Prediction of coronary artery disease in patients undergoing carotid endarterectomy

Toshifumi Shimada, Kazunori Toyoda, Tooru Inoue, Masahiro Kamouchi, Takahiro Matsumoto, Koji Hiyamuta, Tsutomu Imaizumi, Yasushi Okada

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


Object. The authors determined the factors that predict the coexistence of coronary artery disease (CAD) in patients who undergo carotid endarterectomy (CEA). Methods. Data from 200 consecutive Japanese patients who underwent CEA for extracranial carotid artery stenosis were studied. Among 73 patients with CAD, 35 (48%) had three-vessel or left main CAD (that is, severe CAD). Peripheral artery disease was an independent predictor of CAD (odds ratio [OR] 2.61, 95% confidence interval [CI] 1.08-6.3). In addition, diabetes mellitus ([DM]; OR 2.8, 95% CI 1.24-6.32) and peripheral artery disease (PAD) (OR 2.83, 95% CI 1.05-7.57) were independent predictors of severe CAD in the 200 patients. The percentage of patients with CAD as well as those with the severe form of the disease increased stepwise as the number of major coronary risk factors in patients increased. Asymptomatic CAD was newly detected during the pre-CEA assessment in 18 (25%) of the 73 patients in whom CAD was eventually diagnosed. Diabetes mellitus was an independent predictor of occult CAD among the 200 patients (OR 4.83, 95% CI 1.53-15.2). Conclusions. In patients with DM, PAD, or multiple major coronary risk factors who have been scheduled for CEA, one should carefully search for concomitant CAD, especially severe CAD, even when the patient has had no previous episode of angina.

Original languageEnglish
Pages (from-to)593-596
Number of pages4
JournalJournal of Neurosurgery
Issue number4
Publication statusPublished - Oct 2005

All Science Journal Classification (ASJC) codes

  • Surgery
  • Clinical Neurology


Dive into the research topics of 'Prediction of coronary artery disease in patients undergoing carotid endarterectomy'. Together they form a unique fingerprint.

Cite this