PRIor Myocardial Infarction Identification on Electrocardiogram

Abstract Background: Chronic myocardial infarction (MI) is a serious cardiovascular disease associated with high mortality rates, making early diagnosis and timely intervention essential for improving patient outcomes. However, some patients may present without clear symptoms or relevant medical histories, complicating the diagnostic process. Currently, diagnosis predominantly relies on electrocardiograms (ECGs) and imaging tests. Although cardiac magnetic resonance imaging (MRI) is regarded as the gold standard, its high cost and complexity hinder its clinical application. Consequently, there is an urgent need for new ECG diagnostic criteria to mitigate the risks of misdiagnosis and missed diagnoses.

Objective: This study aims to explore new diagnostic criteria to enhance the accuracy of ECG diagnoses for chronic MI.

Methods: This research is a prospective, multicenter cohort study designed to assess the impact of newly developed ECG diagnostic criteria on the accuracy of chronic myocardial infarction (MI) diagnoses. The study spans a 60-month period, including a 12-month patient enrollment phase. Participants will comprise individuals aged 35 to 85 who meet the inclusion criteria: those diagnosed with chronic myocardial infarction via ECG, those with a definitive history of MI (≥3 months), or individuals clinically suspected of having coronary artery disease with at least two coronary risk factors. Data collection will include clinical symptoms, signs, ECG findings, and cardiac magnetic resonance (CMR) findings, the latter serving as a primary endpoint. Follow-up will focus on changes in patients' symptoms and ECG assessments. Statistical analysis software will be employed to evaluate the influence of the new diagnostic criteria on rates of missed and misdiagnosis.

Abstract Background: Chronic myocardial infarction (MI) is a serious cardiovascular disease associated with high mortality rates, making early diagnosis and timely intervention essential for improving patient outcomes. However, some patients may present without clear symptoms or relevant medical histories, complicating the diagnostic process. Currently, diagnosis predominantly relies on electrocardiograms (ECGs) and imaging tests. Although cardiac magnetic resonance imaging (MRI) is regarded as the gold standard, its high cost and complexity hinder its clinical application. Consequently, there is an urgent need for new ECG diagnostic criteria to mitigate the risks of misdiagnosis and missed diagnoses.

Objective: This study aims to explore new diagnostic criteria to enhance the accuracy of ECG diagnoses for chronic MI.

Methods: This research is a prospective, multicenter cohort study designed to assess the impact of newly developed ECG diagnostic criteria on the accuracy of chronic myocardial infarction (MI) diagnoses. The study spans a 60-month period, including a 12-month patient enrollment phase. Participants will comprise individuals aged 35 to 85 who meet the inclusion criteria: those diagnosed with chronic myocardial infarction via ECG, those with a definitive history of MI (≥3 months), or individuals clinically suspected of having coronary artery disease with at least two coronary risk factors. Data collection will include clinical symptoms, signs, ECG findings, and cardiac magnetic resonance (CMR) findings, the latter serving as a primary endpoint. Follow-up will focus on changes in patients' symptoms and ECG assessments. Statistical analysis software will be employed to evaluate the influence of the new diagnostic criteria on rates of missed and misdiagnosis.

Eligibility Criteria:
Inclusion Criteria:

* Aged between 35 and 85 years.
* Patients must meet at least one of the following conditions:

  * Diagnosis of prior MI based on ECG (as per the fourth universal definition of MI).
  * History of prior MI (≥3 months post-MI).
  * Any clinical suspicion of coronary artery disease (CAD) with at least two of the following risk factors:

Male age \>50 years or female age \>60 years. Diabetes mellitus. Hypertension. Hypercholesterolemia requiring medication. Family history of premature CAD (first-degree relatives: male ≤55 years, female ≤65 years).

Body mass index (BMI) ≥30 kg/m². History of peripheral vascular disease. History of coronary artery intervention or bypass surgery. Informed consent obtained

Exclusion Criteria:

* Life expectancy \<1 year due to non-cardiovascular diseases.
* Contraindications to cardiac MRI or inability to complete the examination.
* History of non-ischemic cardiomyopathy.
* History of heart transplantation.
* Acute MI within the past 30 days.
* During pregnancy.