Myocardial Infarction Prediction

June 4, 2013 updated by: Javad Kojuri, Shiraz University of Medical Sciences

Prediction of Acute Myocardial Infarction With Artificial Neural Networks in Patients With Nondiagnostic Electrocardiogram

prediction of MI in patients with chest pain and nondiagnostic ECG was done in 2 weeks

Study Overview

Detailed Description

Myocardial infarction remains one the leading causes of mortality and morbidity and involves a high cost of care. Early prediction can be helpful in preventing the development of myocardial infarction with appropriate diagnosis and treatment. Artificial neural networks have opened new horizons in learning about the natural history of diseases and predicting cardiac disease.

Methods: A total of 935 cardiac patients with chest pain and nondiagnostic electrocardiogram (ECG) were enrolled and followed for 2 weeks in two groups based on the appearance of myocardial infarction. Two types of data were used for all patients: nominal (clinical data) and quantitative (ECG findings). Two different artificial neural networks - radial basis function (RBF) and multi-layer perceptron (MLP) - were used.

Study Type

Interventional

Enrollment (Actual)

1100

Phase

  • Not Applicable

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

40 years to 72 years (ADULT, OLDER_ADULT)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

Inclusion Criteria:

  • patient with chest pain refered to ER with nondiagnostic ECG

Exclusion Criteria:

  • 1) Absence of a history of myocardial infarction
  • 2) Absence of bundle branch block, Wolf-Parkinson-White abnormality, ventricular hypertrophy or previous ECG signs of myocardial infarction,
  • 3) Absence of a history of percutaneous coronary surgery or coronary artery bypass grafting,
  • 4) Absence of ECG abnormalities attributable to drugs such as digoxin or tricyclic antidepressants.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: DIAGNOSTIC
  • Allocation: NON_RANDOMIZED
  • Interventional Model: PARALLEL
  • Masking: QUADRUPLE

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
PLACEBO_COMPARATOR: those without MI in 2 weeks
patient without MI in 2 weeks
Other Names:
  • sofware detected risk of new myocardial infraction
ACTIVE_COMPARATOR: patient with MI
group with MI in 2 weeks
Other Names:
  • sofware detected risk of new myocardial infraction

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
myocardial infarction
Time Frame: 2 weeks
2 weeks

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
hospital admission due to cardiac events
Time Frame: 2 weeks
may be includes unstable angina, cardiac arrest or PCIor CABG
2 weeks

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start

January 1, 2011

Primary Completion (ACTUAL)

April 1, 2012

Study Completion (ACTUAL)

June 1, 2012

Study Registration Dates

First Submitted

May 24, 2013

First Submitted That Met QC Criteria

June 4, 2013

First Posted (ESTIMATE)

June 6, 2013

Study Record Updates

Last Update Posted (ESTIMATE)

June 6, 2013

Last Update Submitted That Met QC Criteria

June 4, 2013

Last Verified

June 1, 2013

More Information

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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