The goal of this study is to test the accuracy of new blood and urine tests in people with heart failure. The main question it aims to answer is: \- Do new blood and urine tests correlate with fluid status? This will be determined by comparison to routine and gold-standard tests in a range of patients with heart failure.
Heart failure (HF) is a common condition that is associated with recurrent and prolonged hospital admissions (hospitalisation). HF hospitalisation is associated with poor outcomes and therefore the identification of patients at risk of HF hospitalisation, and avoidance of these events, is of great importance. HF hospitalisations are frequently preceded by a period of increasing congestion (pressure elevation within heart chambers and excess body fluid). The identification of congestion can be difficult. Current tests have limitations and signs of congestion such as lung crackles or leg swelling that can be recognised by health care professionals are often seen at a late stage before an intervention can be made to prevent hospitalisation. Reliably identifying congestion prior to the development of these signs would facilitate earlier intervention (treatment to de-congest) and may prevent hospitalisations. Patients who do require hospital admission are often discharged with residual congestion which is associated with readmission and increased risk of death. Tests that correlate closely with the degree of congestion and track with decongestion could guide therapy and help with decision-making about suitability for hospital discharge. The investigators propose to recruit 140 patients. Patients will be identified during hospitalisation with HF or prior to implantation of a cardiac resynchronisation therapy (CRT) device. Each patient will have a history, physical examination, electrocardiogram (ECG), echocardiogram (cardiac ultrasound) and lung ultrasound performed. Some patients will have a procedure to record pressure measurements within the heart (right heart catheterisation) if clinically indicated as routine care. Blood and urine tests will also be taken. The aim of this study is to evaluate the accuracy of novel blood and urine tests at measuring congestion compared with standard assessments. This may help in the discovery and development of new and improved tests for assessing congestion.
Study Type
OBSERVATIONAL
Enrollment
140
Urine and circulating blood biomarkers in all cohorts
Golden Jubilee National Hospital
Clydebank, United Kingdom
Queen Elizabeth University Hospital
Glasgow, United Kingdom
Correlation between concentrations of circulating biomarkers of congestion and pulmonary capillary wedge pressure (PCWP) and right atrial pressure (RAP).
Cohorts A/B - patients with heart failure (HF) undergoing right heart catheterisation (RHC): to determine the correlation between concentrations of circulating biomarkers of congestion and PCWP and RAP.
Time frame: 18 months
Correlation of change in congestion measured by concentrations of circulating biomarkers of congestion and change in lung ultrasound (LUS)
Cohort C: to determine the correlation of change in congestion measured by concentrations of circulating biomarkers of congestion and change in LUS.
Time frame: 18 months
Correlation of change in congestion measured by concentrations of circulating biomarkers of congestion and change in weight.
Cohort C: to determine the correlation of change in congestion measured by concentrations of circulating biomarkers of congestion and change in weight.
Time frame: 18 months
Correlation between congestion measured by concentrations of circulating biomarkers of congestion and physical signs (including EVEREST clinical congestion score [ECCS] and degree of pulmonary oedema).
Cohorts A/B/C: to determine the correlation between congestion measured by concentrations of circulating biomarkers of congestion and physical signs (including ECCS and degree of pulmonary oedema).
Time frame: 18 months
Correlation between congestion measured by concentrations of circulating biomarkers of congestion and LUS.
Cohorts A/B/C: to determine the correlation between congestion measured by concentrations of circulating biomarkers of congestion and LUS.
Time frame: 18 months
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.
Correlation between congestion measured by concentrations of circulating biomarkers of congestion and transthoracic echocardiography (TTE).
Cohorts A/B/C: to determine the correlation between congestion measured by concentrations of circulating biomarkers of congestion and TTE.
Time frame: 18 months
Correlation of change in congestion measured by change in concentrations of circulating biomarkers and change in congestion measured by physical signs (including ECCS and degree of pulmonary oedema).
Cohort C: to determine the correlation of change in congestion measured by change in concentrations of circulating biomarkers and change in congestion measured by physical signs (including ECCS and degree of pulmonary oedema).
Time frame: 18 months
Correlation of change in congestion measured by change in concentrations of circulating biomarkers and change in congestion measured by TTE.
Cohort C: to determine the correlation of change in congestion measured by change in concentrations of circulating biomarkers and change in congestion measured by TTE.
Time frame: 18 months
Correlation between congestion measured by TTE and PCWP and RAP.
Cohort A/B: to determine the correlation between congestion measured by TTE and PCWP and RAP.
Time frame: 18 months
Correlation between congestion measured by LUS and PCWP and RAP.
Cohort A/B: to determine the correlation between congestion measured by LUS and PCWP and RAP.
Time frame: 18 months