Relationship between relevant inflammatory markers and short-term functional outcomes of acute ischemic stroke treated with mechanical thrombectomy: a retrospective cohort study

 Predicting failure to recover DOES NOTHING FOR SURVIVORS! You're fired!

Relationship between relevant inflammatory markers and short-term functional outcomes of acute ischemic stroke treated with mechanical thrombectomy: a retrospective cohort study

• 

  Jin-Cheng Liu 1,2†

• J

  Jie Wen 2†

• S

  Shi-Xiong Peng 2

• H

  Hao Ren 2

• Y

  Yiran Liu 2

• C

  Cui Zhou 2

• 

  Xiao Hu 1

• 

  Qi Li 1*

• 1. Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China

• 2. Department of Neurology, Xiangyang Hospital of Traditional Chinese Medicine, Xiangyang, Hubei, China

Abstract

Background and purpose: 

Perioperative inflammatory markers are considered critical factors influencing long-term postoperative survival. This study evaluated the neutrophil-to-high-density lipoprotein ratio (NHR), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammatory response index (SII), and systemic inflammatory response index (SIRI) in relation to functional outcomes in patients with acute ischemic stroke who underwent mechanical thrombectomy (MT). Our objective is to determine the prognostic value of inflammatory composite indices for 90-day functional outcomes in patients with acute ischemic stroke undergoing mechanical thrombectomy and to develop a multivariable prediction model integrating these indices for individualized outcome risk stratification.

Method: 

A total of 112 patients who underwent MT were enrolled between April 2021 and December 2023. Blood tests were performed at admission. Logistic regression analysis was used to evaluate the relationship between NHR, NLR, PLR, LMR, SII, SIRI and poor functional outcomes at 3 months (mRS Score 3–6). Receiver operating characteristic (ROC) curve analysis was conducted to assess the ability of NHR, NLR, PLR, LMR, SII, and SIRI to predict 90-day functional outcomes.

Results: 

A total of 54 patients (48%) had poor functional outcomes at 3 months. The median stroke onset to admission time was [6.7] hours (IQR, [3.45]–[8.05]) for poor functional outcome and [9.0] hours (IQR, [7.45]–[14.15]) for good functional outcome. Mean age of the study cohort was 67.5 years, and 64.3% were male. Multivariate logistic regression analysis revealed that NHR (odds ratio [OR], 1.150; 95% confidence interval [CI] 1.002–1.320, p = 0.046) was an independent predictor for poor functional outcome after adjusting for other clinical and imaging parameters.

Conclusion: 

NHR was independently associated with poor functional outcomes at 3 months in patients with acute ischemic stroke who underwent MT. These findings need to be confirmed in larger samples.(The research you should be doing is PREVNTING THAT POOR FUNCTIONAL OUTCOME! And you're so blitheringly stupid you can't figure that out?

Relationship Between Lymphocyte-Associated Inflammatory Markers and Post-Stroke Cognitive Impairment

 ABSOLUTELY USELESS!  Nothing here helps survivors recover. You're all fired for not knowing that the only goal in stroke is 100% recovery

Relationship Between Lymphocyte-Associated Inflammatory Markers and Post-Stroke Cognitive Impairment

Authors Hu QY, Liu J, Cui CH, Guo MF, Shi YT, Zhang XM, Jia BF, Li XY, Sun SJ

Received 10 June 2025

Accepted for publication 6 September 2025

Published 25 September 2025 Volume 2025:18 Pages 13347—13358

DOI https://doi.org/10.2147/JIR.S545953

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Ning Quan

Qian-Ying Hu,^1,* Juan Liu,^1,* Cai-Hong Cui,¹ Mei-Fang Guo,² Yu-Tong Shi,² Xiao-Man Zhang,² Bing-Fei Jia,² Xin-Yu Li,² Su-Juan Sun<sup>3

