The PICM Risk Prediction Study - Application of AI to Pacing

Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorGuy's and St Thomas' NHS Foundation Trust

About this trial

Development of pacing induced cardiomyopathy (PICM) is correlated to a high morbidity as signified by an increase in heart failure admissions and mortality. At present a lack of data leads to a failure to identify patients who are at risk of PICM and would benefit from pre-selection to physiological pacing. In the light of the foregoing, there is an urgent need for novel non-invasive detection techniques which would aid risk stratification, offer a better understanding of the prevalence and incidence of PICM in individuals with pacing devices and the contribution of additional risk factors.

Eligibility criteria

Qualifiers

All patients who received a pacing device (VVI, DDD, ICD, leadless pacemaker) from the GSTT/RBH/KCH/ICH database in the last 10 years (from 01/01/2014)

All patients who are >18 years old.

Male and Female

Disqualifiers

Patients who did not receive a pacing device (VVI, DDD, ICD, leadless pacemaker)

All patients <18 years old

Patients with congenital heart disease

Patients who have received artificial heart valves or underwent cardiac bypass surgery

Trial design

Treatments tested in this trial

  • Machine learning

Treatment groups

10,000 Participants
are divided into 2 treatment groups

Sponsors and collaborators

Guy's and St Thomas' NHS Foundation Trust

Lead sponsor

Imperial College Healthcare NHS Trust

Collaborator

King's College Hospital NHS Trust

Collaborator