Submitted: 25 Jun 2020
Accepted: 23 Nov 2020
ePublished: 13 Jan 2021
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J Cardiovasc Thorac Res. 2021;13(1): 37-42.
doi: 10.34172/jcvtr.2021.03
  Abstract View: 116
  PDF Download: 39

Original Article

Prevalence and predictors of slow coronary flow phenomenon in Kermanshah province

Mohammad Rouzbahani 1 ORCID logo, Saeid Farajolahi 1, Nafiseh Montazeri 1, Parisa Janjani 1, Nahid Salehi 1, Alireza Rai 1, Reza Heidari Moghadam 1, Arsalan Naderipour 2, Asal Kanjorpor 1, Etrat Javadirad 3, Javad Azimivghar 1* ORCID logo

1 Cardiovascular Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
2 Department of Emergency Medicine, School of Paramedics, Kermanshah University of Medical Sciences, Kermanshah, Iran
3 Clinical Research Development Center of Imam Khomeini Hospital, Kermanshah University of Medical Sciences, Kermanshah, Iran
*Corresponding Author: Javad Azimivaghar, Email: Sepehr.amiri1398@gmail.com


Introduction: This study was conducted to investigate prevalence and predictors of slow coronary flow phenomenon (SCF) phenomenon.

Methods: This cross-sectional study was performed at Imam Ali Cardiovascular Hospital affiliated with the Kermanshah University of Medical Sciences (KUMS), Kermanshah province, Iran. From March 2017 to March 2019, all the patients who underwent coronary angiography were enrolled in this study. Data were obtained using a checklist developed based on the study’s aims. Independent samples t tests and chi- square test (or Fisher exact test) were used to assess the differences between subgroups. Multiple logistic regression model was applied to evaluate independent predictors of SCF phenomenon.

Results: In this study, 172 (1.43%) patients with SCF phenomenon were identified. Patients with SCF were more likely to be obese (27.58±3.28 vs. 24.12±3.26, P<0.001), hyperlipidemic (44.2 vs. 31.7, P<0.001), hypertensive (53.5 vs. 39.1, P<0.001), and smoker (37.2 vs. 27.2, P=0.006). Mean ejection fraction (EF) (51.91±6.33 vs. 55.15±9.64, P<0.001) was significantly lower in the patients with SCF compared to the healthy controls with normal epicardial coronary arteries. Mean level of serum triglycerides (162.26±45.94 vs. 145.29±35.62, P<0.001) was significantly higher in the patients with SCF. Left anterior descending artery was the most common involved coronary artery (n = 159, 92.4%), followed by left circumflex artery (n = 50, 29.1%) and right coronary artery (n = 47, 27.4%). Body mass index (BMI) (OR 1.78, 95% CI 1.04-2.15, P<0.001) and hypertension (OR 1.59, CI 1.30-5.67, P=0.003) were independent predictors of SCF phenomenon.

Conclusion: The prevalence of SCF in our study was not different from the most other previous reports. BMI and hypertension independently predicted the presence of SCF phenomenon.

Keywords: Coronary Angiography, Slow Coronary Flow Phenomenon, Predictor, Prevalence
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