Chronic Kidney Disease as a Comorbidity in Heart Failure

Estimated Glomerular Filtration Rate Slope as an Endpoint in Cardiovascular Trials

PURPOSE OF REVIEW

End stage kidney disease can be a slow process and it may be challenging to achieve required follow-up for sufficient events. Therefore, a surrogate kidney endpoint, such as estimated glomerular filtration rate (eGFR) slope maybe attractive to assess the kidney in cardiovascular trials, especially heart failure (HF).

RECENT FINDINGS

eGFR slope can generate informative results in a shorter follow-up period, has decreased risk of type-2 error, and is less sensitive to eGFR shifts compared with other surrogate kidney endpoints (eGFR decline≥40% or doubling creatinine). However, eGFR slope has its limitations with acute effects, heterogeneity in slope calculation/reporting, and deviations from linearity. eGFR slope is a kidney endpoint which may be well-suited for HF trials. Cross-collaborated guideline recommendations are needed to optimize the use of eGFR slope as a kidney endpoint in patients with HF.

Machine Learning-Based Mortality Prediction in Chronic Kidney Disease among Heart Failure Patients: Insights and Outcomes from the Jordanian Heart Failure Registry

Background and Objectives: Heart failure (HF) is a prevalent and debilitating condition that imposes a significant burden on healthcare systems and adversely affects the quality of life of patients worldwide. Comorbidities such as chronic kidney disease (CKD), arterial hypertension, and diabetes mellitus (DM) are common among HF patients, as they share similar risk factors. This study aimed to identify the prognostic significance of multiple factors and their correlation with disease prognosis and outcomes in a Jordanian cohort. Materials and Methods: Data from the Jordanian Heart Failure Registry (JoHFR) were analyzed, encompassing medical records from acute and chronic HF patients attending public and private cardiology clinics and hospitals across Jordan. An online form was utilized for data collection, focusing on three kidney function tests, estimated glomerular filtration rate (eGFR), blood urea nitrogen (BUN), and creatinine levels, with the eGFR calculated using the Cockcroft-Gault formula. We also built six machine learning models to predict mortality in our cohort. Results: From the JoHFR, 2151 HF patients were included, with 644, 1799, and 1927 records analyzed for eGFR, BUN, and creatinine levels, respectively. Age negatively impacted all measures (p ≤ 0.001), while smokers surprisingly showed better results than non-smokers (p ≤ 0.001). Males had more normal eGFR levels compared to females (p = 0.002). Comorbidities such as hypertension, diabetes, arrhythmias, and implanted devices were inversely related to eGFR (all with p-values <0.05). Higher BUN levels were associated with chronic HF, dyslipidemia, and ASCVD (p ≤ 0.001). Higher creatinine levels were linked to hypertension, diabetes, dyslipidemia, arrhythmias, and previous HF history (all with p-values <0.05). Low eGFR levels were associated with increased mechanical ventilation needs (p = 0.049) and mortality (p ≤ 0.001), while BUN levels did not significantly affect these outcomes. Machine learning analysis employing the Random Forest Classifier revealed that length of hospital stay and creatinine >115 were the most significant predictors of mortality. The classifier achieved an accuracy of 90.02% with an AUC of 80.51%, indicating its efficacy in predictive modeling. Conclusions: This study reveals the intricate relationship among kidney function tests, comorbidities, and clinical outcomes in HF patients in Jordan, highlighting the importance of kidney function as a predictive tool. Integrating machine learning models into clinical practice may enhance the predictive accuracy of patient outcomes, thereby supporting a more personalized approach to managing HF and related kidney dysfunction. Further research is necessary to validate these findings and to develop innovative treatment strategies for the CKD population within the HF cohort.

Educational status affects prognosis of patients with heart failure with reduced ejection fraction: A post-hoc analysis from the WARCEF trial

AIMS

The influence of social determinants of health (SDOH) on the prognosis of Heart Failure and reduced Ejection Fraction (HFrEF) is increasingly reported. We aim to evaluate the contribution of educational status on outcomes in patients with HFrEF.

