
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)12858-7
10.1016/j.heliyon.2024.e36827
e36827
Research Article
Neutrophil to lymphocyte ratio and five-year mortality in patients with acute ischemic stroke
Shan Yisi 1
Zhang Rong 1
Lu Juan
Huang Lingling
Wang Yadong
Long Fengdan
Sun Yaming sunyaming2001@126.com
⁎
Department of Neurology, The Affiliated Zhangjiagang TCM Hospital of Yangzhou University, Suzhou, 215600, China
⁎ Corresponding author. Department of Neurology, The Affiliated Zhangjiagang TCM Hospital of Yangzhou University, Suzhou City, Jiangsu, 215600, China. sunyaming2001@126.com
1 These authors contributed equally to this work.

23 8 2024
15 9 2024
23 8 2024
10 17 e368278 4 2024
21 8 2024
22 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Background

Previous studies linked neutrophil to lymphocyte ratio (NLR) with short-term mortality after acute ischemic stroke (AIS), but its relationship with long-term mortality remains unclear. This study investigates the association between NLR and five-year mortality in AIS patients.

Method

We analyzed 416 AIS patients from April 2012 to January 2016 at Zhangjiagang TCM Hospital. Admission NLR was divided into quartiles: Q1 (<2.00), Q2 (2.00–3.05), Q3 (3.06–5.46), and Q4 (≥5.46). We assessed 5-year all-cause and vascular mortality using Kaplan-Meier, Cox regression, and receiver operating characteristic (ROC) curve analyses.

Results

Over five years, 134 (32.2 %) all-cause deaths and 114 (27.4 %) vascular deaths occurred. Elevated NLR was significantly associated with increased risks of all-cause and vascular mortality. Multivariate Cox analysis identified stroke history (HR: 1.57, 95 % CI 1.08–2.30), baseline National Institutes of Health Stroke Scale (NIHSS) score (HR: 1.09, 95 % CI 1.05–1.12), and NLR (HR: 1.09, 95 % CI 1.05–1.12) as independent risk factors for all-cause mortality. These factors also predicted 5-year vascular mortality: stroke history (HR: 1.65, 95 % CI 1.10–2.49), NIHSS score (HR: 1.10, 95 % CI 1.06–1.13), and NLR (HR: 1.08, 95 % CI 1.05–1.10). NLR quartiles were significantly linked to both outcomes: all-cause mortality HRs were Q2 (1.87, 95 % CI 1.00–3.51), Q3 (2.40, 95 % CI 1.31–4.39), Q4 (2.77, 95 % CI 1.47–5.24), P for trend = 0.001; vascular mortality HRs were Q2 (1.76, 95 % CI 0.88–3.55), Q3 (2.34, 95 % CI 1.14–4.40), Q4 (2.57, 95 % CI 1.28–5.16), P for trend = 0.002. Kaplan-Meier survival analysis revealed significantly higher mortality rates in higher NLR quartiles (log-rank p < 0.001). ROC analysis identified optimal NLR cutoff values of 3.42 for predicting 5-year all-cause mortality (AUC 0.689) and 3.51 for vascular-cause mortality (AUC 0.700), with moderate sensitivity and specificity.

Conclusions

Higher NLR at admission was linked with five-year all-cause mortality and mortality attributed explicitly to vascular causes in AIS patients.

Keywords

Neutrophil to lymphocyte ratio
Acute ischemic stroke
All-cause mortality
Vascular-cause mortality
==== Body
pmc1 Introduction

Stroke is a prominent contributor to mortality rates on a global scale [1]. In China, it is noteworthy that the prevalence of heart disease has been superseded by another health condition, resulting in a shift in the most common cause of mortality [2]. Although intravenous thrombolysis and endovascular thrombectomy have made significant advances in acute ischemic stroke (AIS) treatment, understanding key factors that influence patient mortality is crucial for clinicians aiming to improve clinical outcomes.

The inflammatory response plays a vital role in the physiological mechanisms of ischemic stroke, especially the response after acute stroke, and has an essential function in post-ischemic injury. The infiltration of neutrophils, lymphocytes, and platelets into damaged brain tissue and the liberation of neurotoxins and inflammatory cytokines lead to further deterioration of neurological function [3,4] and even lead to fatality. Previous investigations have consistently demonstrated that elevated neutrophils and reduced lymphocytes are closely linked to poor prognosis of ischemic stroke [5,6].Therefore, neutrophil to lymphocyte ratio (NLR) may be correlated to clinical prognosis, including death, in ischemic stroke patients.

Earlier investigations have shown that NLR has been used as a factor that can be used to anticipate mortality rates over an extended period in individuals diagnosed with acute ST-segment elevation myocardial infarction [7,8]. Nevertheless, there is a lack of consensus concerning the correlation between NLR and mortality in ischemic stroke patients. Yu [9]et al. showed that NLR failed to accurately predict the occurrence of in-hospital mortality among ischemic stroke patients. Recent research has indicated that elevated levels of NLR are associated with a poor prognosis and death three months after AIS [[10], [11], [12]]. Meanwhile, the association of NLR with long-term all-cause death from ischemic stroke, especially from vascular death, remains unclear. Therefore, our investigation aimed to establish a link between the NLR and the incidence of 5-year all-cause mortality and vascular mortality in individuals with AIS.

