Development of a successful novel technology for sudden cardiac death risk stratification for clinical use - LifeMap
Development of a successful novel technology for sudden cardiac death risk stratification for clinical use - LifeMap
批准号:
MR/S037306/1
负责人:
Ghulam Ng
金额:
$103.6万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --
中文摘要
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英文摘要
Sudden Cardiac Death (SCD) is responsible for over 3 million deaths worldwide annually, 100,000 deaths in the UK alone. People die because their heart suddenly develops a lethal heart rhythm that stops it from coordinating and working as a pump. An implantable cardioverter defibrillator (ICD) is a small, £10,000 device, similar to a pacemaker that is placed under the skin, around the shoulder in a small operation. The ICD then sits quietly monitoring the heart; it can detect a lethal heart rhythm in seconds and treat it to restore normal function sometimes without the patient even being aware that their life has been saved. Unfortunately, we lack an effective means to work out who really needs an ICD. Current guidelines are based on crude clinical information and only 40% of ICD recipients deemed "high-risk" by these guidelines ever make use of them during the first 5 years of follow up. On the other hand, the majority of people who die of SCD may have a risk factor, such as a previous myocardial infarction (heart attack) but the guidelines regard them as "low-risk". For these patients there is currently no way of working out who truly is at low risk and who really needs an ICD to protect them. We have developed two novel ECG markers based on patented algorithms with supportive clinical scientific evidence in different patient populations. This innovative test is called LifeMap and has been shown to be highly effective for risk assessment of sudden cardiac death. LifeMap analyses the ECG over a spectrum of heart rates and can be performed either in a 10 minute minimally invasive procedure or with exercise. This proposal aims to translate the currently laborious research technique into an effective clinical tool by automating the software, creating a user interface and making it straightforward to acquire clean exercise ECG signals. This grant would bring LifeMap to the next phase of development; ready for a large scale clinical trial following which it could be implemented into daily practice.
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DOI:
10.3389/fphys.2022.946718
发表时间:
2022
期刊:
Frontiers in physiology
影响因子:
4
作者:
[]
通讯作者:
DOI:
10.23919/cinc53138.2021.9662757
发表时间:
2021-09
期刊:
2021 Computing in Cardiology (CinC)
影响因子:
--
作者:
[Long Chen;Zheheng Jiang;T. Almeida;F. Schlindwein;Jakevir S. Shoker;André Ng;Huiyu Zhou;Xin Li]
通讯作者:
Long Chen;Zheheng Jiang;T. Almeida;F. Schlindwein;Jakevir S. Shoker;André Ng;Huiyu Zhou;Xin Li
DOI:
10.3389/fphys.2022.826449
发表时间:
2022
期刊:
Frontiers in physiology
影响因子:
4
作者:
[Chu GS, Li X, Stafford PJ, Vanheusden FJ, Salinet JL, Almeida TP, Dastagir N, Sandilands AJ, Kirchhof P, Schlindwein FS, Ng GA]
通讯作者:
Ng GA
DOI:
10.1007/s10840-022-01351-5
发表时间:
2023-03
期刊:
JOURNAL OF INTERVENTIONAL CARDIAC ELECTROPHYSIOLOGY
影响因子:
1.8
作者:
[Chu, Gavin, Calvert, Peter, Sidhu, Bharat, Mavilakandy, Akash, Kotb, Ahmed, Tovmassian, Lilith, Kozhuharov, Nikola, Bierme, Cedric, Denham, Nathan, Pius, Charlene, O'Brien, Jim, Ding, Wern Yew, Luther, Vishal, Snowdon, Richard L., Ng, G. Andre, Gupta, Dhiraj]
通讯作者:
Gupta, Dhiraj
DOI:
10.1109/tbme.2024.3363077
发表时间:
2024-07-01
期刊:
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
影响因子:
4.6
作者:
[Chen,Long, Jiang,Zheheng, Li,Xin]
通讯作者:
Li,Xin
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