATCH-DM/NT-proBNP ($1061) compared with other 2-step screening strategies (NT-proBNP/hs-cTn: $2894; NT-proBNP/echo-DbCM: $16 358).

CONCLUSIONS

Selective NT-proBNP testing based on the WATCH-DM score efficiently identified a high-risk primary prevention population with diabetes expected to derive marked absolute benefits from SGLT2i to prevent HF.

Myocardial Calcium Handling in Type 2 Diabetes: A Novel Therapeutic Target

Type 2 diabetes (T2D) is a multisystem disease with rapidly increasing global prevalence. Heart failure has emerged as a major complication of T2D. Dysregulated myocardial calcium handling is evident in the failing heart and this may be a key driver of cardiomyopathy in T2D, but until recently this has only been demonstrated in animal models. In this review, we describe the physiological concepts behind calcium handling within the cardiomyocyte and the application of novel imaging techniques for the quantification of myocardial calcium uptake. We take an in-depth look at the evidence for the impairment of calcium handling in T2D using pre-clinical models as well as in vivo studies, following which we discuss potential novel therapeutic approaches targeting dysregulated myocardial calcium handling in T2D.

Deep Learning Models for Predicting Left Heart Abnormalities From Single-Lead Electrocardiogram for the Development of Wearable Devices

BACKGROUND

Left heart abnormalities are risk factors for heart failure. However, echocardiography is not always available. Electrocardiograms (ECGs), which are now available from wearable devices, have the potential to detect these abnormalities. Nevertheless, whether a model can detect left heart abnormalities from single Lead I ECG data remains unclear.

METHODS AND RESULTS

We developed Lead I ECG models to detect low ejection fraction (EF), wall motion abnormality, left ventricular hypertrophy (LVH), left ventricular dilatation, and left atrial dilatation. We used a dataset comprising 229,439 paired sets of ECG and echocardiography data from 8 facilities, and validated the model using external verification with data from 2 facilities. The area under the receiver operating characteristic curves of our model was 0.913 for low EF, 0.832 for wall motion abnormality, 0.797 for LVH, 0.838 for left ventricular dilatation, and 0.802 for left atrial dilatation. In interpretation tests with 12 cardiologists, the accuracy of the model was 78.3% for low EF and 68.3% for LVH. Compared with cardiologists who read the 12-lead ECGs, the model's performance was superior for LVH and similar for low EF.

CONCLUSIONS

From a multicenter study dataset, we developed models to predict left heart abnormalities using Lead I on the ECG. The Lead I ECG models show superior or equivalent performance to cardiologists using 12-lead ECGs.

Biomarkers for Heart Failure Prediction and Prevention

Heart failure (HF) is a global pandemic affecting over 64 million people worldwide. Its prevalence is on an upward trajectory, with associated increasing healthcare expenditure. Organizations including the American College of Cardiology (ACC) and the American Heart Association (AHA) have identified HF prevention as an important focus. Recently, the ACC/AHA/Heart Failure Society of America (HFSA) Guidelines on heart failure were updated with a new Class IIa, Level of Evidence B recommendation for biomarker-based screening in patients at risk of developing heart failure. In this review, we evaluate the studies that have assessed the various roles and contributions of biomarkers in the prediction and prevention of heart failure. We examined studies that have utilized biomarkers to detect cardiac dysfunction or abnormality for HF risk prediction and screening before patients develop clinical signs and symptoms of HF. We also included studies with biomarkers on prognostication and risk prediction over and above existing HF risk prediction models and studies that address the utility of changes in biomarkers over time for HF risk. We discuss studies of biomarkers to guide management and assess the efficacy of prevention strategies and multi-biomarker and multimodality approaches to improve risk prediction.

Monocyte to high-density lipoprotein cholesterol ratio predicts poor outcomes in ischaemic heart failure patients combined with diabetes: a retrospective study

BACKGROUND

The prevalence of ischaemic heart failure (HF) continues to increase. Diabetes mellitus (DM) concomitant with ischaemic HF increases the risk of major adverse cardiovascular events (MACEs). As a promising predictor for cardiovascular diseases, the predictive value of the monocyte to high-density lipoprotein cholesterol ratio (MHR) for MACE in the ischaemic HF with DM cohort has never been investigated before.

OBJECTIVE

We aimed to investigate the MHR as a predictor for MACE in ischaemic HF patients with DM who underwent percutaneous coronary intervention (PCI).

METHODS

This observational study enrolled 1049 patients with ischaemic HF and DM undergoing PCI from June 2017 to June 2019. The baseline data were collected. MACEs, including all-cause mortality, nonfatal myocardial infarction, and any revascularization, were recorded within the 36-month follow-up. The characteristics and incidence of MACE were analysed in four groups stratified by the quartiles of MHR. The hazard ratio for MACE was analysed with Cox regression models. The incidence of MACE in the four groups was evaluated by Kaplan‒Meier survival analysis. Restricted cubic spline analysis was performed to determine the nonlinear correlation between the MHR and MACE.

RESULTS

After the 36-month follow-up, 407 patients (38.8%) experienced MACEs. The incidence of MACE was significantly higher among patients in the upper MHR quartile than among those in the lower MHR quartiles (23.4% vs. 36.0% vs. 41.4% and 54.6%; P < 0.001, respectively), which was consistent with the Kaplan‒Meier survival analyses (P < 0.0001). A multivariate Cox regression model showed that the MHR was an independent risk factor for MACE after variables were adjusted (adjusted HR: 2.11; 95% CI 1.47-3.03; P < 0.001). Its predictive effects on MACE showed no interaction with hypercholesterolemia (P > 0.05).

CONCLUSION

The MHR was a significant and independent predictor of MACEs in ischaemic HF patients with DM undergoing PCI.

Sex differences in the association between minor nonspecific ST-segment and T-wave abnormalities and coronary artery calcification

BACKGROUND AND AIMS

Although minor nonspecific ST-segment and T-wave abnormalities (NSSTTA) have been associated with adverse cardiovascular outcomes, their relationship with subclinical atherosclerosis remains controversial. Therefore, the associations between electrocardiographic (ECG) abnormalities, including NSSTTA, and coronary artery calcification (CAC) were investigated in this study.

METHODS

This cross-sectional study included 136,461 Korean participants with no known cardiovascular disease or cancer, who underwent a health checkup including ECG and computed tomography to measure the coronary artery calcium score (CACS) by Agatston method between 2010 and 2018. ECG abnormalities were defined in accordance with the Minnesota Code using an automated ECG analysis program. A multinomial logistic regression model was used to calculate prevalence ratios (PRs) with 95% confidence intervals (CI) for each CACS category.

RESULTS

In men, both NSSTTA and major ECG abnormalities were associated with all levels of CACS. The multivariable-adjusted PRs (95% CI) for CACS >400 comparing NSSTTA and major ECG abnormalities to the reference (neither NSSTTA nor major ECG abnormalities) were 1.88 (1.29-2.74) and 1.50 (1.18-1.91), respectively. Women with major ECG abnormalities were more likely to have a CACS of 101-400, the PRs (95% CI) comparing major ECG abnormalities to the reference group was 1.75 (1.18-2.57). NSSTTA were not associated with any CACS level in women.

CONCLUSIONS

NSSTTA and major ECG abnormalities are associated with CAC in men, though NSSTTA were not associated with CAC in women, suggesting that NSSTTA should be considered sex-specific risk factors for coronary artery disease in men, but not in women.

