calculated as a simple ratio between the neutrophil and lymphocyte counts measured in peripheral blood, is a biomarker which conjugates two faces of the immune system: the innate immune response, mainly due to neutrophils, and adaptive immunity, supported by lymphocytes.1,2

Recently, the neutrophil-to-lymphocyte ratio (NLR) has become a powerful predictor of death in patients with cardiovascular disease or peripheral arterial occlusive disease. Previous studies reported a correlation between stroke severity and NLR determined at admission.3,4

Several studies suggested that the initial NLR was associated with mortality and infarct size in ischemic stroke patients. In the study of Gökhan et al.,5 it was found that neutrophil and lymphocyte counts were also significantly higher in patients with acute ischemic and hemorrhagic stroke compared to TIA patients. Rodríguez-Yáñez and Castillo6 showed that the lowest leukocyte count was in the lacunar patient group in patients with acute stroke. Despite these promising findings, the prognostic value of NLR in acute ischemic stroke remains to be fully elucidated, particularly in the Indian population. Present study was aimed to study relationship of neutrophil to lymphocytes ratio in patients with acute ischemic stroke

Present study was single-center, prospective, observational study, conducted in department of general medicine, at tertiary care hospital, India. Study period was from May 2022 To August 2024. Study was approved by institutional ethical committee.

Inclusion criteria

• Patients more than 18 years of age presenting first time with symptoms and signs consistent with acute ischemic stroke and /or CT findings suggestive of acute infarct, relatives willing to participate in present study

Exclusion criteria

• Transient ischemic attack (TIA)
• Subdural haemorrhage
• Epidural haemorrhage
• Poisoning
• Symptoms caused by trauma
• Cerebral venous sinus thrombosis
• Previous history of stroke
• Patients who don’t give consent for participation in the study.

Study was explained to participants in local language & written informed consent was taken. The following data was collected from each patient which includes, sociodemographic information like name, age, address, occupation, sex, present illness, co-morbidities, weight, height, BMI. Examination of patient also included general examination and system examination specifically neurological along with recording of vitals. National institute of health stroke scale (NIHSS) was calculated at the time of admission.

A complete blood count and well spread peripheral smear was sent at the time of admission and neutrophil to lymphocyte ratio was calculated. A computed tomogram of the patient was done to identify ischemic stroke. Bilateral carotid artery Doppler was done. Liver function test, kidney function test, lipid profile and Other investigations as deemed necessary by the treating physician were conducted and their findings were noted.

Data was collected by using a structure proforma. Data entered in MS excel sheet and analyzed by using SPSS IBM USA. Qualitative data was expressed in terms of proportions. Quantitative data was expressed in terms of Mean and Standard deviation Descriptive statistics of each variable was presented in terms of Mean, standard deviation, standard error of mean. Association between two qualitative variables were seen by using Chi square/ Fischer’s exact test. Correlation between two quantitative variables were assessed by using Pearson’s correlation coefficient test (r). A p value of <0.05 was considered as statistically significant whereas a p value <0.001 was considered as highly significant.

In present study, majority of individuals are in the 61-80 years age group (45.83%), followed by 41-60 years (38.33%) & 21-40 years (10.83%). The mean age of the study population is 58.97 ± 14.97 years, indicating a relatively older population with a significant proportion being over 60 years. There was male predominance (67.5 %) noted.

Table 1: General characteristics

Most common infarct areas are the left middle cerebral artery (MCA) and the right MCA, comprising 34.17% and 33.33% of cases, respectively. Other significant territories include the left posterior cerebral artery (PCA) (10.83%) and the right PCA (5.83%). Bilateral involvement of MCA was seen in 5.00% of patients, while bilateral PCA infarcts occurred in 2.50% of cases.

Table 2: Distribution of Territory of infarct

Most patients (65.83%) had their NLR estimated within 24 hours of symptom onset, followed by 24.17% within 25-48 hours. A smaller proportion of patients, 5.00%, had their NLR assessed between 49-96 hours, and another 5.00% had it done after more than 96 hours. The mean time lapse was 33.23 ± 34.64 hours.

