Effect Of Thrombolytic Therapy On High Neutrophil-to-Lymphocyte Ratio In Predicting Stroke-Associated Pneumonia After Acute Ischemic Stroke

doi:10.21203/rs.3.rs-1509675/v1

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Research Article

Effect Of Thrombolytic Therapy On High Neutrophil-to-Lymphocyte Ratio In Predicting Stroke-Associated Pneumonia After Acute Ischemic Stroke

https://doi.org/10.21203/rs.3.rs-1509675/v1

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Background and Purpose

In patients with acute ischemic stroke (AIS) undergoing intravenous thrombolysis (IVT), there are few studies assessing the predictive effect of blood cell inflammatory markers on stroke-associated pneumonia (SAP), short-term and long-term prognosis. In this study, we evaluated whether the neutrophil-to-lymphocyte ratio (NLR) can predict SAP and functional prognosis in patients receiving IVT.

Methods

We assessed 388 patients undergoing IVT for acute ischemic stroke. Blood parameters were sampled before thrombolysis (within 30 mins after admission) and within 12–24 h after thrombolysis. The primary outcome measure was the occurrence of SAP as well as the prognosis after IVT. Multivariate logistic regression analysis was performed to analyze the association between NLR and the occurrence of SAP. We also used receiver operating characteristic curve analysis to assess the discriminative ability of NLR measured at different times in predicting SAP and prognosis. Further exploration of the correlation between NLR and baseline variables was conducted using Pearson correlation and multivariate linear regression analysis.

Results

Among the total patients, SAP occurred in 60 (15%) patients. Multivariate analysis showed that NLR was significantly associated with SAP (NLR before IVT: aOR = 1.288; 95%CI = 1.123–1.476; p < 0.001; NLR after IVT (aOR = 1.113, 95%CI = 1.007–1.23; p = 0.036). The receiver operating characteristic curve showed that the predictive ability of NLR after IVT was better than NLR before IVT (area under the curve [AUC] of NLR after IVT: 0.80, 95%CI = 0.74–0.86; p < 0.001; NLR before IVT: 0.72, 95%CI = 0.66–0.80; p < 0.001), not only in predicting the occurrence of SAP but also in predicting short-term functional outcomes and one-year mortality. Furthermore, NLR after IVT was significantly correlated with the initial NIHSS score (p < 0.001) and early neurological outcomes after IVT (p < 0.001).

Conclusions

We demonstrated that increased NLR has a significant predictive effect on the occurrence of SAP and can be used to predict functional dependence and one-year mortality. NLR measured within 12–24 h after IVT had better predictive validity than that measured before IVT.

inflammation

thrombolysis

stroke

neutrophil

lymphocyte

pneumonia

prognosis

Acute Ischemic stroke (AIS) is a devastating cerebrovascular event that occurs when blood flow in the brain region is interrupted due to cerebrovascular obstruction. Although the direct cause of brain injury is caused by the insufficient blood supply to the brain, the deterioration of neurological deficit is closely related to the inflammatory process after AIS. It has been proved that stroke will destroy the homeostasis of the normal and strictly regulated immune system, and predispose patients to predicaments such as immunosuppression and infection [1–3]. Stroke-associated pneumonia (SAP) is one of the major clinical complications encountered by stroke survivors, of which etiology was mainly due to the disruption of immune homeostasis after stroke [2, 4]. SAP has been known to worsen clinical outcomes, lengthen hospitalization durations, and increase the occurrence of severe disabilities and medical costs [5–7]. However, the diagnosis of SAP is challenging because the hallmark symptoms of clinical infection, such as fever, leucocytosis and elevated C reactive protein (CRP), can be caused by the destruction of thermoregulation and non-infectious inflammation or infections elsewhere[8]. In addition, the administration of some drugs, such as aspirin and paracetamol, can mask fever. Even chest X-ray, as a core component of diagnosis, has limited utility, because there may be no infiltration in the early stage and may only be useful in the late stage of infection [9]. However, late treatment may reduce the rehabilitation rate and worsen the functional prognosis of patients [10]. Therefore, identifying effective markers is needed to more accurately predict the occurrence of SAP.

Intravenous thrombolysis (IVT) therapy is currently one of the best medical treatments available for patients with AIS. As is well-known, patients receiving IVT usually have a relatively shorter onset to treatment (OTT) time, which might have an impact on the early inflammation response in AIS patients. Therefore, studies are needed to fully explore the role of inflammation in acute ischemic stroke, especially after IVT.

