Clinical trial NCT04981496: Novel ICD Arrhythmia Detection Algorithm
Official title: Improving Implantable Cardioverter-defibrillator Arrhythmia Detection: Development of a Novel Arrhythmia Detection Algorithm
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: ICD
Implantable Defibrillator User
Cardiomyopathies
Keywords: ICD
arrhythmia
algorithm
haemodynamic sensor
bipolar electrogram
Lead sponsor: Imperial College London
Sponsor class: OTHER
First posted: 2021-07-29
Enrollment: 90
Sex: ALL
Minimum age (years): 18
Maximum age (years): 99
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: OTHER
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Study A and B Patients who are having a clinically indicated ICD implantation or its battery replaced.

Study C Patients who already have an ICD implanted and are undergoing a clinically indicated VT ablation.

Study D Patients who already have an ICD implanted and are able to safely raise their heart rates through exercise.

Study E Patients who already have an ICD implanted and attend hospital with a spontaneous arrhythmia.

Brief summary: Implantable cardioverter defibrillators (ICD) are used to treat life-threatening heart rhythm disturbances (arrhythmias).

They have been proven to reduce the risk of sudden cardiac death; however, there are limitations with current ICDs. Firstly, they may deliver inappropriate therapies (therapies delivered in the absence of life-threatening arrhythmias). Secondly, slower life-threatening arrhythmias may be left untreated because current programming recommendations, designed to minimise inappropriate therapies, rely predominantly on heart rates. Therefore, there is considerable potential to make ICDs safer with more sophisticated ICD algorithms.

In this research study the investigators will collect data from participants with newly implanted or existing ICDs whilst they are in induced or spontaneously occurring abnormal rhythms. The data will come from sensors placed on the skin that can measure blood flow or electrical properties of the body. In addition, in 20 participants, the investigators will also collect further data from a small loop recorder implanted under the skin.

The investigators will use this data to help develop and validate new methods of reliably identifying life-threatening arrhythmias so that future ICDs deliver therapies when only needed.

The research is funded by the British Heart Foundation, and will take place at Hammersmith Hospital over 3 years. The investigators aim to recruit 100 patients in total.

Detailed description: This novel arrhythmia detection algorithm will incorporate a haemodynamic sensor and extra bipolar electrogram with an aim to outperform current commercially used arrhythmia detection algorithms that rely primarily on heart rate.

Eligibility criteria: Inclusion Criteria:

Study A and B

1. Patients referred for conventional defibrillator implantation or generator change.
2. Adults (age \> 18 years)
3. Willing to take part and able to give consent.

Study C

1. Patients with defibrillators who are undergoing a VT ablation.
2. Adults (age \> 18 years)
3. Willing to take part and able to give consent.

Study D

1. Patients with defibrillators already implanted who are able to exercise and raise their heart rate substantially
2. Adults (age \> 18 years)
3. Willing to take part and able to give consent.

Study E

1. Patients with a defibrillator already implanted admitted with atrial arrhythmias, ventricular tachycardia or RV lead fracture.
2. Adults (age \> 18 years)
3. Willing to take part and able to give consent.

Exclusion Criteria:

Exclusion criteria for studies A-E:

1. Unable to give consent.
2. Children (age \< 18 years)
3. Pregnant women.

Exclusion criteria for studies A and B if undergoing VF induction:

1. Intracardiac thrombus
2. AF without regular anticoagulation
3. Severe aortic stenosis
4. Severe ischaemic heart disease
5. Decompensated heart failure

Exclusion criteria for study D

1. Recent heart attack or stroke (within the last month)
2. Thromboembolic event undergoing active treatment
3. Severe aortic stenosis
4. Severe ischaemic heart disease
5. Hypertrophic obstructive cardiomyopathy
6. Uncontrolled ventricular arrhythmias
7. Physically unable to exercise, for example due to arthritis.

Primary outcomes:
measure: Outperforming current arrhythmia detection algorithms
timeFrame: 3 years
Secondary outcomes:
Other outcomes:
Locations:
city: London
country: United Kingdom
facility: Hammersmith Hospital
Study officials:
References: