Journal of Clinical Laboratory Analysis 00: 1–6 (2016)
Atrial Fibrillation is Strongly Associated With the Neutrophil to Lymphocyte Ratio in Acute Ischemic Stroke Patients: A Retrospective Study Kyungdong Min,1 Seungwon Kwon,1* Seung-Yeon Cho,1 Woo Jun Choi,2 Seong-Uk Park,1 Woo-Sang Jung,1 Sang-Kwan Moon,1 Jung-Mi Park,1 Chang-Nam Ko,1 and Ki-Ho Cho1 1
Department of Cardiology and Neurology, College of Korean Medicine, Kyung Hee University, Seoul, Korea 2 Department of Korean Medicine Cardiology and Neurology, Graduate School, Kyung Hee University, Seoul, Korea
Background: No study has investigated the relationship between hospital-admission neutrophil and lymphocyte ratio (NLR) and various stroke risk factors. We sought to determine which stroke risk factor could be the most appropriate predictor of NLR in acute ischemic stroke. Methods: We collected data on various stroke risk factors and National Institutes of Health Stroke Scale (NIHSS) score in 1,053 acute ischemic stroke patients. The regression analysis was adjusted for confounding factors such as stroke risk factors. Results: There was a trend of increased NLR with a rise in alcohol consumption, the prevalence of hypertension, cardioembolism (CE) etiology, the NIHSS scores in men and the prevalence of atrial
fibrillation, other heart diseases, CE and small vessel occlusion etiology and the NIHSS scores in women. Multiple linear regression analyses, adjusted for confounding factors, showed that the atrial fibrillation and NIHSS scores in men and atrial fibrillation, diabetes mellitus as well as NIHSS scores in women had a significant positive association with NLR. However, a negative association was showed for body mass index (BMI). Conclusion: We confirmed that the atrial fibrillation can be a predictor of high NLR in acute stroke patients, and diabetes mellitus as well as low BMI could be a predictor of high NLR in female acute ischemic stroke patients. J. Clin. Lab. Anal. 00:1–6, © 2016 Wiley Periodicals, Inc. 2016.
Key words: acute ischemic stroke; atrial fibrillation; diabetes mellitus; neutrophil to lymphocyte ratio; stroke prognosis
INTRODUCTION The neutrophil to lymphocyte ratio (NLR) is an important measure of systemic inflammation that has been used as a marker of subclinical inflammation. Recently, NLR has been used to predict the prognosis of cerebrovascular disease, including ischemic stroke and transient ischemic attack (TIA; 1–6). Previous studies have suggested that a higher NLR in acute ischemic stroke patients is associated with increased short-term mortality (2), poor prognosis (1, 3–5), and a poor 90-day outcome after endovascular stroke therapy (6). In a clinical setting, most hospitals conduct a complete blood cell count (CBC) and differential blood count test. Furthermore, as this test is © 2016 Wiley Periodicals, Inc.
inexpensive and simple, NLR could be a suitable marker for detecting the prognosis of acute ischemic stroke. However, to the best of our knowledge, no study has previously investigated the relationship between hospital-admission NLR and various stroke risk factors. We hypothesized that some of the ischemic stroke *Correspondence to: Seungwon Kwon, Department of Cardiology and Neurology, College of Korean Medicine, Kyung Hee University, 1 Hoegi-dong, Dongdaemun-gu, Seoul 02447, Korea. E-mail:
[email protected] Received 10 April 2016; Accepted 9 July 2016 DOI 10.1002/jcla.22041 Published online in Wiley Online Library (wileyonlinelibrary.com).
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risk factors could play a role in elevating NLR in acute ischemic stroke patients. Furthermore, it could be another predictor for the prognosis of acute ischemic stroke. Therefore, in this study, we sought to determine which stroke risk factor could be the most appropriate predictor of NLR in acute ischemic stroke. METHODS
echocardiography. Other heart diseases were defined through the presence of medication related to those diseases and abnormal findings in the 12-lead electrocardiography, 24-hr holter electrocardiography, or echocardiography. Carotid artery and cerebral artery stenosis were defined by relevant findings (more than 50% stenosis) in magnetic resonance angiography, computed tomography angiography, transfemoral cerebral angiography, carotid duplex ultrasonography or transcranial Doppler sonography.
