Artificial Intelligence With Deep Learning and Genes on Cardiovascular Disease

NCT03877614 | Unknown

• 1 other identifier: A-ER-107-149
• Study Type: observational
• Target: 5,000
• Locations: 1 country
• Sites: 1

Brief Summary

An association study with large database from electronic medical record system, images, outcome analysis and genetic single nucleotide polymorphism variations by machine learning and artificial intelligence methods in a Taiwanese and Chinese medical center based population

Conditions

Cardiovascular Diseases

Outcome Measures

Primary Outcomes (1)

• Major cardiovascular events

  The rate of myocardial infarction, stroke, death, cardiovascular death, heart failure with hospitalization

  5 years

Secondary Outcomes (4)

• Heart function changes

  5 years

• Lipid profiles

  5 years

• Arrhythmia events

  5 years

• Recurrent acute coronary events

  5 years

Study Arms (2)

Cardiovascular high-risk (disease) group

A. Coronary artery disease B. Congestive heart failure with reduced ejection fraction C. Hypertrophic cardiomyopathy D. Atrial fibrillation E. Pulmonary hypertension F. Fabry's disease

Other: ASCVD risk score

Cardiovascular Low-risk (control) group

Patient with only risk factors with ASCVD score\<10% will be recognized as the comparison group

Other: ASCVD risk score

Interventions

ASCVD risk score OTHER

ASCVD score\< 10% will be in the control or low-risk group

Cardiovascular Low-risk (control) group; Cardiovascular high-risk (disease) group

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Pipeline for case enrollment: 1. We will enroll investigating subjects from the clinics of near 10 physicians screened by our assistant or physicians themselves, with nearly 100-120 cases/month. According to our initial experience during our previous hospital-based grant in 2018 showed feasible case number to be enrolled, nearly 1000 case within 3 months enrollment. In total, we plan to recruit 5000 subjects with cardiovascular disease or with risk factors within 3 years. (IRB approval A-ER-107-149) 2. Our study subjects will be evaluated whether they fulfill the cases criteria by an independent physician every month. 3. In comparison with disease, the risk factor only group (500 cases) will be the matching group on genetic background and outcome comparison.

You may qualify if:

• Patients' selection criteria and enrollment plan:
• We will enroll subjects from either cardiovascular clinics or inpatients from the National Cheng Kung University Hospital from 2018 to 2021 after the signature of inform consent from patients and their families. The major enrollment criteria include one of the flowing diseases or conditions:
• A. Coronary artery disease:
• History of myocardial infarction
• Coronary artery disease with computer tomography angiography image study with at least one vessel luminal stenosis \>70%
• Coronary artery stents implantation by hospital-based image database
• Thallium-201 scan positive/treadmill test positive with additional 2 risk factors, including
• Diabetes mellitus
• Hypertension
• Dyslipidemia
• Family history of sudden death, coronary bypass surgery, cerebral vascular attacks (CVA), premature myocardial infarction
• Smoking behaviors
• B. Congestive heart failure with reduced ejection fraction
• \. Echocardiography left ventricular ejection fraction \<40%
• C. Hypertrophic cardiomyopathy:

You may not qualify if:

• Patients unwilling to be enrolled
• Concentration of DNA collection was inadequate after 3 times of collection

Sponsors & Collaborators

• National Cheng-Kung University Hospital: lead

Study Sites (1)

Department of Internal Medicine, National Cheng Kung University Hospital

Tainan, 704, Taiwan

RECRUITING

Related Publications (2)

• Hsu YL, Huang MS, Chang HY, Lee CH, Chen DP, Li YH, Chao TH, Liu YW, Liu PY. Application of genetic risk score for in-stent restenosis of second- and third-generation drug-eluting stents in geriatric patients. BMC Geriatr. 2023 Jul 19;23(1):443. doi: 10.1186/s12877-023-04103-w.

  PMID: 37468836 DERIVED

• Lee PT, Huang MH, Huang TC, Hsu CH, Lin SH, Liu PY. High Burden of Premature Ventricular Complex Increases the Risk of New-Onset Atrial Fibrillation. J Am Heart Assoc. 2023 Feb 21;12(4):e027674. doi: 10.1161/JAHA.122.027674. Epub 2023 Feb 15.

  PMID: 36789835 DERIVED

Biospecimen

Retention: SAMPLES WITH DNA

Salivary DNA with genetic polymorphism chips comparative analysis

MeSH Terms

Conditions

Cardiovascular Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director of Cardiology, Internal Medicine and Professor of Institute of Clinical Medicine

Study Record Dates

• First Submitted: March 8, 2019
• First Posted: March 15, 2019
• Study Start: August 28, 2018
• Primary Completion: December 1, 2021
• Study Completion: June 1, 2022
• Last Updated: March 15, 2019

Record last verified: 2019-03

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)