Introduction

Heart failure, a life-threatening condition, is characterised by the heart being unable to pump a sufficient supply of blood to meet the body’s metabolic demands.¹ Heart failure affects over 64 million individuals worldwide, with prevalence on an exponential rise.^2,3 As the world population and life expectancy continue to grow, it presents itself as a major public health concern, becoming a looming global epidemic. Not only does heart failure significantly affect an individual’s quality of life, causing shortness of breath, fatigue, and wheezing, but it also creates an additional economic burden on the already overwhelmed healthcare system, costing globally $108 billion annually.⁴ This highlights the importance of early detection, allowing optimal treatment and preventing premature death. 

Importance Of Early Detection

Typically, the progression of heart failure is slow and long-term, with symptoms initially being asymptomatic. Without early detection, the condition advances severely, becoming difficult to manage. This highlights the importance of identifying and treating heart failure early on to improve patient prognosis when there is still the possibility of recovery.⁵ The healthcare system ‌takes a reactive approach, usually when symptoms have already progressed substantially, contributing to healthcare costs. However, early detection involves being proactive to reduce avoidable health deterioration. 

Stages Of Heart Failure

• Stage A (Asymptomatic)- The patient does not present symptoms or structural abnormalities but is at risk of developing heart failure because of family or medical history. Risk factors may be present, including metabolic syndrome, hypertension, or diabetes.
• Stage B (Asymptomatic)- This stage has been described as ‘silent heart failure,’ where the patient does not present symptoms but has developed structural heart disease. 
• Stage C (Symptomatic)- The patient has heart failure with current or past symptoms. 
• Stage D (Symptomatic)- The patient is not recovering despite the use of aggressive treatment, with hospitalisation required.⁶

The first two stages of heart failure are asymptomatic, reinforcing the importance of early detection and diagnosis for optimal recovery. 

Causes And Mechanisms Of Heart Failure

Disruption of the valves leads to cardiac abnormalities, particularly dysfunction of systolic (ejection) or diastolic (filling) of the ventricles, causing heart failure. 

Biomarkers For Early Detection Of Heart Failure

Biomarkers are used as an indicator to detect or confirm whether a condition is present, contributing heavily to an accurate diagnosis and monitoring of the condition’s progression.⁷ They can detect heart failure even before symptoms develop, making them a promising tool for early detection.

Natriuretic Peptides 

Natriuretic peptides were the first biomarkers to be recognised as a diagnostic tool for heart failure, with them being extensively studied and used. They are produced and released in greater concentrations when myocardial stretch and biomechanical stress are present, often seen in individuals experiencing heart failure.⁸ Different types of natriuretic peptides measured for heart failure are brain natriuretic peptide (BNP), N-terminal brain natriuretic pro-peptide (NT-proBNP), and mid-regional atrial natriuretic pro-peptide (MR-proANP). Levels of natriuretic peptides are an excellent indicator of heart failure, as well as a tool to optimise management and improve prognosis. 

The first major clinical trial, named the ‘Breathing Not Properly Study’ measuring BNP levels, found a statistically significant correlation between those diagnosed with heart failure and elevated levels of BNP compared to those without heart failure.⁹ In addition, BNP levels were greater in those with a higher severity of heart failure. BNP has also proven to be more accurate (83%) compared to other established criteria used for heart failure diagnosis: NHNESC (67%) and Framingham criteria (73%). This highlights the importance of natriuretic peptides in early detection.¹⁰

Although elevated levels of natriuretic peptides are a proven diagnostic tool, production has also been associated with systemic inflammation, hypoxia, and brain trauma, making it challenging to differentiate heart failure from similar conditions. In addition, conditions such as obesity and diabetes lower concentrations, making it challenging to diagnose heart failure accurately. Because of the interference of other variables, natriuretic peptides can lead to misdiagnosis of heart failure.   

Galectin-3

Galectin-3 is another novel biomarker for the diagnosis and prognosis of heart failure, expressed by immune cells.¹¹ It plays a role in the inflammatory response, being readily available on the cell surface, making it easily accessible to be secreted into the bloodstream from inflammatory cells. Therefore, galectin-3 is a biomarker for fibrosis and cardiac inflammation. Clinical studies have provided supporting evidence that higher concentrations of galectin-3 correlate with cardiac fibrosis in heart failure however, there have also been conflicting results. 

However, it should be noted that galectin-3 is still in its early infancy as a biomarker for heart failure, with studies typically using small sample sizes. As well as this, galectin-3 is not a heart-specific marker, as elevated levels are also a biomarker for kidney disease, viral infections and diabetes, making it difficult to identify the source of the increased concentration. Despite this, galectin-3 is still a promising diagnostic biomarker for early heart failure.¹²

Diagnosis For Heart Failure 

There is no single symptom that can be used to diagnose heart failure alone; however, methods involve clinical history, physical examination, and an electrocardiogram.¹³ 

Clinical History

• Family History is essential for creating a wider understanding of whether the patient may have a predisposition to heart failure due to  having genetic mutations  
• Symptoms should be assessed regarding dyspnea (shortness of breath), chest pains, hypertension, and high blood pressure¹⁴ 
• Lifestyle should be evaluated in terms of the consumption of alcohol, smoking, and a high-fat diet 

Physical Examination

• Heart Rate to indicate any abnormalities
• Jugular Venous Distention is carried out as it can show volume overload in the jugular veins, increasing the probability of heart failure diagnosis^15,16 

Other Diagnostic Assessments

• Laboratory Tests: As mentioned earlier, biomarkers such as natriuretic peptides, cardiac troponins, and galectin-3 can be measured from blood samples to indicate the presence of heart failure 
• Chest Radiography (X-ray): To identify pulmonary causes of dyspnea, with pulmonary venous congestion on X-ray suggesting heart failure 
• Electrocardiography: Recording the electrical activity of the heart. Although no single feature is indicative of heart failure, atrial and ventricular arrhythmias have been associated with the condition 
• Echocardiogram: Assesses the size, mass, and function of the left ventricle, measuring the ejection fraction of how much blood the left ventricle pumps out with each contraction
• CT and MRI: Can assess regional wall motion and measure the ejection fraction¹⁷ 

Future Innovations For Early Detection In Heart Failure

Due to high mortality rates and the risks arising from heart failure, researchers have begun to shift their attention to novel diagnostic tools to reshape and improve the quality of life for heart failure in terms of early detection. 

Artificial Intelligence- Machine Learning

Machine learning, a branch of AI, uses algorithms to analyse data to make predictions and find patterns. Machine learning is particularly advantageous for the early diagnosis of heart failure because it can handle an extensive set of data, involving medical records, imaging data, and genomics, to enhance accuracy. This is important because heart failure is a complex condition with a range of mechanisms and comorbidities, manifesting as structural and functional dysfunction. Through the use of machine learning and ‌layers of artificial neural networks, the development of heart failure can be predicted, allowing early detection. An AI-Clinical Decision Support System (AI-CDSS) has been developed to act as a medical assistant platform, where it has shown a diagnostic accuracy of 98% for heart failure. As well as this, AI can be integrated as a wearable device, allowing remote monitoring.¹⁸

Genomics And Next-Generation Sequencing

Genetic screening for individuals with a family history of cardiac abnormalities involves identifying genes related to heart failure. This can be carried out by next-generation gene sequencing, a technology used for DNA sequencing to study genetic variation or mutation of a disease. This technique has high sensitivity and specificity, allowing interpretation of the results to be easy and efficient. However, next-generation sequencing kits are limited due to the high costs associated with them.¹⁹

Summary

With heart failure on an exponential rise, it presents itself as a looming, major public health concern. Traditionally, the diagnosis of heart failure focuses on symptoms; however, this is when the disease has already progressed significantly, being at the later stages of the condition. This highlights the importance of shifting our attention from a reactive approach to a proactive outlook by identifying novel, early diagnostic innovations. Recent research has particularly focused on the use of biomarkers, machine learning, and next-generation sequencing. These techniques have shown promising results, being a powerful tool for the early detection of heart failure with the ability to reshape the way other conditions are diagnosed as well.