Subjects and Data Collection In the present study, we collected patient information from January 2010 to September 2015 at Kyung Hee University Korean Medicine Hospital. We selected 1,053 subjects (576 men and 477 women) who met the following inclusion criteria: (1) acute ischemic stroke patients who were admitted to the hospital within 7 days from onset, (2) patients who received a CBC and differential blood count test at admission. Subjects with missing data were excluded. We retrospectively collected data from subjects’ medical records including sex, age, and body mass index (BMI), current smoking, alcohol consumption and National Institutes of Health Stroke Scale (NIHSS) score. We also investigated the prevalence of ischemic stroke risk factors, such as hypertension, diabetes mellitus, dyslipidemia, atrial fibrillation, other heart diseases (including coronary heart disease, cardiac valve disease, and heart failure, etc.), previous stroke (frequency), family history of stroke, carotid artery stenosis, and cerebral artery stenosis based on medical records. Etiologies of ischemic stroke based on the Trial of Org 10172 in Acute Stroke Treatment classification of the stroke (7, 8) were investigated. We calculated the NLR based on the CBC results at admission. We evaluated alcohol consumption by asking patients about their consumption amount per drinking event and weekly frequency of drinking during the previous year. Through these answers, we categorized alcohol consumption state as follows: no drink, moderate, heavy, and binge drinker based on the Drinking Levels of the National Institute on Alcohol Abuse and Alcoholism. Subjects were also questioned regarding smoking status and asked to provide information on the number of packs per day and the smoking duration (pack-year (pack-yr)). The prevalence of hypertension, dyslipidemia, and diabetes mellitus were defined by the presence of medication for each diseases or a medical doctor’s diagnosis. The prevalence of atrial fibrillation was defined via the presence of atrial fibrillation in 12-lead electrocardiography, 24-hr holter electrocardiography, or
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Physical Measurements BMI was calculated by dividing the body weight (kg) by the height squared (m2). Complete Blood Count Measurements CBC and differential counts were measured using an ADVIAÒ2120i (Siemens, Munich, Germany). The NLR was calculated by the following equation: NLR ¼ Neutrophil counts/Lymphocyte counts:
Statistical Analysis All analyses were performed independently for each sex. We also divided subjects into two groups according to their NLR values: the low NLR group (NLR ≤ 2.5538, which was the median value of NLR in this study) and the high NLR group (NLR > 2.5538). Baseline characteristics (age, BMI, NIHSS score, NLR date from onset in days), current smoking, alcohol consumption, and prevalence of risk factors) were compared between men and women. Paired t-tests were performed for continuous values and chi-square tests were performed for categorical values. In the regression analysis, NLR was the dependent variable. We remove the variables without statistical significance in a stepwise fashion until the adjusted R2 reached the highest value. The analysis was adjusted for the following confounding factors: NIHSS score, current smoking history, alcohol consumption, and a medical history of atrial fibrillation, dyslipidemia, or other heart diseases in men; NIHSS score, age, BMI, and a medical history of atrial fibrillation, diabetes mellitus, or carotid artery stenosis in women. All statistical analyses were performed using SPSS version 10.0 (SPSS Inc., Chicago, IL, USA), and significance was defined as a P-value < 0.05. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki.
Association of NLR and Atrial Fibrillation
RESULTS
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NLR, smoking status, alcohol consumption, hypertension, dyslipidemia, and other heart diseases prevalence between men and women. Taken together, this suggests that male and female study participants have dramatic lifestyle differences that greatly influence the occurrence of ischemic stroke (Table 1).