Diuretic-resistant heart failure and the role of ultrafiltration: A proposed protocol

Acute heart failure (HF) decompensation generally manifests with signs and symptoms of congestion that strongly predict poor poor patient outcome. Loop diuretics are the cornerstone of therapy to counteract fluid overload and are widely used for acute management and chronic stabilization of HF. However, a diminished response to loop diuretics is a common problem, affecting the patient's clinical course and potentially prolonging hospitalization. Diuretic resistance is defined as failure to decongest despite appropriate and escalating loop diuretic therapy. We propose a protocol for the management of diuretic resistance. The initial approach should include an assessment of causes of pseudo-diuretic resistance. Adjustments to loop diuretic therapy, such as increasing doses and frequency of administration and sequential nephron blockade, may be successful. For hospitalized patients with progressive disease there are more invasive methods for fluid removal. Switching from oral to intravenous loop diuretics is essential to avoid variable absorption and for symptomatic relief. Extracorporeal ultrafiltration is also an option since this technique is highly effective at removing plasma fluid from blood. While extracorporeal ultrafiltration is an invasive solution, peritoneal dialysis is a home-based, intermittent therapeutic option that can enable efficient management of fluid overload, preventing HF-related hospital admission, and improving quality of life. As a last resort for fluid removal, a peritoneal dialysis regimen should fully exploit its decongestive properties and should be tailored to the patient's characteristics and clinical needs.

Evaluation of plasma sphingolipids as mediators of the relationship between kidney disease and cardiovascular events

BACKGROUND

Sphingolipids are a family of circulating lipids with regulatory and signaling roles that are strongly associated with both eGFR and cardiovascular disease. Patients with chronic kidney disease (CKD) are at high risk for cardiovascular events, and have different plasma concentrations of certain plasma sphingolipids compared to patients with normal kidney function. We hypothesize that circulating sphingolipids partially mediate the associations between eGFR and cardiovascular events.

METHODS

We measured the circulating concentrations of 8 sphingolipids, including 4 ceramides and 4 sphingomyelins with the fatty acids 16:0, 20:0, 22:0, and 24:0, in plasma from 3,463 participants in a population-based cohort (Cardiovascular Health Study) without prevalent cardiovascular disease. We tested the adjusted mediation effects by these sphingolipids of the associations between eGFR and incident cardiovascular disease via quasi-Bayesian Monte Carlo method with 2,000 simulations, using a Bonferroni correction for significance.

FINDINGS

The mean (±SD) eGFR was 70 (±16) mL/min/1.73 m2; 62% of participants were women. Lower eGFR was associated with higher plasma ceramide-16:0 and sphingomyelin-16:0, and lower ceramides and sphingomyelins-20:0 and -22:0. Lower eGFR was associated with risk of incident heart failure and ischemic stroke, but not myocardial infarction. Five of eight sphingolipids partially mediated the association between eGFR and heart failure. The sphingolipids associated with the greatest proportion mediated were ceramide-16:0 (proportion mediated 13%, 95% CI 8-22%) and sphingomyelin-16:0 (proportion mediated 10%, 95% CI 5-17%). No sphingolipids mediated the association between eGFR and ischemic stroke.

INTERPRETATION

Plasma sphingolipids partially mediated the association between lower eGFR and incident heart failure. Altered sphingolipids metabolism may be a novel mechanism for heart failure in patients with CKD.

FUNDING

This study was supported by T32 DK007467 and a KidneyCure Ben J. Lipps Research Fellowship (Dr. Lidgard). Sphingolipid measurements were supported by R01 HL128575 (Dr. Lemaitre) and R01 HL111375 (Dr. Hoofnagle) from the National Heart, Lung, and Blood Institute (NHLBI).

Association between the diagnostic classification of newly diagnosed coronary artery disease and future heart failure development

OBJECTIVE

The first clinical manifestation of coronary artery disease (CAD) varies widely from unheralded myocardial infarction (MI) to mild, incidentally detected disease. The primary objective of this study was to quantify the association between different initial CAD diagnostic classifications and future heart failure.

METHODS

This retrospective study incorporated the electronic health record of a single integrated health care system. Newly diagnosed CAD was classified into a mutually exclusive hierarchy as MI, CAD with coronary artery bypass graft (CABG), CAD with percutaneous coronary intervention, CAD only, unstable angina, and stable angina. An acute CAD presentation was defined when the diagnosis was associated with a hospital admission. New heart failure was identified after the CAD diagnosis.

RESULTS

Among 28 693 newly diagnosed CAD patients, initial presentation was acute in 47% and manifested as MI in 26%. Within 30 days of CAD diagnosis, MI [hazard ratio (HR) = 5.1; 95% confidence interval: 4.1-6.5] and unstable angina (3.2; 2.4-4.4) classifications were associated with the highest heart failure risk (compared to stable angina), as was acute presentation (2.9; 2.7-3.2). Among stable, heart failure-free CAD patients followed on average 7.4 years, initial MI (adjusted HR = 1.6; 1.4-1.7) and CAD with CABG (1.5; 1.2-1.8) were associated with higher long-term heart failure risk, but an initial acute presentation was not (1.0; 0.9-1.0).

CONCLUSION

Nearly 50% of initial CAD diagnoses are associated with hospitalization, and these patients are at high risk of early heart failure. Among stable CAD patients, MI remained the diagnostic classification associated with the highest long-term heart failure risk, however, having an initial acute CAD presentation was not associated with long-term heart failure.

Opportunistic screening for asymptomatic left ventricular dysfunction in type 2 diabetes mellitus

BACKGROUND

International guidelines recommend natriuretic peptide biomarker-based screening for patients at high heart failure (HF) risk to allow early detection. There have been few reports about the incorporation of screening procedure to existing clinical practice.

OBJECTIVE

To implement screening of left ventricular dysfunction in patients with type 2 diabetes mellitus (DM).

METHOD

A prospective screening study at the DM complication screening centre was performed.

RESULTS

Between 2018 and 2019, 1043 patients (age: 63.7±12.4 years; male: 56.3%) with mean glycated haemoglobin of 7.25%±1.34% were recruited. 81.8% patients had concomitant hypertension, 31.1% had coronary artery disease, 8.0% had previous stroke, 5.5% had peripheral artery disease and 30.7% had chronic kidney disease (CKD) stages 3-5. 43 patients (4.1%) had an elevated N-terminal prohormone of brain natriuretic peptide (NT-proBNP) concentration above the age-specific diagnostic thresholds for HF, and 43 patients (4.1%) had newly detected atrial fibrillation (AF). The prevalence of elevated NT-proBNP increased with age from 0.85% in patients aged <50 years to 7.14% in those aged 70-79 years and worsening kidney function from 0.43% in patients with CKD stage 1 to 42.86% in CKD stage 5. In multivariate logistic regression, male gender (OR: 3.67 (1.47-9.16), p = 0.005*), prior stroke (OR: 3.26 (1.38-7.69), p = 0.007*), CKD (p<0.001*) and newly detected AF (OR: 7.02 (2.65-18.57), p<0.001*) were significantly associated with elevated NT-proBNP. Among patients with elevated NT-proBNP, their mean left ventricular ejection fraction (LVEF) was 51.4%±14.7%, and 45% patients had an LVEF <50%.

CONCLUSION

NT-proBNP and ECG screening could be implemented with relative ease to facilitate early detection of cardiovascular complication and improve long-term outcomes.

Heart Diseases of Uncertain Etiology: A New Definition of Heart Failure for Epidemiological Studies

It has been a long time since, in the spectrum of ischemic (IHD) or coronary (CHD) heart diseases, a differentiation was performed between the forms presenting with and those without pain [...].