2 Materials and methods

2.1 Study design and population

We identified AIS patients from Zhangjiagang Traditional Chinese Medicine (TCM) Hospital between April 2012 to January 2016. According to World Health Organization (WHO) guidelines, AIS was identified and validated by computed tomography or magnetic resonance imaging. The following additional criteria were also excluded: (1) 72-h period from the time of onset to admission (n = 116); (2) clinical data missing (n = 6); (3) no neutrophil count or lymphocyte count (n = 5); and (4) follow-up at 5-year loss (n = 8); a total of 416 patients, for whom data was available, were ultimately included in the present study (a flowchart depicting the process of choosing participants; Fig. 1). The Ethics Committee of Zhangjiagang TCM Hospital approved the current investigation, with a waiver of informed consent from patients as a result of the retrospective nature of the investigation.Fig. 1 Flowchart of participants selection.

Fig. 1

2.2 Data Collection

Herein, we gathered baseline demographic data encompassing stroke severity and vascular risk factors as determined by the National Institutes of Health Stroke Scale (NIHSS), medication usage, diagnosis-related information, and imaging data. The vascular risk factors encompassed in this study comprised hypertension, diabetes mellitus, a prior history of stroke, a prior atrial fibrillation history, a previous occurrence of coronary heart disease, alcohol consumption, and present or past smoking status.

Blood samples were obtained within a 24-h following the patient's admission to the hospital. The quantification of white blood cell and peripheral differential counts was conducted. The analysis of serum low-density lipoprotein cholesterol (LDL-C) and other biochemical parameters was performed by a commercially available Olympus AU5400 automatic biochemical analyzer (First Chemical CO, LTD, Japan) and commercial reagents. The NLR was determined by dividing the neutrophil count by the lymphocyte count.

2.3 Outcome assessment and follow-up

In this study, the primary research outcome was 5-year mortality. Follow-up data were collected by examining hospital records or interviews conducted in person or via telephone with patients, their families, or their physicians. The determination of the cause of death was made based on an analysis of medical records and death certificates.

2.4 Statistical analysis

Normally distributed continuous variables were reported as mean ± standard deviation (SD), while non-normally distributed variables were presented as the median and interquartile range (IQR). Categorical variables were described with frequency and percentage (%). Statistical analyses included the t-test for continuous variables, the Chi-square or Fisher's exact test for categorical variables, and the Mann-Whitney U test for non-normally distributed variables. Patients were grouped into quartiles based on their admission NLR values. Differences in continuous variables among NLR quartile groups were assessed using one-way ANOVA or the Kruskal-Wallis test. Cox regression analysis evaluated the relationship between mortality outcome and clinical features, including variables with a P < 0.1 in the multivariate analysis. Additionally, Cox regression was used to examine the association between NLR and end-point event, with and without adjustment for relevant confounding factors. Receiver operating characteristic (ROC) curves determined cutoff values for mortality prediction, and Kaplan-Meier analysis evaluated prognostic value, with significance set at P < 0.05. Data were analyzed using SPSS version 22.0 and visualized with GraphPad Prism version 9.3.

3 Results

3.1 Baseline characteristics

A total of 134 (32.2 %) all-cause deaths and 114 (27.4 %) vascular-related deaths were documented over the five-year follow-up period. Table 1 summarizes the baseline characteristics of the study population. In the cohort stratified by 5-year all-cause mortality, there were no significant differences in gender, alcohol consumption, hypertension, diabetes mellitus, history of coronary heart disease (CHD), diastolic blood pressure (BP), total cholesterol (TC), LDL-C, and fasting plasma glucose (FPG) between survivors and non-survivors. However, significant differences were observed in age, smoking status, atrial fibrillation, systolic BP, heart rate, white blood cell (WBC) count, triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and NLR. Notably, NLR levels were significantly higher in the non-survivor group compared to the survivor group. Similarly, in the cohort stratified by 5-year vascular mortality, no statistical differences were found in alcohol consumption, hypertension, diabetes mellitus, history of CHD, diastolic BP, TC, LDL-C, HDL-C, and FPG between the groups. However, age, gender, smoking status, atrial fibrillation, systolic BP, heart rate, WBC count, TG, and NLR showed substantial differences. Similarly, NLR levels were notably elevated in non-survivors compared to survivors (Fig. 2).Table 1 Baseline characteristics of the study subjects.

