The Universal Myocardial infarction (MI) definition divides MIs into different types. Type 1 MIs (T1MI) result spontaneously from atherosclerotic plaque instability. Type 2 MIs (T2MI) are due to secondary causes of myocardial oxygen demand/supply mismatch such as occurs with sepsis. T2MI are much more common among those with HIV than in the general population. T1MI and T2MI have different mechanisms, risk factors, and potential treatments suggesting that they should be distinguished to achieve a better scientific understanding of MIs in HIV. We sought to determine whether MI type could be accurately predicted by patient characteristics without adjudication in HIV-infected individuals. We developed a statistical model to predict T2MI versus T1MI using adjudicated events from six sites utilizing demographic characteristics, traditional cardiovascular, and HIV-related risk factors. Validation was assessed in a seventh site via mean calibration, and discrimination level was assessed by the area under the curve (AUC). Of 812 MIs, 388 were T2MI. HIV-related factors including hepatitis C infection were predictive of T2MI, whereas traditional cardiovascular risk factors including total cholesterol predicted T1MI. The score predicted 69 T2MI in the validation sample resulting in poor calibration, given that 90 T2MIs were observed. The development sample AUC was 0.75 versus 0.65 in the validation sample, suggesting relatively poor discrimination. The level of discrimination to predict MI type based on patient characteristics is insufficient for individual level prediction. Adjudication is required to distinguish MI types, which is necessary to advance understanding of this important outcome among HIV populations.
Keywords: Bayesian model averaging; HIV; adjudication; cardiovascular disease; cohort research; myocardial infarction.