Viewing Study NCT05208567


Ignite Creation Date: 2025-12-25 @ 12:31 AM
Ignite Modification Date: 2025-12-25 @ 10:38 PM
Study NCT ID: NCT05208567
Status: RECRUITING
Last Update Posted: 2024-11-21
First Post: 2022-01-21
Is NOT Gene Therapy: False
Has Adverse Events: False

Brief Title: London Valvular Heart Disease and Reduced Ejection Fraction Detection in a Multi-ethnic Community Using Cardiac Ultrasound
Sponsor: Queen Mary University of London
Organization:

Study Overview

Official Title: London Valvular Heart Disease and Reduced Ejection Fraction Detection in a Multi-ethnic Community Using Cardiac Ultrasound
Status: RECRUITING
Status Verified Date: 2024-11
Last Known Status: None
Delayed Posting: No
If Stopped, Why?: Not Stopped
Has Expanded Access: False
If Expanded Access, NCT#: N/A
Has Expanded Access, NCT# Status: N/A
Acronym: LOVE
Brief Summary: Heart Valve Disease and Heart failure contribute to 25% of hospital emergency admissions while heart failure alone has become one of the most common causes for hospitalisation in people over the age of 65. The burden of disease is likely to be high in a multi-ethnic community but there is a paucity of data. Management of heart valve disease requires appropriate surveillance and timely surgery. Similarly heart failure management requires treatment with medications aimed at slowing prevention of symptoms and preventing premature death. The NHS long term plan priorities early detection and treatment of valve disease and heart failure in order to reduce the burden on emergency services and improve the health of the population.

Diagnosis is made using cardiac ultrasound, however staff with the required skills-set are critically limited in the community.

The investigators will train non-expert staff within primary care to perform abbreviated cardiac ultrasound to detect heart valve disease or heart failure. This will be opportunistic scanning to reduce healthcare footfall.

All scans will be reviewed by an expert and the investigators will use the anonymised data to develop machine learning tools to begin working with academic partners to develop tools that can improve the reliability of diagnosis from ultrasound.

The investigators hope to identify the proportion with the above conditions in a multi-ethnic community and assess the feasibility of developing a program where staff can be trained for community detection, streamlined referrals can be created bridging the gap between primary and secondary care, reducing hospital emergency admissions, while ensuring patients are managed optimally.
Detailed Description: None

Study Oversight

Has Oversight DMC: False
Is a FDA Regulated Drug?: False
Is a FDA Regulated Device?: False
Is an Unapproved Device?: None
Is a PPSD?: None
Is a US Export?: None
Is an FDA AA801 Violation?: