Association of Long-term Change in N-Terminal Pro-B-Type Natriuretic Peptide With Incident Heart Failure and Death

Plasma Biomarkers for Hypertension-Mediated Organ Damage Detection: A Narrative Review

Hypertension (HT) is a disease that poses a serious threat to human health, mediating organ damage such as the cardiovascular (CV) system, kidneys, central nervous system (CNS), and retinae, ultimately increasing the risk of death due to damage to the entire vascular system. Thus, the widespread prevalence of hypertension brings enormous health problems and socioeconomic burdens worldwide. The goal of hypertension management is to prevent the risk of hypertension-mediated organ damage and excess mortality of cardiovascular diseases. To achieve this goal, hypertension guidelines recommend accurate monitoring of blood pressure and assessment of associated target organ damage. Early identification of organ damage mediated by hypertension is therefore crucial. Plasma biomarkers as a non-invasive test can help identify patients with organ damage mediated by hypertension who will benefit from antihypertensive treatment optimization and improved prognosis. In this review, we provide an overview of some currently available, under-researched, potential plasma biomarkers of organ damage mediated by hypertension, looking for biomarkers that can be detected by simple testing to identify hypertensive patients with organ damage, which is of great significance in clinical work. Natriuretic peptides (NPs) can be utilized as a traditional biomarker to detect hypertension-mediated organ damage, especially for heart failure. Nevertheless, we additionally may need to combine two or more plasma biomarkers to monitor organ damage in the early stages of hypertension.

Scalable Risk Stratification for Heart Failure Using Artificial Intelligence applied to 12-lead Electrocardiographic Images: A Multinational Study

Background

Current risk stratification strategies for heart failure (HF) risk require either specific blood-based biomarkers or comprehensive clinical evaluation. In this study, we evaluated the use of artificial intelligence (AI) applied to images of electrocardiograms (ECGs) to predict HF risk.

Methods

Across multinational longitudinal cohorts in the integrated Yale New Haven Health System (YNHHS) and in population-based UK Biobank (UKB) and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), we identified individuals without HF at baseline. Incident HF was defined based on the first occurrence of an HF hospitalization. We evaluated an AI-ECG model that defines the cross-sectional probability of left ventricular dysfunction from a single image of a 12-lead ECG and its association with incident HF. We accounted for the competing risk of death using the Fine-Gray subdistribution model and evaluated the discrimination using Harrel's c-statistic. The pooled cohort equations to prevent HF (PCP-HF) were used as a comparator for estimating incident HF risk.

Results

Among 231,285 individuals at YNHHS, 4472 had a primary HF hospitalization over 4.5 years (IQR 2.5-6.6) of follow-up. In UKB and ELSA-Brasil, among 42,741 and 13,454 people, 46 and 31 developed HF over a follow-up of 3.1 (2.1-4.5) and 4.2 (3.7-4.5) years, respectively. A positive AI-ECG screen portended a 4-fold higher risk of incident HF among YNHHS patients (age-, sex-adjusted HR [aHR] 3.88 [95% CI, 3.63-4.14]). In UKB and ELSA-Brasil, a positive-screen ECG portended 13- and 24-fold higher hazard of incident HF, respectively (aHR: UKBB, 12.85 [6.87-24.02]; ELSA-Brasil, 23.50 [11.09-49.81]). The association was consistent after accounting for comorbidities and the competing risk of death. Higher model output probabilities were progressively associated with a higher risk for HF. The model's discrimination for incident HF was 0.718 in YNHHS, 0.769 in UKB, and 0.810 in ELSA-Brasil. Across cohorts, incorporating model probability with PCP-HF yielded a significant improvement in discrimination over PCP-HF alone.

Conclusions

An AI model applied to images of 12-lead ECGs can identify those at elevated risk of HF across multinational cohorts. As a digital biomarker of HF risk that requires just an ECG image, this AI-ECG approach can enable scalable and efficient screening for HF risk.

Navigating Heart Failure: Unveiling Sex Disparities in Guideline-Directed Medical Therapy Combinations

Major heart failure (HF) trials remain insufficient in terms of assessing the differences in clinical characteristics, biomarkers, treatment efficacy, and safety because of the under-representation of women. The study aimed to present sex-related disparities in HF management, including differences in demographics, co-morbidities, cardiac biomarkers, prescribed medications, and treatment outcomes. The study utilized anonymized data from the Turkish Ministry of Health's National Electronic Database between January 1, 2016, and December 31, 2022. The cohort analysis included 2,501,231 adult patients with HF. Specific therapeutic combinations were analyzed using a Cox regression model to obtain relative risk reduction for all-cause death. The primary end point was all-cause mortality. In the cohort, 48.7% (n = 1,218,911) were male, whereas 51.3% (n = 1,282,320) were female. Female patients exhibited a higher median age (71 vs 68 years) and manifested higher prevalence of diabetes mellitus, anemia, atrial fibrillation, anxiety, and ischemic stroke. Male patients demonstrated higher rates of previous myocardial infarction, dyslipidemia, chronic obstructive pulmonary disease, and chronic kidney disease. Higher concentrations of natriuretic peptides were observed in female patients. Renin-angiotensin aldosterone inhibitor, β blockers, mineralocorticoid receptor antagonists, sodium/glucose cotransporter 2 inhibitor (SGLT2i), and ivabradine were more commonly prescribed in male patients, whereas loop diuretics, digoxin, and ferric carboxymaltose were more frequent in female patients. Male patients had higher rates of cardiac resynchronization therapy and implantable cardioverter defibrillator implantation rates. All-cause mortality and hospitalization rates were higher in male patients. Compared with monotherapy, all combinations, including SGLT2i, showed a beneficial effect on all-cause mortality in both female and male patients with HF. In hospitalized patients with HF, the addition of digoxin to renin-angiotensin aldosterone inhibitor, mineralocorticoid receptor antagonists, and β blockers was superior to monotherapy regarding all-cause mortality in female patients with HF compared with male patients with HF. In conclusion, this study highlights that sex-specific responses to HF medication combinations compared with monotherapy and differences in co-morbidities underscore the importance of tailored management strategies. Digoxin showed a contrasting effect on all-cause mortality between both sexes after hospitalization, whereas SGLT2i exhibited a consistent beneficial effect in both sexes when added to all combinations.

Characteristics and Prognosis of Type 2 Myocardial Infarction Through Worsening Renal Function and NT-proBNP in Older Adults with Pneumonia

Background

Type 2 myocardial infarction (MI) is becoming more recognized. This study aimed to assess the factors linked to type 2 MI in older adults with pneumonia and further determine the predictive factors of 90-day adverse events (refractory heart failure, cardiogenic shock, and all-cause mortality).

Methods

A single-center retrospective analysis was conducted among older adults with pneumonia. The primary outcome was the prevalence of type 2 MI. The secondary objective was to assess the adverse events in these patients with type 2 MI within 90 days.

Results

A total of 2618 patients were included. Of these, 361 patients (13.8%) suffered from type 2 MI. Multivariable predictors of type 2 MI were chronic kidney disease (CKD), age-adjusted Charlson comorbidity index (ACCI) score, and NT-proBNP > 4165pg/mL. Moreover, the independent predictive factors of 90-day adverse events included NT-proBNP > 4165pg/mL, age, ACCI score, and CKD. The Kaplan-Meier adverse events curves revealed that the type 2 MI patients with CKD and NT-proBNP > 4165pg/mL had a higher risk than CKD or NT-proBNP > 4165pg/mL alone.

Conclusion

Type 2 MI in older pneumonia hospitalization represents a heterogeneous population. Elevated NT-proBNP level and prevalence of CKD are important predictors of type 2 MI and 90-day adverse events in type 2 MI patients.

Prognostic Impact of Repeated NT-proBNP Measurements in Patients With Heart Failure With Reduced Ejection Fraction

BACKGROUND

Although clinical studies have demonstrated the association between a single N-terminal pro-B-type natriuretic peptide (NT-proBNP) measurement and clinical outcomes in chronic heart failure, the biomarker is frequently measured serially in clinical practice.

OBJECTIVES

The aim of this study was to determine the added prognostic value of repeated NT-proBNP measurements compared with single measurements alone for chronic heart failure patients.

METHODS

In the GUIDE-IT (Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure) study, 894 study participants with chronic heart failure with reduced ejection fraction were enrolled at 45 outpatient sites in the United States and Canada. Repeated NT-proBNP levels were measured over a 2-year study period. Associations between repeated NT-proBNP measurements and trial endpoints were assessed using a joint longitudinal and survival model.

RESULTS

After adjustment for baseline covariates, each doubling of the baseline NT-proBNP level was associated with a HR of 1.17 (95% CI: 1.08-1.28; P = 0.0003) for the primary trial endpoint of cardiovascular death or heart failure hospitalization. Serial measurements increased the adjusted HR for the primary trial endpoint to 1.66 (95% CI: 1.50-1.84; P < 0.0001), and a similar increased risk was observed across secondary trial endpoints. In joint modeling, an increase in NT-proBNP occurred weeks before the onset of adjudicated events.

CONCLUSIONS

Repeated NT-proBNP measurements are a strong predictor of outcomes in heart failure with reduced ejection fraction with an increase in concentration occurring well before event onset. These results may support routine NT-proBNP monitoring to assist in clinical decision making. (Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure [GUIDE-IT]; NCT01685840).