Peripheral inflammatory markers in the acute phase of stroke are associated with worse functional prognosis, survival, and long-term recurrent vascular events[1]. In recent years, an ever-increasing number of studies have shown that neutrophil-to-lymphocyte ratio (NLR), which is easily obtained from blood cell counts, could adequately predict the severity of systemic inflammation and infection, for example in sepsis, solid tumors, and even COVID-19 [11–13]. A strong relationship between NLR and the occurrence of SAP has been reported in prior studies [14, 15], but few studies have compared the effects of NLR at different time points of thrombolytic therapy in predicting SAP and functional outcomes of AIS. Therefore, this research fills the gap. By recording two-time points, we were able to observe the potential, undetected but existing inflammatory process in the different stages of stroke, thus predicting the onset of SAP before clinical manifestations, and detecting false-negative SAP missed by physicians. Furthermore, we planned to explore the utility of NLR in predicting short-term and long-term functional prognosis, as well as mortality.

Study design

This is a single-center cohort study evaluating patients undergoing IVT for acute ischemic stroke between 2019 and 2020 in the Neurology Department of the First Affiliated Hospital of Wenzhou Medical University. Data were collected retrospectively for treated patients. Informed consent was obtained from participants or their legal representatives. Our study was approved by the Ethics Committee of the First Affiliated Hospital of Wenzhou Medical University and was conducted by the ethical guidelines of the 1975 Declaration of Helsinki. The data supporting the results of this study are available from the corresponding author upon reasonable request from any qualified investigator.

Population

The inclusion criteria were age ≥ 18 years, with an acute, focal neurological deficit, hemorrhage excluded and treatment initiated less than 4.5 h after symptom onset. Eligible patients were treated with intravenous tPA according to national clinical guidelines during the study period. Exclusion criteria were as follows: (1) transient ischemic attack, (2) complicated with severe malignant tumor or severe pathologies of the liver, kidneys, (3) active infection within the 2 weeks before admission, and (4) incomplete information or missing clinical 1-year Modified Rankin Scale (mRS) score.

Data collection and assessment

Information, such as demographic characteristics (age, sex), vascular risk factors (hypertension, diabetes mellitus, ischemic heart disease, hyperlipidemia, atrial fibrillation, smoking, drinking, previous stroke), clinical factors (stroke severity, dysphagia, stroke etiology), treatment parameters (OTT, DNT), and blood parameters, was collected (see Table 1 for details). OTT time refers to the time from symptom onset to treatment with IVT, and DNT time refers to door-to-needle time. Blood parameters in the current analysis were obtained before IVT (within 30 mins after admission) and within 12–24 h after IVT respectively. The included blood parameters were leukocytes, neutrophils, lymphocytes, monocytes, NLR, and CRP. The NLR was calculated after dividing absolute neutrophil counts by absolute lymphocyte counts. Dysphagia assessment was performed by a trained speech therapist in the first 24 h after admission by the modified water swallowing test, a Japanese bedside dysphagia assessment [16]. Patients were evaluated on swallowing reflex, wet hoarseness, and cough after drinking 30 ml of water, and were grouped according to the Functional Oral Intake Scale (FOIS) score (1–3: use of an alternative route for feeding; 4–5: oral feeding with a necessity for the modification of food consistency; and 6–7: no modifications in food consistency) [17, 18]. The computed tomography or magnetic resonance was reported by at least two professional radiologists. The large infarct volume was defined as the main blood supply area of large vessels with an infarct diameter greater than 3 cm and involving more than 2 anatomical sites. The A2DS2 score is a well-established tool for predicting SAP, which includes age (1 point for ≥ 75years), atrial fibrillation (1 point), dysphagia (2 points), sex (1 point for male sex), and initial NIHSS score (0 point for NIHSS score 0–4, 3 points for NIHSS score 5–15, and 5 points for NIHSS score ≥ 16) [19].

