Utilising AI Analysis of Sounds To prEdict heaRt failurE decOmpensation

Summary

Heart failure impacts more than 2% of people in the UK (United Kingdom) and leads to about 5% of emergency hospital visits. Patients might have slowly worsening symptoms or suddenly face acute decompensated heart failure (ADHF), marked by intense difficulty in breathing due to fast-developing lung congestion. This is a serious emergency requiring in-hospital treatment and monitoring. Once stable, patients usually have a phase where symptoms remain constant. But as time goes on, those with heart failure often face more frequent and prolonged episodes of ADHF.

Fluid build-up (pulmonary congestion) in the lungs is a key issue in heart failure, and catching it early helps avoid unexpected hospital stays. Spotting these early signs outside the hospital can be tough, as symptoms aren't always clear. Study investigators are working on a new, non-invasive way to identify these early signs using AI (artificial intelligence) to analyse subtle changes in a patient's voice, cough, and breathing sounds. This tool will act as an early warning for patients and their heart care teams, allowing quicker treatment. This could make heart failure episodes less severe and reduce the need for hospital visits.

This research has two parts. First, a small pilot trial with up to 50 patients. The findings will guide and inform a larger study involving up to 200 patients. From this larger study, investigators will develop the final version of the AI algorithm. The results from the Part A and Part B of this research will guide the investigators in planning a future clinical trial. This trial will confirm if the AI algorithm can be effectively used as a medical tool for heart failure care within the NHS (National Health Service). Study investigators will seek the necessary ethical approval before starting this trial.

Conditions

• Heart Failure

Interventions

OTHER

Height, weight, and BMI

Height, weight measurement and BMI calculation

OTHER

Medical history

Brief medical history including medications/allergies and heart failure related healthcare utilisation over previous 12 months

OTHER

Physical examination

Brief physical examination

DIAGNOSTIC_TEST

Venous blood samples

Venous blood samples, to include WCC, HB, CRP and NTproBNP

OTHER

Resting vital signs

HR, BP, RR, oxygen saturations on air)

DIAGNOSTIC_TEST

Transthoracic echocardiogram

LVEF, IVC collapsibility, LV filling pressure, PA pressure

OTHER

Sound recordings

Sound recordings (voice/cough/chest) recorded with the in-built microphone in a smartphone

DIAGNOSTIC_TEST

Lung ultrasound

Lung ultrasound

OTHER

KCCQ questionnaire

Kansas City Cardiomyopathy Questionnaire

OTHER

ASCEND-HF score

An in-hospital congestion score which risk stratifies patients admitted with worsening heart failure, developed for the Acute study of clinical effectiveness of Nesiritide in decompensated heart failure trial

OTHER

Composite Everest congestion score

A shortened version of the original 18-point score from the EVEREST trial

DIAGNOSTIC_TEST

Bio impedance and total body water measurement

Bio impedance and total body water measurement using TANITA device

Sponsors & Collaborators

• University of Cambridge

  collaborator OTHER

• Cambridge University Hospitals NHS Foundation Trust

  lead OTHER

Principal Investigators

• Joseph Cheriyan · Cambridge University Hospitals NHS Foundation Trust

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2024-09-18

Primary Completion

2027-08-15

Completion

2027-08-15

Countries

• United Kingdom

Study Locations