Abstract Body (Do not enter title and authors here): Background: The 4th Universal Definition of Myocardial Injury (UDMI) recognizes several categories of myocardial injury, including acute myocardial infarction (MI) which is further sub-classified into five types. However, data on these different types of myocardial injury and their risk factors is limited.

Methods: In the MESA study of 6814 participants, 15905 clinical events were identified over the first 14 years, 4079 of which meet MESA criteria for physician adjudication for a possible cardiovascular event. Herein, we developed a standardized data format and a REDCap tool with an interactive robust logic algorithm to re-adjudicate all 4079 cases for the presence and classification of all 9 types of myocardial injury as defined by the 4^th UDMI. Adjudication process as shown in Figure 1. The prevalence of myocardial injury types was evaluated using descriptive statistics, and adjudicator agreement was assessed using Cohen’s kappa (κ) statistics and percent agreement.

Results: Out of 4079 events, adjudication is completed on 2282, of which 15% classified into subtypes of myocardial injury. Adjudication was achieved for 91% of the events in phase 1, 7% in phase 2, 2% in phase 3. The overall agreement between two adjudicators for the presence of myocardial injury was 91% (κ: 0.67), but the agreement for the specific subtype was 53% (κ: 0.38). The most common events were Type 1 MI (N= 114), followed by Type 2 MI (N= 95), and Acute non-ischemic myocardial injury (N= 85) (Figure 2). Compared to the original MESA adjudication for the presence of MI, 97% (N= 72) of probable MI and 8% (N= 174) of no MI were reclassified into five and six types of myocardial injury events respectively.

Conclusion: This study highlights the complexities in identifying subtypes of myocardial injury based on current definition. This study provides a novel dataset to explore diverse correlations with these myocardial injury subtypes.