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Myocardial Perfusion SPECT Utility in Predicting Cardiovascular Events Among Indonesian Diabetic Patients
Manoefris Kasim1, Geoffrey M Currie, Markus Tjahjono
1National Cardiovascular Center, Harapan Kita Hospital, Department of Cardiology, Indonesia University.
Insights
Abnormal myocardial perfusion imaging (MPI) strongly predicts major adverse cardiac events in Indonesian diabetic patients with suspected or known coronary artery disease (CAD). This finding aids in crucial cardiovascular risk stratification for this high-risk population.
Area of Science:
- Cardiology
- Nuclear Cardiology
- Diabetology
Background:
- Indonesia faces a high burden of diabetes, with coronary artery disease (CAD) as a leading cause of mortality.
- Early detection and risk stratification are vital for managing diabetic patients at risk of cardiac events.
- Myocardial perfusion imaging (MPI) is a valuable tool for diagnosing obstructive CAD and predicting cardiac events.
Purpose of the Study:
- To evaluate the predictive value of abnormal adenosine stress MPI for adverse cardiovascular events in an Indonesian diabetic population.
- To assess the prognostic significance of MPI in cardiovascular risk stratification among diabetic patients with suspected or known CAD.
Main Methods:
- A cohort of 300 patients with suspected or known CAD underwent adenosine stress MPI.
- The primary endpoint was major adverse cardiac event (MACE), defined as cardiac death or nonfatal myocardial infarction.
- Follow-up averaged 26.7 months, with outcomes analyzed using multivariable Cox proportional hazard models and Kaplan-Meier survival curves.
Main Results:
- The incidence of MACE was significantly higher in diabetic patients (18.3%) compared to non-diabetic patients (9%).
- Abnormal MPI (HR: 9.30), post-stress left ventricular ejection fraction ≤30% (HR: 2.72), and diabetic status (HR: 2.28) were independent predictors of MACE.
- Diabetic patients with abnormal MPI exhibited the worst event-free survival.
Conclusions:
- Abnormal adenosine stress MPI is a potent, independent predictor of adverse cardiovascular events in Indonesian patients with suspected or known CAD.
- MPI offers incremental prognostic value for cardiovascular risk stratification in diabetic patients.
- These findings highlight the importance of MPI in managing high-risk diabetic populations in Indonesia.
Background:
Indonesia has the fourth largest number of diabetes patients after India, China and the USA. Coronary artery disease (CAD) is the most common cause of death in diabetic patients. Early detection and risk stratification is important for optimal management. Abnormal myocardial perfusion imaging (MPI) is an early manifestation in the ischemic cascade. Previous studies have demonstrated the use of MPI to accurately diagnose obstructive CAD and predict adverse cardiac events. This study evaluated whether MPI predicts adverse cardiac event in an Indonesian diabetic population.
Method:
The study was undertaken in a consecutive cohort of patients with suspected or known CAD fulfilling entry criteria. All had adenosine stress MPI. The end point was a major adverse cardiac event (MACE) defined as cardiac death or nonfatal myocardial infarction (MI).
Results:
Inclusion and exclusion criteria were satisfied by 300 patients with a mean follow-up of 26.7 ± 8.8 months. The incidence of MACEs was 18.3% among diabetic patients, versus 9% in the non-diabetic population (p < 0.001). A multivariable Cox proportional hazard model demonstratedin dependent predictors for a MACE as abnormal MPI [HR: 9.30 (3.01 - 28.72), p < 0.001], post stress left ventricular ejection fraction (LVEF) ≤30% [HR:2.72 (1.21 - 6.15), p = 0.016] and the patients diabetic status [HR:2.28 (1.04 - 5.01), p = 0.04]. The Kaplan Meier event free survival curve constructed for the different subgroups based on the patients' diabetic status and MPI findings demonstrated that diabetic patients with an abnormal MPI had the worst event free survival (log rank p value < 0.001).
Conclusions:
In an Indonesian population with suspected or known CAD abnormal adenosine stress MPI is an independent and potent predictor for adverse cardiovascular events and provides incremental prognostic value in cardiovascular risk stratification of patients with diabetes.
