Myocardial Infarction Prediction

Shiraz University of Medical Sciences1,100 enrolled

Overview

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

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

Allocation

NON_RANDOMIZED

Purpose

DIAGNOSTIC

Masking

QUADRUPLE

Enrollment

1,100

Conditions

Myocardial Infarction Artificial Neural Network

Interventions

ANN prediction of myocardial infarctionOTHER

Eligibility

Sex: ALLMin age: 40 YearsMax age: 72 Years

Medical Language ↔ Plain English

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.

Outcomes

Primary Outcomes

myocardial infarction

Time frame: 2 weeks

Secondary Outcomes

hospital admission due to cardiac events

may be includes unstable angina, cardiac arrest or PCIor CABG

Time frame: 2 weeks

Data from ClinicalTrials.gov

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