METHODS

We used data from the WARCEF trial, which randomized HFrEF patients with sinus rhythm to receive Warfarin or Aspirin; educational status of patients enrolled was collected at baseline. We defined three levels of education: low, medium and high level, according to the highest qualification achieved or highest school grade attended. We analysed the impact of the educational status on the risk of the primary composite outcome of all-cause death, ischemic stroke (IS) and intracerebral haemorrhage (ICH); components of the primary outcome were also analysed as secondary outcomes.

RESULTS

2295 patients were included in this analysis; of these, 992 (43.2%) had a low educational level, 947 (41.3%) had a medium education level and the remaining 356 (15.5%) showed a high educational level. Compared to patients with high educational level, those with low educational status showed a high risk of the primary composite outcome (adjusted hazard ratio [aHR]: 1.31, 95% confidence intervals [CI] 1.02-1.69); a non-statistically significant association was observed in those with medium educational level (aHR: 1.20, 95%CI: .93-1.55). Similar results were observed for all-cause death, while no statistically significant differences were observed for IS or ICH.

CONCLUSION

Compared to patients with high educational levels, those with low educational status had worse prognosis. SDOH should be considered in patients with HFrEF.

CLINICAL TRIAL REGISTRATION

NCT00041938.

The Factors Influencing Chronic Kidney Disease Incidence: Database from the Korean National Health Insurance Sharing Service (NHISS)

Background: The global prevalence of chronic kidney disease (CKD) is increasing, with diabetes accounting for the highest proportion. We analyzed the influence of clinical factors on the incidence of CKD according to the renal function, primary focusing on patients with diabetes. Methods: We used the Sample Cohorts Database provided by the National Health Insurance Sharing Service (NHISS) in Korea. Participants aged ≥ 40 years who underwent a health checkup in 2009 were categorized into six groups based on their eGFR values (<60 mL/min, 60-89 mL/min, ≥90 mL/min) and the presence of diabetes. And all patients with CKD at 2009 screening were excluded. The participants were tracked from 2010 to 31 December 2019. The CKD incidence rate according to the eGFR values and the effect of the accompanying factors on CKD incidence were confirmed. Results: 148,089 people without CKD were analyzed. The CKD incidence rate was highest in those with eGFR < 60 mL/min with diabetes and lowest in those with eGFR ≥ 90 mL/min without diabetes. The CKD incidence rates were similar between the eGFR < 60 mL/min group without diabetes and the eGFR 60-89 mL/min group with diabetes. Compared to under 44 years of age, the hazard ratio of CKD incidence was 8 times higher in over 75 years of age. Men had a 1.7-fold higher risk of developing CKD than women. Current smoker, hypertension, dyslipidemia, myocardial infarction history, and atrial fibrillation and flutter increased the risk of CKD incidence. Age, diabetes, and baseline eGFR are important factors in the occurrence of CKD. As age increases, the risk of developing CKD in men increases compared to women. Conclusions: These results will be helpful in predicting risk groups for CKD and establishing strategies to lowering CKD incidence.

Non-invasive assessment of stroke volume and cardiovascular parameters based on peripheral pressure waveform

Cardiovascular diseases are the leading cause of death globally, making the development of non-invasive and simple-to-use tools that bring insights into the state of the cardiovascular system of utmost importance. We investigated the possibility of using peripheral pulse wave recordings to estimate stroke volume (SV) and subject-specific parameters describing the selected properties of the cardiovascular system. Peripheral pressure waveforms were recorded in the radial artery using applanation tonometry (SphygmoCor) in 35 hemodialysis (HD) patients and 14 healthy subjects. The pressure waveforms were then used to estimate subject-specific parameters of a mathematical model of pulse wave propagation coupled with the elastance-based model of the left ventricle. Bioimpedance cardiography measurements (PhysioFlow) were performed to validate the model-estimated SV. Mean absolute percentage error between the simulated and measured pressure waveforms was 4.0% and 2.8% for the HD and control group, respectively. We obtained a moderate correlation between the model-estimated and bioimpedance-based SV (r = 0.57, p<0.05, and r = 0.58, p<0.001, for the control group and HD patients, respectively). We also observed a correlation between the estimated end-systolic elastance of the left ventricle and the peripheral systolic pressure in both HD patients (r = 0.84, p<0.001) and the control group (r = 0.70, p<0.01). These preliminary results suggest that, after additional validation and possibly further refinement to increase accuracy, the proposed methodology could support non-invasive assessment of stroke volume and selected heart function parameters and vascular properties. Importantly, the proposed method could be potentially implemented in the existing devices measuring peripheral pressure waveforms.