Table 3: Distribution of Time lapse between onset of symptoms and NLR estimation

Most patients (82.50%) experienced moderate strokes, while minor strokes were reported in 14.17% of cases. Moderate to severe and severe strokes were relatively rare, accounting for 1.67% and 0.83%, respectively. Only one patient (0.83%) did not experience a stroke.

Table 4: Distribution of Type of stroke

Systemic hypertension was the most common comorbidity, present in 70.00% of patients, followed by diabetes mellitus (41.67%) and alcoholism (47.50%). Smoking was reported in 28.33% of the population, while ischemic heart disease and atrial fibrillation were seen in 12.50% and 4.17% of patients, respectively.

Table 5: Distribution of Comorbidities

88.33% of patients were discharged from the hospital, while 11.67% of patients died.

Table 6: Distribution of Outcome

The mortality rate among females was higher at 20.5%, compared to males, where the mortality rate was 7.4%. The p-value was 0.036, suggesting a statistically significant association between sex and outcomes, with females showing higher mortality.

Mortality was significantly associated with diabetes mellitus, where 4.0% of diabetic patients died (p = 0.027). Other comorbidities, including systemic hypertension, ischemic heart disease, atrial fibrillation, smoking, and alcoholism, did not show statistically significant associations with mortality, as indicated by their p-values.

Mortality was highest in patients with right MCA and right PCA involvement (100%), followed by those with bilateral MCA involvement (16.7%) and left PCA infarct (15.4%). In contrast, patients with infarcts in some other territories, such as bilateral PCA and left MCA, had lower mortality rates. The p-value of 0.552 indicates that the differences in outcomes based on infarct territory were not statistically significant.

Table 7: Association of outcome with Age

A clear trend of increasing mortality rates across NIHSS score categories, from 0% in minor strokes (0-4) to 8.33% in moderate strokes (5-15), and 16.67% in moderate to severe strokes (16+). The p-value of 0.086 is highlighted, indicating no statistical significance.

Table 8: Association of outcome with Type of stroke according to NIHSS score

Patients who were discharged had a mean NLR of 9.40 ± 7.84, while those who died had a higher mean NLR of 12.54 ± 9.16. The p-value for this comparison was 0.171, indicating that the difference in NLR between patients who were discharged and those who died was not statistically significant.

Table 9: Association of outcome with NLR

The Pearson’s correlation coefficient (r) was 0.029 with a p-value of 0.751, indicating that there was a weak positive correlation between NLR and the NIHSS score which was also statistically not significant.

Table 10: Correlation between NLR and NIHSS score

Diabetes mellitus was found to be a significant predictor of outcomes, with an odds ratio of 0.185 and a p-value of 0.048, indicating that diabetic patients had a lower likelihood of survival. Other comorbidities, including systemic hypertension, ischemic heart disease, atrial fibrillation, smoking, and alcoholism, were not significant predictors of outcomes, as reflected in their p-values

Table 11. Multivariate regression analysis for Comorbidities

Wan et al.,⁷ performed a meta-analysis and found that their statistical results support the conclusion that NLR is significantly correlated with poor prognosis in patients with stroke. The pooled ORs of higher NLR for poor functional outcome in acute ischemic and hemorrhagic patients were 1.689 (95% CI = 1.184–2.409, p < 0.001) and 1.125 (95% CI = 1.022– 1.239, p < 0.001), respectively, and the overall pooled OR after acute stroke was 1.257 (95% CI = 1.146–1.379, p < 0.001).

In study by Sharabh et al.,⁸ mean NLR calculated within 24 h of hospital admission in patients who died (NLR=8.47 (standard deviation (SD)=4.67)) was significantly higher (p=0.009) than in those who survived (NLR=5.84 (SD=2.62)). Upon ROC analysis, patients with NLR >6.03 on the day of admission demonstrated a higher risk of in-hospital mortality (p=0.015 (95% CI: 0.577-0.855)). An area under the curve (AUC) of 0.72 with a sensitivity of 92.86% and a specificity of 54.35%, and an elevated NLR (cut-off >6.03) obtained within 24 hours of hospital admission are indicators of a higher risk of in-hospital mortality in stroke patients. Hence, patients presenting with a high NLR at admission should be prioritized for personalized targeted treatment, potentially reducing mortality and post-stroke complications.