Table 1Characteristics	5-year all-cause mortality cohort	5-year vascular-cause mortality cohort	
All subjects	Non-survivors	Survivors	P-value	Non-survivors	Survivors	P-value	
N = 416	N = 134	N = 282	N = 114	N = 302	
Age, y	72.0 (16.0)	80.0 (10.0)	67.0 (16.0)	<0.001	80.0 (9.0)	68.0 (16.0)	<0.001	
Male/female	207/209	59/75	148/134	0.107	47/67	160/142	0.032	
Smoking (%)	107 (25.7)	24 (17.9)	83 (29.4)	0.012	19 (16.7)	88 (29.1)	0.009	
Drinking (%)	81 (19.5)	20 (14.9)	61 (21.6)	0.107	17 (14.9)	64 (21.2)	0.149	
Hypertension	288 (69.2)	98 (73.1)	190 (67.4)	0.234	84 (73.7)	204 (67.5)	0.227	
Diabetes mellitus	90 (21.6)	24 (17.9)	66 (23.4)	0.203	21 (18.4)	69 (22.8)	0.328	
History of CHD	22 (5.3)	12 (4.3)	10 (7.5)	0.172	9 (7.9)	13 (4.3)	0.144	
Atrial fibrillation	63 (15.1)	37 (27.6)	26 (9.2)	<0.001	34 (29.8)	29 (9.6)	<0.001	
Systolic BP, mmHg	150.0 (25.0)	160.0 (30.0)	150.0 (33.0)	0.001	160.0 (30.0)	150.0 (28.0)	0.003	
Diastolic BP, mmHg	88.5 (15.0)	89.5 (20.0)	85.0 (13.0)	0.218	90.0 (20.0)	85.0 (13.0)	0.126	
Heart rate (times/min)	75.0 (10.0)	78.0 (15.0)	72.0 (10.0)	0.001	80.0 (15.0)	72.0 (10.0)	<0.001	
WBC count ( × 109/L)	6.4 (2.9)	6.9 (3.9)	6.3 (2.6)	0.041	7.0 (3.8)	6.3 (2.6)	0.007	
NLR	3.1 (3.5)	4.6 (5.0)	2.7 (2.4)	<0.001	4.8 (5.5)	2.7 (2.4)	<0.001	
TC, mmol/L	4.5 (1.4)	4.4 (1.5)	4.6 (1.4)	0.263	4.5 (1.5)	4.6 (1.4)	0.360	
TG, mmol/L	1.3 (1.0)	1.4 (1.1)	1.1 (0.6)	<0.001	1.0 (0.7)	1.4 (1.1)	<0.001	
LDL-C, mmol/L	2.7 (1.2)	2.5 (1.4)	2.7 (1.2)	0.277	2.5 (1.5)	2.7 (1.2)	0.307	
HDL-C, mmol/L	1.3 (0.5)	1.4 (0.6)	1.3 (0.5)	0.041	1.4 (0.5)	1.3 (0.5)	0.099	
FPG, mmol/L	5.5 (1.7)	5.5 (1.6)	5.4 (1.8)	0.491	5.7 (1.9)	5.5 (1.5)	0.835	
Data are expressed as mean ± standard deviation, or median (interquartile range), or number of patients (%).

Abbreviation: CHD, coronary heart disease; BP, blood pressure; WBC, white blood cell; NLR, neutrophil to lymphocyte ratio; TC, total cholesterol; TG, triglyceride; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; FPG, fasting plasma glucose.

Fig. 2 Comparison of NLR levels between groups.

Fig. 2

3.2 Clinical features and mortality outcomes

As shown in Table 2, univariate Cox regression analysis revealed that 5-year all-cause mortality was significantly associated with a history of stroke, time from onset to sample, baseline NIHSS score, and NLR. Specifically, the associations were as follows: history of stroke (HR: 1.48, 95 % CI 1.02–2.15, P = 0.037), time from onset to sample (HR: 0.99, 95 % CI 0.98–1.00, P = 0.050), baseline NIHSS score (HR: 1.11, 95 % CI 1.09–1.14, P < 0.001), and NLR (HR: 1.11, 95 % CI 1.08–1.14, P < 0.001). Additionally, the Oxfordshire Community Stroke Project (OCSP) subtype was linked to mortality outcomes. Multivariate analysis confirmed that a history of stroke (HR: 1.57, 95 % CI 1.08–2.30, P = 0.019), baseline NIHSS score (HR: 1.09, 95 % CI 1.05–1.12, P < 0.001), and NLR (HR: 1.09, 95 % CI 1.05–1.12, P < 0.001) remained significant predictors of all-cause mortality. Furthermore, these factors were also identified as independent prognostic indicators for 5-year vascular mortality: history of stroke (HR: 1.65, 95 % CI 1.10–2.49, P = 0.017), baseline NIHSS score (HR: 1.10, 95 % CI 1.06–1.13, P < 0.001), and NLR (HR: 1.08, 95 % CI 1.05–1.10, P < 0.001).Table 2 Relationship between mortality outcome and clinical features.

