Stroke is a medical emergency, characterized by the abrupt development of localized neurological impairment within a vascular territory caused by an underlying cerebrovascular etiology.[1,2] With India reporting the highest number of stroke cases globally, the long-term care of these patients has placed an unimaginably heavy burden not only on thousands of patients' families but also on the public healthcare system. Identifying reliable and economical biomarkers to predict stroke severity and outcomes is therefore beneficial to the healthcare providers and families alike.[3,4] Post-ischemia inflammation, driven by leukocyte activation and pro-inflammatory mediator release from the damaged endothelium, platelets, and brain tissue, has been hypothesized to play a role in different stages of ischemic brain injury.[5,6] Previous studies have reported that leukocytosis at admission correlates with both stroke severity and unfavorable clinical outcomes in patients with acute ischemic stroke (AIS).[7] Although platelets have been recognized as key players in inflammation and thrombogenesis, the association between their elevated counts and stroke severity or prognosis remains unclear .[6,8] In this context, the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR) have recently gained attention as promising, cost-effective biomarkers of inflammation that may be useful in predicting stroke prognosis.[9,10] Moreover, NLR and PLR have been concurrently utilized as prognostic indicators in patients with malignancy, coronary artery disease, and subarachnoid hemorrhage.[11,12] However, there remains limited evidence regarding the combined prognostic significance of NLR and PLR in predicting both the severity and short-term functional outcome of AIS. Therefore, this study aimed to evaluate the role of these inexpensive hematologic parameters in predicting the short-term prognosis of AIS.

This prospective observational study was conducted at a tertiary care hospital in central India over an 18-month period. This study was approved by the institutional research and ethics committee. Sample size was calculated using the formula Z2pq/e2 (taking the prevalence of AIS to be 7.1% in India as per previous studies[13], the sample size came out to be 102). Thus, this study recruited 102 adult patients (aged >18 years) who were clinically and radiologically diagnosed with AIS within 72 hours of symptom onset. Patients were included if they met the World Health Organization (WHO) criteria for AIS [14], presented within 72 hours of symptom onset, and provided informed consent for participation. Exclusion criteria comprised patients with clinical features indicative of acute or chronic CNS infections, hemorrhagic stroke, cerebral venous sinus thrombosis, prior endovascular therapy or thrombolysis, or current use of anti-inflammatory medications such as corticosteroids or immunosuppressants. Patients with comorbidities like chronic hepatic or renal disease which might impact the NLR or PLR value were also excluded from the study. Demographic data, detailed clinical history and examination findings of all patients were recorded in a pre-structured proforma. Neurological assessment including the Glasgow Coma Scale[15] and the National Institutes of Health Stroke Scale (NIHSS)[3] was calculated to determine stroke severity. Patients were divided into two groups[16] 1: NIHSS < 16 (0-15) as minor to moderate stroke 2: NIHSS ≥ 16 (16-42) as moderately severe to severe stroke Routine laboratory investigations including Complete blood count (CBC) were performed at admission and repeated at 7 days or at the time of discharge (if earlier). NLR and PLR were calculated from CBC parameters (if earlier). Sample for complete blood count was analysed in the department of Pathology whereas other investigations were done in department of Biochemistry of our hospital. STATISTICAL ANALYSIS Data were recorded in a pre-structured proforma and transcribed into Microsoft Excel spreadsheet. Statistical Analysis was performed using IBM SPSS software version 20. Categorical data were expressed as frequency and percentage whereas continuous data were expressed as mean and standard deviation. Comparisons of NLR and PLR between the two stroke severity groups were conducted using one-way analysis of variance (ANOVA) and unpaired t-tests. Receiver operating characteristics (ROC) curve analysis was employed to determine the predictive ability of NLR and PLR for assessing the moderately severe to severe stroke (NIHSS ≥16) and to predict deterioration in clinical outcome (deterioration in NIHSS at discharge as compared to admission NIHSS). P value <0.05 was considered statistically significant.