Baseline Characteristics Subject were a mean age of 65.69 11.86 (mean SD) and 70.08 10.66 years old for men and women, respectively. The mean BMI was 23.89 2.90 kg/m2 for men and 23.64 3.45 kg/m2 for women. The mean NLR was 3.49 3.60 for men and 3.09 2.40 for women. The most frequent etiology of ischemic stroke was small vessel occlusion (SVO) in both sexes. The mean amount of smoking was 17.29 23.25 pack-yr for men and 1.72 8.54 pack-yr for women. The alcohol consumption was as follows: 21.9% moderate, 32.8% heavy, 4.3% binge for men and 12.2% moderate, 4.4% heavy, 0.0% binge for women. There were significant differences in age,
Comparison of Baseline Characteristics Between the Low NLR Group and High NLR Group We divided the subjects into two groups according to the median NLR value (2.5538). There were statistically significant differences between the two groups in the amount of alcohol consumption, prevalence of hypertension, etiology of cardioembolism (CE) and NIHSS scores for men and in BMI, prevalence of
TABLE 1. Baseline Characteristics Men N Age (years) BMI (kg/m2) NIHSS NLR NLR date from on set (days) Smoking (pack-yr)
Ischemic stroke type (TOAST) LAA SVO CE SOE SUE Hypertension Dyslipidemia Diabetes Atrial fibrillation Other heart diseases Previous stroke No One time Two times Three times Family history of stroke Carotid artery stenosis Cerebral artery stenosis Alcohol consumption No Moderate Heavy Binge
576 576 576 576 576 576
Women Mean SD
N
477 477 477 477 477 477
65.69 23.89 4.52 3.49 1.94 17.29
11.86 2.90 2.71 3.60 11.68 23.25
Mean SD
P-value
<0.001 0.186 0.602 0.040 0.394 <0.001
70.08 23.64 4.61 3.09 2.40 1.72
10.66 3.45 2.82 2.40 2.13 8.54
N
%
N
%
142 366 32 2 33 373 241 184 41 22
24.7 63.5 5.6 0.3 5.7 64.8 41.8 31.9 7.1 3.8
93 336 21 3 23 362 247 161 40 36
19.5 70.4 4.4 0.6 4.8 75.9 51.8 33.8 8.4 7.5
416 151 6 1 142 301 262
72.2 26.2 1.0 0.2 24.7 52.3 45.5
355 118 8 3 105 244 227
74.4 23.3 1.7 0.6 22.0 51.2 47.6
236 126 189 25
41.0 21.9 32.8 4.3
398 58 21 0
83.4 12.2 4.4 0.0
0.053 0.018 0.479 0.663 0.582 <0.001 0.001 0.553 0.486 0.010 0.348
0.342 0.710 0.535 <0.001
P-values were evaluated using the paired t-test (for continuous values) and the chi-square test (for categorical values). Bold values mean the significance of P-value (<0.05). BMI, body mass index; NIHSS, National Institutes of Health Stroke Scale; NLR, neutrophil to lymphocyte ratio; TOAST: Trial of Org 10172 in Acute Stroke Treatment; LAA, large artery atherosclerosis; CE, cardioembolism; SVO, small vessel occlusion; SOE, stroke of other determined etiology; SUE, stroke of undetermined etiology; pack-yr, pack-year.
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TABLE 2. Comparison Between the Low NLR Group and High NLR Group (A) Men Age BMI (kg/m2) Neutrophil/lymphocyte ratio Smoking (pack-yr) Current smoking (yes/no) Alcohol consumption (yes/no) Previous stroke One time Two times Three times Prevalence of risk factor Hypertension Dyslipidemia Diabetes mellitus Atrial fibrillation Carotid artery stenosis Cerebral artery stenosis Other heart diseases Stroke family history Ischemic stroke type (TOAST) LAA SVO CE SOE SUE NIHSS (B) Women Age BMI (kg/m2) Neutrophil/lymphocyte ratio Smoking (pack-yr) Current smoking (yes/no) Alcohol consumption (yes/no) Previous stroke One time Two times Three times Prevalence of risk factor Hypertension Dyslipidemia Diabetes mellitus Atrial fibrillation Carotid artery stenosis Cerebral artery stenosis Other heart diseases Stroke family history Ischemic stroke type (TOAST) LAA SVO CE SOE SUE NIHSS
Low NLR group (n = 273)
High NLR group (n = 303)
P-value
65.14 11.16 23.89 2.89 1.87 0.45 18.61 24.35 107 (39.2%) 177 (64.84%)
66.18 12.46 23.90 2.91 4.95 4.47 16.08 22.16 95 (31.4%) 166 (54.79%)
0.288 0.937 <0.001 0.199 0.054 0.017 0.449
66 (24.26%) 2 (0.74%) 0 (0%)
85 (28.15%) 4 (1.32%) 1 (0.33%)
161 124 86 15 149 116 6 75
(58.97%) (45.42%) (31.50%) (5.49%) (54.58%) (42.49%) (2.20%) (27.47%)
212 117 98 26 152 146 16 67
(66.97%) (38.61%) (32.34%) (8.58%) (50.33%) (49.17%) (5.28%) (22.11%)
0.007 0.108 0.858 0.194 0.317 0.181 0.080 0.147
65 (23.8%) 182 (66.7%) 8 (2.9%) 8 (2.9%) 15 (5.5%) 4.15 2.31
77 (25.%4) 184 (60.7%) 24 (7.9%) 24 (7.9%) 18 (5.9%) 4.86 2.98
Low NLR group (n = 253)
High NLR group (n = 224)
P-value
69.20 10.07 23.95 3.15 1.72 0.47 1.65 8.24 19 (7.51%) 42 (16.60%)
71.08 11.24 23.28 3.74 4.64 2.75 1.80 8.89 12 (5.36%) 38 (16.96%)
0.054 0.036 <0.001 0.853 0.359 1.000 0.751
57 (22.53%) 3 (1.19%) 2 (0.79%)
54 (24.11%) 5 (2.23%) 1 (0.45%)
192 134 83 10 127 115 13 59
(75.89%) (53.17%) (32.81%) (3.95%) (50.20%) (45.45%) (5.14%) (23.32%)