Table 2Death from any cause	Univariable	Multivariable	Death from vascular cause	Univariable	Multivariable	
Variables	HR (95 % CI)	P-value	HR (95 % CI)	P-value	Variables	HR (95 % CI)	P-value	HR (95 % CI)	P-value	
History of stroke	1.48 (1.02–2.15)	0.037	1.57 (1.08–2.30)	0.019	History of stroke	1.53 (1.03–2.28)	0.035	1.65 (1.10–2.49)	0.017	
Thrombolytic therapy	1.74 (0.77–3.95)	0.184			Thrombolytic therapy	1.69 (0.69–4.14)	0.252			
Time onset-to-sample	0.99 (0.98–1.00)	0.050	1.00 (0.99–1.01)	0.787	Time onset-to-sample	0.98 (0.97–0.99)	0.013	0.99 (0.98–1.01)	0.383	
Length of stay	1.00 (0.97–1.03)	0.902			Length of stay	1.01 (0.98–1.04)	0.610			
Baseline NIHSS score	1.11 (1.09–1.14)	<0.001	1.09 (1.05–1.12)	<0.001	Baseline NIHSS score	1.13 (1.10–1.15)	<0.001	1.10 (1.06–1.13)	<0.001	
NLR	1.11 (1.08–1.14)	<0.001	1.09 (1.05–1.12)	<0.001	NLR	1.11 (1.09–1.14)	<0.001	1.08 (1.05–1.11)	<0.001	
Subtype of OCSP					Subtype of OCSP					
TACI	1.00 (reference)		1.00 (reference)		TACI	1.00 (reference)		1.00 (reference)		
PACI	0.21 (0.12–0.36)	<0.001	0.75 (0.38–1.50)	0.421	PACI	0.18 (0.11–0.32)	<0.001	0.77 (0.38–1.59)	0.483	
POCI	0.19 (0.10–0.39)	<0.001	0.70 (0.31–1.56)	0.378	POCI	0.19 (0.09–0.38)	<0.001	0.79 (0.35–1.79)	0.567	
LACI	0.12 (0.07–0.21)	<0.001	0.64 (0.28–1.45)	0.282	LACI	0.10 (0.05–0.17)	<0.001	0.66 (0.28–1.58)	0.352	
Abbreviation: HR, hazard ratio; CI, confidence interval; NIHSS, National Institutes of Health Stroke Scale; NLR, neutrophil to lymphocyte ratio; OCSP, Oxfordshire Community Stroke Project; TACI, Total Anterior Circulation Infarct; PACI, Partial Anterior Circulation Infarct; POCI, Posterior Circulation Infarct; LACI, Lacunar Circulation Infarct.

3.3 Characteristics of study participants according to NLR quartiles

Admission NLR was categorized into quartiles: Q1 (<2.00), Q2 (2.00–3.05), Q3 (3.06–5.46), and Q4 (≥5.46). Table 3 lists the features of the investigation population-related NLR quartile. In comparison to patients with fewer NLR levels, those with higher NLR levels were more likely to be old and more likely to have atrial fibrillation. Other stroke risk factors were not different across NLR quartile groups. Patients exhibiting elevated NLR levels also displayed notable distinctions in their metabolic profile, characterized by heightened levels of white blood cells (WBCs). Patients who were in the greater quartiles of NLR exhibited a greater likelihood of presenting with severe neurologic deficits upon admission. Moreover, patients with higher NLR levels had more 5-year mortality.Table 3 Characteristics of study participants according to NLR quartiles.

Table 3Characteristics	NLR	
Q1
<2.00
N = 104	Q2
2.00–3.05
N = 105	Q3
3.06–5.46
N = 104	Q4
≥5.46
N = 103	P-value	
Age, y	70.0 (14.0)	71.0 (15.0)	73.0 (17.0)	77.0 (17.0)	0.016	
Male/female	45/59	60/45	58/46	44/59	0.055	
Smoking (%)	28 (26.9)	31 (29.5)	35 (33.7)	13 (12.6)	0.004	
Drinking (%)	23 (22.1)	27 (25.7)	22 (21.2)	9 (8.7)	0.013	
Hypertension	74 (71.2)	71 (67.6)	69 (66.3)	74 (71.8)	0.790	
Diabetes mellitus	21 (20.2)	23 (21.9)	26 (25.0)	20 (19.4)	0.771	
History of CHD	2 (1.9)	4 (3.8)	7 (6.7)	9 (8.7)	0.128	
Atrial fibrillation	8 (7.7)	11 (10.5)	13 (12.5)	31 (30.1)	<0.001	
Systolic BP, mmHg	150.0 (34.0)	150.0 (33.0)	155.5 (25.0)	160.0 (30.0)	0.007	
Diastolic BP, mmHg	85.0 (10.0)	85.0 (10.0)	85.5 (15.0)	90.0 (20.0)	0.193	
Heart rate (times/min)	75.0 (10.0)	72.0 (11.0)	72.0 (10.0)	80.0 (15.0)	0.008	
WBC count ( × 109/L)	5.7 (2.1)	5.8 (2.3)	6.5 (2.5)	8.6 (3.8)	<0.001	
TC, mmol/L	4.5 (1.3)	4.8 (1.4)	4.5 (1.4)	4.5 (1.6)	0.365	
TG, mmol/L	1.5 (1.2)	1.4 (1.0)	1.3 (0.8)	1.0 (0.7)	<0.001	
LDL-C, mmol/L	2.6 (1.1)	2.8 (1.1)	2.5 (1.3)	2.7 (1.5)	0.616	
HDL-C, mmol/L	1.3 (0.5)	1.3 (0.5)	1.2 (0.5)	1.3 (0.5)	0.243	
FPG, mmol/L	5.4 (1.2)	5.3 (1.3)	5.5 (1.9)	6 (2.1)	0.033	
History of stroke	31 (29.8)	25 (23.8)	22 (21.2)	23 (22.3)	0.474	
Thrombolytic therapy	3 (2.9)	1 (1.0)	3 (2.9)	6 (5.8)	0.245	
Time onset-to-sample, h	12.0 (45.0)	15.0 (28.0)	10.5 (20.0)	5.0 (12.0)	<0.001	
Length of stay, day	10.0 (6.0)	11.0 (6.0)	11.5 (5.0)	11.0 (8.0)	0.083	
Baseline NIHSS score	4.0 (4.0)	4.0 (4.0)	4.0 (4.0)	8.0 (10.0)	<0.001	
Subtype of OCSP					<0.001	
TACI	3 (2.9)	2 (1.9)	4 (3.8)	14 (13.6)		
PACI	34 (32.7)	43 (41.0)	37 (35.6)	45 (43.7)		
POCI	5 (4.8)	11 (10.5)	12 (11.5)	19 (18.4)		
LACI	62 (59.6)	49 (46.7)	51 (49.0)	25 (24.3)		
All-cause mortality (%)	16 (15.4)	27 (25.7)	34 (32.7)	57 (55.3)	<0.001	
Vascular-cause mortality (%)	13 (12.5)	22 (21.0)	27 (26.0)	52 (50.5)	<0.001	
Data are expressed as mean ± standard deviation, or median (interquartile range), or number of patients (%).