Table 1 shows the relevant clinical history and anthropometric parameters of patients enrolled in our study. Mean age of patients presenting with AIS was 60.25±13.9 years and more than half of the patients (51%) belonged to the elderly age group (>60 years). There was a stark male preponderance noted for AIS (61.8%), with a male: female ratio of about 1.6:1. Majority of patients were residents of urban area (56.9%). 65.7% cases were hypertensive, and 37.3% cases had a past history of diabetes. Mean BMI of patients was 23.6±3.5 kg/m2 and 34.3% cases were obese (BMI ≥25 kg/m2). Table 1- Distribution of cases with Acute Ischemic Stroke (AIS) according to baseline variables Baseline variables No. of patients (n=102) Percentage (100%) Age (years) ≤40 12 11.8 41-50 7 6.9 51-60 31 30.4 61-70 28 27.5 >70 24 23.5 Gender Male 63 61.8 Female 39 38.2 Residence Rural 44 43.1 Urban 58 56.9 Clinical history Family history of stroke 10 9.8 Alcoholism 44 43.1 Smoking 54 52.9 Hypertension 67 65.7 Diabetes 38 37.3 Dyslipidaemia 12 11.8 BMI <18.5 (Underweight) 6 5.9 18.5-22.9 (Normal) 39 38.2 23-24.9 (Overweight) 22 21.6 ≥25 (Obese) 35 34.3 Table 2- Association of NLR and PLR with severity of acute ischemic stroke Ratio NIHSS Score P value <16 (n=42) ≥16 (n=60) NLR 4.31±2.04 8.61±3.12 0.001 PLR 195.0±55.1 222.5±50.8 0.03 Table 2 shows the association of NLR and PLR values with stroke severity. Mean NLR as well as PLR values were significantly higher in cases with moderately severe to severe stroke as compared to those with minor to moderate stroke, and this difference was statistically significant (p<0.05) (Table 2). Table 3- ROC curve analysis of NLR and PLR for predicting moderately severe to severe stroke Test Result Variable(s) Area P value Asymptotic 95% Confidence Interval Cut off Sensitivity Specificity Lower Bound Upper Bound NLR 0.879 0.001 0.812 0.946 5.4 81.7 81 PLR 0.648 0.011 0.537 0.759 196.7 73.3 57.1 ROC curve analysis revealed NLR to be a good predictor of moderately severe to severe stroke (AUC- 0.879; 95% CI- 0.812-0.946; p<0.05). At a cut off of 5.4, NLR had a sensitivity of 81.7% and specificity of 81% for predicting moderately severe to severe stroke. PLR, however, emerged as a poor predictor of moderately severe to severe stroke (AUC- 0.648; 95% CI- 0.537-0.759; p<0.05) and at a cut off of 196.7, PLR had a sensitivity and specificity of 73.3% and 57.1% respectively for predicting moderately severe to severe stroke (Table 3, Figure 2). Table 4- Association of NLR and PLR with outcome at discharge Variables Outcome at discharge P value Improved Remained same Deteriorated Mean SD Mean SD Mean SD NLR 6.4 3.2 6.8 3.6 8.1 3.7 0.179 PLR 208.5 49.3 210.9 58.7 219.2 62.3 0.753 Although the mean NLR and PLR values were lower in patients who improved at discharge as compared to those who deteriorated, we observed no significant association of mean NLR and PLR values with the patient outcome at discharge (p>0.05) (Table 4). Table 5- ROC curve analysis of NLR and PLR for predicting deterioration in NIHSS Deterioration in NIHSS Area P value Asymptotic 95% Confidence Interval Cut off Sensitivity Specificity Lower Bound Upper Bound NLR 0.632 0.069 0.492 0.772 7.44 65 65.9 PLR 0.507 0.919 0.368 0.646 198.5 60 42.7

NLR and PLR are two novel inflammatory biomarkers that have lately shown potential as significant prognostic indicators in AIS patients.[9,10] The present study was conducted on a total of 102 patients presenting with AIS to evaluate the usefulness of NLR and PLR in predicting stroke severity (using NIHSS) and short-term outcomes. Majority of the patients enrolled in our study (58.8%) had moderately severe to severe stroke (NIHSS≥16) at the time of admission, whereas the remaining 41.2% cases presented with minor to moderate stroke (NIHSS <16). The mean NIHSS score of AIS patients at admission was 18.6±8.2. These findings were in contrast to those of Prabhu et al., who found majority of the patients (83%) with AIS to have minor to moderate stroke at the time of admission.[16] On the other hand, in the study done by Chandra et al., 18.5% patients presented with moderate to severe stroke (NIHSS scores 16–42), 60.0% had moderate stroke (NIHSS scores 5–15), and 21.5% had minor stroke (NIHSS scores 1-4) at the time of admission.[17] Chen et al. assessed the functional outcome using Modified Rankin Scale (mRS), and found NIHSS score to be significantly higher in cases with poor functional outcome (Z = 8.47, p < 0.01).[18] Upcoming research has established that inflammation is a key player in not only the development but also the prognosis of AIS. During stroke, damage to the brain tissue is caused by the secretion and accumulation of metalloproteinases, perforins, cytokines, and neutrophil extracellular traps by neutrophils, monocytes, and other immune cells. Following ischemia, inflammatory mediators are also released from the damaged brain tissue, thereby exacerbating the local inflammatory response. It has also been demonstrated that the ratio of different inflammatory indicators—like the NLR and PLR—provides a higher predictive value than the individual inflammatory markers themselves, thereby making them economically viable potential predictors of AIS.[18] We observed that patients with moderately severe to severe stroke had a significantly higher mean NLR value than those with minor to moderate stroke (8.61±3.12 vs. 4.31±2.04; p=0.001). ROC curve analysis demonstrated that NLR was a good predictor of moderately severe to severe stroke (AUC- 0.879; 95% CI- 0.812-0.946; p<0.05), with a sensitivity of 81.7% and a specificity of 81% for predicting moderately severe to severe stroke at a cut off of 5.4. These findings were in concordance with those of Prabhu et al., who found the mean NLR to be significantly higher in patients with moderate to severe stroke than those with minor to moderate stroke (13.8±24.62 vs 5.93±5.16; p=0.007). They also found a significant positive correlation of NLR with the NIHSS rating upon admission (r=0.285; p<0.003), indicating its utility in assessing the stroke severity.[16] Zhao et al. also established that a higher NLR value at presentation was linked to early neurological deterioration in AIS patients.[19] Additionally, Ozgen et al. found NLR to be significantly associated with poor clinical outcome as well as higher mortality (p=0.043 and 0.001 respectively).[10] Ma et al., similarly, observed that a higher NLR value was linked to adverse clinical outcomes in AIS patients, and this association was statistically significant (OR, 1.076; 95% CI, 1.037–1.117; p < 0.001).[20] Similar association of higher NLR values at admission with stroke severity was established by Cormuk et al. in their study.[21] Inflammatory cascades constitute a pivotal component of ischemic stroke pathogenesis. The ischemic insult activates innate immune pathways, resulting in endothelial dysfunction and thrombogenic remodelling of the vascular microenvironment. Platelets are key effectors in this process, augmenting thrombus formation and amplifying the release of pro-inflammatory cytokines that sustain vascular inflammation and exacerbate ischemic injury. Conversely, lymphocytes have been shown to have anti-inflammatory properties that could prevent the development of atherosclerosis and control immunological responses. As a result, PLR, which measures the ratio of platelets to lymphocytes, has drawn attention as a sign of systemic inflammation that may be indicative of stroke severity.[20] In our study, patients with moderately severe to severe stroke recorded a significantly higher mean PLR value than those with minor to moderate stroke (222.5±50.8 vs 195.0±55.1; p=0.03). PLR, however, was a poor predictor of moderately severe to severe stroke (AUC- 0.648; 95% CI- 0.537-0.759; p<0.05), and at a cut off of 196.7, PLR had a sensitivity and specificity of 73.3% and 57.1% for predicting moderately severe to severe stroke. Our findings were supported by those of Chandra et al., who recorded that patients with moderate to severe stroke had a significantly higher PLR than those with minor stroke (153.6 vs 119.4; p=0.002), and established that a higher PLR value was significantly correlated with stroke severity.