A study led by King’s College London (KCL) has revealed that Black patients are less likely to be underdiagnosed with a common type of heart failure when using artificial intelligence (AI), compared to in routine practice.

The research, funded by the British Heart Foundation, could help researchers understand the extent of heart failure with preserved ejection fraction (HFpEF) underdiagnosis across ethnicities, as well as reduce bias and improve diagnoses.

Heart failure is estimated to affect more than one million people in the UK, 50% of whom have HFpEF, which occurs when the heart pumps out blood normally but cannot fill up as well, leading to signs and symptoms of failure such as breathlessness, fatigue and dizziness.

Using an AI algorithm called Natural Language Processing (NLP), which reads and understands medical text and analyses electronic medical records, researchers identified nearly 1,973 patients who met the current European Society of Cardiology guidelines for a diagnosis of HFpEF – 64% of whom were white, 29% were Black and 7% were Asian.

Aiming to see if these same patients would be effectively diagnosed in routine care without NLP, researchers found that Black and Asian patients were less likely to be underdiagnosed using the AI.

The team believes that this is due to HFpEF being diagnosed partly by using scores from a H2FPEF test, which is not used in the algorithm, while the NLP considers other possible contributing factors, specifically atrial fibrillation, which was more common in people with white and Asian backgrounds, compared to hypertension, which was more common in Black patients.

Ultimately, researchers believe that the HFpEF diagnostic tool could have led to more Black patients being missed and emphasise the need to improve the diagnosis of HPpEF while also analysing AI utilisation to bring about a more accurate diagnosis.

A new study led by researchers from Cardiff University, King’s College London (KCL), Swansea University and the University of Calgary has revealed that Janssen’s psoriasis drug, Stelara (ustekinumab), shows promise in treating childhood diabetes.

Funded by a Medical Research Council and National Institute for Health and Care Research partnership, the study found that Stelara was more effective in treating the early stages of type 1 diabetes (T1D) in children and adolescents.

Accounting for approximately 10% of diabetes cases in the UK, T1D occurs when the pancreas does not produce insulin or makes very little insulin.

Since 2009, the immunotherapy Stelara has been used to treat psoriasis, a skin condition characterised by flaky patches of skin that affects around 60 million people globally, as well as other immune conditions, including psoriatic arthritis, severe Crohn’s disease and severe ulcerative colitis.

In the study, researchers tested Stelara in 72 adolescents between the ages of 12 and 18 with recent-onset T1D.

They found that Stelara preserved vital insulin-producing cells known as Th17 cells and also identified the specific immune cells that cause this destruction, enabling precise and targeted therapies to maximise benefits and minimise side effects.

“Th17 cells make up only one in 1,000… blood immune cells, but they seem to play an important role in destroying insulin-producing cells. This explains why [Stelara] has so few side effects,” explained KCL’s Professor Tim Tree.

Furthermore, after 12 months of using Stelara, researchers found that C-peptide levels, a sign that the body is producing insulin, were 49% higher.

Dr Peter Taylor, Cardiff University’s Systems Immunity Research Institute, commented: “It is now possible with a simple finger-prick antibody test to detect children who will develop T1D years before they need insulin.