Abbreviation: CHD, coronary heart disease; BP, blood pressure; WBC, white blood cell; NLR, neutrophil to lymphocyte ratio; TC, total cholesterol; TG, triglyceride; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; FPG, fasting plasma glucose; NIHSS, National Institutes of Health Stroke Scale; OCSP, Oxfordshire Community Stroke Project; TACI, Total Anterior Circulation Infarct; PACI, Partial Anterior Circulation Infarct; POCI, Posterior Circulation Infarct; LACI, Lacunar Circulation Infarct.

3.4 Association of NLR quartiles with mortality outcomes

Table 4 illustrates the association between NLR quartiles and mortality outcomes. In the cohort stratified by 5-year all-cause mortality, Model 4, adjusted for age, smoking status, atrial fibrillation, systolic BP, heart rate, WBC count, HDL-C, TG, baseline NIHSS score, and history of stroke, revealed multivariate hazard ratios (HRs) for all-cause mortality as follows: Q2 (HR: 1.87, 95 % CI 1.00–3.51), Q3 (HR: 2.40, 95 % CI 1.31–4.39), and Q4 (HR: 2.77, 95 % CI 1.47–5.24), with a trend P-value of 0.001. For vascular-cause mortality, in the fully adjusted model, the multivariate HRs for Q2, Q3, and Q4 compared to Q1 (reference) were 1.76 (95 % CI 0.88–3.55), 2.34 (95 % CI 1.14–4.40), and 2.57 (95 % CI 1.28–5.16), respectively (P for trend = 0.002).Table 4 Association of NLR quartiles with mortality outcome.

Table 4Death from any cause	HR (95 % CI)		Death from vascular cause	HR (95 % CI)		
Q1
<2.00 N = 104	Q2
2.00–3.05 N = 105	Q3
3.06–5.46 N = 104	Q4
≥5.46
N = 103	P-trend	Q1
<2.00 N = 104	Q2
2.00–3.05 N = 105	Q3
3.06–5.46 N = 104	Q4
≥5.46
N = 103	P-trend	
Model1: crude, no adjustment	1.0	1.72 (0.93–3.19)	2.39 (1.32–4.33)	4.92 (2.83–8.59)	<0.001	Model1: crude, no adjustment	1.0	1.72 (0.87–3.41)	2.32 (1.20–4.50)	5.42 (2.95–9.97)	<0.001	
P-value		0.086	0.004	<0.001		P-value		0.121	0.013	<0.001		
Model2: adjusting for age, smoking, AF	1.0	1.71 (0.92–3.19)	2.38 (1.31–4.35)	4.19 (2.38–7.41)	<0.001	Model2: adjusting for age, smoking, gender, AF	1.0	1.68 (0.84–3.38)	2.30 (1.18–4.51)	4.45 (2.38–8.31)	<0.001	
P-value		0.089	0.005	<0.001		P-value		0.143	0.015	<0.001		
Model3: adjusting for age, smoking, AF, systolic BP, heart rate, WBC, HDL-C, TG	1.0	1.74 (0.93–3.24)	2.27 (1.23–4.16)	3.11 (1.65–5.86)	<0.001	Model3: adjusting for age, smoking, gender, AF, systolic BP, heart rate, WBC, TG	1.0	1.66 (0.83–3.34)	2.13 (1.08–4.22)	2.98 (1.49–5.97)	<0.001	
P-value		0.084	0.008	<0.001		P-value		0.155	0.029	0.002		
Model4: adjusting for age, smoking, AF, systolic BP, heart rate,WBC, HDL-C, TG, baseline NIHSS score, history of stroke	1.0	1.87 (1.00–3.51)	2.40 (1.31–4.39)	2.77 (1.47–5.24)	0.001	Model4: adjusting for age, smoking, gender, AF, systolic BP, heart rate, WBC, TG, baseline NIHSS score, history of stroke	1.0	1.76 (0.88–3.55)	2.34 (1.14–4.40)	2.57 (1.28–5.16)	0.002	
P-value		0.050	0.005	0.002		P-value		0.112	0.020	0.008		
Abbreviation: HR, hazard ratio; CI, confidence interval; AF, atrial fibrillation; BP, blood pressure; WBC, white blood cell; HDL-C, high-density lipoprotein cholesterol; TG, triglyceride; NIHSS, National Institutes of Health Stroke Scale; NLR, neutrophil to lymphocyte ratio.