[17] Similarly, Ma et al. found that a higher PLR was significantly linked to adverse outcomes after controlling for confounding variables (OR, 1.001; 95% CI, 1.000–1.003; p = 0.045).[20] Sung et al. also discovered a significant positive correlation of PLR with NIHSS (r=0.269; p<0.001), thereby establishing a direct correlation of PLR with stroke severity.[22] At the time of discharge, we again assessed the NIHSS score and recorded an improvement in 54.9% cases, whereas in 25.5% cases NIHSS score remained same. The condition, however, deteriorated in 19.6% cases. Of the 60 patients who were admitted with moderately severe to severe stroke, the NIHSS score improved in 43.3%, deteriorated in 26.7% and score remained same in 30% cases. Overall, a significantly greater percentage of patients hospitalized with minor to moderate stroke had an improvement in their NIHSS score at discharge compared to those with moderately severe to severe stroke (p=0.015). We also assessed the role of NLR and PLR in predicting deterioration in the condition of patients and found NLR to be a poor predictor of deterioration (AUC- 0.632; 95% CI-0.492-0.772; p>0.05), whereas PLR failed to predict deterioration in condition of patients (AUC- 0.507; 95% CI- 0.368-0.646; p>0.05). Prabhu et al. documented an improvement in the condition of 63.2% stroke cases whereas NIHSS score remained same in 34% cases and mortality was documented in 2.8% cases. The authors also found that a significantly higher proportion of patients with minor to moderate stroke improved (67%), whereas a significantly higher proportion of patients with severe stroke succumbed to death (16.7%; p<0.001).[16] In the study done by Sharma et al., the PLR value increased significantly from baseline in patients whose condition deteriorated (263.42±108.98 to 346.28±125.35; p=0.016); however, in patients who improved, it drastically decreased (242.27±75.14 to 167.19±57.91; p=0.0001); and in patients whose condition remained static, it did not change significantly (181.35±105.40 to 183.36±111.61; p=0.955).[23] Ma et al., however, observed no significant corelation of NLR and PLR with 3-month mortality in patients with AIS (all adjusted p>0.05).[20] Our study, however, had certain limitations. The study was conducted as a unicentric study on a small sample of patients, with homogeneous group of population and thus, the findings of the study cannot be generalised. In hospital outcomes were assessed in terms of improvement in NIHSS score on day 7 or discharge (if earlier) as compared to admission NIHSS scores, however, long term outcomes could not evaluated. Only predictive value of NLR and PLR were assessed, however, predictive value of other ratios such as MLR were not assessed.

NLR and PLR are easily available and cost-effective markers of assessment of severity of stroke. Although the NIHSS is a commonly used and accurate tool for assessing the severity of strokes, it ignores underlying inflammatory processes and instead concentrates on neurological abnormalities. Amongst the two ratios, NLR was found to have better predictive ability for assessment of stroke prognosis as compared to PLR. For the purpose of forecasting severity of condition in patients with AIS, the NLR may be a simple and affordable diagnostic tool. Thus, incorporation of NLR and PLR in evaluation of patients with AIS may offer a more comprehensive picture of the condition of patient and may help in directing early intervention strategies.