Impact of Diabetes and Hypertension on Left Ventricular Structure and Function: The Jackson Heart Study

Background Diabetes and hypertension have been associated with adverse left ventricular (LV) remodeling. While they often occur concurrently, their individual effects are understudied. We aimed to assess the independent effects of diabetes and hypertension on LV remodeling in Black adults. Methods and Results The JHS (Jackson Heart Study) participants (n=4143 Black adults) with echocardiographic measures from baseline exam were stratified into 4 groups: neither diabetes nor hypertension (n=1643), only diabetes (n=152), only hypertension (n=1669), or both diabetes and hypertension (n=679). Echocardiographic measures of LV structure and function among these groups were evaluated by multivariable regression adjusting for covariates. Mean age of the participants was 52±1 years, and 63.7% were women. LV mass index was not different in participants with only diabetes compared with participants with neither diabetes nor hypertension (P=0.8). LV mass index was 7.9% (6.0 g/m2) higher in participants with only hypertension and 10.8% (8.1 g/m2) higher in participants with both diabetes and hypertension compared with those with neither (P<0.001). LV wall thickness (relative, posterior, and septal) and brain natriuretic peptide levels in participants with only diabetes were not significantly higher than participants with neither (P>0.05). However, participants with both diabetes and hypertension demonstrated higher LV wall thickness and brain natriuretic peptide levels than participants with neither (P<0.05). Conclusions In this cross-sectional analysis, diabetes was not associated with altered LV structure or function in Black adults unless participants also had hypertension. Our findings suggest hypertension is the main contributor to cardiac structural and functional changes in Black adults with diabetes.

The Prevalence and Risk Factors of Chronic Heart Failure in the Mongolian Population

BACKGROUND

The prevalence of heart failure in the Mongolian population is unknown. Thus, in this study, we aimed to define the prevalence of heart failure in the Mongolian population and to identify significant risk factors for heart failure among Mongolian adults.

METHODS

This population-based study included individuals 20 years and older from seven provinces as well as six districts of the capital city of Mongolia. The prevalence of heart failure was based on the European Society of Cardiology diagnostic criteria.

RESULTS

In total, 3480 participants were enrolled, of which 1345 (38.6%) participants were males, and the median age was 41.0 years (IQR 30-54 years). The overall prevalence of heart failure was 4.94%. Patients with heart failure had significantly higher body mass index, heart rate, oxygen saturation, respiratory rate, and systolic/diastolic blood pressure than patients without heart failure. In the logistic regression analysis, hypertension (OR 4.855, 95% CI 3.127-7.538), previous myocardial infarction (OR 5.117, 95% CI 3.040-9.350), and valvular heart disease (OR 3.872, 95% CI 2.112-7.099) were significantly correlated with heart failure.

CONCLUSIONS

This is the first report on the prevalence of heart failure in the Mongolian population. Among the cardiovascular diseases, hypertension, old myocardial infarction, and valvular heart disease were identified as the three foremost risk factors in the development of heart failure.

Incremental prognostic value of positron emission tomography derived left ventricular mass

BACKGROUND

Left ventricular hypertrophy has been shown to be an independent predictor of outcomes in patients with coronary artery disease (CAD). We aimed to determine the incremental prognostic value of positron emission tomography (PET) derived left ventricular mass (LVM) to clinical variables and myocardial flow reserve (MFR).

METHODS

We included consecutive patients who had clinically indicated PET myocardial perfusion imaging for suspected or established CAD. Patients were followed from the date of PET imaging for major adverse cardiovascular events (MACE, inclusive of all-cause death, non-fatal myocardial infarction, and percutaneous coronary intervention/coronary artery bypass grafting 90 days after imaging).

RESULTS

A total of 2357 patients underwent PET MPI during the study period (47% female, mean age 66 ± 12 years, 87% hypertensive, 47% diabetic, 79% dyslipidemia). After a mean follow-up of 11.6 ± 6.6 months, 141 patients (6.0%, 5.1 per 1000 person-year) experienced MACE (86 D/24 MI/39 PCI/9 CABG). In nested multivariable Cox models, LVM was not independently associated with outcomes (HR 1.00, P = .157) and had no incremental prognostic value (C index: 0.75, P = .571) over MFR and clinical variables.

CONCLUSION

Our analysis shows that LVM provides no independent and incremental prognostic value over MFR and clinical variables.

Association Between Arterial Stiffness and New-Onset Heart Failure: The Kailuan Study

BACKGROUND

Arterial stiffness (AS) was associated with heart failure (HF) in previous studies based on specific populations with small samples and the effects of age and blood pressure on AS were not taken into account. Whether AS was independently associated with new-onset HF in community dwellers has not been fully investigated to date.

METHODS

Individuals who participated in health evaluations and underwent synchronized brachial-ankle pulse wave velocity (baPWV) screening in 2010 to 2019 were included. They were free of HF and atrial fibrillation at baseline. The participants were allocated to 3 groups according to their baPWV values. Normal AS was defined as baPWV <1400 cm/s, borderline AS was defined as 1400≤baPWV<1800 cm/s, and elevated AS was defined as baPWV ≥1800 cm/s. Cox proportional hazard regression was used to calculate hazard ratios with 95% CIs of new-onset HF across different AS groups.

RESULTS

A total of 40 064 participants were enrolled with a mean age of 48.81±12.67 years. During a mean 5.53 years of follow-up, 411 participants developed HF. Compared with the normal AS group, the hazard ratio (95% CI) for incident HF was 1.97 (1.36-2.86) for the borderline AS group and 2.24 (1.49-3.38) for the elevated AS group in the multivariable-adjusted model. For each 1 SD (359 cm/s) increase in baPWV, the hazard ratio (95% CI) for new-onset HF was 1.10 (1.02-1.20).

CONCLUSIONS

AS was positively associated with a higher risk of new-onset HF independently of traditional risk factors, with a dose-responsive effect.

Interconnection between cardiovascular, renal and metabolic disorders: A narrative review with a focus on Japan

Insights from epidemiological, clinical and basic research are illuminating the interplay between metabolic disorders, cardiovascular disease (CVD) and kidney dysfunction, termed cardio-renal-metabolic (CRM) disease. Broadly defined, CRM disease involves multidirectional interactions between metabolic diseases such as type 2 diabetes (T2D), various types of CVD and chronic kidney disease (CKD). T2D confers increased risk for heart failure, which-although well known-has only recently come into focus for treatment, and may differ by ethnicity, whereas atherosclerotic heart disease is a well-established complication of T2D. Many people with T2D also have CKD, with a higher risk in Asians than their Western counterparts. Furthermore, CVD increases the risk of CKD and vice versa, with heart failure, notably, present in approximately half of CKD patients. Molecular mechanisms involved in CRM disease include hyperglycaemia, insulin resistance, hyperactivity of the renin-angiotensin-aldosterone system, production of advanced glycation end-products, oxidative stress, lipotoxicity, endoplasmic reticulum stress, calcium-handling abnormalities, mitochondrial malfunction and deficient energy production, and chronic inflammation. Pathophysiological manifestations of these processes include diabetic cardiomyopathy, vascular endothelial dysfunction, cardiac and renal fibrosis, glomerular hyperfiltration, renal hypoperfusion and venous congestion, reduced exercise tolerance leading to metabolic dysfunction, and calcification of atherosclerotic plaque. Importantly, recognition of the interaction between CRM diseases would enable a more holistic approach to CRM care, rather than isolated treatment of individual conditions, which may improve patient outcomes. Finally, aspects of CRM diseases may differ between Western and East Asian countries such as Japan, a super-ageing country, with potential differences in epidemiology, complications and prognosis that represent an important avenue for future research.

