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Specific Electrophenotypes in Atrial Fibrillation

IdeNtification of SPecific EleCTrophenotypes in Atrial Fibrillation

Status
Terminated
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05366530
Acronym
INSPECT-AF
Enrollment
1
Registered
2022-05-09
Start date
2022-05-19
Completion date
2024-08-27
Last updated
2026-03-12

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Atrial Fibrillation

Brief summary

This study will investigate a common heart rhythm disturbance (arrhythmia), atrial fibrillation (AF), to improve understanding of how best to treat it in different patients. Direct current cardioversion (DCCV) is a procedure that can revert the heart to a normal rhythm, however almost all patients will only have a transient benefit, and their heart will return to the abnormal rhythm, AF. Ablation is an invasive procedure that creates scar tissue within the heart to reduce the arrhythmias, with a longer lasting effect than DCCV. It has been used with success in AF that occurs occasionally (paroxysmal) but is not as effective in AF that is more long-lasting, also known as persistent AF. Persistent AF is major cause of symptoms of breathlessness and palpitations and significantly increases the risk of stroke. Doctors are unable to accurately predict which patients will benefit most from an ablation, this can lead to as many as 50% of patients not benefitting from the procedure. The aim is to better predict which patients will benefit from an ablation. The study will include patients undergoing AF ablation or DCCV and perform additional tests including blood tests a heart MRI scan, a special type of heart tracing with up to 252 points and a short period of extra recordings from within the heart during the ablation procedure. Several techniques will be used to analyse this data, including machine learning, to develop a means predict which patients will benefit the most from the ablation procedure, without needing to use any recordings from within the heart.

Interventions

OTHERBiomarkers, electrocardiographic imaging, intracardiac electrograms, cardiac magnetic resonance imaging

ECGi is a non-invasive body surface mapping technique that collects electrocardiographic data using 252 leads, and combines it with subject specific anatomic data acquired from cross sectional imaging to recreate epicardial electrograms.

Sponsors

Imperial College London
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 85 Years
Healthy volunteers
No

Inclusion criteria

* Suitable candidate for catheter mapping/ablation for arrhythmias or direct current cardioversion for atrial fibrillation * Signed Informed Consent

Exclusion criteria

* Severe cerebrovascular disease * Moderate to severe renal impairment (eGFR \< 30) * Active gastrointestinal bleeding * Active infection or fever * Short life expectancy * Significant anaemia * Severe uncontrolled systemic hypertension * Severe electrolyte imbalance * Congestive heart failure - NYHA Class IV * Recent myocardial infarction * Bleeding or clotting disorders * Uncontrolled diabetes * Inability to receive IV or oral Anticoagulants * Unable to give informed consent * Pregnancy

Design outcomes

Primary

MeasureTime frameDescription
Freedom From Atrial Fibrillation1 yearPercentage of patients who do not have a recurrence of atrial fibrillation

Countries

United Kingdom

Baseline characteristics

Characteristic
Age, Categorical
<=18 years
0 Participants
Age, Categorical
>=65 years
1 Participants
Age, Categorical
Between 18 and 65 years
0 Participants
Region of Enrollment
United Kingdom
1 participants
Sex: Female, Male
Female
0 Participants
Sex: Female, Male
Male
1 Participants

Adverse events

Event typeEG000
affected / at risk
deaths
Total, all-cause mortality
0 / 1
other
Total, other adverse events
0 / 1
serious
Total, serious adverse events
0 / 1

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Mar 13, 2026