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Yonsei medical journal · Feb 2020
Feasibility and Applicability of Wireless Handheld Ultrasound Measurement of Carotid Intima-Media Thickness in Patients with Cardiac Symptoms.
- Albert Youngwoo Jang, Jeongwon Ryu, Pyung Chun Oh, Jeonggeun Moon, and Wook Jin Chung.
- Department of Cardiovascular Medicine, Gachon University Gil Medical Center, Incheon, Korea.
- Yonsei Med. J. 2020 Feb 1; 61 (2): 129-136.
PurposeRoutine screening for carotid intima-media thickness (CIMT) and cardiovascular (CV) disease in asymptomatic patients has been criticized for the high costs and large number of patients required for detecting one patient with coronary artery disease (CAD). In order to overcome the low cost-effectiveness thereof, we investigated the feasibility of an economic wireless handheld ultrasound (WHUS) device for CIMT measurement in symptomatic patients.Materials And MethodsA total of 100 consecutive patients with cardiac symptoms were enrolled. CIMT was measured in all patients. Coronary angiography was performed in 75 patients indicated for the exam.ResultsThe mean of maximal CIMT measured from left/right common carotid artery and bulb (max-CIMT) by the WHUS device showed excellent agreement [intraclass correlation coefficient (ICC)=0.960] with a standard ultrasound device and great interobserver repeatability (ICC>0.9 between all observers). Receiver operating characteristic curve analysis showed that the predictive power for CAD was improved when max-CIMT and plaque information (plaque≥2) was added [area under the curve (AUC): 0.838] to the traditional clinical CV risk factors (AUC: 0.769). The cutoff values for CAD prediction with the standard device and the WHUS device were 1.05 mm (AUC: 0.807, sensitivity: 0.78, specificity: 0.53) and 1.10 mm (AUC: 0.725, sensitivity: 0.98, specificity: 0.27), respectively.Conclusionmax-CIMT measured by a WHUS device showed excellent agreement and repeatability, compared with standard ultrasound. Combined max-CIMT and plaque information added predictive power to the traditional clinical CV risk factors in detecting high-risk CAD patients.© Copyright: Yonsei University College of Medicine 2020.
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