Network analysis of symptoms, physiological, psychological and environmental risk factors based on unpleasant symptom theory in patients with chronic heart failure

BACKGROUND

Somatic symptoms and related factors in patients with chronic heart failure have been extensively researched. However, more insight into the complex interconnections among these constructs is needed, as most studies focus on them independently from each other.

AIMS

The aim of this study is to gain a comprehensive understanding of how somatic symptoms and related factors are interconnected among patients with chronic heart failure.

METHODS

A total of 379 patients were enrolled. Network analysis was used to explore the interconnections among the somatic symptoms and related risk factors.

RESULTS

The four core symptoms of chronic heart failure were daytime dyspnea, dyspnea when lying down, fatigue and difficulty sleeping. Within the network, the edge weights of depression-anxiety, subjective social support-objective social support, and subjective social support-social support availability were more significant than others. Among physiological, psychological and environmental factors, the edge weights of NYHA-dyspnea, depression-difficulty sleeping, and social support availability-dyspnea when lying down were more significant than others. Depression and anxiety had the highest centrality, indicating stronger and closer connections with other nodes.

CONCLUSIONS

Psychological and environmental factors stood out in the network, suggesting the potential value of interventions targeting these factors to improve overall health.

Predictors of Kidney Function Outcomes and Their Relation to SGLT2 Inhibitor Dapagliflozin in Patients with Type 2 Diabetes Mellitus Who Had Chronic Heart Failure

INTRODUCTION

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have a favorable impact on the kidney function in patients with heart failure (HF), while there is no clear evidence of what factors predict this effect. The aim of the study was to identify plausible predictors for kidney function outcome among patients with HF and investigate their association with SGLT2i.

METHODS

We prospectively enrolled 480 patients with type 2 diabetes mellitus (T2DM) treated with diet and metformin and concomitant chronic HF and followed them for 52 weeks. In the study, we determined kidney outcome as a composite of ≥ 40% reduced estimated glomerular filtration rate from baseline, newly diagnosed end-stage kidney disease or kidney replacement therapy. The relevant medical information and measurement of the biomarkers (N-terminal natriuretic pro-peptide, irisin, apelin, adropin, C-reactive protein, tumor necrosis factor-alpha) were collected at baseline and at the end of the study.

RESULTS

The composite kidney outcome was detected in 88 (18.3%) patients of the entire population. All patients received guideline-recommended optimal therapy, which was adjusted to phenotype/severity of HF, cardiovascular risk and comorbidity profiles, and fasting glycemia. Levels of irisin, adropin and apelin significantly increased in patients without clinical endpoint, whereas in those with composite endpoint the biomarker levels exhibited a decrease with borderline statistical significance (p = 0.05). We noticed that irisin ≤ 4.50 ng/ml at baseline and a ≤ 15% increase in irisin serum levels added more valuable predictive information than the reference variable. However, the combination of irisin ≤ 4.50 ng/ml at baseline and ≤ 15% increase in irisin serum levels (area under curve = 0.91; 95% confidence interval = 0.87-0.95) improved the discriminative value of each biomarker alone.

CONCLUSION

We suggest that low levels of irisin and its inadequate increase during administration of SGLT2i are promising predictors for unfavorable kidney outcome among patients with T2DM and concomitant HF.

Chronic Kidney Disease Associated with Ischemic Heart Disease: To What Extent Do Biomarkers Help?

