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Published on: April 13, 2015
Plasma atherogenic indices are independent predictors of slow coronary flow
Abdulmecit Afsin1, Hakan Kaya2, Arif Suner3
1Department of Cardiology, Adiyaman Training and Research Hospital, Adiyaman, Turkey.
Insights
Atherogenic indices, including atherogenic index of plasma (AIP) and Castelli risk index II (CRI-II), are independent predictors of coronary slow flow (CSF). These findings highlight the role of atherogenic dyslipidemia in CSF development.
Area of Science:
- Cardiology
- Atherosclerosis Research
- Lipid Metabolism
Background:
- Coronary slow flow (CSF) pathophysiology is not fully understood.
- Subclinical diffuse atherosclerosis is increasingly implicated in CSF etiology.
- This study investigates the link between atherogenic indices and CSF.
Purpose of the Study:
- To explore the relationship between atherogenic indices and coronary slow flow (CSF).
- To identify potential predictors of CSF among various atherogenic markers.
Main Methods:
- Retrospective study including 130 patients with CSF and 130 controls with normal coronary flow.
- Calculation of atherogenic index of plasma (AIP) and Castelli risk indices (CRI-I, CRI-II) from lipid parameters.
- Logistic regression and receiver operating characteristic (ROC) analyses were performed.
Main Results:
- Atherogenic index of plasma (AIP) and Castelli risk index II (CRI-II) were identified as independent predictors of CSF.
- Optimal cutoff values for AIP (0.66) and CRI-II (3.27) demonstrated significant predictive value for CSF.
- ROC analysis showed AUC of 0.695 for AIP and 0.726 for CRI-II.
Conclusions:
- AIP and CRI-II levels are significant independent predictors of coronary slow flow (CSF).
- These findings suggest atherogenic dyslipidemia plays a role in CSF pathophysiology.
- Further prospective studies are needed to confirm these results in larger populations.
Background:
Although the pathophysiology of coronary slow flow (CSF) has not been fully elucidated, emerging data increasingly support potential role for subclinical diffuse atherosclerosis in the etiology of CSF. We aimed to investigate relationship between atherogenic indices and CSF.
Methods:
130 patients with CSF diagnosed according to Thrombolysis in Myocardial Infarction (TIMI)-frame count (TFC) method and 130 controls who had normal coronary flow (NCF) were included in this retrospective study. Atherogenic indices (atherogenic index of plasma [AIP], Castelli risk indices I and II [CRI-I and II]) were calculated using conventional lipid parameters.
Results:
The logistic regression analyses demonstrated that AIP (OR, 5.463; 95% confidence interval [CI], 1.357-21.991; p = 0.017) and CRI-II (OR, 1.624; 95% CI, 1.138-2.319; p = 0.008) were independent predictors of CSF. Receiver operating characteristic analysis showed that the optimal cutoff value to predict the occurrence of CSF was 0.66 for AIP (sensitivity, 59%; specificity, 73%; area under curve [AUC], 0.695; p < 0.001) and 3.27 for CRI-II (sensitivity, 60%; specificity, 79%; AUC, 0.726; p < 0.001).
Conclusions:
AIP and CRI-II levels were independent predictors of CSF. Prospective studies in larger cohorts of patients may elucidate the role of atherogenic dyslipidemia in the pathophysiology of CSF.
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