Biomarkers for the Assessment of Congestion in Patients With Ambulatory and Hospitalised Heart Failure

Heart Failure Clinical Trial

— BIO-CONGEST  

Official title:

Biomarkers for the Assessment of Congestion in Patients With Ambulatory and Hospitalised Heart Failure

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT06459999
• Other study ID #: GN23CA095
• Status: Not yet recruiting
• Start date: June 2024
• Est. completion date: December 2025

Study information

• Verified date: June 2024
• Source: NHS Greater Glasgow and Clyde
• Contact: Kieran F Docherty, MBChB, PhD
• Phone: 01413301672
• Email: kieran.docherty[@]glasgow.ac.uk
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

Description:

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.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 140
• Est. completion date: December 2025
• Est. primary completion date: September 2025
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Written informed consent.

• Male or female =18 years of age.

• Cohort A

• Meet European Society of Cardiology (ESC) criteria for diagnosis of HF1, including HF with reduced (HFrEF), mildly reduced (HFmrEF) and preserved ejection fractions (HFpEF).

• Hospitalised for the management of HF or outpatients.

• Undergoing clinically-indicated RHC or repeat clinically-indicated RHC.

• Cohort B

• Meet ESC criteria for diagnosis of HFrEF.

• Undergoing implantation of CRT device and a simultaneous clinically-indicated RHC.

• Cohort C

• Meet ESC criteria for diagnosis of HF, including HFrEF, HFmrEF, HFpEF.

• Requiring treatment with IV diuretics.

Exclusion Criteria:

• Unwilling to consent.

• Unable to consent to inclusion in study due to cognitive impairment.

• Previously enrolled in the BIO-CONGEST study.

• Current participation in a blinded drug interventional trial (or treatment within four weeks).

• Pregnancy or breast-feeding (cohorts A + B where applicable).

• Currently uncontrolled cardiac arrhythmia.

• Severe aortic valvular disease.

• Increased body mass index where satisfactory echocardiographic images are not possible.

• Conditions that may confound congestion assessments in the opinion of the investigator, including: severe obstructive lung disease, severe fibrotic lung disease, severe liver disease, relevant active malignancy including lung cancer, pelvic cancer with caval compression, superior vena cava (SVC) obstruction syndrome, active viral or bacterial bronchopneumonia - chest x-ray (CXR) within four weeks showing consolidation, pulmonary contusion, pneumothorax, pneumonectomy, lobectomy, pulmonary embolism within the previous three months, indwelling intercostal chest drain, left ventricular assist device (LVAD), COVID-19 infection, type-1 acute myocardial infarction.

Related Conditions & MeSH terms

• Congestion
• Heart Failure

Intervention

Diagnostic Test:
• Urine and circulating blood biomarkers
Urine and circulating blood biomarkers in all cohorts

Locations

Country	Name	City	State
United Kingdom	Golden Jubilee National Hospital	Clydebank
United Kingdom	Queen Elizabeth University Hospital	Glasgow

Sponsors (3)

Lead Sponsor	Collaborator
NHS Greater Glasgow and Clyde	Roche Diagnostics GmbH, University of Glasgow

Country where clinical trial is conducted

United Kingdom, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Correlation between concentrations of circulating biomarkers of congestion and measures derived from RHC: right ventricle (RV) pressure, pulmonary artery (PA) pressure.	Cohort A/B: correlation coefficient between concentrations of circulating biomarkers of congestion and measures derived from RHC: right ventricle (RV) pressure, pulmonary artery (PA) pressure.	18 months
Other	Correlation between change in concentrations of circulating biomarkers of congestion and change in other measures of congestion (as description below).	Cohort A (in those undergoing repeat RHC): correlation coefficient between change in concentrations of circulating biomarkers of congestion and change in: PCWP and RAP.; Number of B-lines on LUS.; Weight.; Measures derived from RHC (RV, PA pressures).; Measures derived from TTE (including IVC size, TR Vmax and E/e').; Physical signs of congestion (including ECCS and degree of pulmonary oedema).	18 months
Other	Regression analyses between frequency of rehospitalization or death and circulating biomarkers of congestion during hospital admission.	Cohort C: Regression analyses between frequency of rehospitalization or death within 3 months after discharge and: Concentrations of circulating biomarkers of congestion from the first blood draw.; Concentrations of circulating biomarkers of congestion from the last blood draw.; Change in concentrations of circulating biomarkers of congestion.	18 months
Primary	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.	18 months
Primary	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.	18 months
Primary	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.	18 months
Secondary	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).	18 months
Secondary	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.	18 months
Secondary	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.	18 months
Secondary	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).	18 months
Secondary	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.	18 months
Secondary	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.	18 months
Secondary	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.	18 months