3.5 Kaplan-Meier survival analysis for 5-year mortality

The Kaplan-Meier curves in Fig. 3, Fig. 4 illustrate the relationship between quartiles and 5-year all-cause mortality and death from vascular causes. The findings revealed significant gradients in both 5-year mortality rates for all causes and mortality rates attributed explicitly to vascular causes across the quartiles of NLR. Notably, the high NLR group exhibited a substantially elevated hazard of death. The observed difference was significant based on the log-rank test (P < 0.001).Fig. 3 NLR quartiles and 5-year all-cause mortality.

Fig. 3

Fig. 4 NLR quartiles and 5-year vascular-cause mortality.

Fig. 4

3.6 The value of NLR for predicting the mortality outcomes

ROC analysis of NLR to predict mortality outcomes revealed (Fig. 5, Fig. 6) that NLR value 3.42 was the best cutoff level for predicting 5-year all-cause mortality, which gave 65.7 % sensitivity and 64.9 % specificity with an area under the curve (AUC) of 0.689 (95 % CI 0.63–0.75, P < 0.001). Moreover, 3.51 was the optimal cutoff level to predict 5-year vascular-cause mortality, presenting 66.7 % sensitivity and 66.2 % specificity with an AUC of 0.700 (95 % CI 0.64–0.76, P < 0.001).Fig. 5 ROC analysis of NLR to predict 5-year all-cause mortality outcome.

Fig. 5

Fig. 6 Predictive Value of NLR for 5-year vascular-cause mortality.

Fig. 6

4 Discussion

Herein, we aim to assess the prognostic validity of admission NLR in predicting both all-cause mortality and mortality attributed explicitly to vascular causes over five years in our study. This investigation utilized data from a cohort of 416 patients. The outcomes of our investigation indicate a significant association between elevated NLR upon admission and increased mortality rates over five years, encompassing both all-cause mortality and mortality attributed explicitly to vascular causes.

Recent studies have demonstrated that the NLR serves as a predictor for early neurological deterioration and mortality at the three-month mark in AIS patients [[13], [14], [15]]. Although patients with ischemic stroke can currently receive intravascular reperfusion therapy, the mortality in these patients is still high. NLR within 24 h before [16] or after [17,18] intravenous thrombolysis or intravascular thrombectomy can predict hemorrhagic transformation and 3-month mortality. Additionally, several investigations have investigated the strong association between the NLR and one-year mortality in AIS [19,20]. Quan [20] et al. discovered that an elevated NLR level within the initial 24 h following admission is linked to a heightened risk of adverse clinical outcomes, both in the short-term and long-term, among ischemic stroke patients, irrespective of the underlying cause. The NLR ≥3.180, with a sensitivity of 58.39 % and specificity of 66.69 %, can potentially be a predictive factor for one-year mortality. Additionally, we increased the duration of the follow-up period and observed that the aforementioned correlation remained statistically significant after a 5-year follow-up. NLR was determined to be a significant independent prognostic factor for all-cause mortality. Hence, the NLR may be regarded as a prognostic indicator for both short-term and long-term mortality outcomes among individuals afflicted with ischemic stroke. In our ROC analysis of NLR for predicting 5-year all-cause mortality, a cutoff value of 3.42 demonstrated 65.7 % sensitivity and 64.9 % specificity, with an AUC of 0.689. The optimal cutoff for predicting 5-year vascular-cause mortality was 3.51, yielding 66.7 % sensitivity and 66.2 % specificity, with an AUC of 0.700. Although these AUC values indicate moderate predictive ability, NLR could be a valuable marker for long-term mortality risk stratification in clinical practice.

In our study, stroke causes high 5-year mortality (32.2 %), and NLR was a better indicator of five-year vascular death, which may have several explanations. First, after ischemic stroke, the blood-brain barrier breakdown in the local region, caused by ischemia, facilitates the entry of inflammatory factors, such as neutrophils and lymphocytes. These inflammatory factors have long-term effects and may affect the prognosis of ischemic stroke patients, including death. Neutrophils possess the potential to instigate additional thrombus formation through the release of molecules or interactions with platelets. Consequently, they may obstruct microvessels, impede perfusion, and ultimately result in prolonged ischemia [21]. In contrast, lymphocytes exhibit a delayed accumulation in the post-ischemic brain, albeit slower than neutrophils. Lymphocyte response post-stroke has been shown to be increasingly complex, with diverse beneficial and detrimental roles at different time points after stroke for various subsets of lymphocytes. Even 30 days after stroke, lymphocytes were still high, indicating that lymphocytes mediated neuroplasticity and the potential beneficial effect of enhancing post-stroke recovery may last months and years after stroke [22,23].

