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A machine learning-based model for predicting sudden cardiac death risk in patients with dilated cardiomyopathy

A machine learning model for predicting ventricular arrhythmia risk in patients with ischemic or dilated cardiomyopathy: development and validation of a retrospective, multicenter cohort study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600127911
Enrollment
Unknown
Registered
2026-07-09
Start date
2026-08-01
Completion date
Unknown
Last updated
2026-07-13

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

Conditions

Ischemic Cardiomyopathy, Dilated Cardiomyopathy

Interventions

Dilated Cardiomyopathy Cohort:None

Sponsors

The First Affiliated Hospital of Guangxi Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1.Patients with DCM meeting the diagnostic criteria; 2.Willing to participate voluntarily, able to cooperate with follow-up visits, and provide signed informed consent.

Exclusion criteria

Exclusion criteria: 1. Age < 18 years or = 80 years at first visit; 2. History of cardiac arrest or hemodynamically unstable sustained ventricular arrhythmia prior to inclusion in this study; 3. History of implantable cardioverter-defibrillator (ICD) or cardiac resynchronization therapy (CRT) device implantation;

Design outcomes

Primary

MeasureTime frame
C-statistic for predicting sudden cardiac death;—

Countries

China

Contacts

Public ContactXiao Ma

The First Affiliated Hospital of Guangxi Medical University

330991216@qq.com+86 771 535 6618

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jul 23, 2026