Table 1

**Baseline Characteristics of Patients With SAP and Non-SAP With Acute Ischemic Stroke**
	Total (n = 388)	Non-SAP (n = 328)	SAP (n = 60)	P-value
Age(years), median (IQR)	69 ± 12	67 ± 12	75 ± 12	<0.001*
Sex, male(%)	255(66)	213(65)	42(71)	0.337
Drinking, n (%)	155(40)	136(41)	19(32)	0.187
Smoking, n (%)	163(42)	136(41)	27(46)	0.526
Previous stroke, n (%)	52(13)	40(12)	12(20)	0.089
Atrial fibrillation, n (%)	94(24)	71(22)	23(38)	0.006*
Hypertension, n (%)	273(70)	226(69)	47(80)	0.055
Ischemic heart disease, n (%)	27(7)	22(7)	5(8)	0.619
Diabetes mellitus, n (%)	182(47)	152(46)	30(51)	0.510
Hyperlipidemia, n (%)	229(59)	199(60)	30(51)	0.285
Dysphagia, n (%)	47(12)	13(4)	34(58)	<0.001*
FOIS socre, n (%)				<0.001*
1–3	41(11)	14(4)	27(51)
4–5	198(52)	176(53)	22(42)
6–7	145(38)	141(43)	4(8)
A2DS2 score	3(1–5)	3(1–4)	5(4–7)	<0.001*
Blood parameters measured within 30mins after admission
Leukocytes (×10 ⁹ /L), median (IQR)	7.17(5.92–8.95)	7.07(5.72–8.60)	8.48(6.66–10.58)	0.004*
Neutrophils (×10 ⁹ /L), median (IQR)	4.59(3.47–6.24)	4.45(3.36–5.85)	6.29(4.05–8.92)	<0.001*
Monocyte (×10 ⁹ /L), median (IQR)	0.47(0.37–0.61)	0.46(0.36–0.61)	0.52(0.38–0.70)	0.035*
Lymphocyte (×10 ⁹ /L), median (IQR)	1.68(1.28–2.21)	1.74(1.34–2.26)	1.42(1.05–1.75)	0.002*
NLR, median (IQR)	2.59(1.76–4.24)	2.47(1.67–3.94)	4.44(2.70–7.59)	<0.001*
Blood parameters measured within 12-24h after IVT
Leukocytes (×10 ⁹ /L), median (IQR)	7.66(6.42–9.59)	7.44(6.24–9.06)	9.28(7.41–12.13)	<0.001*
Neutrophils (×10 ⁹ /L), median (IQR)	5.37(4.09–7.11)	5.02(3.84–6.71)	7.51(5.62–9.87)	<0.001*
Monocyte (×10 ⁹ /L), median (IQR)	0.51(0.39–0.66)	0.50(0.39–0.65)	0.57(0.38–0.87)	0.060
Lymphocyte (×10 ⁹ /L), median (IQR)	1.47(1.12–1.88)	1.51(1.19–1.91)	1.20(0.83–1.55)	<0.001*
NLR, median (IQR)	3.42(2.32–5.59)	3.13(2.23–4.93)	6.43(4.75–9.02)	<0.001*
CRP (mg/L), median (IQR)	3.32(3.00-9.87)	3.29(3.00-8.47)	9.10(3.78–22.40)	<0.001*
DNT(min), median (IQR)	47(35–59)	46(34–59)	50(39–62)	0.109
OTT, n(%)				0.889
≤90mins	32(8)	27(8)	5(8)
90mins ~ 180mins	184(47)	154(47)	30(50)
≥180mins	172(44)	147(45)	25(42)
Hospital stays (days), median (IQR)	9(7–13)	9(7–12)	14(10–20)	<0.001*
Initial NIHSS score, median (IQR)	5(3–10)	4(3–8)	13(8–17)	<0.001*
Early neurological outcomes, n (%)				0.024*
Neither END nor ENI	176(45)	149(45)	27(45)
ENI	182(47)	159(48)	23(38)
END	30(8)	20(6)	10(17)
Hemorrhagic transformation, n (%)	43(11)	29(9)	14(24)	<0.001*
mRS 0–2 at discharge, n (%)	263(68)	250(76)	13(22)	<0.001*
mRS 0–2 at 1-year, n (%)	265(68)	247(75)	18(31)	<0.001*
Mortality,n (%)	43(11)	21(6)	22(37)	<0.001*
Stroke etiology, n (%)				0.088
Large vessel disease	202(52)	166(50)	36(61)
Cardioembolism	72(19)	60(18)	12(20)
Small vessel occlusion	81(21)	76(23)	5(8)
Undetermined or other etiology	33(9)	27(8)	6(10)
Large infarct volume,n (%)	51(13)	28(9)	23(38)	<0.001*
FOIS, the Functional Oral Intake Scale; CRP, C-reactive protein; NIHSS, National Institutes of Health Stroke Scale; NLR, neutrophil-to-lymphocyte ratio; OTT, onset-to-treatment time; DNT, door-to-needle time; SAP, stroke-associated pneumonia; IQR, interquartile range.
*p < 0.05

Outcome

The main outcome measure was the morbidity of SAP, which is defined as pneumonia diagnosed on admission or within the first 7 days of admission after stroke onset [20]. The diagnosis of pneumonia was made by over two neurologists during the hospital stay based on signs, symptoms, and laboratory measurements suggestive of acute lower respiratory tract infection, and confirmation via chest CT, according to the modified Center for Disease Control and Prevention criteria.

To evaluate the impact of SAP on the clinical outcomes of patients after IVT, we additionally noted post-thrombolysis early neurological outcomes (early neurological improvement [ENI], early neurological deterioration [END]), hemorrhagic transformation, hospitalization duration, NIHSS score, mRS score at discharge and one year from AIS onset, and mortality. END was defined as an increase in the NIHSS score by ≥ 4 points in the total score within 24 h after thrombolysis, and ENI was defined as a decrease in the NIHSS score by ≥ 4 points in the total score or a complete resolution of neurological deficits within 24 h after thrombolysis. A favorable outcome was defined as an mRS score of 0–2 and functional dependence was defined as an mRS score of 3–6. The physicians who performed the NIHSS and the mRS score assessments were specially trained. The follow-up assessments were performed through outpatient visits or telephone calls. Mortality was defined as the percentage of deaths between the time of admission and the 1-year follow-up. Hemorrhagic transformation was defined as any hemorrhage with neurologic deterioration or resulting in death within 2 weeks after admission.