Second, atherosclerosis is a chronic inflammatory process. AIS may be a more intense inflammatory response caused by chronic inflammation, which affects the prognosis of AIS and is closely linked to vascular death. Multiple studies have provided empirical evidence supporting a strong link between the NLR and plaque stability in the carotid artery [24,25], carotid artery stenosis [26], and intracranial artery stenosis [27]. Higher NLR leads to instability of carotid and intracranial artery plaques, leading to the occurrence or recurrence of ischemic stroke and, in severe cases, patient death. This is probably another reason why higher NLR in patients with AIS leads to more vascular death.

Our investigation encountered multiple constraints. First, this investigation consists of a retrospective analysis conducted at a single center. Although some possible relevant factors are eliminated by multi-factor analysis, other non-predicable or improper factors still cannot be eliminated completely. Therefore, correlations reflected by this study might be deflected. Second, this investigation is mainly based on a relatively small Chinese population. The research results shall be recommended carefully to populations with genetic backgrounds. Moreover, patients with missing neutrophil and lymphocyte counts are excluded, which may cause deflection in the research conclusions. Third, the selection process exclusively includes patients admitted to the hospital 72 h following a stroke, which cannot accurately evaluate neutrophil or lymphocyte count during the peak stage. The research conclusions shall be further proved by increasing coverage of occurrence time and cases and by dynamic observation of neutrophil and lymphocyte counts.

5 Conclusions

The presence of an elevated level of NLR upon admission was found to be significantly correlated with both overall mortality and mortality attributed explicitly to vascular causes within a five-year period among individuals diagnosed with AIS.

Ethics and consent statement

This study was approved by the Ethics Committee of the Zhangjiagang TCM Hospital, approval number: No. KY2022-6-5-1。

Competing interests

The authors have declared that no competing interest exists.

Funding

This work was supported by the 10.13039/501100002949 Jiangsu Province elderly health research project (LKM2023039 ), Suzhou key clinical disease diagnosis and treatment technology special project (LCZX202121 ), Zhangjiagang City Science and Technology Planning Project (ZKS2125 ) and Suzhou Medical Health Science and Technology Innovation Project (SKYD2022047 ).

Data availability statement

Data will be made available on reasonable request.

CRediT authorship contribution statement

Yisi Shan: Writing – review & editing, Writing – original draft. Rong Zhang: Writing – original draft. Juan Lu: Data curation. Lingling Huang: Data curation. Yadong Wang: Methodology, Investigation. Fengdan Long: Methodology, Investigation. Yaming Sun: Writing – review & editing, Writing – original draft.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

All authors are grateful to the Zhangjiagang TCM Hospital for support.
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References