DeepMPM: a mortality risk prediction model using longitudinal EHR data

BACKGROUND

Accurate precision approaches have far not been developed for modeling mortality risk in intensive care unit (ICU) patients. Conventional mortality risk prediction methods can hardly extract the information in longitudinal electronic medical records (EHRs) effectively, since they simply aggregate the heterogeneous variables in EHRs, ignoring the complex relationship and interactions between variables and the time dependence in longitudinal records. Recently deep learning approaches have been widely used in modeling longitudinal EHR data. However, most existing deep learning-based risk prediction approaches only use the information of a single disease, neglecting the interactions between multiple diseases and different conditions.

RESULTS

In this paper, we address this unmet need by leveraging disease and treatment information in EHRs to develop a mortality risk prediction model based on deep learning (DeepMPM). DeepMPM utilizes a two-level attention mechanism, i.e. visit-level and variable-level attention, to derive the representation of patient risk status from patient's multiple longitudinal medical records. Benefiting from using EHR of patients with multiple diseases and different conditions, DeepMPM can achieve state-of-the-art performances in mortality risk prediction.

CONCLUSIONS

Experiment results on MIMIC III database demonstrates that with the disease and treatment information DeepMPM can achieve a good performance in terms of Area Under ROC Curve (0.85). Moreover, DeepMPM can successfully model the complex interactions between diseases to achieve better representation learning of disease and treatment than other deep learning approaches, so as to improve the accuracy of mortality prediction. A case study also shows that DeepMPM offers the potential to provide users with insights into feature correlation in data as well as model behavior for each prediction.

Determination of sources of error and improvement in accuracy of left ventricular mass measurement by echocardiography

Abnormal Left ventricular mass (LVM) prognosticates adverse cardiovascular events. Conventionally, LVM measured by echo assumes a prolate ellipsoid (PE) shape; however, it poorly correlates with reference standard of cardiac magnetic resonance imaging (CMR) derived LVM. PE model assumes LVL = 2 × LVID. We developed a new echo LVM formula based on LV length and tested for accuracy against CMR. A retrospective study of consecutive patients with an echocardiogram and CMR within 3 months. Derivation (n = 170) and validation cohorts (n = 54) were used to test the new formula. Following analysis of correlation of interventricular septum (IVS), LV internal dimension (LVID), posterior wall (PW) and LVL between echo and CMR, a novel paraboloid-shape linear regression (PLR) model was derived. LVM by both models were compared to CMR. Poor correlation observed between actual and assumed LVL (0.52 with CMR; 0.44 with echo). Strong correlation was noted between echo and CMR measured LVL, LVID, IVS (r > 0.80) and a moderate correlation with PW (r = 0.62). Strong correlation of LVL was harnessed to develop PLR model, which significantly decreased paired error in derivation cohort (from 64 ± 42 to 22 ± 21 gm) and validation cohort (from 63 ± 46 to 25 ± 18 gm). Furthermore, it demonstrates significant reduction in absolute, relative errors and variability along with superior correlation in both cohorts. Between echo and CMR, LVL demonstrates one of the best correlation among LV dimensions. The assumption, LVL = 2 × LVID appears inaccurate. PLR model incorporates LVL and significantly improves accuracy, reduces variability of LVM.

Automatic Detection of Left Ventricular Dilatation and Hypertrophy from Electrocardiograms Using Deep Learning

Left ventricular dilatation (LVD) and left ventricular hypertrophy (LVH) are risk factors for heart failure, and their detection improves heart failure screening. This study aimed to investigate the ability of deep learning to detect LVD and LVH from a 12-lead electrocardiogram (ECG). Using ECG and echocardiographic data, we developed deep learning and machine learning models to detect LVD and LVH. We also examined conventional ECG criteria for the diagnosis of LVH. We calculated the area under the receiver operating characteristic (AUROC) curve, sensitivity, specificity, and accuracy of each model and compared the performance of the models. We analyzed data for 18,954 patients (mean age (standard deviation): 64.2 (16.5) years, men: 56.7%). For the detection of LVD, the value (95% confidence interval) of the AUROC was 0.810 (0.801-0.819) for the deep learning model, and this was significantly higher than that of the logistic regression and random forest methods (P < 0.001). The AUROCs for the logistic regression and random forest methods (machine learning models) were 0.770 (0.761-0.779) and 0.757 (0.747-0.767), respectively. For the detection of LVH, the AUROC was 0.784 (0.777-0.791) for the deep learning model, and this was significantly higher than that of the logistic regression and random forest methods and conventional ECG criteria (P < 0.001). The AUROCs for the logistic regression and random forest methods were 0.758 (0.751-0.765) and 0.716 (0.708-0.724), respectively. This study suggests that deep learning is a useful method to detect LVD and LVH from 12-lead ECGs.

Proteomics and Population Biology in the Cardiovascular Health Study (CHS): design of a study with mentored access and active data sharing

BACKGROUND

In the last decade, genomic studies have identified and replicated thousands of genetic associations with measures of health and disease and contributed to the understanding of the etiology of a variety of health conditions. Proteins are key biomarkers in clinical medicine and often drug-therapy targets. Like genomics, proteomics can advance our understanding of biology.

METHODS AND RESULTS

In the setting of the Cardiovascular Health Study (CHS), a cohort study of older adults, an aptamer-based method that has high sensitivity for low-abundance proteins was used to assay 4979 proteins in frozen, stored plasma from 3188 participants (61% women, mean age 74 years). CHS provides active support, including central analysis, for seven phenotype-specific working groups (WGs). Each CHS WG is led by one or two senior investigators and includes 10 to 20 early or mid-career scientists. In this setting of mentored access, the proteomic data and analytic methods are widely shared with the WGs and investigators so that they may evaluate associations between baseline levels of circulating proteins and the incidence of a variety of health outcomes in prospective cohort analyses. We describe the design of CHS, the CHS Proteomics Study, characteristics of participants, quality control measures, and structural characteristics of the data provided to CHS WGs. We additionally highlight plans for validation and replication of novel proteomic associations.

CONCLUSION

The CHS Proteomics Study offers an opportunity for collaborative data sharing to improve our understanding of the etiology of a variety of health conditions in older adults.

Heart Failure With Preserved Ejection Fraction: Heterogeneous Syndrome, Diverse Preclinical Models

Heart failure with preserved ejection fraction (HFpEF) represents one of the greatest challenges facing cardiovascular medicine today. Despite being the most common form of heart failure worldwide, there has been limited success in developing therapeutics for this syndrome. This is largely due to our incomplete understanding of the biology driving its systemic pathophysiology and the heterogeneity of clinical phenotypes, which are increasingly being recognized as distinct HFpEF phenogroups. Development of efficacious therapeutics fundamentally relies on robust preclinical models that not only faithfully recapitulate key features of the clinical syndrome but also enable rigorous investigation of putative mechanisms of disease in the context of clinically relevant phenotypes. In this review, we propose a preclinical research strategy that is conceptually grounded in model diversification and aims to better align with our evolving understanding of the heterogeneity of clinical HFpEF. Although heterogeneity is often viewed as a major obstacle in preclinical HFpEF research, we challenge this notion and argue that embracing it may be the key to demystifying its pathobiology. Here, we first provide an overarching guideline for developing HFpEF models through a stepwise approach of comprehensive cardiac and extra-cardiac phenotyping. We then present an overview of currently available models, focused on the 3 leading phenogroups, which are primarily based on aging, cardiometabolic stress, and chronic hypertension. We discuss how well these models reflect their clinically relevant phenogroup and highlight some of the more recent mechanistic insights they are providing into the complex pathophysiology underlying HFpEF.

Multi-system trajectories and the incidence of heart failure in the Framingham Offspring Study

BACKGROUND

Heart failure is a multi-system disease, with non-cardiac systems playing a key role in disease pathogenesis.

OBJECTIVE

Investigate whether longitudinal multi-system trajectories incrementally predict heart failure risk compared to single-occasion traits.