1</sup>Department of Rehabilitation Medicine, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, People’s Republic of China; ²Department of Basic Medical Sciences, Hebei University, Baoding, Hebei, 071000, People’s Republic of China; ³Department of Nursing, Hebei General Hospital, Shijiazhuang, Hebei, 050000, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Su-Juan Sun, Department of Nursing, Hebei General Hospital, No. 348 Heping West Road, Xinhua District, Shijiazhuang, Hebei, 050000, People’s Republic of China, Tel +86 13933093071, Email sujuansunssjm@126.com Cai-Hong Cui, Department of Rehabilitation Medicine, Affiliated Hospital of Hebei University, No. 212 of Yuhua East Road, Lianchi District, Baoding, Hebei, 071000, People’s Republic of China, Tel +86 13463236473, Email caihongcuicchk@126.com

Objective: To determine whether differences in lymphocyte-related inflammatory markers in the ultra-early phase of stroke (within 24 hours of onset) are associated with post-stroke cognitive impairment in the early recovery phase (within 30 days of stroke onset), and to further assess the predictive value of these markers.
Methods: The study population consisted of patients who underwent rehabilitation treatment at the Rehabilitation Department of Hebei University Affiliated Hospital between December 2024 and June 2025, within 30 days of stroke onset, ie, during the early recovery phase of stroke. Patients were grouped based on whether they developed cognitive impairment. A retrospective analysis was conducted of patients’ blood markers and neurological deficit scores within 24 hours of stroke onset to examine the relationship between ultra-early blood markers and neurological deficits and post-stroke cognitive impairment.
Results: There were no significant differences in baseline data between the two groups. However, the proportion of hemorrhagic stroke patients was significantly higher in the PSCI group than in the non-PSCI group (39.7% vs 18.8%, P=0.026< 0.05). NLR and NIHSS scores showed significant differences between the two groups. Multivariate analysis indicated that NIHSS (OR=1.297, 95% CI: 1.167– 1.442, p< 0.001) was independently associated with PSCI, while NLR (OR=1.107, 95% CI: 0.995– 1.231, p=0.063) showed a borderline association with PSCI. MLR showed differences between the two groups in univariate analysis (P=0.018) but was excluded in multivariate analysis. ULR did not show significant differences.
Conclusion: NIHSS is a strong predictive factor (P < 0.05), with a cut of value of 12 calculated by the ROC curve. NLR is at the threshold for an independent risk factor. Subsequent ROC curves indicate that NLR has low diagnostic sensitivity but high specificity, making it more suitable for screening rather than diagnostic use. MLR and ULR did not demonstrate high predictive value; further studies should be conducted to expand the sample size, perform subgroup analyses, and increase follow-up.

Keywords: post-stroke cognitive impairment, NIHSS, NLR, MLR, ULR

Background

The 2020 China Stroke Report shows that the prevalence of stroke in China is 1,114.8 per 100,000 people, the annual incidence rate is 246.8 per 100,000 people, and the mortality rate is 149.49 per 100,000 people. China has become the country with the highest lifetime risk of stroke and the heaviest disease burden globally.¹ Post-stroke cognitive impairment (PSCI) refers to a clinical syndrome characterized by cognitive impairment that occurs after a stroke event and persists for up to six months. According to literature reports, approximately one-third of stroke patients experience.² The diagnosis of PSCI is typically based on clinical assessment, neuropsychological assessment, and neuroimaging. The Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) are the most widely used cognitive tests in PSCI research.³ However, both are subject to copyright restrictions, which pose challenges for research. Meanwhile, the new cognitive test Mini-Cog, which is simple to administer and time-efficient, can aid in detecting the early stages of cognitive impairment. In a post-hoc analysis of a population-based study of older adults in the United States, the Mini-Cog scores classified as “possibly impaired” or “possibly normal” using the algorithm were comparable to those of the MMSE with a cutoff point of 25 in terms of sensitivity (76% vs 79%) and specificity (89% vs 88%) for dementia.-Cog, which was scored as “possibly impaired” or “possibly normal” by the algorithm, showed similar sensitivity (76% vs 79%) and specificity (89% vs 88%) for dementia compared to the MMSE with a cutoff point of 25. These results were comparable to those obtained using traditional neuropsychological assessments (sensitivity 75%, specificity 90%).⁴ A meta-analysis indicated that for cognitive impairment (including dementia and mild cognitive impairment) in primary care settings, Mini-Cog showed 73% sensitivity and 84% specificity. In secondary care settings, Mini-Cog showed 73% sensitivity and 76% specificity⁵ All performed well.