Statistical analysis

The continuous variables were presented as mean ± standard deviation or medians (interquartile range), and in the case of categorical data, counts and percentages were shown. Continuous variables were tested for normality with the use of the Kolmogorov-Smirnov test and then compared, as appropriate, by a Student’s t-test or by the Mann-Whitney U test. Pearson’s χ2 test or Fisher’s exact test was used to compare categorical variables. The multivariable logistic regression was used to identify significant predictors of SAP and it was adjusted for variables that were selected from univariate analysis with p < 0.1 and previous studies. The predictive power of NLR was compared with conventional inflammatory markers using the area under the receiver operating characteristic curve (AUROC), and the optimal cut-off point was calculated based on Youden’s index. In addition, the relationship between NLR and relevant baseline variables was performed using Pearson correlation. Variables with p < 0.05 in Pearson correlation analysis were further analyzed by multiple linear regression. All statistical analysis was performed using SPSS version 26 (IBM SPSS, Chicago, IL). The receiver operating characteristic curve (ROC) was performed using GraphPad Prism 8. A two-tailed value of p < 0.05 was considered significant.

Participants' Characteristics

Of the 467 ischemic stroke patients receiving IVT enrolled from January 2019 to December 2020, 79 patients were subsequently excluded for incomplete information or loss of follow-up (n = 52), transient ischemic attack (n = 6), and complicating with severe malignant tumors in the following year (n = 2), and severe renal dysfunction (n = 10), active infection within the 2 weeks before admission(n = 9), leaving 388 subjects for the final analyses. Table 1 displays the characteristics of included patients according to dichotomized SAP. The prevalence of SAP was 15% (n = 60). Across the entire study population, the mean age was 69 years, 66% of patients were male. The median initial NIHSS score and hospital stays of the cohort were 5(3–10) and 9(7–13), respectively. 263 subjects (68%) achieved favorable outcome at discharge.

As shown in Table 1, compared to those with non-SAP, patients with SAP were older (mean 75 versus 67 years, p < 0.001), more likely to combine with dysphagia (58% vs 4%, p < 0.001), atrial fibrillation (38% vs 22%, p = 0.006), and hemorrhagic transformation (24% vs 9%, p < 0.001), and had higher median initial NIHSS score (13 vs 4, p < 0.001), A2DS2 score (5 vs 3, p < 0.001), longer hospital duration (14 vs 9 days, p < 0.001), higher rate of FOIS score of 1–3 (51% vs 4%, p < 0.001), higher rate of large infarct volume (38% vs 9%, p < 0.001), and higher rate of END (17% vs 6%, p = 0.024). The favorable outcome at discharge (22% vs 76%, p < 0.001) and 1-year (31% vs 75%, p < 0.001) were less commonly found in patients with SAP, but mortality (37% vs 6%, p < 0.001) was more frequency. Patients with SAP also had higher counts of leukocyte, neutrophil, lymphocyte, monocyte, and higher levels of CRP than those with non-SAP. In the total group, OTT time of less than 90mins accounts for 8%, and the median DNT time is 47 mins, both of which have no significant correlation with the occurrence of SAP. In the current study, no significant difference in stroke etiology, drinking, smoking, history of previous stroke, hyperlipidemia, hypertension, diabetes mellitus was shown between the two groups.

Association between NLR and SAP

It can be seen from the data in Table 1 that the SAP group reported significantly higher NLR than the non-SAP group (4.44 ~ 6.43 vs 2.47 ~ 3.13, p < 0.001). When we divided the NLR respectively into two groups bounded by 3, patients in the high NLR groups had more pneumonia events (24%~27% vs 3%~7%, p < 0.001) compared with patients in the low NLR groups (Table 2). In the multivariable logistic regression analysis (Table 3), the NLR before IVT (adjusted odds ratio [aOR] = 1.288; 95% confidence interval [CI] = 1.123–1.476; p < 0.001), as well as the NLR after IVT (aOR = 1.113, 95%CI = 1.007–1.23; p = 0.036), remained an independent predictor of SAP after adjusting for confounders. Initial NIHSS score (aOR = 1.118; 95%CI = 1.036–1.205; p = 0.004), dysphagia (aOR = 18.859; 95%CI = 7.282–48.839; p < 0.001), atrial fibrillation (aOR = 4.387; 95%CI = 1.110-17.341; p = 0.035), A2SD2 score (aOR = 1.656; 95%CI = 1.4-1.959; p < 0.001) were also significant predictors of SAP in Model 1 (Table 3). And Model 2 shows similar results (Table 3).

