MedTrace Logo

The PICM Risk Prediction Study - Application of AI to Pacing

NCT06449079 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 10000

Last updated 2024-06-07

No results posted yet for this study

Summary

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.

Conditions

  • Heart Failure
  • Pacemaker-Induced Cardiomyopathy
  • Pacemaker Complication

Interventions

OTHER

Machine learning

Analysis of data with machine learning methods

Sponsors & Collaborators

  • Imperial College Healthcare NHS Trust

    collaborator OTHER

  • King's College Hospital NHS Trust

    collaborator OTHER

  • Guy's and St Thomas' NHS Foundation Trust

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-07-30
Primary Completion
2026-10-30
Completion
2026-10-30

Countries

  • United Kingdom

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06449079 on ClinicalTrials.gov