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

Abstract

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.