Blood biomarkers in acute ischemic stroke: The prognostic value of neutrophil-to-lymphocyte ratio and mean platelet volume.

Abstract

Background: The neutrophil-to-lymphocyte ratio (NLR) and mean platelet volume (MPV) reflect systemic inflammation, which plays an important role in the process of treating ischemic strokes. Few studies have evaluated the association between blood biomarkers and clinical outcomes in ischemic strokes in intensive care units (ICUs).

Objectives: This retrospective study aims to explore the relationship between blood biomarkers and the clinical outcomes of acute ischemic stroke (AIS) patients.

Material and methods: Basic descriptive statistics of the patients admitted to the ICU with the diagnosis of AIS according to sociodemographic, clinical and laboratory findings were collected. Receiver operating characteristic (ROC) curve analysis was used to determine the cutoff point for NLR and MPV variables based on the diagnosis in statistical analyses and crosstab analyses of variables. The χ2 and Fisher's exact tests were used to assess the statistical relationship between categorical variables. In addition, the odds ratio (OR) was utilized to show the strength of the relationship between the categorical NLR, MPV and modified Rankin Scale (mRS) variables. Finally, the Mann-Whitney U test was used to compare the medians of 2 independent groups.

Results: A total of 1,379 records were identified in the database search. Eighty-seven patients who met the inclusion criteria and were hospitalized in the ICU were included in the study. The optimal cutoff point was determined to be 4.0 for NLR and 9.0 for the MPV. A statistically significant relationship was found between high medians of the NLR and the MPV and unfavorable functional outcomes using a 5% significance level (p < 0.001 and p < 0.001, respectively).

Conclusions: We showed that the NLR and MPV are associated with stroke severity, unfavorable functional outcomes and mortality in AIS. These findings provide new insights into the mechanisms and treatment strategies of AIS. The results show that these accessible values can be used as independent predictive biomarkers.