In addition to clinical examinations, neuropsychological assessments, and imaging studies, various blood biomarkers have become a focal point of research. By measuring indicators associated with brain injury in the early stages of stroke, it is possible to predict the occurrence of PSCI, which aids in the early identification of PSCI and facilitates further rehabilitation interventions. Inflammatory factors are closely associated with cognitive impairment. Clinically, lymphocyte-related inflammatory markers, such as the neutrophil-lymphocyte ratio (NLR), have been shown to have predictive value in a prospective cohort study of cognitive impairment following ischemic stroke. Peripheral NLR levels are significantly elevated in PSCI patients.³

Another inflammatory marker closely related to lymphocytes—the monocyte-to-lymphocyte ratio (MLR)—is more commonly used in the prediction of cardiovascular disease.⁶ The serum uric acid to lymphocyte ratio (ULR) has been validated as a new lymphocyte-related inflammatory marker with superior predictive value for hemorrhagic stroke compared to uric acid or lymphocyte levels alone in a large prospective cohort study conducted in China.⁷ This study was conducted to further clarify whether differences in inflammatory markers, especially lymphocyte-related inflammatory markers, in the ultra-early stage of stroke (within 24 hours of onset), including hemorrhagic stroke, are associated with post-stroke cognitive impairment in the early recovery stage (within 30 days of stroke onset).⁸

Research Methods

This study is a retrospective study targeting patients who underwent rehabilitation therapy at the Rehabilitation Department of Hebei University Affiliated Hospital between December 2024 and June 2025, specifically those within 30 days post-stroke, ie, in the early recovery phase of stroke. The study population was divided into an observation group (PSCI group) and a control group (non-PSCI group) based on the occurrence of cognitive impairment. A retrospective analysis was conducted of blood markers and neurological deficit scores within 24 hours of stroke onset, to investigate the relationship between ultra-early blood markers and neurological deficits and the occurrence of cognitive impairment after stroke.

Refer to previous literature,³ the inclusion criteria are as follows: (1) age ≥ 18 years; (2) confirmed by cranial computed tomography (CT) or magnetic resonance imaging (MRI);² (3) Patients who have experienced a stroke within the past 30 days, are in the early stages of recovery, have stable conditions, are conscious, can speak fluently, and are able to cooperate with rehabilitation assessments and treatments; (4) Patients who visited the Department of Neurology, Department of Neurosurgery, Department of Critical Care Medicine, or other relevant departments at Hebei University Affiliated Hospital within 24 hours of experiencing a stroke, with complete clinical data and traceable medical records from within 24 hours of the onset of symptoms.

Refer to previous literature,³ the exclusion criteria are as follows: (1) Patients who had been diagnosed with cognitive impairment disorders prior to the stroke, including Alzheimer’s disease, frontotemporal dementia, Parkinson’s disease dementia, Lewy body dementia, mixed dementia, and other types of cognitive impairment or dementia caused by various reasons; (2) Patients unable to cooperate with cognitive function assessments, including those with severe aphasia, hearing impairments, dysarthria, impaired consciousness, visual impairments, or those unable to write normally due to limb dysfunction caused by stroke; (3) Patients with unstable conditions who are unable to cooperate with assessments and rehabilitation therapy, including but not limited to those with severe illnesses such as cardiovascular diseases (eg, severe heart failure, severe arrhythmias), renal diseases (eg, renal failure), pulmonary diseases (eg, severe pneumonia, respiratory failure), etc.; (4) Patients who had conditions prior to the stroke that could trigger inflammatory and immune responses (eg, acute infections, tumors, blood disorders, autoimmune diseases, recent major surgeries, or trauma); (5) Patients who had been taking medications that could interfere with the inflammatory and immune systems prior to the stroke (eg, antibiotics, corticosteroids, immunosuppressants, targeted therapies, etc).; (6) Patients with a history of recurrent strokes.

Based on the Mini-Cog score, patients were divided into a post-stroke cognitive impairment (PSCI) group and a group without post-stroke cognitive impairment. This study complies with the World Medical Association’s Declaration of Helsinki and has been approved by the Ethics Committee of Hebei University Affiliated Hospital (the Ethics Committee of Affiliated Hospital of Hebei University:HDFYLL - KY - 2024 - 120).

