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
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