Table 2

**Baseline Characteristics of Patients With Low and High NLRs**
	NLR measured within 12-24h after IVT			NLR measured before IVT
	Low NLR	High NLR	P-value	Low NLR	High NLR	P-value
	(NLR < 3, n = 158)	(NLR > 3, n = 230)	P-value	(NLR < 3, n = 228)	(NLR > 3, n = 160)	P-value
Age(years), median (IQR)	67 ± 12	70 ± 13	0.002*	67 ± 12	70 ± 12	0.140
Sex, male,n(%)	107(68)	148(64)	0.492	151(66)	104(65)	0.802
Pneumonia events ,n(%)	4(3)	55(24)	< 0.001*	16(7)	43(27)	< 0.001*
Atrial fibrillation, n (%)	33(21)	54(23)	0.548	44(19)	43(27)	0.078
Previous stroke, n (%)	21(13)	31(13)	0.958	28(12)	24(15)	0.439
Hyperlipidemia, n (%)	102(65)	127(55)	0.066	148(65)	81(51)	0.005*
Diabetes mellitus, n (%)	73(46)	109(47)	0.818	106(46)	76(48)	0.845
Hypertension, n (%)	103(65)	170(74)	0.065	160(70)	113(71)	0.924
Ischemic heart disease, n (%)	11(7)	16(7)	0.998	15(7)	12(8)	0.726
A2DS2 score, median (IQR)	2(1–4)	4(1–5)	< 0.001*	2(1–4)	4(2–5)	< 0.001*
Dysphagia, n (%)	5(3)	42(18)	< 0.001*	16(7)	31(19)	< 0.001*
DNT(h), median (IQR)	43 (34–58)	48 (36–60)	0.093	44 (34–59)	49 (36–59)	0.217
OTT, n(%)
≤90mins	8(5)	10(4)	0.378	23(10)	9(6)	0.013*
90mins ~ 180mins	69(44)	117(51)		117(52)	67(42)
≥180mins	81(51)	103(45)		87(38)	85(53)
Initial NIHSS, median (IQR)	3(2–6)	7(3–12)	< 0.001*	4(2–8)	7(3–10)	< 0.001*
Early neurological outcomes, n (%)
Neither END nor ENI	70(44)	106(46)	0.086	97(43)	79(49)	0.002*
ENI	81(51)	101(44)		120(53)	62(39)
END	7(4)	23(10)		10(4)	20(12)
Hemorrhagic transformation, n (%)	6(4)	37(16)	< 0.001*	14(6)	29(18)	< 0.001*
mRS 0–2 at discharge, n (%)	137(87)	126(55)	< 0.001*	180(79)	83(52)	< 0.001*
mRS 0–2 at 1-year, n (%)	133(84)	132(57)	< 0.001*	176(77)	89(56)	< 0.001*
Mortality,n (%)	3(2)	40(17)	< 0.001*	13(6)	30(19)	< 0.001*
Large infarct volume,n (%)	7(4)	44(19)	< 0.001*	20(9)	31(19)	0.003*
CRP, C-reactive protein; NIHSS, National Institutes of Health Stroke Scale; NLR, neutrophil-to-lymphocyte ratio; OTT, onset-to-treatment time; DNT, door-to-needle time; SAP, stroke-associated pneumonia; IQR, interquartile range.
*p < 0.05

Table 3

**Multivariate logistic regression analysis of possible predicts of SAP**
	^aModel 1		^bModel 2
	Adjusted OR	P Value	Adjusted OR	P Value
NLR	1.288(1.123–1.476)	< 0.001*	1.127(1.017–1.249)	0.023*
Age	1.027(0.990–1.066)	0.150	1.02(0.984–1.057)	0.290
Sex(male)	1.303(0.443–3.834)	0.631	1.43(0.507–4.033)	0.499
Initial NIHSS score	1.118(1.036–1.205)	0.004*	1.112(1.031–1.199)	0.006*
Dysphagia	18.859(7.282–48.839)	< 0.001*	14.576(5.708–37.218)	< 0.001*
A2SD2 score	1.656(1.4-1.959)	< 0.001*	1.574(1.331–1.863)	< 0.001*
Atrial fibrillation	4.387(1.110-17.341)	0.035*	6.523(1.826–23.298)	0.004*
Hyperlipidemia	1.087(0.479–2.469)	0.842	0.974(0.44–2.156)	0.948
Diabetes mellitus	1.543(0.694–3.431)	0.288	1.958(0.883–4.338)	0.098
Previous stroke	0.936(0.3-2.922)	0.910	1.308(0.439–3.895)	0.630
Hypertension	1.135(0.435–2.96)	0.796	1.101(0.436–2.782)	0.838
Ischemic heart disease	0.825(0.217–3.134)	0.778	0.97(0.260–3.615)	0.964
Drinking	0.720(0.276–1.881)	0.503	0.588(0.233–1.486)	0.262
Smoking	2.842(0.978–8.257)	0.055	2.761(0.977–7.806)	0.055
NIHSS, National Institutes of Health Stroke Scale; NLR, neutrophil-to-lymphocyte ratio; OR, odds ratio; and SAP, stroke-associated pneumonia.
^aModel 1:NLR measured before IVT(within 30mins after admission).
^bModel 2:NLR measured within 12-24h after IVT.
Both Model 1 and 2 were adjusted with P < 0.10 in univariate analysis and diabetes mellitus, smoking,drinking, ischemic heart disease, hyperlipidemia and stroke etiology.
*p < 0.05.

ROC analysis for SAP showed that the area under the curve of NLR after IVT (0.80, 95%CI = 0.74–0.86; p < 0.001) was higher than NLR before IVT (0.72, 95%CI = 0.66–0.80; p < 0.001) and conventional inflammatory markers, such as lymphocyte counts (0.68, 95%CI = 0.61–0.75; p < 0.001), neutrophils (0.70, 95%CI = 0.63–0.77; p < 0.001), monocyte (0.59, 95%CI = 0.51–0.67; p = 0.034) and leukocyte counts (0.66, 95%CI = 0.58–0.73; p < 0.001) (Fig. 1). Surprisingly, NLR after IVT was similar in AUROC to the widely accepted A2SD2 score (0.80, 95%CI = 0.74–0.86; p < 0.001). The optimal point of NLR after IVT identified by the Youden index was 4.4 with 80% sensitivity, 70% specificity (Youden index = 0.507). In addition, the AUROC of NLR after IVT was also higher than that of NLR before IVT in ROC analysis for functional dependence at discharge and mortality (Fig. 1).

Association between NLR and relevant baseline variables

As shown in Table 2, compared with patients in the high NLR groups when measured before IVT, patients in the low NLR groups had higher median initial NIHSS score (7 vs 4, p < 0.001) and A2DS2 score (4 vs 2, p < 0.001), higher rate of END (12% vs 4%, p = 0.002), higher rate of OTT time ≥ 180 mins (53% vs 38%, p = 0.013) and higher rate of large infarct volume (19% vs 9%, p = 0.003), more likely to combine with dysphagia (19% vs 7%, p < 0.001), hemorrhagic transformation (18% vs 6%, p < 0.001), and had higher mortality (19% vs 6%, p < 0.001), and less favorable outcome both at discharge (52% vs 79%, p < 0.001) and one year (56% vs 77%, p < 0.001). In the group when NLR was measured within 12–24 h after IVT, the A2DS2 score, initial NIHSS score, dysphagia, hemorrhagic transformation, favorable outcomes, and mortality were also associated with NLR (p < 0.05).

In Pearson correlation analysis (see Table 4), NLR before IVT was significantly correlated with the initial NIHSS score (p < 0.001) and OTT (p < 0.001), but NLR after IVT was significantly correlated with the initial NIHSS score (p < 0.001), age (p < 0.001) and early NIHSS changes (p = 0.004). Some of these associations remained statistically significant (NLR measured before IVT: Initial NIHSS: β = 0.124, p < 0.001; OTT: β = 0.009, p < 0.001; NLR measured within 12–24 h after IVT: Early NIHSS changes: β = -0.249, p < 0.001; Initial NIHSS: β = 0.360, p < 0.001) in a multivariate linear regression model where we corrected for parameters that have a known influence on peripheral leukocyte counts (diabetes mellitus, hyperlipidemia, smoking, drinking, ischemic heart disease, Table 5). The association between NLR and OTT time appeared to be affected by intravenous thrombolytic therapy, and the association between NLR and early NIHSS changes was only significant in the group when NLR was measured within 12–24 h after IVT.

Table 4

**Pearson correlation between NLR and relevant baseline variables**
	^aModel 1		^bModel 2
	Pearson correlation	P value	Pearson correlation	P value
Age(years)	0.068	0.183	0.195	< 0.001*
OTT(min)	0.217	< 0.001*	-0.054	0.285
DNT(min)	0.028	0.583	0.074	0.145
Initial NIHSS	0.273	< 0.001*	0.432	< 0.001*
Early NIHSS changes	-0.073	0.153	-0.144	0.004*
OTT, onset-to-treatment time; DNT, door-to-needle time; Early NIHSS changes = Δdelta (NIHSS score before IVT- NIHSS score within 24 h after IVT).
^aModel 1:NLR measured before IVT(within 30mins after admission).
^bModel 2:NLR measured within 12-24h after IVT.

