Prognostic Implications of Machine Learning Algorithm–Supported Diagnostic Classification of Myocardial Injury Using the Fourth Universal Definition of Myocardial Infarction

Background: With widespread adoption of high-sensitivity troponin assays, more individuals with myocardial injury are now identified, with type 1 myocardial infarction (T1MI) being less common despite having the most well-established evidence base to inform care. This study assesses the temporal time course of cardiovascular events among various forms of myocardial injury. 

Method: Consecutive hospital encounters were identified. Using the first episode of care during the sampling period, myocardial injury classifications (i.e., T1MI, acute injury/type 2 myocardial infarction [T2MI], chronic injury, and no injury) were established via two machine learning algorithms. The temporal time course of increased hazard for mortality, recurrent myocardial infarction, heart failure, and arrhythmia over 3 years were explored. 

Results: There were 176,787 index episodes; 6.9% were classified as T1MI, 6.0% as acute injury/T2MI, and 26.7% as chronic injury. Although each classification was associated with an early increased risk of all-cause mortality compared with no injury (incidence rate ratio [IRR]<30 days: T1MI: 19.97 [95% confidence interval 12.50–32.69]; acute injury/T2MI: 26.51 [16.80–42.97]; chronic injury: 15.37 [10.22–23.95]), the instantaneous relative hazard for recurrent myocardial infarction was highest in those with initial T1MI (IRR<30 days: T1MI: 28.81 [22.75–36.76]; acute injury/T2MI: 10.23 [7.60–13.77]; chronic injury:5.54 [4.34–7.41]). In contrast, the instantaneous hazard for heart failure in those with initial acute injury/T2MI and chronic injury remained increased over long-term follow up unlike in T1MI (IRR1 3 yrs: T1MI: 5.52 [4.99–6.09]; acute injury/T2MI: 10.36 [9.51–11.30]; chronic injury:7.40 [6.90–7.94]). 

Conclusions: The substantial and persistent rate of late cardiac events highlights the need to establish an evidence base for the therapeutic management of “non-T1MI” diagnostic classifications and suggests opportunity to improve late outcomes using existing and emerging therapies.