METHODS

We evaluated 3,412 participants from the Framingham Heart Study Offspring cohort, free of heart failure, who attended examination cycle 5 and at least one examination between 1995-2008 (mean age 67 years, 54% women). We related trajectories for the following organ systems and metabolic functions to heart failure risk using Cox regression: kidney (estimated glomerular filtration rate), lung (forced vital capacity and the ratio of forced expiratory volume in one second/forced vital capacity), neuromotor (gait time), muscular (grip strength), cardiac (left ventricular mass index and heart rate), vascular function (pulse pressure), cholesterol (ratio of total/high-density lipoprotein), adiposity (body mass index), inflammation (C-reactive protein) and glucose homeostasis (hemoglobin A1c). Using traits selected via forward selection, we derived a trajectory risk score and related it to heart failure risk.

RESULTS

We observed 276 heart failure events during a median follow up of 10 years. Participants with the 'worst' multi-system trajectory profile had the highest heart failure risk. A one-unit increase in the trajectory risk score was associated with a 2.72-fold increase in heart failure risk (95% CI 2.21-3.34; p<0.001). The mean c-statistics for models including the trajectory risk score and single-occasion traits were 0.87 (95% CI 0.83-0.91) and 0.83 (95% CI 0.80-0.86), respectively.

CONCLUSION

Incorporating multi-system trajectories reflective of the aging process may add incremental information to heart failure risk assessment when compared to using single-occasion traits.

Cardiovascular Biomarkers: Lessons of the Past and Prospects for the Future

Cardiovascular diseases (CVDs) are a major healthcare burden on the population worldwide. Early detection of this disease is important in prevention and treatment to minimise morbidity and mortality. Biomarkers are a critical tool to either diagnose, screen, or provide prognostic information for pathological conditions. This review discusses the historical cardiac biomarkers used to detect these conditions, discussing their application and their limitations. Identification of new biomarkers have since replaced these and are now in use in routine clinical practice, but still do not detect all disease. Future cardiac biomarkers are showing promise in early studies, but further studies are required to show their value in improving detection of CVD above the current biomarkers. Additionally, the analytical platforms that would allow them to be adopted in healthcare are yet to be established. There is also the need to identify whether these biomarkers can be used for diagnostic, prognostic, or screening purposes, which will impact their implementation in routine clinical practice.

Depressive Symptoms and Incident Heart Failure Risk in the Southern Community Cohort Study

OBJECTIVES

This study aims to examine whether greater frequency of depressive symptoms associates with increased risk of incident heart failure (HF).

BACKGROUND

Depressive symptoms associate with adverse prognosis in patients with prevalent HF. Their association with incident HF is less studied, particularly in low-income and minority individuals.

METHODS

We studied 23,937 Black or White Southern Community Cohort Study participants (median age: 53 years, 70% Black, 64% women) enrolled between 2002 and 2009, without prevalent HF, receiving Centers for Medicare and Medicaid Services coverage. Cox models adjusted for traditional HF risk factors, socioeconomic and behavioral factors, social support, and antidepressant medications were used to quantify the association between depressive symptoms assessed at enrollment via the Center for Epidemiologic Studies Depression Scale (CESD-10) and incident HF ascertained from Centers for Medicare and Medicaid Services International Classification of Diseases-9th Revision (ICD-9) (code: 428.x) and ICD-10 (codes: I50, I110) codes through December 31, 2016.

RESULTS

The median CESD-10 score was 9 (IQR: 5 to 13). Over a median 11-year follow-up, 6,081 (25%) participants developed HF. The strongest correlates of CESD-10 score were antidepressant medication use, age, and socioeconomic factors, rather than traditional HF risk factors. Greater frequency of depressive symptoms associated with increased incident HF risk (per 8-U higher CESD-10 HR: 1.04; 95% CI: 1.00 to 1.09; P = 0.038) without variation by race or sex. The association between depressive symptoms and incident HF varied by antidepressant use (interaction-P = 0.03) with increased risk among individuals not taking antidepressants.

CONCLUSIONS

In this high-risk, low-income, cohort of predominantly Black participants, greater frequency of depressive symptoms significantly associates with higher risk of incident HF.

Real-time exercise reduces impaired cardiac function in breast cancer patients undergoing chemotherapy: A randomized controlled trial

BACKGROUND

Previous studies have reported that chemotherapy results in substantial long-term risk of heart failure. Exercise ameliorates exercise responses and exercise tolerance in patients receiving chemotherapy. The cardioprotective effect of real-time exercise in breast cancer is still unclear.

OBJECTIVES

The aim of the present study was to determine the effect of real-time moderate-to-high-intensity exercise training in women with breast cancer undergoing chemotherapy and to follow up on parameters of cardiac function and exercise capacity at different times. We hypothesized that early moderate-to-high-intensity exercise training has beneficial effects on cardiac function in women with breast cancer undergoing chemotherapy.

METHODS

This was a randomized controlled study that included 32 women randomly allocated into the control or exercise group. Exercise began with the first cycle of chemotherapy, and the training program was maintained during chemotherapy with 2 to 3 sessions per week for 3 months. Patients were instructed to perform moderate-to-high-intensity training with aerobic and resistance training. Outcome measurements were echocardiography and cardiopulmonary exercise test. The primary outcome was the change in left ventricle ejection fraction (LVEF). The secondary outcome was peak oxygen consumption (peak VO2).

RESULTS

The control group showed lower cardiac systolic function than the exercise group [mean (SD) LVEF 62% (2) and 70% (5), P<0.05], reduced cardiac diastolic function, and cardiac hypertrophy at 3, 6 and 12 months after chemotherapy. At 6 months after chemotherapy, the exercise group exhibited relatively higher exercise capacity than controls [mean (SD) VO2 12.1 (2.2) and 13.6 (2.2) mL/kg/min, P<0.05]. The main effect size of the study based on echocardiography outcomes was 0.25 (95% confidence interval 0.23 to 0.27), a medium effect size.

CONCLUSIONS

Moderate-to-high-intensity exercise training in breast cancer patients undergoing chemotherapy may prevent impaired cardiac function.

CLINICAL TRIAL REGISTRATION

https://www.

CLINICALTRIALS

in.th (Identifier TCTR20190330002).

Can chronic kidney disease lead to chronic heart failure, and does worsening chronic heart failure lead to chronic kidney disease progression

PURPOSE OF REVIEW

The objective of this review is to discuss if chronic kidney disease (CKD) leads to chronic heart failure (CHF), and does worsening CHF lead to CKD progression and how a new medication class can modify the risk of both outcomes.

RECENT FINDINGS

Sodium-glucose cotransporter 2 (SGLT2) inhibitors are similarly effective on cardiovascular (CV) - and kidney-related outcomes in the presence of CV and CKD.

SUMMARY

SGLT2 inhibitors can reduce the risk of CHF events and CKD progression, and may have synergistic effects in patients with cardiorenal syndrome.