Table 5

**Multivariate linear regression analysis for the prediction of NLR**
	^aModel 1			^bModel 2
	β	P value	VIF	β	P value	VIF
Constant	1.183	0.010		3.065	< 0.001
Age(years)				0.004	0.780	1
Early NIHSS changes				-0.249	< 0.001*	1
Initial NIHSS	0.124	< 0.001*	1	0.360	< 0.001*	1
OTT(min)	0.009	< 0.001*	1
F	7.984			18.760
adjusted R²	0.112			0.284
P value	< 0.001			< 0.001
OTT, onset-to-treatment time; DNT, door-to-needle time; Early NIHSS changes = Δdelta (NIHSS score before IVT- NIHSS score within 24 h after IVT).
^aModel 1:NLR measured before IVT(within 30mins after admission).
^bModel 2:NLR measured within 12-24h after IVT.
Both Model 1 and 2 were adjusted with diabetes mellitus, hyperlipidemia, smoking, drinking, ischemic heart disease.
*p < 0.05.

First of all, this current study supported that a high NLR level was an independent predictor of SAP in stroke patients, and had better predictive validity than established biomarkers like leukocyte counts, which was in agreement with findings of previous research [14, 15, 21]. Furthermore, a high NLR level also is an independent risk factor for poor short- and long-term outcomes, as well as for mortality, further highlighting the clinical implications of this easily obtained ratio for everyday practice.

Moreover, our research showed that NLR measured before IVT, as well as within 12–24 h after IVT, can both predict the onset of SAP, functional dependence, and mortality after stroke. However, NLR measured within 12–24 h after IVT had a higher predictive value. As indicated in this study, the area under the ROC curve of NLR measured within 12–24 h after IVT was larger compared with that before thrombolytic treatment. The calculated cut-off therefore further showed adequate sensitivity and specificity (sens.: 80%, spec.: 70%). Intriguingly, NLR measured within 12–24 h after IVT was similar in AUROC of SAP to the widely accepted A2SD2 score (0.80, p < 0.001 vs 0.80, p < 0.001). Since stroke patients undergoing IVT are often admitted as an emergency and may lack a clear history, monitoring NLR is a more effective and simple method compared to the A2SD2 score in predicting SAP.

A possible explanation for the above result might be that the dynamic development of neuroinflammation after a stroke takes several hours and the immune activity changes after taking thrombolytic treatment. Ischemic stroke causes cell death by blocking blood flow to the brain and depriving cells of nutrients. This, in turn, activates immune cells to produce pro-inflammatory factors and produces a hierarchical biological effect of systemic inflammation in acute stroke patients, with an increase in peripheral blood neutrophils count. Subsequent increased activity of the adrenal medulla and hypothalamic axis leads to stroke-induced immunosuppression syndrome, which can lead to lymphocyte apoptosis and T cell inactivation, with resulting infectious complications. Indeed, while leukocyte numbers increase, lymphopenia occurs within 6 h and lasts for at least 6 days after stroke in patients [22]. Furthermore, the number of circulating lymphocytes recovered one day after stroke in uninfected patients, while infected patients showed persistent lymphopenia [23]. In this study, the blood collection time of NLR after IVT was about 12–24 hours after stroke, which gave sufficient time for the inflammatory response to development.

In addition, after reperfusion therapy, the recovery of cerebral blood flow further induces the production of ROS and the destruction of the blood-brain barrier, which makes it easier for immune cells in the peripheral circulation to penetrate the brain, promoting brain cell swelling and exacerbating tissue damage in the injury site and the ischemic penumbra [24, 25]. Therefore, reperfusion injury caused by thrombolytic therapy should be given special consideration in inflammatory events after AIS.

Previous studies have proved that early thrombolytic therapy can save the penumbra and reduce the development of inflammation [26, 27]. Therefore, if inflammation indicators such as NLR are still high after thrombolytic therapy, it may be an indicator of irreversible injury in the edema penumbra. In addition, in our cohort, the low NLR group had a better effect on IVT, as shown by a lower rate of END and lower incidence of hemorrhagic transformation. This is consistent with a previous study that has shown that higher NLR is associated with reperfusion failure after endovascular treatment [21]. Therefore, although NLR can effectively predict the occurrence of SAP and is a relatively easily available indicator, the optimal time to detect NLR must be considered.

