Impact of diabetes on the risk stratification using stress single-photon emission computed tomography myocardial perfusion imaging in patients with symptoms suggestive of coronary artery disease.

Published

Journal Article

BACKGROUND: Coronary artery disease can develop prematurely and is the leading cause of death among diabetics, making noninvasive risk stratification desirable. METHODS AND RESULTS: Patients with symptoms of coronary artery disease who were undergoing stress myocardial perfusion imaging (MPI) from 5 centers were prospectively followed (2.5+/-1.5 years) for the subsequent occurrence of cardiac death, myocardial infarction (MI), and revascularization. Stress MPI results were categorized as normal or abnormal (fixed or ischemic defects and 1, 2, or 3 vessel distribution). Of 4755 patients, 929 (19.5%) were diabetic. Patients with diabetes, despite an increased revascularization rate, had 80 cardiac events (8.6%; 39 deaths and 41 MIs) compared with 172 cardiac events (4.5%; 69 deaths and 103 MIs) in the nondiabetic cohort (P<0.0001). Abnormal stress MPI was an independent predictor of cardiac death and MI in both populations. Diabetics with ischemic defects had an increased number of cardiac events (P<0.001), with the highest MI rates (17.1%) observed with 3-vessel ischemia. Similarly, a multivessel fixed defect was associated with the highest rate of cardiac death (13.6%) among diabetics. The unadjusted cardiac survival rate was lower for diabetic patients (91% versus 97%, P<0.001), but it became comparable once adjusted for the pretest clinical risk and stress MPI results. In multivariable Cox analysis, both ischemic and fixed MPI defects independently predicted cardiac death alone or cardiac death/MI. Diabetic women had the worst outcome for any given extent of myocardial ischemia. CONCLUSIONS: In this large cohort of diabetics undergoing stress MPI, the presence and the extent of abnormal stress MPI independently predicted subsequent cardiac events. Using stress MPI in conjunction with clinical information can provide risk stratification of diabetic patients.

Full Text

Duke Authors

Cited Authors

  • Giri, S; Shaw, LJ; Murthy, DR; Travin, MI; Miller, DD; Hachamovitch, R; Borges-Neto, S; Berman, DS; Waters, DD; Heller, GV

Published Date

  • January 1, 2002

Published In

Volume / Issue

  • 105 / 1

Start / End Page

  • 32 - 40

PubMed ID

  • 11772873

Pubmed Central ID

  • 11772873

Electronic International Standard Serial Number (EISSN)

  • 1524-4539

Digital Object Identifier (DOI)

  • 10.1161/hc5001.100528

Language

  • eng

Conference Location

  • United States