Projects Delivered

Acute heart failure is a life-threatening condition where the heart is suddenly unable to pump blood around the body. It can be challenging to diagnose because the symptoms often mimic other conditions. Previous studies have showed that delays in making the correct diagnosis result in worse outcomes. We therefore developed a decision-support tool called CoDE-HF that uses a computer algorithm to combine levels of a blood test called NT-proBNP with patient factors to calculate the probability of acute heart failure for an individual.

In this project, we wish to evaluate the performance of CoDE-HF in approximately 2,000 patients attending the Emergency Department with suspected acute heart failure. We will store surplus material from their blood tests to measure NT-proBNP and link information from their electronic health records with other routinely collected medical information in regional and national databases in order to evaluate this algorithm.

COVID-19 can be identified by looking for changes in the lungs on chest x-rays and computed tomography (CT) scans. Different imaging features may be associated with different patterns of disease. In addition, radiological imaging can identify features of other diseases that affect the heart and the lungs. These other diseases may affect the outcomes of patients with COVID-19. This study will review the radiological imaging of patients with COVID-19 and identify features of heart and lung disease which can be used to find patients who do better or worse after COVID-19 infection. This will help us identify the overlap between COVID-19 and other diseases affecting the heart and the lungs, and may help identify groups of patients who are at an increased risk.

Almost 10% of the global population has diabetes and rising; 15-17% of all UK hospital (inpatient) beds are occupied by people with diabetes at any time, costing ~£2.5 billion/ year. Significant numbers suffer a deterioration in diabetes care (such as low or high blood glucose events, and preventable foot ulcers) during hospital stays, as a result of poor management, in part due to general hospital staff being poorly trained in diabetes management.

This proposal aims to develop a computer-based (digital) tool to support clinicians in hospitals make better decisions. The tool will identify ‘at risk’ individuals; support triage of patients, and give advice around the correct decisions for foot care and medication changes/ titration. This tool makes use of historical information (data) contained in medical records to find patterns in the data that predict when escalation of treatment or expert input is needed, ahead of time, thus preventing serious health outcomes/ medical emergencies/ reducing hospital stay, preventing ill health and death. This project is a collaboration between MyWay Digital Health (MWDH), a University of Dundee spin-out, NHS staff and academia.

In late April 2020, a change in COVID-19 testing strategy was implemented in NHS Lothian after a Scottish Government instruction to test all patients over 70 years old being admitted to hospital irrespective of displaying symptoms or not. This project sought to provide an initial analysis on what this change in testing criteria meant for the numbers of tests being undertaken for those in different age categories.

Chronic obstructive pulmonary disease (COPD) is a common lung condition, often caused by smoking. Patients living with COPD may suffer from shortness of breath and this can worsen unpredictably in flare-ups known as exacerbations. These often require hospital care. COPD is the commonest cause of emergency attendance to the hospital with breathlessness, and the third commonest cause of death worldwide. We plan to use health data from deidentified people with COPD to find risk factors for these exacerbations and other harmful outcomes including death. This will include using machine learning techniques, where advanced computers look for patterns in records that might otherwise be missed. Our aim is to create a new prediction tool that could be used to target care to patients identified at risk of deterioration. This is being delivered by Lenus Health in partnership with NHS Lothian to quickly move developments from this project into patient care.

Frailty and multi-morbidity are terms used to describe people at risk of worsening health, increasing disability and death. These are often older people who have multiple health problems and frequently present to health and social care services at a point of crisis. However, identifying these vulnerable people earlier may allow extra support and assessment to prevent such crises. There are multiple ways of identifying multi-morbid people, but our current record systems for primary care (GP practices) and secondary care (hospitals) are not well connected. In this project, we aim to bring data together data from GP and hospital records to provide a combined view of patients’ health. We will provide reports of multimorbidity that may be used to test new approaches to the care of these patients. No individual level patient data will be shared as part of this project.

‘Atrial fibrillation’ is the term used to describe an irregular heartbeat, a common condition that often requires treatment with blood-thinning medication (‘anticoagulation’) to reduce the risk of stroke. Until recently, most patients were treated with blood-thinning medication called warfarin. However, patients taking warfarin need regular blood tests to monitor the drug levels and can require dose changes following these blood tests.

However, new drugs called ‘Direct Oral Anticoagulants’ (DOACs) have recently been developed. In patients with atrial fibrillation and normal kidney function, these drugs are as safe and effective as warfarin, but without the need for any blood tests or dose changes, making them much more acceptable to patients. Few studies have looked at whether these drugs are safe and effective in patients with either very bad or very good kidney function. This is important because these extreme levels of kidney function can be quite common – perhaps affecting ~1 in 5 patients – and also because DOACs are mostly removed from the body by the kidneys. Therefore, it is easy to appreciate that abnormal kidney function might impact on the amount of drug left in your body.

Here, we will use a large dataset containing a range of reliable and accurate data collected as part of patient care to improve our understanding of the safety and effectiveness of DOACs, compared to warfarin or no anticoagulation treatment, in patients with atrial fibrillation and abnormal kidney function.

There have been reports of rare and specific blood clots after vaccination with Covid-19 vaccines. There is a need to determine this risk for individuals as early as possible. This study will determine if the risk can be identified during a hospital admission.