Rapid testing for acute coronary syndromes: faster treatment, lower hospital admissions, cost-efficient

Patients arriving at emergency departments with chest pain traditionally required emergency hospital admission for testing, which took up to three days to complete. Our research led to improved diagnostic technologies, meaning patients can now be diagnosed and treated quicker. Most are discharged on the same day, reducing hospital admissions and saving NHS resources.

Doctors rule out heart problems by detecting troponins in the blood. Troponins are proteins found in heart muscle that are released into the bloodstream during acute coronary syndromes (ACS), including heart attack.

Traditionally, all patients with suspected ACS were admitted to hospital for up to three days to allow sufficient time for levels of troponins in the blood to rise to detectable levels. Only around 30% of patients admitted actually had ACS.

Improving diagnostic technologies

Our research led to three new methods of investigating chest pain using high-sensitivity cardiac troponin assays. These tests detect troponin at much lower levels than previous tests allowed, meaning results are available quicker and reduce unnecessary hospital stays.

Professor Rick Body

Rick is a Professor and Consultant in Emergency Medicine, and Group Director of Research & Innovation at Manchester University NHS Foundation Trust.

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One of the methods, called Limit of Detection (LoD), uses a single blood test to detect very low concentrations of cardiac troponin. We were the first to report the use of this test to ‘rule-out’ diagnosis of Acute Myocardial Infarction (AMI) (heart attack).

As part of Roche’s international TRAPID-AMI trial, we evaluated another rapid 'rule-out' method, the 1-hour algorithm. This method uses serial blood tests taken one hour apart. We found that it was more than 99% accurate in ruling out AMI. Secondary analysis confirmed that the LoD strategy was also 99% accurate in ruling out AMI.

We also developed the Troponin-only Manchester Acute Coronary Syndromes (T-MACS) decision aid. This is a clinical prediction model that uses a computer algorithm to calculate individual patients' probability of heart attack.

This calculation is based on a single blood test on arrival at the emergency department, patient symptoms, and electrocardiogram (ECG) findings (a simple test to check heart rhythm and electrical activity). It assigns patients to a risk group and suggests a course of action for clinicians to follow.

The impact

Changing UK and international care

LoD testing is advocated by UK NICE and European Society of Cardiology (ESC) guidelines. ESC also recommended the use of the 1-hour algorithm, if available.

To date, this algorithm has demonstrated patient benefit in trials in Sweden, Netherlands, Northern Ireland, Thailand, Switzerland and Argentina.

In 2019, the American College of Cardiology recommended transition to high sensitivity troponin testing for all hospital services. Professor Body was an expert panel member.

Reducing NHS costs

Economic analysis found that UK use of the 1-hour algorithm saves more than £2,000 per patient in treatment costs.

The implementation of high-sensitivity troponin rule-out pathways nationally across the NHS is underway. NHS England stated that "this could lead to overall national benefits upwards of £20 million as a direct result of this improved rule-out".

Diagnosing patients quicker

T-MACS has been used by Manchester University NHS Foundation Trust since 2016 and is now in use across nine Greater Manchester hospitals. It has guided the care of over 30,000 Greater Manchester patients to date.

Whereas over 80% of patients were previously admitted for up to three days, 66% of patients are now managed in reclining chairs in an ambulatory care environment. 62% of patients are categorised as low risk, and 95% of these patients go home on the same day with no adverse effects.

What next?

Rick is now working with ambulance staff to see if T-MACS could be used before patients arrive at hospital, meaning patients could receive the correct treatment even quicker. He is also working with colleagues to refine the algorithms used to optimise T-MACS for diverse populations and those with pre-existing conditions.

Importantly, Rick is also working to introduce shared decision-making based on T-MACS results, allowing patients and clinicians to make joint decisions on care and ensuring patients' voices are heard.