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The application of machine learning to predict the occurrence of arrhythmia after acute myocardial infarction

The application of machine learning to predict the occurrence of arrhythmia after acute myocardial infarction

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2100041960
Enrollment
Unknown
Registered
2021-01-10
Start date
2021-01-15
Completion date
Unknown
Last updated
2021-03-30

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

Conditions

Acute myocardial infarction

Interventions

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Sponsors

The First Affiliated Hospital of Harbin Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1. From January 2014 to January 2019, he visited the First Affiliated Hospital of Harbin Medical University, 2. Patients over 18 years old diagnosed with acute myocardial infarction. 3. All patients underwent coronary angiography, transthoracic three-dimensional echocardiography and 24-hour Holter.

Exclusion criteria

Exclusion criteria: 1. Subjects with incomplete clinical data record; 2. The subjects who had been confirmed to have some kind of arrhythmia in the past; 3. Subjects without PCI after admission; 4. Subjects with hypertrophic cardiomyopathy, myocarditis, valvular heart disease, cor pulmonale and autoimmune diseases; 5. Patients with malignant tumor and undergoing radiotherapy and chemotherapy.

Design outcomes

Primary

MeasureTime frame
Accuracy;

Countries

China

Contacts

Public ContactJingjie Li

The Frist Affiliated Hospital of Harbin Medical University

circulation9999@163.com+86 13359999353

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 20, 2026