Peripheral Artery Disease as a Predictor of Coronary Artery Disease in Patients Undergoing Coronary Angiography

Autor: Ahmed Ali, Simra Shahid, Shehar Bano, Jatender Kumar, Umama Bhurgri, Love Kumar, Amber Rizwan, Suman Dembra, Ashok Kumar, Dua Khalid
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Cureus
ISSN: 2168-8184
Popis: Background Peripheral artery disease (PAD) may be a useful tool to predict coronary artery disease (CAD) in patients undergoing coronary angiography. If proven that PAD can be a good predictor of CAD, it can help in early and cost-effective diagnosis of CAD. Methodology This observational study was conducted from January 2020 to February 2021 in the cardiology unit of a tertiary care hospital. Participants older than 40 years, with a history of uncontrolled hypertension and unstable angina, who warranted the need of angiography were enrolled in study. After enrollment and recording history, these cases were assessed for the presence of PAD based on ankle brachial index (ABI). ABI values less than 0.9 were labelled as participants with PAD. Then these cases underwent coronary angiography at the same institute, and the presence of greater than 50% stenosis of any coronary vessel on angiography was taken as positive CAD. Results In this study, PAD was identified in 152 (62.8%) participants. A total of 165 (68.1%) participants had greater than 50% stenosis on angiography. Out of 152 participants with ABI less than 0.9, 140 had greater than 50% stenosis on angiography. In total, 90 participants had ABI more than 0.9, of which 35 participants had greater than 50% stenosis. Sensitivity of PAD in predicting coronary artery stenosis was 80.0% (95% confidence interval [CI]: 73.30%-85.66%), specificity was 82.09% (95% CI: 70.80%-90.39%), and accuracy was 80.58% (95% CI: 75.02%-85.37%). Conclusions Our study demonstrated that the sensitivity, specificity, and accuracy of PAD in predicting coronary artery stenosis were significant. Hence, we conclude that PAD can be an excellent predictor of CAD by helping in early and cost-effective diagnosis of CAD.
Databáze: OpenAIRE