Chronic kidney disease represents a complex and multifaceted pathology characterized by the presence of structural or functional renal anomalies associated with a persistent reduction in renal function. As the disease progresses, complications arise due to the chronic inflammatory syndrome, hydro-electrolytic disorders, and toxicity secondary to the uremic environment. Cardiovascular complications are the leading cause of death for these patients. Ischemic cardiac pathology can be both a consequence and complication of chronic kidney disease, highlighting the need to identify specific cardiorenal dysfunction biomarkers targeting pathophysiological mechanisms common to both conditions. This identification is crucial for establishing accurate diagnoses, prognoses, and risk stratifications for patients. This work is intended to elucidate the intricate relationship between chronic kidney disease and ischemic heart disease and to investigate the roles of cardiorenal biomarkers, including cardiac troponin, natriuretic peptides, galectin-3, copeptin, fibroblast growth factor 23 and its co-receptor Klotho, soluble suppression of tumorigenicity 2, and plasma growth differentiation factor 15.

Causal relationship from heart failure to kidney function and CKD: A bidirectional two-sample mendelian randomization study

BACKGROUND

Heart Failure (HF) is a widespread condition that affects millions of people, and it is caused by issues with the heart and blood vessels. Even though we know hypertension, coronary artery disease, obesity, diabetes, and genetics can increase the risk of HF and Chronic Kidney Disease (CKD), the exact cause of these conditions remains a mystery. To bridge this gap, we adopted Mendelian Randomization (MR), which relies on genetic variants as proxies.

METHODS

We used data from European populations for our Bidirectional Two-Sample MR Study, which included 930,014 controls and 47,309 cases of HF from the HERMES consortium, as well as 736,396 controls and 51,256 cases of CKD. We also employed several MR variations, including MR-Egger, Inverse Variance Weighted (IVW), and Weighted Median Estimator (WME), to guarantee the results were accurate and comprehensive.).

RESULTS

In this study, the MR analysis found that individuals with a genetic predisposition for HF have an elevated risk of CKD. Our study revealed a significant association between the genetic prediction of HF and the risk of CKD, as evidenced by the IVW method [with an odds ratio (OR) of 1.12 (95% CI, 1.03-1.21), p = 0.009] and the WME [with an OR of 1.14 (95% CI, 1.03-1.26), p = 0.008]. This causal relationship remained robust even after conducting MR analysis while adjusting for the effects of diabetes and hypertension, yielding ORs of 1.13 (IVW:95% CI, 1.03-1.23), 1.12 (MR-Egger: 95% CI, 0.85-1.48), and 1.15 (WME:95% CI, 1.04-1.27) (p = 0.008). However, in the reverse analysis aiming to explore CKD and renal function as exposures and HF as the outcome, we did not observe a statistically significant causal link between CKD and HF.

CONCLUSION

Our study demonstrates the significance of HF in CKD progression, thus having meaningful implications for treatment and the potential for discovering new therapies. To better understand the relationship between HF and CKD, we need to conduct research in a variety of populations.

Sustaining Quality of Life with Education-Based Treatment for Hypertension Patients During COVID-19 Adaptation

Purpose: Determine the impact of education-based treatment on sustaining quality of life during COVID-19 adaptation. Designs: A randomized, 2-group, structured, holistic education-based intervention within eight weeks in preserving total quality of life (QoL) for hypertension patients with conventional care. Methods: Utilizing randomized controlled trials, 380 patients with hypertension are separated into two groups and evaluated. The patients are separated into two groups totaling 190 individuals each group. The intervention group is treated with a holistic education-based intervention. After two months, the EQ-5D-5L is used to evaluate the quality of life. Findings: The QoL pretest for the intervention group revealed that 25 (13.2%) patients had good QoL (Score = 1), while the QoL posttest revealed that the number of patients with good QoL had grown to 48 (25.3%). Using Kolmogorov-Smirnov for data analysis yielded non-normally distributed data. The p-value for the Wilcoxon signed ranks test is .001. Conclusions: The intervention group is better equipped to deal with COVID-19 and has a higher quality of life. Education-based hypertension treatment can sustain a high quality of life.