Fibronectin type III domain-containing 5 improves aging-related cardiac dysfunction in mice

Aging is an important risk factor for cardiovascular diseases, and aging‐related cardiac dysfunction serves as a major determinant of morbidity and mortality in elderly populations. Our previous study has identified fibronectin type III domain‐containing 5 (FNDC5) and its cleaved form, irisin, as the cardioprotectant against doxorubicin‐induced cardiomyopathy. Herein, aging or matched young mice were overexpressed with FNDC5 by adeno‐associated virus serotype 9 (AAV9) vectors, or subcutaneously infused with irisin to uncover the role of FNDC5 in aging‐related cardiac dysfunction. To verify the involvement of nucleotide‐binding oligomerization domain‐like receptor with a pyrin domain 3 (NLRP3) and AMP‐activated protein kinase α (AMPKα), Nlrp3 or Ampkα2 global knockout mice were used. Besides, young mice were injected with AAV9‐FNDC5 and maintained for 12 months to determine the preventive effect of FNDC5. Moreover, neonatal rat cardiomyocytes were stimulated with tumor necrosis factor‐α (TNF‐α) to examine the role of FNDC5 in vitro. We found that FNDC5 was downregulated in aging hearts. Cardiac‐specific overexpression of FNDC5 or irisin infusion significantly suppressed NLRP3 inflammasome and cardiac inflammation, thereby attenuating aging‐related cardiac remodeling and dysfunction. In addition, irisin treatment also inhibited cellular senescence in TNF‐α‐stimulated cardiomyocytes in vitro. Mechanistically, FNDC5 activated AMPKα through blocking the lysosomal degradation of glucagon‐like peptide‐1 receptor. More importantly, FNDC5 gene transfer in early life could delay the onset of cardiac dysfunction during aging process. We prove that FNDC5 improves aging‐related cardiac dysfunction by activating AMPKα, and it might be a promising therapeutic target to support cardiovascular health in elderly populations.

Composite Biomarkers for Assessing Frailty Status in Stable Older Adults With Cardiovascular Disease

Background: The relationship between frailty status and laboratory measurements in cardiovascular disease (CVD) remains unclear. We investigated which laboratory measurements indicated frailty in stable older CVD patients.

Methods and Results: One-hundred thirty-eight stable older CVD patients were evaluated by laboratory measurements, with frailty assessed using the Kihon Checklist (KCL). Laboratory measurements were compared between frail and non-frail groups. Across the entire cohort, mean age was 81.7 years, mean left ventricular ejection fraction was 57.8%, and mean plasma B-type natriuretic peptide was 182 pg/mL. KCL scores were used to divide patients into non-frail (n=43; KCL <8) and frail (n=95; KCL ≥8) groups. Serum iron was significantly lower in the frail than non-frail group (mean [±SD] 61.2±30.3 vs. 89.5±26.1 μg/dL, respectively; P<0.001). Blood urea nitrogen (BUN; 27.3±16.5 vs. 19.7±8.2 mg/dL; P=0.013) and C-reactive protein (CRP; 1.05±1.99 vs. 0.15±0.21 mg/dL; P=0.004) were significantly higher in the frail than non-frail group. Multivariate analysis revealed that serum iron, CRP, and BUN were significant independent predictors of frailty (β=−0.069, 0.917, and 0.086, respectively).

Conclusions: Frailty status was significantly associated with iron, CRP, and BUN in stable older CVD patients. Composite biomarkers (inflammation, iron deficiency, and renal perfusion) may be useful for assessing frailty in these patients.

Race- and Gender-Based Differences in Cardiac Structure and Function and Risk of Heart Failure

BACKGROUND

Although heart failure (HF) risk and cardiac structure/function reportedly differ according to race and gender, limited data exist in late life when risk of HF is highest.

OBJECTIVES

The goal of this study was to evaluate race/gender-based differences in HF risk factors, cardiac structure/function, and incident HF in late life.

METHODS

This analysis included 5,149 HF-free participants from ARIC (Atherosclerosis Risk In Communities), a prospective epidemiologic cohort study, who attended visit 5 (2011-2013) and underwent echocardiography. Participants were subsequently followed up for a median 5.5 years for incident HF/death.

RESULTS

Patients' mean age was 75 ± 5 years, 59% were women, and 20% were Black. Male gender and Black race were associated with lower mean left ventricular ejection fraction. Black race was also associated with greater left ventricular wall thickness and concentricity, differences that persisted after adjusting for cardiovascular comorbidities. After adjusting for cardiovascular comorbidities, men were at higher risk for HF and heart failure with reduced ejection fraction (HFrEF) in Black participants compared with White participants (HF: HR of 2.36 [95% CI: 1.37-4.08] vs 1.16 [95% CI: 0.89-1.51], interaction P = 0.016; HFrEF: HR of 3.70 [95% CI: 1.72-7.95] vs 1.55 [95% CI: 1.01-2.37] respectively, interaction P = 0.039). Black race was associated with a higher incidence of HF overall and HFrEF in men only (HF: 1.65 [95% CI: 1.07-2.53] vs 0.76 [95% CI: 0.49-1.17]; HFrEF: HR of 2.55 [95% CI: 1.46-4.44] vs 0.91 [95% CI: 0.46-1.83]). No race/gender-based differences were observed in risk of incident heart failure with preserved ejection fraction.

CONCLUSIONS

Among older persons free of HF, men and Black participants exhibit worse systolic performance and are at heightened risk for HFrEF, whereas the risk of heart failure with preserved ejection fraction is similar across gender and race groups.

Diabetes Status Modifies the Association Between Different Measures of Obesity and Heart Failure Risk Among Older Adults: A Pooled Analysis of Community-Based NHLBI Cohorts

BACKGROUND

Obesity and diabetes are associated with a higher risk of heart failure (HF). The interrelationships between different measures of adiposity-overall obesity, central obesity, fat mass (FM)-and diabetes status for HF risk are not well-established.

METHODS

Participant-level data from the ARIC study (Atherosclerosis Risk in Communities; visit 5) and the CHS (Cardiovascular Health Study; visit 1) cohorts were obtained from the National Heart, Lung, and Blood Institute Biologic Specimen and Data Repository Information Coordinating Center, harmonized, and pooled for the present analysis, excluding individuals with prevalent HF. FM was estimated in all participants using established anthropometric prediction equations additionally validated using the bioelectrical impedance-based FM in the ARIC subgroup. Incident HF events on follow-up were captured across both cohorts using similar adjudication methods. Multivariable-adjusted Fine-Gray models were created to evaluate the associations of body mass index (BMI), waist circumference (WC), and FM with risk of HF in the overall cohort as well as among those with versus without diabetes at baseline. The population attributable risk of overall obesity (BMI≥30 kg/m²), abdominal obesity (WC>88 and 102 cm in women and men, respectively), and high FM (above sex-specific median) for incident HF was evaluated among participants with and without diabetes.

RESULTS

The study included 10 387 participants (52.9% ARIC; 25.1% diabetes; median age, 74 years). The correlation between predicted and bioelectrical impedance-based FM was high (R²=0.90; n=5038). During a 5-year follow-up, 447 participants developed HF (4.3%). Higher levels of each adiposity measure were significantly associated with higher HF risk (hazard ratio [95% CI] per 1 SD higher BMI=1.15 [1.05, 1.27], WC=1.22 [1.10, 1.36]; FM=1.13 [1.02, 1.25]). A significant interaction was noted between diabetes status and measures of BMI (P interaction=0.04) and WC (P interaction=0.004) for the risk of HF. In stratified analysis, higher measures of each adiposity parameter were significantly associated with higher HF risk in individuals with diabetes (hazard ratio [95% CI] per 1 SD higher BMI=1.29 [1.14-1.47]; WC=1.48 [1.29-1.70]; FM=1.25 [1.09-1.43]) but not those without diabetes, including participants with prediabetes and euglycemia. The population attributable risk percentage of overall obesity, abdominal obesity, and high FM for incident HF was higher among participants with diabetes (12.8%, 29.9%, and 13.7%, respectively) versus those without diabetes (≤1% for each).

CONCLUSIONS

Higher BMI, WC, and FM are strongly associated with greater risk of HF among older adults, particularly among those with prevalent diabetes.

Shared Genetic Architecture and Causal Relationship Between Asthma and Cardiovascular Diseases: A Large-Scale Cross-Trait Analysis

Background: Accumulating evidence has suggested that there is a positive association between asthma and cardiovascular diseases (CVDs), implying a common architecture between them. However, the shared genetic architecture and causality of asthma and CVDs remain unclear.