Data Collection

Baseline Characteristics

Age, sex, body mass index (BMI), educational attainment (elementary, middle school, university),smoking and alcohol use,were collected.

Clinical Variables

This included past medical history (including coronary heart disease, diabetes, and hypertension, the definition criteria are a previous clear diagnosis of a related disease and/or long-term use of therapeutic drugs prior to onset, stroke type (hemorrhagic or ischemic).

Observation Indicators

Extract and analyze medical records from the acute phase within 24 hours of onset, extracting data on neutrophils, lymphocytes, monocytes, and uric acid, and calculate NLR, MLR, and ULR. Uric acid levels were analyzed using the Fusion biochemical analyzer from Johnson & Johnson, and blood cell counts were measured using the XN-L™ Series blood analyzer from Sysmex Corporation. Stroke severity was assessed using the National Institute of Health Stroke Scale (NIHSS) to evaluate neurological deficit scores.⁹

Cognitive Function Assessment and Grouping

The official Chinese version of the Mini-Cog official website was used to assess the cognitive function of the patients, which was truncated into a control group (no cognitive impairment group) and an observation group (cognitive impairment group) with 4 points.

The sample size calculation formula is:  where the expected prevalence rate (P) is 1/3 (33%) as described in the background section above, the confidence interval is 95%, and the allowable error is 0.1. The minimum sample size calculated is 85 cases, which will be assessed by therapists who are trained and proficient in using the Mini-Cog. A total of 127 cases were ultimately included in this study, 69 in the control group and 58 in the observation group.

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Prognostic value of lymphocyte-to-monocyte ratio in acute ischemic stroke: a systematic review and meta-analysis

 ABSOLUTELY FUCKING USELESS! Nothing here gets survivors recovered! You're all fired!

Prognostic value of lymphocyte-to-monocyte ratio in acute ischemic stroke: a systematic review and meta-analysis

Chengli Tian^1,2†Yilin Yang^1,2†Jun Wan²Ran Wang²Ke Zhou²Yuanli Li²Wenlong Guo¹Huijun Li²Yu Zhang^1*

• ¹Center for Evidence-Based Medicine, Affiliated Hospital of Chengdu University, Chengdu, Sichuan, China
• ²Department of Critical Care Medicine, Affiliated Hospital of Chengdu University, Chengdu, Sichuan, China

Background: The findings from studies exploring the prognostic relevance of the lymphocyte-to-monocyte ratio (LMR) in individuals with acute ischemic stroke (AIS) have shown variability. We aimed to conduct a meta-analysis to determine the prognostic significance of LMR in this patient population.

Methods: We carried out a meta-analysis utilizing information from major databases, including PubMed, Embase, and Web of Science until October 26, 2024. Effect sizes, represented as odds ratios (ORs) along with their corresponding 95% confidence intervals (CI), were synthesized employing a random-effects model in Review Manager Version 5.4. To investigate possible sources of variability, we conducted subgroup analyses. Additionally, publication bias was assessed through the use of a funnel plot. Poor functional outcome at 3 months, as indicated via a modified Rankin Scale score of ≥3, was the main outcome. A moderate to severe stroke, determined by a National Institutes of Health Stroke Scale score of ≥6, was the secondary outcome.

Results: Six trials totaling 1,225 individuals were included in our analysis. In AIS patients, we discovered a significant correlation between lower LMR and poorer functional outcome at 3 months, with an OR of 0.63, 95% CI of 0.49 to 0.80, and a p-value of 0.0002. Additionally, lower LMR may be associated with developing moderate to severe stroke, with an OR of 0.89 (95% CI: 0.82–0.97; p = 0.008). In subgroup analyses with an LMR cutoff, a significant association was observed between lower LMR and greater functional impairment in AIS patients, with an odds ratio of 0.74 (95% CI: 0.62–0.88; p = 0.0005) for LMR ≥ 3 and 0.54 (95% CI: 0.47–0.61; p < 0.00001) for LMR < 3. Additionally, when country-stratified, Asian continued to have a significant correlation between worse functional outcome and lower LMR (OR 0.62, 95% CI: 0.50–0.77, p < 0.0001).

Conclusion: This meta-analysis indicated that LMR was a prognostic factor for clinical outcomes in AIS patients.

