Predictors and clinical outcomes of slow flow phenomenon in diabetic patients with chronic coronary syndrome
Year: 2024
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Coronary slow flow (CSF) is characterized by late distal coronary perfusion of coronary arteries at the time of angiography despite the vessels appearing normal. The importance of CSF is still debatable. Therefore, this study aimed to investigate CSF's predictors and clinical outcomes in diabetic patients with chronic coronary syndrome (CCS). PATIENT AND METHODS: This retrospective study included 250 diabetic patients diagnosed with chronic stable angina and referred for coronary angiography (CAG), showing normal coronaries with CSF (Group I) and 240 diabetic patients with normal coronaries and normal flow (Group II). The patients in both groups were followed up for one year to evaluate clinical outcomes. RESULTS: The incidence of major adverse cardiac events (MACE) was higher in Group I than in Group II, but the difference was not statistically significant except when the composite endpoints of STEMI, NSTEMI, and unstable angina were combined under the term ACS. The independent predictors of CSF, as detected by multivariate regression analysis, were body mass index (BMI) (OR = 0.694, 95% CI = 0.295-0.842, P = 0.010), blood glucose during catheterization (OR = 0.647, 95% CI = 0.298-0.874, P = 0.008), serum triglycerides (OR = 0.574, 95% CI = 0.289-0.746, P = 0.010), and the neutrophil/lymphocyte ratio (NLR) (OR = 0.618, 95% CI = 0.479-0.892, P = 0.001). CONCLUSION: Serum triglyceride levels, BMI, NLR, and high blood glucose levels at the time of catheterization were independent predictors of CSF in diabetic patients. MACE levels were higher in diabetic patients with CSF.
Source: BMC Cardiovascular Disorders
Authors: Mohamed A. Khalil, Mohamed Khalfallah, Ayman Elsheikh
Institution: Tanta University
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,890
OpenAlex ID: W4402899775