Methods: Based on the genome-wide association study (GWAS) summary statistics of recently published studies, our study examined the genetic correlation, shared genetic variants, and causal relationship between asthma (N = 127,669) and CVDs (N = 86,995–521,612). Statistical methods included high-definition likelihood (HDL), cross-trait meta-analyses of large-scale GWAS, transcriptome-wide association studies (TWAS), and Mendelian randomization (MR).

Results: First, we observed a significant genetic correlation between asthma and heart failure (HF) (Rg = 0.278, P = 5 × 10⁻⁴). Through cross-trait analyses, we identified a total of 145 shared loci between asthma and HF. Fifteen novel loci were not previously reported for association with either asthma or HF. Second, we mapped these 145 loci to a total of 99 genes whose expressions are enriched in a broad spectrum of tissues, including the seminal vesicle, tonsil, appendix, spleen, skin, lymph nodes, breast, cervix and uterus, skeletal muscle, small intestine, lung, prostate, cardiac muscle, and liver. TWAS analysis identified five significant genes shared between asthma and HF in tissues from the hemic and immune system, digestive system, integumentary system, and nervous system. GSDMA, GSDMB, and ORMDL3 are statistically independent genetic effects from all shared TWAS genes between asthma and HF. Third, through MR analysis, genetic liability to asthma was significantly associated with heart failure at the Bonferroni-corrected significance level. The odds ratio (OR) is 1.07 [95% confidence interval (CI): 1.03–1.12; p = 1.31 × 10⁻³] per one-unit increase in log_e odds of asthma.

Conclusion: These findings provide strong evidence of genetic correlations and causal relationship between asthma and HF, suggesting a shared genetic architecture for these two diseases.

Incorporation of natriuretic peptides with clinical risk scores to predict heart failure among individuals with dysglycaemia

AIMS

To evaluate the performance of the WATCH-DM risk score, a clinical risk score for heart failure (HF), in patients with dysglycaemia and in combination with natriuretic peptides (NPs).

METHODS AND RESULTS

Adults with diabetes/pre-diabetes free of HF at baseline from four cohort studies (ARIC, CHS, FHS, and MESA) were included. The machine learning- [WATCH-DM(ml)] and integer-based [WATCH-DM(i)] scores were used to estimate the 5-year risk of incident HF. Discrimination was assessed by Harrell's concordance index (C-index) and calibration by the Greenwood-Nam-D'Agostino (GND) statistic. Improvement in model performance with the addition of NP levels was assessed by C-index and continuous net reclassification improvement (NRI). Of the 8938 participants included, 3554 (39.8%) had diabetes and 432 (4.8%) developed HF within 5 years. The WATCH-DM(ml) and WATCH-DM(i) scores demonstrated high discrimination for predicting HF risk among individuals with dysglycaemia (C-indices = 0.80 and 0.71, respectively), with no evidence of miscalibration (GND P ≥0.10). The C-index of elevated NP levels alone for predicting incident HF among individuals with dysglycaemia was significantly higher among participants with low/intermediate (<13) vs. high (≥13) WATCH-DM(i) scores [0.71 (95% confidence interval 0.68-0.74) vs. 0.64 (95% confidence interval 0.61-0.66)]. When NP levels were combined with the WATCH-DM(i) score, HF risk discrimination improvement and NRI varied across the spectrum of risk with greater improvement observed at low/intermediate risk [WATCH-DM(i) <13] vs. high risk [WATCH-DM(i) ≥13] (C-index = 0.73 vs. 0.71; NRI = 0.45 vs. 0.17).

CONCLUSION

The WATCH-DM risk score can accurately predict incident HF risk in community-based individuals with dysglycaemia. The addition of NP levels is associated with greater improvement in the HF risk prediction performance among individuals with low/intermediate risk than those with high risk.

Medical therapies for prevention of cardiovascular and renal events in patients with atrial fibrillation and diabetes mellitus

Atrial fibrillation (AF), type 2 diabetes mellitus (DM), and chronic kidney disease (CKD) are three global epidemics with significant effects on morbidity and mortality. Diabetes is a risk factor for AF, and a risk factor for thromboembolism, comorbidity, and mortality when AF is present. The pathophysiology of diabetes-related AF and interrelationships with cardiovascular events and renal events is not fully understood but is in part related to structural, electrical, electromechanical, and autonomic remodelling. The current practice guidelines offer limited recommendations on the management of patients with AF (or risk of AF) and diabetes with its own heterogeneity for the prevention of cardiovascular and renal events. This document discusses possible clinical approaches for these patients. In the last decade, there have been major improvements for the prevention of stroke in AF patients with direct oral anticoagulants, which are preferable to vitamin K antagonists for stroke prevention in DM. Because of the increased risk rate for several cardiovascular adverse events in diabetic patients, a similar relative risk reduction generally translates into greater absolute risk reduction in the diabetic population. Recent trials with non-insulin diabetes drugs using glucagon-like peptide-1 agonists and sodium-glucose cotransporter-2 inhibitors showed a significant reduction for the risk of major adverse cardiovascular events in patients with type 2 DM. Sodium-glucose cotransporter-2 inhibitors also showed a large reduction in hospitalization for heart failure and renal events, which need to be more completely evaluated in patients with AF. Mechanisms, risks, and optimal management of AF patients with DM who have or are under risk of developing heart failure or CKD are also discussed in this document. The benefits of medical therapies for these patients still need to be put into perspective, and gaps in evidence on some of these issues are likely to be addressed in future years.

Neck Stabilization Exercises Enhance Respiratory Function after Stroke: Respiratory Function Index Change Trajectory Analyzed Using a Hierarchical Linear Model

Background and Objectives: This study aimed to assess the effect of neck stabilization exercise on respiratory function in stroke patients through longitudinal observation and determine whether there is a difference in its effect based on the side of paralysis in the patients. It is difficult to observe the amount of change observed in individuals and groups as most intergroup comparison studies only use mean values. To address these shortcomings, this study adopted a hierarchical linear model (HLM) in our trajectory analysis. Materials and Methods: We conducted neck stabilization training three times a week for four weeks in a single group of 21 stroke patients. To evaluate respiratory function, their forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), forced expiration ratio (FEV1/FVC), and peak cough flow (PCF) were measured. Data analysis was performed using HLM 8.0. Results: A significant increase was found in the respiratory function after neck stabilization training (p < 0.05). While neck stabilization training overall was longitudinally effective, the growth rate of respiratory function in left-sided paralytic patients was less than the whole group value. Conversely, the growth rate of respiratory function in right-sided paralytic patients was greater than the whole group value. Conclusions: This study demonstrated that neck stabilization training is longitudinally effective in improving respiratory function in stroke patients. Additionally, the growth rate of respiratory function was greater in patients with right side paralysis than in patients with left side paralysis.

Incidence and Outcomes of Acute Heart Failure With Preserved Versus Reduced Ejection Fraction in SPRINT

BACKGROUND

In the SPRINT (Systolic Blood Pressure Intervention Trial), intensive BP treatment reduced acute decompensated heart failure (ADHF) events. Here, we report the effect on HF with preserved ejection fraction (HFpEF) and HF with reduced EF (HFrEF) and their subsequent outcomes.

METHODS

Incident ADHF was defined as hospitalization or emergency department visit, confirmed, and formally adjudicated by a blinded events committee using standardized protocols. HFpEF was defined as EF ≥45%, and HFrEF was EF <45%.

