Neutrophil-to-lymphocyte Ratio (NLR) As A Clinical Prognosis Predictor For Acute Cerebral Infarction

ObjectiveWe described the clinical feature of acute ischemic stroke（AIS）,and used the marker of the immunity and inflammation（neutrophil-to-lymphocyte ratio（NLR））to evaluate the clinical prognosis for acute cerebral infarction.MethodPatients with AIS admitted to the hospital were selected for this study.A complete blood count analysis was performed using the peripheral venous blood samples taken on admission in the department of emergency,Peripheral venous blood samples for biochemical tests were collected on the morning（between 6:00 and 7:00 AM）of the second day after admission with an overnight fast.We collected baseline demographic and clinical information including age,sex,and the presence of cerebral vascular risk factors such as hypertension and diabetes.The severity of AIS was assessed according to the National Institute of Health Stroke Scale（NIHSS）.We evaluated the NIHSS in patients at the admission time.The outcome of acute ischemic stroke was measure by modified Rankin Scale score（MRS）.All patients received MRI scanning within 72 hours after the admission,In DWI images,infarct volume was calculated.Clinical characteristics were analyzed using descriptive statistic tests.Continuous data were tested for normal distribution using the Kolmogorov–Smirnov test.Continuous variables that followed normal distribution were expressed as mean±standard deviation;other variables that did not follow normal distributions were presented as the median and the interquartile range.Categorical variables are expressed as constituent ratios.Differences for continuous variables between groups were assessed by the Student’s t test or Mann–Whitney U test.Differences in categorical variable distribution between groups were assessed by the x² test.A Jonckheere-Terpstra test was performed in our research.The optimal cut-off value key parameter was calculated by applying a receiver operating curve analysis.We further calculated the poor outcome risk factors with binary logistic regression model.All statistical analyses were performed using SPSS 17.0.ResultsOne hundred forty-three patients with AIS were enrolled.Firstly,The study population was categorized into three tertiles each containing 48,49,and 46 patients according to the NLR value,In the first tertile(median NLR 1.7,25^{t h}–75^th percentile1.40–2.02),the poor outcome rate was 27.1%;in the second tertile(median NLR2.79,25^th–75^{t h} percentile 2.36–3.29),the poor outcome rate was 42.9%;and in the third tertile(median NLR 6.18,25^{t h}–75^{t h} percentile 4.57–9.82),the poor outcome rate was 89.1%,showed a statistical significance between each tertiles（P<0.001）.Then,A N LR value of2.995 was calculated by receiver operating curve analysis as an optimal cutoff value to discriminate between good outcome and poor outcome in patients with AIS,A NLR value of 2.995 as a cutoff value had a sensitivity of 75%and a specificity of 61%for differentiating the good outcome and poor outcome.Then,According to the cutoff value of NLR at 2.995,we categorized our patients into two groups:low NLR group containing 78patients（NLR≤2.995）and high NLR group containing 65 patients（N LR>2.995）.In the low NLR group,19 patients（24.4%）had 3-month poor outcome,whereas in the high NLR group,56 patients（86.2%）had 3-month poor outcome.Compared with patients in the low NLR group,patients in the high NLR group had higher poor outcome rate（P<0.001）.In this study,75 patients（52%）had poor outcome,We used binary logistic regression to evaluate risk factor for poor outcome of AIS and found that the NLR was independently associated with the poor outcome of 3 months（P<0.001）.The optimal cut-off value for NLR as a predictor for 3-month outcome was 2.995.Therefore,in our study,high NLRs inversely predicted 3-month outcome in patients with AIS.ConclusionIn this study,we first evaluated the relationships between the N LR at stroke onset and the 3-month outcome in patients with AIS.Our results indicated that N LR at the admission was an independent predictor o f 3-month outcome in patients with the first-ever patients with AIS.At same time,targeting N LR may be a new venue for prospective trials in patients with AIS.