Introduction

A stroke is characterized by its abrupt onset, representing a sudden neurological disruption resulting from the abrupt cessation of cerebral blood flow, which leads to a wide spectrum of neurological deficits (1). Strokes are generally classified into two main categories: ischemic and hemorrhagic. Of these, ischemic strokes account for approximately 80% of all cases, with an alarmingly high global incidence of over 13.7 million cases annually, leading to around 5.5 million deaths each year (2). Although strokes can affect individuals across all age groups, they primarily affect older adults. However, there has been a concerning rise in the incidence among younger populations (2, 3). Among the different types of stroke, acute ischemic stroke (AIS) is the most common, placing a significant strain on healthcare systems due to its high morbidity and mortality rates, as well as the considerable risks of fatal outcomes and long-term disabling effects (4). Thus, identifying reliable prognostic markers is crucial for informed clinical decision-making and personalized patient care.

Increasing evidence indicates that AIS triggers an inflammatory response (5–7). There is growing interest in the part inflammatory indicators play in the pathophysiology and outcome of AIS. A cost-effective and easily accessible composite indicator of inflammation in cerebrovascular disease, the lymphocyte-to-monocyte ratio (LMR), which was computed by dividing the lymphocyte count by the monocyte count, integrates the prognostic significance of individual lymphocyte and monocyte levels in relation to AIS (8). Previous research has indicated an association between LMR and the severity as well as outcomes of inflammation-related maladies such as myocardial infarction, chronic autoimmune diseases, and peripheral ischemia (9–11).

The link between LMR and adverse outcomes in AIS patients continues to be a subject of debate. Although a number of studies have shown a correlation between AIS patients’ inferior prognosis and lower LMR levels (12–15), others have failed to establish a significant link between LMR and negative clinical outcomes (16). In light of these discrepant results, we carried out this meta-analysis to delve deeper into the relationship between LMR and adverse outcomes among AIS patients.

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Predictive value of circulating inflammatory biomarkers for early-onset post-stroke cognitive impairment: a prospective cohort study

 

This prediction doesn't get survivors recovered, does it? So useless research!

You're fired!

Predictive value of circulating inflammatory biomarkers for early-onset post-stroke cognitive impairment: a prospective cohort study

Weiquan Huang^1†Libin Liao^1†Qian Liu²Rongchao Ma¹Wentong Hu¹Yuan Dai^3*Luna Wang^3*Dujuan Sha^1,2,3,4*

• ¹Department of General Practice, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, China
• ²Department of General Practice, Nanjing Drum Tower Hospital Clinical College of Xuzhou Medical University, Nanjing, China
• ³Department of General Practice, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
• ⁴Institute of Functional Biomolecules, State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, Nanjing, China

Introduction: Stroke ranks as the second leading cause of mortality and the third leading cause of disability globally. Post-stroke cognitive impairment (PSCI) is a prevalent complication following acute ischemic stroke, imposing substantial burdens on patients, families, and society. This study aimed to explore the potential of circulating immune-inflammatory markers as predictors of PSCI.

Methods: Conducted as a prospective observational cohort study from June 2023 to August 2024 at the Affiliated Drum Tower Hospital, Medical School of Nanjing University, it included patients experiencing their first acute ischemic stroke within 72 h of symptom onset. Cognitive assessments were conducted 7 to 10 days post-stroke using the Montreal Cognitive Assessment (MoCA), with scores below 23 indicating PSCI.

Results: A total of 146 patients meeting the inclusion criteria were recruited, with 71 patients exhibiting PSCI during the acute phase of stroke. Compared to patients in the post-stroke no cognitive impairment (PSNCI) group, those with PSCI demonstrated significantly elevated peripheral blood neutrophil-to-lymphocyte ratio (NLR), globulin-to-lymphocyte ratio (GLR), and C-reactive protein-to-lymphocyte ratio (CLR), while the lymphocyte-to-monocyte ratio (LMR) was notably reduced (all p < 0.05). Both univariate and multivariate logistic regression analyses identified GLR as independently associated with PSCI. After adjusting for common clinical variables, the odds ratio (OR) for the highest tertile of GLR compared to the lowest was 6.20 (95% CI, 2.10–18.33; p = 0.001). The optimal GLR cutoff was 18.22, with a sensitivity of 62.0%, specificity of 78.7%, and an area under curve (AUC) of 0.726.

