Journal of Medicine and Palliative Care (JOMPAC) is an open access scientific journal with independent, unbiased, and double-blind review under international guidelines. The purpose of JOMPAC is to contribute to the literature by publishing articles on health sciences and medicine.

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Original Article
Neutrophil-to-high-density lipoprotein ratio: an independent predictor of infarct-related artery patency in patients with acute myocardial infarction
Aims: The definition of an infarct-related artery (IRA) is a coronary artery occluded by a thrombus or atheroma that causes ischemia during acute myocardial infarction (AMI). Early patency of the IRA is the primary goal of treatment in patients with AMI. The neutrophil/ high-density lipoprotein cholesterol (HDL-C) ratio (NHR) has been recognized as a new inflammatory marker. We aimed to show the possible relationship between NHR and preprocedural IRA patency.
Methods: Four hundred patients were screened, and 318 were included in the study after exclusion criteria. IRA flow rate before the coronary procedure was determined according to the previously described thrombolysis in myocardial infarction (TIMI). TIMI current 0,1 and 2 patients were considered IRA non-patent, and TIMI-3 patients were considered IRA patent and were divided into two groups. Regression analysis was performed for possible parameters in predicting IRA patency, evaluated in univariable analysis, and those with p-value <0.05 were assessed in multivariable analysis.
Results: The mean age was 62.3±11.9 years, and 73.4% were male. In multivariable logistic regression analysis, high peak troponin (ng/ml) (p<0.001, OR: 0.936, 95% CIs: 0.910-0.962) and NHR (p= 0.020, OR: 0.043, 95% CIs: 0.003-0.603) levels were found to be independent predictors of patent IRA.
Conclusion: Our study investigated the relationship between IRA patency and NHR in AMI patients. The main finding of our research is that significantly higher NHR and peak troponin levels were associated with non-patent IRA patients and were independent predictors.

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Volume 4, Issue 5, 2023
Page : 400-405