1. Hui C, Tadi P, Khan Suheb MZ, et al. Ischemic Stroke. [Updated 2024 Apr 20]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK499997/ 2. Tadi P, Lui F. Acute Stroke. [Updated 2023 Aug 17]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK535369/ 3. Jones SP, Baqai K, Clegg A, Georgiou R, Harris C, Holland EJ, Kalkonde Y, Lightbody CE, Maulik PK, Srivastava PM, Pandian JD. Stroke in India: A systematic review of the incidence, prevalence, and case fatality. Int J of Stroke. 2022 Feb;17(2):132-40. 4. Chen C, Gu L, Chen L, Hu W, Feng X, Qiu F, Fan Z, Chen Q, Qiu J, Shao B. Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio as potential predictors of prognosis in acute ischemic stroke. Front Neurol. 2021 Jan 25;11:525621. 5. Anrather J, Iadecola C. Inflammation and stroke: an overview. Neurotherapeutics. 2016 Oct 1;13(4):661-70. 6. Thomas MR, Storey RF. The role of platelets in inflammation. Thromb Haemost. 2015;114(09):449-58. 7. Furlan J, Vergouwen M, Silver F. White blood cell count as a marker of stroke severity and clinical outcomes after acute ischemic stroke (P03. 011). 8. Jennings LK. Mechanisms of platelet activation: need for new strategies to protect against platelet-mediated atherothrombosis. Thromb Haemost. 2009;102(08):248-57. 9. Lux D, Alakbarzade V, Bridge L, Clark CN, Clarke B, Zhang L, Khan U, Pereira AC. The association of neutrophil-lymphocyte ratio and lymphocyte-monocyte ratio with 3-month clinical outcome after mechanical thrombectomy following stroke. Journal of Neuroinflammation. 2020 Feb 18;17(1):60. 10. Ozgen E, Guzel M, Akpinar CK, Yucel M, Demir MT, Baydin A. The relationship between neutrophil/lymphocyte, monocyte//lymphocyte, platelet/lymphocyte ratios and clinical outcomes after ninety days in patients who were diagnosed as having acute ischemic stroke in the emergency room and underwent a mechanical thrombectomy. Bratisl Med J 2020; 121 (9):634–9. 11. Sari I, Sunbul M, Mammadov C, Durmus E, Bozbay M, Kivrak T, Gerin F. Relation of neutrophil-to-lymphocyte and platelet-to-lymphocyte ratio with coronary artery disease severity in patients undergoing coronary angiography. Kardiologia Polska (Polish Heart Journal). 2015;73(12):1310-6. 12. Tao C, Wang J, Hu X, Ma J, Li H, You C. Clinical value of neutrophil to lymphocyte and platelet to lymphocyte ratio after aneurysmal subarachnoid hemorrhage. Neurocritical care. 2017 Jun;26:393-401. 13. Hedau VN, Patil T. Mounting Stroke Crisis in India: A Systematic Review. Cureus. 2024 Mar;16(3). 14. Stroke--1989. Recommendations on stroke prevention, diagnosis, and therapy. Report of the WHO Task Force on Stroke and other Cerebrovascular Disorders. Stroke. 1989 Oct;20(10):1407-31 15. Sternbach GL. The Glasgow coma scale. The Journal of emergency medicine. 2000 Jul 1;19(1):67-71. 16. Prabhu S, Harshavardhan L. Role of Platelet to Lymphocyte Ratio, Neutrophil to Lymphocyte Ratio and Lymphocyte to Monocyte Ratio in Acute Ischaemic Stroke Severity: A Prospective Cohort StudyJ Clin of Diagn Res.2023; 17(10):OC12-OC16. 17. Chandra AB, MA U, Reddy MK, Sai Raghavendra KV. Platelet-to-lymphocyte ratio and its correlation with NIHSS for prognosis and severity of acute ischemic stroke. Int J Med Public Health. 2024 Oct;14(4). 18. Chen L, Zhang L, Li Y, Zhang Q, Fang Q, Tang X. Association of the Neutrophil-to-Lymphocyte Ratio with 90-Day Functional Outcomes in Patients with Acute Ischemic Stroke. Brain Sciences. 2024 Mar 4;14(3):250. 19. Zhao L, Zhou S, Dai Q, Li J. Neutrophil Lymphocyte Ratio Predicts Early Neurological Deterioration in Patients with Anterior Circulation Stroke. Int J Gen Med. 2024 Nov 16;17:5325-5331. 20. Ma J, Guo W, Xu J, Li S, Ren C, Wu L, Wu C, Li C, Chen J, Duan J, Ma Q. Association of platelet-to-lymphocyte ratio and neutrophil-to-lymphocyte ratio with outcomes in stroke patients achieving successful recanalization by endovascular thrombectomy. Front Neurol. 2022 Dec 16;13:1039060. 21. Çomruk G, Fırat YE, Geyik S, Cengiz EK, Neyal AM. Neutrophil-lymphocyte Ratio may be an Early Predictor of the Prognosis in Ischemic Stroke Cases. Turkish Journal of Neurology. 2022;28(4):212-6. 22. Sung PH, Chen KH, Lin HS, Chu CH, Chiang JY, Yip HK. The correlation between severity of neurological impairment and left ventricular function in patients after acute ischemic stroke. Journal of clinical medicine. 2019 Feb 5;8(2):190. 23. Sharma D, Gandhi N. Role of Platelet to Lymphocyte Ratio (PLR) and its correlation with NIHSS (National Institute of Health Stroke Scale) for prediction of severity in patients of acute ischemic stroke. J Assoc Physicians India. 2021 Jan;69(1):56-60