Viewing Study NCT07057492


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Study NCT ID: NCT07057492
Status: COMPLETED
Last Update Posted: 2025-07-09
First Post: 2025-07-02
Is NOT Gene Therapy: True
Has Adverse Events: False

Brief Title: A Prospective Multicenter Clinical Study on the Long-term Prognosis of Patients With ST-segment Elevation Myocardial Infarction Using Cardiac Magnetic Resonance Imaging.
Sponsor: Chinese PLA General Hospital
Organization:

Study Overview

Official Title: A Prospective Multicenter Clinical Study on the Long-term Prognosis of Patients With ST-segment Elevation Myocardial Infarction Using Cardiac Magnetic Resonance Imaging.
Status: COMPLETED
Status Verified Date: 2018-01
Last Known Status: None
Delayed Posting: No
If Stopped, Why?: Not Stopped
Has Expanded Access: False
If Expanded Access, NCT#: N/A
Has Expanded Access, NCT# Status: N/A
Acronym: None
Brief Summary: This prospective, multicenter study was designed to develop and validate a risk prediction model for major adverse cardiovascular events (MACE) in patients with acute ST-segment elevation myocardial infarction (STEMI) based on cardiac magnetic resonance (CMR) parameters.

From January 2018 to December 2023, consecutive acute STEMI patients who underwent primary percutaneous coronary intervention (PCI) were enrolled across eight participating medical centers. Baseline clinical characteristics were systematically collected, and all patients underwent CMR examination 5-7 days after PCI to assess myocardial injury and functional parameters. The primary composite endpoint, MACE, included cardiovascular death, recurrent myocardial infarction, hospitalization for heart failure, and unplanned revascularization.

To ensure robust model development and validation, the study assigned patients from four centers to form the development cohort, while those from the other four centers constituted the external validation cohort. Predictive variables were initially screened using least absolute shrinkage and selection operator (LASSO) regression, followed by multivariable Cox proportional hazards regression to identify independent predictors. A nomogram was subsequently constructed to provide individualized risk stratification. Model performance was evaluated in terms of discrimination (C-index, ROC analysis), calibration (calibration curves), and clinical utility (decision curve analysis).

This study aims to develop a CMR-based prediction model to better identify high-risk STEMI patients, providing clinicians with valuable tools for early intervention and personalized management.
Detailed Description: None

Study Oversight

Has Oversight DMC: None
Is a FDA Regulated Drug?: False
Is a FDA Regulated Device?: False
Is an Unapproved Device?: None
Is a PPSD?: None
Is a US Export?: None
Is an FDA AA801 Violation?: