Significance of Microalbuminuria in Predicting Silent Myocardial Ischemia in Patients with Type 2 Diabetes Using Myocardial Perfusion Imaging
Journal Title: Molecular Imaging and Radionuclide Therapy - Year 2019, Vol 28, Issue 2
Abstract
Objectives: In light of increased risk of cardiovascular events and the poor prognosis of coronary artery disease (CAD) in diabetic versus non-diabetic patients and also with respect to the importance of early diagnosis of CAD in this status, the study was aimed to assess the importance of microalbuminuria in predicting silent myocardial ischemia (SMI) in patients with type 2 diabetes using myocardial perfusion imaging (MPI). Methods: This study included 120 patients with diabetes type 2, but without previously known CAD or any cardiac symptoms that were stratified into two groups based on presence/absence of microalbuminuria. All participants underwent CAD evaluation using gated myocardial perfusion single-photon emission computed tomography (MPS) imaging. Other clinical and laboratory indices were also recorded. Results: Studied population consisted of 84 males (70%) and 36 females (30%), totally 120 patients with mean age of 58.61±9.90). In total, asymptomatic ischemia was detected in 78 (65%) of the included diabetic patients. Stress induced ischemia was found in 56 patients (87.5%) of albumin+ (Alb) group and in 22 patients (39.3%) of Alb- group. The frequency of stress induced ischemia was 10.81 times higher in the patients with microalbuminuria compared to Alb- ones [p<0.001, Odds ratio: 10.81, 95% confidence interval: 4.33-26.99]. On the other hand, no relationship was found between the presence of stress induced ischemia and therapy type, diabetes duration, history of evident retinopathy, history of hypertension and also serum levels of hemoglobin A1c (p>0.05). Conclusion: The current study showed that abnormal MPI findings are significantly more common in diabetic patients with microalbuminuria. With respect to low cost and availability of urine Alb detection tests, it might be as a biomarker for prediction of SMI in daibetic population.
Authors and Affiliations
Tayyebeh Emami, Zohreh Naeimei, Azita Salehifard, Zahra Azizmohammadi, Dariush Iranpour, Mohammadreza Kalantarhormozi, Esmail Jafari, Ali Gholamrezanezhad, Majid Assadi
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- EP ID EP591703
- DOI 10.4274/mirt.galenos.2019.93798
- Views 134
- Downloads 0
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