1 Sacco R.L. Kasner S.E. Broderick J.P. Caplan L.R. Connors J.J. Culebras A. An updated definition of stroke for the 21st century: a statement for healthcare professionals from the American Heart Association/American Stroke Association Stroke 44 7 2013 2064 2089 10.1161/STR.0b013e318296aeca 23652265
2 Zhou M. Wang H. Zeng X. Yin P. Zhu J. Chen W. Mortality, morbidity, and risk factors in China and its provinces, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017 Lancet 394 10204 2019 1145 1158 10.1016/s0140-6736(19)30427-1 31248666
3 Shekhar S. Cunningham M.W. Pabbidi M.R. Wang S. Booz G.W. Fan F. Targeting vascular inflammation in ischemic stroke: recent developments on novel immunomodulatory approaches Eur. J. Pharmacol. 833 2018 531 544 10.1016/j.ejphar.2018.06.028 29935175
4 Kim J.Y. Park J. Chang J.Y. Kim S.H. Lee J.E. Inflammation after ischemic stroke: the role of leukocytes and glial cells Exp Neurobiol 25 5 2016 241 251 10.5607/en.2016.25.5.241 27790058
5 Jayaraj R.L. Azimullah S. Beiram R. Jalal F.Y. Rosenberg G.A. Neuroinflammation: friend and foe for ischemic stroke J. Neuroinflammation 16 2019 10.1186/s12974-019-1516-2
6 Yuan M. Han B. Xia Y. Liu Y. Wang C. Zhang C. Augmentation of Peripheral Lymphocyte-Derived Cholinergic Activity in Patients with Acute Ischemic Stroke vol. 19 2019
7 Bressi E. Mangiacapra F. Ricottini E. Cavallari I. Colaiori I. Di Gioia G. Impact of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio on 5-year clinical outcomes of patients with stable coronary artery disease undergoing elective percutaneous coronary intervention J Cardiovasc Transl Res 11 6 2018 517 523 10.1007/s12265-018-9829-6 30276618
8 Han Y.C. Yang T.H. Kim D.I. Jin H.Y. Chung S.R. Seo J.S. Neutrophil to lymphocyte ratio predicts long-term clinical outcomes in patients with ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention Korean Circ J 43 2 2013 93 99 10.4070/kcj.2013.43.2.93 23508782
9 Yu S. Arima H. Bertmar C. Clarke S. Herkes G. Krause M. Neutrophil to lymphocyte ratio and early clinical outcomes in patients with acute ischemic stroke J. Neurol. Sci. 387 2018 115 118 10.1016/j.jns.2018.02.002 29571846
10 Song S.Y. Zhao X.X. Rajah G. Hua C. Kang R.J. Han Y.P. Clinical significance of baseline neutrophil-to-lymphocyte ratio in patients with ischemic stroke or hemorrhagic stroke: an updated meta-analysis Front. Neurol. 10 2019 1032 10.3389/fneur.2019.01032 31636598
11 Wang L. Song Q. Wang C. Wu S. Deng L. Li Y. Neutrophil to lymphocyte ratio predicts poor outcomes after acute ischemic stroke: a cohort study and systematic review J. Neurol. Sci. 406 2019 116445 10.1016/j.jns.2019.116445
12 Zhang J. Ren Q. Song Y. He M. Zeng Y. Liu Z. Prognostic role of neutrophil-lymphocyte ratio in patients with acute ischemic stroke Medicine (Baltim.) 96 45 2017 e8624 10.1097/MD.0000000000008624
13 Zhang R. Wu X. Hu W. Zhao L. Zhao S. Zhang J. Neutrophil-to-lymphocyte ratio predicts hemorrhagic transformation in ischemic stroke: a meta-analysis Brain Behav 9 9 2019 e01382 10.1002/brb3.1382
14 Sarejloo S. Kheradjoo H. Haghi S.E. Hosseini S. Gargari M.K. Azarhomayoun A. Neutrophil-to-Lymphocyte ratio and early neurological deterioration in stroke patients: a systematic review and meta-analysis BioMed Res. Int. 2022 2022 8656864 10.1155/2022/8656864
15 Kocaturk O. Besli F. Gungoren F. Kocaturk M. Tanriverdi Z. The relationship among neutrophil to lymphocyte ratio, stroke territory, and 3-month mortality in patients with acute ischemic stroke Neurol. Sci. 40 1 2019 139 146 10.1007/s10072-018-3604-y 30327959
16 Lee S.H. Jang M.U. Kim Y. Park S.Y. Kim C. Kim Y.J. The neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios predict reperfusion and prognosis after endovascular treatment of acute ischemic stroke J Pers Med 11 8 2021 10.3390/jpm11080696
17 Guo Z. Yu S. Xiao L. Chen X. Ye R. Zheng P. Dynamic change of neutrophil to lymphocyte ratio and hemorrhagic transformation after thrombolysis in stroke J. Neuroinflammation 13 1 2016 199 10.1186/s12974-016-0680-x 27561990
18 Lux D. Alakbarzade V. Bridge L. Clark C.N. Clarke B. Zhang L. The association of neutrophil-lymphocyte ratio and lymphocyte-monocyte ratio with 3-month clinical outcome after mechanical thrombectomy following stroke J. Neuroinflammation 17 1 2020 60 10.1186/s12974-020-01739-y 32070366
19 Li L.H. Chen C.T. Chang Y.C. Chen Y.J. Lee I.H. How C.K. Prognostic role of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and systemic immune inflammation index in acute ischemic stroke: a STROBE-compliant retrospective study Medicine (Baltim.) 100 25 2021 e26354 10.1097/MD.0000000000026354
20 Quan K. Wang A. Zhang X. Meng X. Chen P. Li H. Neutrophil to lymphocyte ratio and adverse clinical outcomes in patients with ischemic stroke Ann. Transl. Med. 9 13 2021 1047 10.21037/atm-21-710 34422959
21 Kleinig T.J. Vink R. Suppression of inflammation in ischemic and hemorrhagic stroke: therapeutic options Curr. Opin. Neurol. 22 3 2009 294 301 10.1097/wco.0b013e32832b4db3 19434798
22 Jones K.A. Maltby S. Plank M.W. Kluge M. Nilsson M. Foster P.S. Peripheral immune cells infiltrate into sites of secondary neurodegeneration after ischemic stroke Brain Behav. Immun. 67 2018 299 307 10.1016/j.bbi.2017.09.006 28911981
23 Xie L. Li W. Hersh J. Liu R. Yang S.H. Experimental ischemic stroke induces long-term T cell activation in the brain J Cereb Blood Flow Metab 39 11 2019 2268 2276 10.1177/0271678X18792372 30092705
24 Li X. Li J. Wu G. Xu Y. Relationship of neutrophil-to-lymphocyte ratio with carotid plaque vulnerability and occurrence of vulnerable carotid plaque in patients with acute ischemic stroke BioMed Res. Int. 2021 2021 1 8 10.1155/2021/6894623 35465048
25 Ruan W. Wang M. Sun C. Yao J. Ma Y. Ma H. Correlation between neutrophil-to-lymphocyte ratio and stability of carotid plaques Clin. Neurol. Neurosurg. 212 2022 107055 10.1016/j.clineuro.2021.107055
26 Köklü E. Yüksel İ.Ö. Arslan Ş. Bayar N. Çağırcı G. Gencer E.S. Is elevated neutrophil-to-lymphocyte ratio a predictor of stroke in patients with intermediate carotid artery stenosis? J. Stroke Cerebrovasc. Dis. 25 3 2016 578 584 10.1016/j.jstrokecerebrovasdis.2015.10.031 26706445
27 Ying Y. Yu F. Luo Y. Feng X. Liao D. Wei M. Neutrophil-to-Lymphocyte ratio as a predictive biomarker for stroke severity and short-term prognosis in acute ischemic stroke with intracranial atherosclerotic stenosis Front. Neurol. 12 2021 10.3389/fneur.2021.705949