For the relevant baseline variables, we found that NLR measured within 12–24 h after IVT was closely related to the severity of the stroke and early neurological outcomes, as indicated by remaining significant correlation with initial NIHSS scores and early NIHSS changes after correction for possible confounders in a multivariate linear regression model. Previous studies have also shown that the severity of stroke is an important risk factor for SAP, and NLR is closely related to infarct volume and may have the ability to predict post-thrombolysis END [28, 29]. Another unexpected finding was that the OTT time was only significantly associated with NLR before IVT. It may suggest that with the increase in OTT time, the potential inflammatory response in patients of AIS before IVT may be more intense. On the other hand, our study also showed that OTT time had no significant effect on NLR measured within 12–24 h after IVT when thrombolytic therapy was actively administered within the time range of 4.5 hours. Therefore, NLR measured within 12–24 h after IVT may be a relatively stable marker for predicting SAP and functional outcome of patients with AIS because it is not affected by OTT time. However, several studies have shown that ultra-early thrombolysis contributes to functional recovery and lower mortality after cerebral infarction [30–32]. Indeed, it should be noted that, in our whole group, the median OTT was 2.93 h, and ultra-early thrombolysis of fewer than 90 mins accounted for only 8% of the total number, which is a relatively small number and may cause deviation. Meanwhile, it is worth noting that the OTT time has a confounding bias with the severity of stroke. Patients with more severe strokes are often found earlier, thus shortening the OTT time. In this study, there was no significant association between DNT and SAP, as well as NLR, so the extension of OTT was mainly related to the time from onset to arrival at the hospital.

This study has some potential limitations. First, the sample size is relatively small mainly because the participants were selected from a single institution. Second, Even if we have formulated strict exclusion criteria, we can not guarantee that patients with latent infection before admission can be completely excluded. However, in this study, the incidence rate of SAP was 15%, which is similar to the incidence reported in previous studies[6, 33–35]. Thus, this bias was within acceptable ranges. Third, it is also a pity that we did not record the specific onset time of pneumonia, nor did we record the severity of pneumonia. Finally, we did not develop an independent validation cohort to provide more credibility. Therefore, the clinical implications of these correlations need to be investigated further in future studies. Despite these limitations mentioned above, our study considered the impact of the thrombolytic treatment on NLR in predicting SAP, indicating that increased systemic inflammation after thrombolysis, expressed by increased NLR measured within 12–24 h after IVT, is more tightly associated with the occurrence of SAP and poor prognosis. Our results complement the role of NLR in cerebrovascular disease and provide a new idea for clinical practice.

In conclusion, increased NLR within 12–24 h after IVT has a significant predictive effect on the occurrence of SAP and can be used to predict the effect of thrombolysis and long-term functional dependence. However, it is necessary to establish an independent validation cohort and explore the correlation between NLR and SAP severity in future research. Meanwhile, further studies are needed to explore whether blocking the deleterious pro-inflammatory pathway can prolong the time window of thrombolysis in the acute stage, augment the beneficial effect of thrombolysis by protecting the penumbra and reducing the hemorrhagic transformation, and identify potential patients in need to have anti-inflammatory neuroprotection after brain ischemic injury.

AIS

Acute ischemic stroke

SAP

Stroke-associated pneumonia (SAP)

IVT

Intravenous thrombolysis

NLR

Neutrophil to lymphocyte ratio

CRP

C-reactive protein

OTT

Onset to treatment time

DNT

to door-to-needle time

FOIS

the Functional Oral Intake Scale

ENI

Early neurological improvement

END

Early neurological deterioration

mRS

Modified Rankin Scale

NIHSS

National Institutes of Health Stroke Scale

IQR

interquartile range

Odds ratio

95% CI

95% Confidence interval

AUROC

Area under the receiver operating characteristic curve.

Acknowledgments

We express our gratitude to all the researchers and patients who participated in this study.

Authors’ contributions

Liu-Zhu Chen and Xiao-Qian Luan conceived and designed the study. Liu-Zhu Chen analyzed and interpreted the data. Liu-Zhu Chen drafted the article and Xiao-Qian Luan revised it. Lu-Qian Zhan, Yi-Si Lin, and Liu-Zhu Chen screened the subjects, collected the basic data, and checked the medical records. Xue-Qian Xu searched the cases in the emergency registration system online. Jin-Cai He and Hu-Wei Xia offered help and guidance. All authors approved the publishing of the final manuscript.

Funding

This research was supported by a grant from Wenzhou Municipal Sci-Tech Bureau Program (Y2020421). We are greatly indebted to the staff and the patients with stroke for their contributions during this study.

Data availability statement

All datasets presented in this study are included in the article/supplementary material.

Ethics approval and consent to participate

Our study was approved by the Ethics Committee of the First Affiliated Hospital of Wenzhou Medical University and was conducted by the ethical guidelines of the 1975 Declaration of Helsinki. Informed consent was obtained from participants or their legal representatives.

Consent for publication

All the authors agree to publish.

Competing interests

The author reports no conflicts of interest in this work.

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Effect Of Thrombolytic Therapy On High Neutrophil-to-Lymphocyte Ratio In Predicting Stroke-Associated Pneumonia After Acute Ischemic Stroke

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