Guinmapang et al.,⁹ noted that group with a low NL ratio (<5.9) had mostly minor-to-moderate strokes, while those with a higher NL ratio (>5.9) had a similar distribution with a higher proportion of moderate and moderate-to-severe strokes. The median number of hospital days was longer for the high NL ratio group. (5 days vs. 3 days, p=0.012). There was a greater proportion of mortalities for the high NL ratio group (31% versus 14%, p=0.003). Upon further analysis, however, upon comparing the expired and surviving patients, there was insufficient evidence to demonstrate a difference between the two groups. In addition, the NIHSS score was more significantly correlated with mortality than the NL ratio.

Lavanya et.al .,¹⁰ noted that the NIHSS score and GCS had a strong positive correlation with the NLR (P =0.001). The median NLR was significantly higher in the mortality group than that in the survival group. The NLR was higher than the normal value in stroke patients, and the NLR at the time of hospital admission may be a predictor of mortality in acute stroke patients. Because of its routine use, low cost, and ease of measurement, the NLR can be used to predict short-term prognosis and in-hospital mortality in stroke patients.

Quan et al.,¹¹ conducted a study that included 13,018 patients; patients included in the study were classified into four groups by NLR quartiles. At both 3- and 12-month follow-up, higher quartile groups were associated with increased risks of death and poor functional outcomes, even after adjustments. For death, the cut-off values of NLR were 3.872 at the 3-month follow-up and 3.180 at the 12-month follow- up. For poor functional outcomes, the cutoff value of NLR was 2.846 at both the 3- and 12-month follow-ups. The association between NLR and stroke recurrence was significant only at 3-month follow-up before adjustments. A high NLR within the first 24 h after admission was associated with an increased risk of both short- and long- term adverse clinical outcomes in patients with ischemic stroke, regardless of etiology.

While NLR showed some potential as a prognostic marker, its clinical utility in this cohort appears limited. The strong association of diabetes with poor outcomes emphasizes the need for aggressive management of this comorbidity in stroke patients. The gender disparity in outcomes highlights the importance of considering sex-specific factors in stroke management.

This research contributes to the existing knowledge on the complex relationship between inflammation, comorbidities, and stroke outcomes. It provides insights into the potential limitations of NLR as a universal prognostic marker in acute ischemic stroke and reinforces the importance of diabetes management and gender considerations in stroke care. Future research directions include larger, multicenter studies to further evaluate NLR's prognostic value, investigation of other inflammatory markers or combinations of markers, and exploration of mechanisms underlying gender disparities in stroke outcomes. Overall, this study underscores the multifactorial nature of stroke outcomes and the need for comprehensive, personalized approaches to stroke management and prognosis.

Limitations of present study were small sample size. Inflammatory process was a relatively complex and we are unable to measure other inflammatory markers such as interleukin 6, tumour necrosis factor etc. in our hospital because of lack of facilities. If NLR could be correlated with these inflammatory markers the results may be better. Accurately determining the optimal time to test NLR in stroke patients needs additional research.

While patients who died had a higher mean NLR compared to those discharged, this difference was not statistically significant. A weak positive correlation was observed between NLR and stroke severity (NIHSS score), but this too lacked statistical significance. These findings suggest that while NLR may have some potential as a prognostic marker, its utility in this specific cohort was limited.

Diabetes mellitus emerged as a significant predictor of mortality in both univariate and multivariate analyses. This underscores the critical importance of optimal diabetes management in acute ischemic stroke patients. Other comorbidities, including hypertension and alcoholism, were prevalent but not significantly associated with outcomes in this study.

A significant difference in mortality rates between females and males was observed, with females showing higher mortality. This finding highlights the need for further research into gender-specific risk factors and responses to acute ischemic stroke.

The predominance of moderate stroke severity and middle cerebral artery territory infarcts in this cohort aligns with typical patterns seen in ischemic stroke populations. No significant association was found between infarct territory and outcomes or NLR values.

Conflict of Interest: None to declare

Source of funding: Nil

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