A Multicenter Study on Early Diagnosis of NSTE-ACS Patients Based on Machine Learning Model

NCT04682756 | Unknown

• 1 other identifier: XMa
• Study Type: observational
• Target: 2,500
• Locations: 1 country
• Sites: 1

Brief Summary

Early diagnosis of NSTEMI and UA patients is mainly through the construction of machine learning model.

Conditions

NSTEMI - Non-ST Segment Elevation MI; Unstable Angina

Keywords

NSTEMI; UA; Machine Learning

Outcome Measures

Primary Outcomes (1)

• Accurate diagnosis of NSTEMI from patients with acute chest pain

  NSTEMI patients are accurately diagnosed from patients with acute chest pain through a trained machine learning algorithm. Our model uses multi-fold cross-validation and ROC-AUC curve as the measurement index, 75% of the data are modeled, and 25% of the data verify the effect of the model. For this reason, we will calculate the accuracy, specificity and likelihood ratio when the sensitivity cutoff value is 0.9.

  Within 1 year

Study Arms (2)

CNN model

Electronic health information of NSTEMI and UA patients in two chest pain centers from 2017 to 2019 was collected，After manual labeling, the characteristics of patient admission records were selected, and through the construction of one-dimensional convolution (CNN) model. Taking the multi-fold cross-validation and ROC-AUC curve as the measurement index, 75% of the data are modeled and 25% of the data are used to verify the effect of the model.

Diagnostic Test: The model of machine learning

XG boost

Through the construction of XG boost model,taking the multi-fold cross-validation and ROC-AUC curve as the measurement index, 75% of the data are modeled and 25% of the data are used to verify the effect of the model.

Diagnostic Test: The model of machine learning

Interventions

The model of machine learning DIAGNOSTIC_TEST

Early diagnosis of NTEMI patients by machine learning model

CNN model; XG boost

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients with NSTEMI and UA were included in the Chest Pain Center of the First Affiliated Hospital of Xinjiang Medical University and the First Affiliated Hospital of Medical College of Shihezi University from 2017 to 2019.

You may qualify if:

• Patients were included and excluded strictly according to the diagnostic criteria of Chinese guidelines for diagnosis and treatment of Non-STsegment elevation acute coronary syndrome (2016). The patients were admitted to the hospital with chest pain as the main complaint, and were admitted to the first affiliated Hospital of Xinjiang Medical University and the first affiliated Hospital of Medical College of Shihezi Univ- ersity. the patients were diagnosed as NSTEMI and UA by coronary angiography (age range from 30 to 75 years old).

You may not qualify if:

• \- 1. Patients with STEMI, aortic dissecting aneurysm, pneumothorax and other non-cardiogenic chest pain. 2.Severe hepatorenal failure, primary tumor without surgical treatment, non-severe infection complicated with shock and pregnant women. 3.Previous severe valvular disease, viral myocarditis, pericardial effusion, cardiac pacemaker implantation, cardiogenic shock with serious complications, hypertensive heart disease, various cardiomyopathy, congenital heart disease, etc.
• Patients with heart disease, AECOPD, lung tumor and hyperthyroidism were diagnosed in the past.

Sponsors & Collaborators

• First Affiliated Hospital of Xinjiang Medical University: lead
• Shihezi University: collaborator

Study Sites (1)

The first affiliated Hospital of Xinjiang Medical University

Ürümqi, Xinjiang, 830000, China

Location

Related Publications (15)

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MeSH Terms

Conditions

Non-ST Elevated Myocardial Infarction; Angina, Unstable

Condition Hierarchy (Ancestors)

Myocardial Infarction; Myocardial Ischemia; Heart Diseases; Cardiovascular Diseases; Vascular Diseases; Infarction; Ischemia; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Necrosis; Angina Pectoris; Chest Pain; Pain; Neurologic Manifestations; Signs and Symptoms

Study Officials

• Aikeliyaer Ainiwaer, M.D

  First Affiliated Hospital of Xinjiang Medical University

  PRINCIPAL INVESTIGATOR

• Quan Qi, Ph.D

  College of Information and Technology, Shihezi University

  STUDY DIRECTOR

• Yi Ying Du, M.D

  First Affiliated Hospital of Xinjiang Medical University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: OTHER
• Target Duration: 3 Months
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Department of Cardiology

Study Record Dates

• First Submitted: December 19, 2020
• First Posted: December 24, 2020
• Study Start: December 20, 2020
• Primary Completion: December 20, 2021
• Study Completion: June 1, 2022
• Last Updated: December 31, 2020

Record last verified: 2020-12

Locations

CN (1)