45 (17.8%) 191 (75.5%) 6 (2.4%) 0 (0%) 11 (4.3%) 4.15 2.55
170 113 78 30 117 112 23 46
(75.89%) (50.45%) (34.82%) (13.39%) (52.23%) (50.00%) (10.27%) (20.54%)
48 (21.4%) 145 (64.7%) 15 (6.7%) 3 (1.3%) 12 (5.4%) 5.14 3.02
0.699 0.142 0.010 0.224 0.859 0.002
0.642 0.582 0.698 <0.001 0.714 0.358 0.038 0.507 0.355 0.012 0.025 0.103 0.671 <0.001
Low NLR group: NLR ≤ 2.5538 which is a median value of NLR, high NLR group: NLR > 2.5538. P-values were obtained via the paired t-test (continuous values) or chi-square test (categorical values). Low NLR group, low neutrophil to lymphocyte ratio group; high IMT group, high neutrophil to lymphocyte ratio group; BMI, body mass index; TOAST, Trial of Org 10172 in Acute Stroke Treatment; LAA, large artery atherosclerosis; CE, cardioembolism; SVO, small vessel occlusion; SOE, stroke of other determined etiology; SUE, stroke of undetermined etiology; NIHSS, National Institutes of Health Stroke Scale; pack-yr, pack-year.
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Association of NLR and Atrial Fibrillation
atrial fibrillation, other heart diseases, etiology of CE and SVO and NIHSS scores for women. Alcohol consumption, prevalence of hypertension, NIHSS scores in men and prevalence of atrial fibrillation, other heart diseases, NIHSS scores in women tended to increase with the NLR. In contrast, BMI in women tended to decrease with the NLR (Table 2). Multiple Linear Regression Model of the NLR in Men Table 3 shows the results of the multiple linear regression analyses of NLR and the baseline characteristics (prevalence of risk factors of stroke, age, NIHSS, etc.). In men, after adjusting for the confounding factors, such as smoking, alcohol consumption, atrial fibrillation, dyslipidemia, other heart diseases, and NIHSS, a significant positive association was observed for atrial fibrillation (P = 0.008) and NIHSS scores (P = 0.018) (adjusted R2 = 0.031, root mean squared error [MSE] = 7016.13). Multiple Linear Regression Model of the NLR in Women In women, multiple linear regression analyses for the confounding factors, such as age, BMI, atrial fibrillation, diabetes mellitus, carotid artery stenosis, and NIHSS, showed a significant positive association for atrial fibrillation (P = 0.002), diabetes mellitus (P = 0.037), and TABLE 3. Results of Multiple Linear Regression for NLR in Men Acute Ischemic Stroke Patients Men
Estimate
SE
P-value
Adjusted R2 0.031
Current smoking Alcohol consumption (yes/no) Prevalence of risk Atrial fibrillation Dyslipidemia Other heart diseases NIHSS
0.326 0.444
0.327 0.321
0.319 0.168
factor 1.611
0.602
0.008
0.384 0.774
0.312 0.803
0.219 0.335
0.137
0.057
0.018
NIHSS scores (P = 0.002) (Table 4). At the same time, a negative association was found for BMI (P = 0.049) (adjusted R2 = 0.031, root MSE = 7016.13). DISCUSSION NLR is currently used as a predictor of prognosis for cardiovascular disease (9), cancer (10, 11), and stroke and TIA (1–6). As a result of its simplicity and inexpensive costs, previous studies have suggested that NLR could be an effective prognostic marker for acute ischemic stroke, cardiovascular disease, and cancer. Furthermore, NLR has been proven as a useful marker for the severity of carotid artery stenosis (12, 13) in acute stroke patients and the risk of stroke in patients with atrial fibrillation (14, 15). However, no previous study has focused on the relationship between NLR and various stroke risk factors, which are found in acute stroke patients. Therefore, the present study aimed to assess the relationship between NLR and ischemic stroke risk factors. This study evaluated the association between NLR and the prevalence of stroke risk factors as well as NIHSS, in order to examine the relationship between subclinical inflammation and the various characteristics of acute ischemic stroke patients. Through this study, we sought to identify which risk factors could be the most appropriate predictor of NLR and the prognosis of acute ischemic stroke. Our findings show
TABLE 4. Results of Multiple Linear Regression for NLR in Women Acute Ischemic Stroke Patients Men
Root MSE 7,016.13
Atrial fibrillation, dyslipidemia, and other heart diseases refer to having a medical history of each disease. P-values were evaluated using the multiple linear regression test (NIHSS was treated as continuous values and current smoking, alcohol consumption, atrial fibrillation, dyslipidemia, and other heart diseases were treated as categorical values). NLR, neutrophil to lymphocyte ratio; NIHSS, National Institutes of Health Stroke Scale; R2, root-square; root MSE, root mean squared error.
