Predictors of non-obstructive coronary slow flow in poorly controlled type 2 diabetes mellitus: a cross-sectional study.

BACKGROUND: Coronary slow flow (CSF) can occur due to various factors, such as inflammation, small vessel disease, endothelial dysfunction, and inadequate glucose control. However, the exact pathological mechanisms behind CSF remain incompletely understood. The objective of this study was to identify the risk factors associated with slow coronary flow in individuals with Type 2 Diabetes Mellitus (T2DM) who have non-obstructive coronary artery disease (CAD) and experience CSF. METHODS: We conducted a prospective cohort study involving 120 patients with T2DM who were referred for invasive coronary angiography due to typical chest pain or inconclusive results from non-invasive tests for myocardial ischemia. Using a 2 × 2 design, we categorized patients into groups based on their glycemic control (adequate or poor) and the presence of CSF (yes or no), defined by a TIMI frame count > 27. All patients had non-obstructive CAD, characterized by diameter stenosis of less than 40%. We identified many variables associated with CSF. RESULTS: Our investigation revealed no significant differences in age, sex, family history of coronary artery disease, ECG ischemia abnormalities, or echocardiographic (ECHO) data between the groups. In patients with adequate glycemic control, hypertension increased the risk of CSF by 5.33 times, smoking by 3.2 times, while dyslipidemia decreased the risk by 0.142. Additionally, hematocrit increased the risk by 2.3, and the platelet-to-lymphocyte ratio (PLR) increased the risk by 1.053. Among patients with poor glycemic control, hematocrit increased the risk by 2.63, and the Neutrophil-to-Lymphocyte Ratio (NLR) by 24.6. Notably, NLR was positively correlated with glycemic control parameters in T2DM patients with CSF. CONCLUSIONS: In T2DM patients with CSF, various factors strongly correlate with glycemic control parameters and can be employed to predict the likelihood of CSF. These factors encompass hypertension, smoking, increased body mass index (BMI), elevated platelet count, hematocrit, NLR, PLR, and C-reactive protein (CRP). TRIAL REGISTRATION: Registry: ZU-IRB (ZU-IRB#9419-3-4-2022), Registered on: 3 April 2022, Email: IRB_123@medicine.zu.edu.eg.

Relationship between inflammatory markers and coronary slow flow in type 2 diabetic patients.

BACKGROUND: Diabetes is a serious and quickly expanding global health problem. Cardiovascular disease is the leading cause of mortality in type 2 diabetes mellitus (T2DM) patients. Coronary slow flow (CSF) is characterised by delayed distal perfusion during coronary angiography with normal coronary arteries. This study aimed to investigate the correlation between CSF and inflammatory markers regarding glycemic status in T2DM. METHODS: This cross-sectional study included 120 patients who were divided equally into 4 groups according to their glycemic control and presence or absence of coronary slow flow: Group I included patients with T2DM with good glycemic control without CSF; Group II included patients with T2DM with good glycemic control and CSF; Group III included patients with T2DM with poor glycemic control without CSF; and Group IV included patients with T2DM with poor glycemic control and CSF. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), C-reactive protein (CRP), platelets, hematocrit, and haemoglobin were also evaluated as risk factors for coronary slow flow. RESULTS: This study showed that body mass index (BMI), hematocrit level, NLR, and CRP demonstrated a moderate but significant correlation (r = 0.53) with CSF in poorly controlled T2DM. NLR cutoff > 2.1 could predict CSF in poorly controlled T2DM with a modest sensitivity and specificity. A 1.9 increase in HbA1c increases the likelihood of coronary slow flow. Dylipidemia increases the likelihood of coronary slow flow by 0.18 times. Other predictors for coronary slow flow include NLR, PLR, CRP, platelets, hematocrit, and hemoglobin. The effect of the predictors is still statistically significant after being adjusted for glycemic status, age, and sex (p < 0.001). CONCLUSIONS: Poor glycemic control increases the incidence of CSF. This supports the hypothesis that CSF is related to endothelial dysfunction as poor glycemic control causes endothelial dysfunction due to inflammation. TRIAL REGISTRATION: ZU-IRB#9419-3-4-2022 Registered 3 April 2022, email.  IRB_123@medicine.zu.edu.eg .