Heart Failure in Patients with Chronic Kidney Disease

The function of the kidney is tightly linked to the function of the heart. Dysfunction/disease of the kidney may initiate, accentuate, or precipitate of the cardiac dysfunction/disease and vice versa, contributing to a negative spiral. Further, the reciprocal association between the heart and the kidney may occur on top of other entities, usually diabetes, hypertension, and atherosclerosis, simultaneously affecting the two organs. Chronic kidney disease (CKD) can influence cardiac function through altered hemodynamics and salt and water retention, leading to venous congestion and therefore, not surprisingly, to heart failure (HF). Management of HF in CKD is challenging due to several factors, including complex interplays between these two conditions, the effect of kidney dysfunction on the metabolism of HF medications, the effect of HF medications on kidney function, and the high risk for anemia and hyperkalemia. As a result, in most HF trials, patients with severe renal impairment (i.e., eGFR 30 mL/min/1.73 m2 or less) are excluded. The present review discusses the epidemiology, pathophysiology, and current medical management in patients with HF developing in the context of CKD.

MCP1 Inverts the Correlation between FGF23 and Omega 6/3 Ratio: Is It Also True in Renal Transplantation?

During chronic kidney disease (CKD) progression, an increase in fibroblast growth factor (FGF23) is present. In stage 5, a positive correlation between FGF23 and omega-6 (n-6) polyunsaturated fatty acids (PUFAs) emerges. Hypothesizing that the rising positive correlation between monocyte chemoattractant protein 1 (MCP1) and n-6 in stage 4 could be the cause, we previously explored FGF23 and MCP1's roles in dyslipidemia and cardiovascular risk in CKD. In the present paper, we retraced the study evaluating 40 kidney transplant patients (KTx), a cohort where several factors might modify the previous relationships found. An ELISA and gas chromatography assessed the MCP1, FGF23, and PUFA levels. Despite the FGF23 increase (p < 0.0001), low MCP1 levels were found. A decrease in the n-6/n-3 ratio (p = 0.042 CKD stage 4 vs. 5) lowered by the increase in both n-3 αlinolenic (p = 0.012) and docosapentaenoic acid (p = 0.049) was observed. A negative correlation between FGF23 and the n-6/n-3 ratio in CKD stage 4 (r2 -0.3 p = 0.043) and none with MCP1 appeared. According to our findings, different mechanisms in the relationship between FGF23, PUFAs, and MCP1 in CKD and KTx patients might be present, which is possibly related to the immunosuppressive status of the last. Future research will further clarify our hypothesis.

Heart Failure Prevalence Rates and Its Association with Other Cardiovascular Diseases and Chronic Kidney Disease: SIMETAP-HF Study

INTRODUCTION AND OBJECTIVES

Heart failure (HF) is a major health problem that causes high mortality and hospitalization rates. This study aims to determine the HF prevalence rates in populations aged both ≥18 years and ≥50 years and to assess its association with cardiovascular diseases and chronic kidney disease.

METHODS

A cross-sectional observational study was conducted in a primary care setting, with a population-based random sample of 6588 people aged 18.0-102.8 years. Crude and adjusted prevalence rates of HF were calculated. The associations of renal and cardiometabolic factors with HF were assessed in both populations using univariate, bivariate and multivariate analysis.

RESULTS

The HF crude prevalence rates were 2.8% (95%CI: 2.4-3.2) in adults (≥18 years), and 4.6% (95%CI: 4.0-5.3) in the population aged ≥ 50 years, without significant differences between males and females in both populations. The age- and sex-adjusted prevalence rates were 2.1% (male: 1.9%; female: 2.3%) in the overall adult population, and 4.5% (male: 4.2%; female: 4.8%) in the population aged ≥ 50 years, reaching 10.0% in the population aged ≥ 70 years. Atrial fibrillation, hypertension, low estimated glomerular filtration rate (eGFR), coronary heart disease (CHD), stroke, sedentary lifestyle, and diabetes were independently associated with HF in both populations. A total of 95.7% (95%CI: 92.7-98.6) of the population with HF had an elevated cardiovascular risk.

CONCLUSIONS

This study reports that HF prevalence increases from 4.5% in the population over 50 years to 10% in the population over 70 years. The main clinical conditions that are HF-related are sedentary lifestyle, atrial fibrillation, hypertension, diabetes, low eGFR, stroke, and CHD.