Identification of novel endogenous control miRNAs in heart failure for normalization of qPCR data

MicroRNAs (miRNAs), a class of non-coding RNAs, are utilized as biomarkers for a wide range of disorders. Circulating miRNAs are proposed as potential markers in the clinical identification of heart failure (HF). However, identifying miRNA biomarkers in HF requires identification of robust endogenous control miRNAs for normalization in differential expression analysis. Hence, this study aimed to identify circulating miRNAs that can be utilized as endogenous controls in HF. We evaluated the expression of eight miRNAs, which were previously reported as endogenous controls in different pathological conditions. Total RNA, including miRNA, was extracted from the serum samples of 30 HF patients (15 HFrEF and 15 HFpEF) and their matched controls (n = 15). We used quantitative PCR to determine the miRNA expression. The stability of the selected endogenous miRNAs was assessed and compared using a standard set of criteria with the RefFinder software. Six of the eight miRNAs analyzed showed consistent expression among all sample groups. Stability analysis ranked hsa-let-7i-5p, hsa-miR-148b-3p, and hsa-miR-484 as the most stable miRNAs, indicating their potential as reliable endogenous controls.

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.

Natriuretic peptide testing strategies in heart failure: A 2023 update

Natriuretic peptides (NPs), including B-type natriuretic peptide (BNP) and N-terminal pro-BNP (NT-proBNP), have been recommended as standard biomarkers for diagnosing heart failure (HF), and one of the strongest risk predictors for mortality and HF hospitalization regardless of ejection fraction (EF) and etiology of HF. BNP is an active neurohormone opposing renin-angiotensin-aldosterone and sympathetic nervous system overactivated in HF, whereas NT-proBNP is an inactive prohormone released from cardiomyocytes in response to wall stress. Despite substantial advances in the development of guideline-directed medical therapy (GDMT) for HF with reduced EF, studies demonstrating direct benefits of NP-guided chronic HF therapy on mortality, HF hospitalization, and GDMT optimization have yielded conflicting results. However, accumulating evidence shows that achieving prespecified BNP or NT-proBNP target over time is significantly associated with favorable outcomes, suggesting that benefits of serially measured NPs may be limited to particular groups of HF patients, such as those with extreme levels of baseline BNP or NT-proBNP, which could represent severe phenotypes of HF associated with natriuretic peptide resistance or cardiorenal syndrome. Over the past decade, clinical utilization of BNP and NT-proBNP has been expanded, especially using serial NP measurements for guiding HF therapy, optimizing GDMT and identifying at-risk patients with HF phenotypes who may be minimally symptomatic or asymptomatic.

Use of 3D Printing Techniques to Fabricate Implantable Microelectrodes for Electrochemical Detection of Biomarkers in the Early Diagnosis of Cardiovascular and Neurodegenerative Diseases

This Review provides a comprehensive overview of 3D printing techniques to fabricate implantable microelectrodes for the electrochemical detection of biomarkers in the early diagnosis of cardiovascular and neurodegenerative diseases. Early diagnosis of these diseases is crucial to improving patient outcomes and reducing healthcare systems' burden. Biomarkers serve as measurable indicators of these diseases, and implantable microelectrodes offer a promising tool for their electrochemical detection. Here, we discuss various 3D printing techniques, including stereolithography (SLA), digital light processing (DLP), fused deposition modeling (FDM), selective laser sintering (SLS), and two-photon polymerization (2PP), highlighting their advantages and limitations in microelectrode fabrication. We also explore the materials used in constructing implantable microelectrodes, emphasizing their biocompatibility and biodegradation properties. The principles of electrochemical detection and the types of sensors utilized are examined, with a focus on their applications in detecting biomarkers for cardiovascular and neurodegenerative diseases. Finally, we address the current challenges and future perspectives in the field of 3D-printed implantable microelectrodes, emphasizing their potential for improving early diagnosis and personalized treatment strategies.

Natriuretic Peptides: It Is Time for Guided Therapeutic Strategies Based on Their Molecular Mechanisms

Natriuretic peptides (NPs) are the principal expression products of the endocrine function of the heart. They exert several beneficial effects, mostly mediated through guanylate cyclase-A coupled receptors, including natriuresis, diuresis, vasorelaxation, blood volume and blood pressure reduction, and regulation of electrolyte homeostasis. As a result of their biological functions, NPs counterbalance neurohormonal dysregulation in heart failure and other cardiovascular diseases. NPs have been also validated as diagnostic and prognostic biomarkers in cardiovascular diseases such as atrial fibrillation, coronary artery disease, and valvular heart disease, as well as in the presence of left ventricular hypertrophy and severe cardiac remodeling. Serial measurements of their levels may be used to contribute to more accurate risk stratification by identifying patients who are more likely to experience death from cardiovascular causes, heart failure, and cardiac hospitalizations and to guide tailored pharmacological and non-pharmacological strategies with the aim to improve clinical outcomes. On these premises, multiple therapeutic strategies based on the biological properties of NPs have been attempted to develop new targeted cardiovascular therapies. Apart from the introduction of the class of angiotensin receptor/neprilysin inhibitors to the current management of heart failure, novel promising molecules including M-atrial natriuretic peptide (a novel atrial NP-based compound) have been tested for the treatment of human hypertension with promising results. Moreover, different therapeutic strategies based on the molecular mechanisms involved in NP regulation and function are under development for the management of heart failure, hypertension, and other cardiovascular conditions.