Conclusion: This study indicates that elevated circulating GLR levels during the acute phase post-stroke onset are an independent risk factor for early-onset PSCI, even after adjusting for clinically relevant variables.

1 Introduction

Stroke is the second leading cause of death and the third leading cause of disability in the world (1). Depending on the etiology and pathogenesis, stroke can be classified as ischemic stroke or hemorrhagic stroke. Of these, ischemic stroke is the most common type, accounting for approximately 87% of all stroke patients (2). Post-stroke cognitive impairment (PSCI) is one of the most common complications of acute ischemic stroke, with a prevalence ranging from 15% to 70%, depending on the clinical features and stroke severity (3), which imposes a heavy burden on the patient, family, and society. PSCI includes cognitive impairment that occurs within 3 to 6 months after stroke and is clinically characterized by persistent impairment in one or more core cognitive domains, such as attention, memory, executive function, language, and visuospatial ability, and is associated with a significantly increased risk of death, disability, and depression up to 5 years after the onset of the stroke (4). Common risk factors for PSCI are advanced age, low education, hypertension, diabetes mellitus, atrial fibrillation, smoking, family history, sedentary lifestyle, stroke subtype, and stroke severity (5–7).

The diagnosis of PSCI is usually based on clinical assessment, neuropsychological evaluation, and neuroimaging (8, 9). The Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) are the most widely used cognitive tests for PSCI research. Factors such as the patient’s education degree, evaluation by different personnel, and the selection of different scales can affect the assessment results; these two tools are mainly applied to neurodegenerative diseases and have low sensitivity in detecting PSCI, which can lead to the underdiagnosis of PSCI (10). Computer tomography (CT) remains the standard imaging modality in clinical practice due to its advantages over magnetic resonance imaging (MRI) in terms of speed, cost, and fewer contraindications (11). MRI brain scans are generally more helpful in dementia assessment and are considered the “gold standard” for neuroimaging-based assessment (12). However, if neuroimaging is to be combined with clinical characterization as the primary diagnostic support for PSCI, it is essential to have experienced imaging physicians and to perform high-quality scans to obtain accurate information.

Therefore, blood biomarkers hold promising potential due to their availability, low invasiveness, objectivity, and cost-effectiveness.(Biomarkers don't get you recovered, do they? So why the fuck are you researching biomarkers?) An increasing number of research studies have shown that blood biomarkers play an important role in the occurrence and development of PSCI. There are currently no precise blood biomarkers for PSCI risk prediction and early diagnosis at home and abroad. Acute cerebral ischemia releases damage-associated molecular patterns that trigger brain intrinsic immune cells (microglia) and recruit peripheral innate immune cells, including neutrophils and monocytes/macrophages for infiltration, leading to exacerbated ischemic injury (13). Meanwhile, cerebral ischemia releases harmful substances, especially necrotic cellular debris, which triggers an inflammatory cascade in the immune system, leading to subsequent repair processes and tissue damage (14). Imbalanced expression of pro- and anti-inflammatory cytokines in the brain activates cerebral microvessels and disrupts the blood–brain barrier, exacerbating neurological dysfunction and ultimately leading to cognitive impairment and dementia (15, 16). Studies have shown a strong correlation between the immune response in the acute phase of stroke and long-term cognitive function (17). A recent study found that the neutrophil-to-lymphocyte ratio (NLR) during the acute phase of ischemic stroke was independently correlated with PSCI at 3 months post-stroke (18), which is consistent with the findings of several other studies (19, 20). Therefore, the immune-inflammatory response plays a significant role in the pathogenic process of PSCI. Peripheral blood cell counts and biochemical indices are among the most accessible laboratory indices in the clinic. In this study, peripheral blood lymphocyte count was combined with neutrophil count, monocyte count, serum globulin, and C-reactive protein (CRP) to investigate the predictive value of the NLR, lymphocyte-to-monocyte ratio (LMR), globulin-to-lymphocyte ratio (GLR), and C-reactive protein-to-lymphocyte ratio (CLR) in early-onset PSCI.

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