RESULTS

Among the 133 participants with incident ADHF who had EF assessment, 69 (52%) had HFpEF and 64 (48%) had HFrEF (P value: 0.73). During average 3.3 years follow-up in those who developed incident ADHF, rates of subsequent all-cause and HF hospital readmission and mortality were high, but there were no significant differences between those who developed HFpEF versus HFrEF. Randomization to the intensive arm had no effect on subsequent mortality or readmissions after the initial ADHF event, irrespective of EF subtype. During follow-up among participants who developed HFpEF, although relatively modest number of events limited statistical power, age was an independent predictor of all-cause mortality, and Black race independently predicted all-cause and HF hospital readmission.

CONCLUSIONS

In SPRINT, intensive BP reduction decreased both acute decompensated HFpEF and HFrEF events. After initial incident ADHF, rates of subsequent hospital admission and mortality were high and were similar for those who developed HFpEF or HFrEF. Randomization to the intensive arm did not alter the risks for subsequent all-cause, or HF events in either HFpEF or HFrEF. Among those who developed HFpEF, age and Black race were independent predictors of clinical outcomes. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01206062.

PULSE-HF: A Simple Clinical and Geriatric Score to Predict Systolic Dysfunction in the Elderly Without Heart Failure

To develop a clinical score to determine preclinical predictors of systolic dysfunction in an outpatient elderly population without a diagnosis of heart failure (HF). PULSE-HF is a cross-sectional study in elderly at-risk (coronary artery disease, diabetes or hypertension) outpatients without a diagnosis of heart failure (HF). The objective in this population was to develop a clinical score to determine preclinical predictors of systolic dysfunction. Clinical and geriatric variables were analyzed; independent predictive factors in the logistic regression analysis were included for the score calculation. Of the 722 subjects enrolled, 47 (6.5%) had a left ventricular ejection fraction (LVEF) < 50%, and 15 (2.1%) a LVEF < 40%. Mean age was 76.5 years (5.18) and 445 (61.6%) were female. Multiple logistic regression analysis identified abnormal Q waves (odds ratio [OR]: 4.36; P = 0.003), cardiomegaly (OR: 3.32; P < 0.001), right bundle branch block (OR: 2.84; P = 0.011), cognitive dysfunction (OR: 2.14; P = 0.027) and NT-proBNP (OR 5.43; P < 0.001) as independent predictors of LVEF < 50%. Two prediction scores were built, without and with NT-proBNP inclusion; the area under ROC curves were 0.70 and 0.76, respectively. As the score increased, the sensitivity decreases but increases specificity, and accuracy (97.17% and 91.64% respectively in ≥6 points). NT-proBNP was associated with an increment in the performance (accuracy of 93.18% for score ≥10). We conclude that a simple score using clinical information might be useful to predicting asymptomatic systolic dysfunction in the elderly.

Pulmonary Function Testing Pre-heart Transplant Predicts Posttransplant Survival

Supplemental Digital Content is available in the text.

Although pulmonary function testing (PFT) is typically performed for heart transplant evaluation, the prognostic utility of PFTs after transplantation is unknown. We evaluated whether PFT parameters were correlated with outcomes following heart transplantation.

Mid-aortic syndrome is associated with increased left ventricular mass index in Takayasu arteritis

Background

Mid-aortic syndrome (MAS) may induce changes in cardiac structure among patients with Takayasu arteritis (TA).

Methods

Consecutive adult patients with TA (January 1, 2011 to January 1, 2018) were enrolled and their data was retrospectively analyzed.

Results

Patients were divided into MAS group (100/457 patients, 21.8%) and non-MAS group (357, 78.1%). The left ventricular mass index (LVMI) was higher in the MAS group than the non-MAS (113.78±26.82 versus 100.74±23.66 g/m², respectively; P<0.001). The MAS group showed higher prevalence than the non-MAS group of mild-to-severe mitral regurgitation (9.0% and 3.9%, respectively; P=0.040) and aortic regurgitation (26% and 14.8%, respectively; P=0.003). No difference was found in the rates of heart failure (27.0% and 19.9% for MAS and non-MAS, respectively; P=0.126). The MAS group also showed lower estimated glomerular filtration rates than the non-MAS group (89.93±18.89 versus 96.16±21.60 mL/min/1.73 m², respectively; P=0.009) and higher prevalence of renal artery stenosis (57% versus 43.7%; P=0.018). MAS was independently related to greater LVMI in both unadjusted model [β=12.60; 95% confidence interval (CI): 7.09–18.11; P<0.001] and the model adjusted for multiple indices (β=9.91; 95% CI: 4.57–15.25; P<0.001) in multivariate linear analysis. The LVMI significantly decreased from 111.49±25.65 to 100.36±22.91 g/m² (P<0.001) among 55 patients who underwent successful revascularization treatment for MAS, while no significant difference (P=0.635) was observed among patients treated with medicine alone.

Conclusions

TA-induced MAS is a potential independent risk factor for increased LVMI, and revascularization therapy for MAS is effective in reversing structural changes in the heart.

Incidence, Determinants and Mortality of Heart Failure Associated With Medical-Surgical Procedures in Patients ≥ 65 Years of Age (from the Cardiovascular Health Study)

Heart failure (HF) and myocardial infarction are serious complications of major noncardiac surgery in older adults. Many factors can contribute to the development of HF during the postoperative period. The incidence of, and risk factors for, procedure-associated heart failure (PHF) occurring at the time of, or shortly after, medical procedures in a population-based sample ≥ 65 years of age have not been fully characterized, particularly in comparison with HF not proximate to medical procedures. This analysis comprises 5,121 men and women free of HF at baseline from the Cardiovascular Health Study who were followed up for 12.0 years (median). HF events were documented by self-report at semi-annual contacts and confirmed by a formal adjudication committee using a review of the participants' medical records and standardized criteria for HF. Incident HF events were additionally adjudicated as either being related or unrelated to a medical procedure (PHF and non-PHF, respectively). We estimated cause-specific hazards ratios for the association of covariates with PHF and non-PHF. There were 1,728 incident HF events in the primary analysis: 168 (10%) classified as PHF, 1,526 (88%) as non-PHF, and 34 unclassified (2%). For those 1,045 participants in whom LV ejection fraction was known at the time of the HF event, it was ≥45% in 89 of 118 participants (75%) with PHF, compared to 517 of 927 participants (55%) with non-PHF (p < 0.001). Increased age, male gender, diabetes, and angina at baseline were associated with both PHF and non-PHF (range of hazard ratios (HR): 1.04-2.05]. Being Black was inversely associated with PHF [HR: 0.46, 95% confidence interval: 0.25-0.86]. Participants with increased age, without baseline angina, and with baseline LVEF<55% were at a significantly lower risk for PHF compared to non-PHF. Among those with PHF, surgical procedures-including cardiac, orthopedic, gastrointestinal, vascular, and urologic-comprised 83.3%, while percutaneous procedures comprised 8.9% (including 6.5% represented by cardiac catheterizations and pacemaker placements). Another group composed of a variety of procedures commonly requiring large fluid volume administration comprised 7.7%. There was a lower all-cause 30-day mortality in the PHF versus the non-PHF group (2.2% vs 5.7%), with a nonsignificant odds ratio of 0.39 in a minimally adjusted model. When individuals with prior myocardial infarction (MI) were excluded in a sensitivity analysis, the proportion of incident HF with concurrent MI was greater for PHF (32.9%) than for non-PHF (19.8%). In conclusion, PHF in older adults is a common entity with relatively low 30-day mortality. Baseline angina, lower age, and LVEF ≥ 55% were associated with a higher risk of PHF compared to non-PHF. Being Black was associated with a lower risk of PHF and PHF as a proportion of HF was lower in Black than in non-Black participants. Compared to non-PHF, PHF more frequently presented with concurrent MI and with preserved LV ejection fraction.