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Estimate
SE
P-value
Adjusted R2 0.066
Age 0.016 BMI 0.63 Prevalence of risk factor Atrial 1.251 fibrillation Diabetes 0.475 mellitus Carotid 0.183 stenosis NIHSS 0.123
0.010 0.032
0.120 0.049
0.396
0.002
0.230
0.037
0.220
0.407
0.039
0.002
Root MSE 2525.629
Atrial fibrillation, diabetes mellitus, and carotid stenosis refer to having a medical history of each disease. P-values were evaluated using the multiple linear regression test (age, BMI, and NIHSS were treated as continuous values and atrial fibrillation, diabetes mellitus, and carotid stenosis were treated as categorical values). NLR, neutrophil to lymphocyte ratio; BMI, body mass index; NIHSS, National Institutes of Health Stroke Scale; R2, root-square; root MSE, root mean squared error.
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that NLR was significantly and positively associated with the prevalence of atrial fibrillation and severity of neurological symptoms (NIHSS scores) in men. Furthermore, NLR was significantly and positively associated with the prevalence of atrial fibrillation, diabetes mellitus, and severity of neurological symptoms (NIHSS scores) in women. On the other hand, in women, NLR was significantly and negatively associated with BMI. Furthermore, in this study, we confirmed that atrial fibrillation can be a predictor of a high NLR value in acute stroke patients, and that the prevalence of diabetes mellitus as well as a low BMI could be a predictor of high NLR value in female acute ischemic stroke patients. We also found that the prevalence of atrial fibrillation has a significant and positive association with NLR in both sexes. In previous studies, atrial fibrillation has been shown to have a strong relationship with systematic inflammation and inflammation has been further suggested to play a vital role in the pathogenesis of atrial fibrillation. For example, the inflammatory response after cardiac surgery has been a proven predictor of postoperative atrial fibrillation (16). Increased levels of plasma neopterin, which is synthesized by human macrophages upon stimulation with the cytokine interferon-gamma, is indicative of a pro-inflammatory immune status observed in patients with persistent atrial fibrillation (17). Monocyte toll-like receptor-4 expression was also an independent predictor of atrial fibrillation recurrence (18). Moreover, another study suggests that increased M1 macrophage infiltration is associated with thrombogenesis in rheumatic mitral stenosis patients with atrial fibrillation (19). We believe that these previous findings are in agreement with the results of the present study. Furthermore, we assumed that a persistent subclinical inflammatory state among patients with atrial fibrillation would affect the severity of the inflammatory response in acute ischemic stroke and negatively affect the prognosis of acute ischemic stroke. The limitations of this study are as follows. First, as this was a retrospective study using data from a single hospital, we cannot make a concrete conclusion in support of our hypothesis. Second, the number of subjects was relatively small. Thus, further evaluation in an additional future large-scale prospective study is required. REFERENCES 1. Zhao L, Dai Q, Chen X, et al. Neutrophil-to-lymphocyte ratio predicts length of stay and acute hospital cost in patients with acute ischemic stroke. J Stroke Cerebrovasc Dis 2016;25:739–44. 2. Tokgoz S, Kayrak M, Akpinar Z, Seyithanoglu A, G€ uney F, Y€ ur€ uten B. Neutrophil lymphocyte ratio as a predictor of stroke. J Stroke Cerebrovasc Dis 2013;22:1169–1174.
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