
==== Front
Neurol Ther
Neurol Ther
Neurology and Therapy
2193-8253
2193-6536
Springer Healthcare Cheshire

39117893
645
10.1007/s40120-024-00645-2
Original Research
Systemic Inflammatory Response Index and the Short-Term Functional Outcome of Patients with Acute Ischemic Stroke: A Meta-analysis
http://orcid.org/0009-0002-5230-4164
Han Ying hanying_fmuh@hotmail.com

1
Lin Nan 12
1 https://ror.org/055gkcy74 grid.411176.4 0000 0004 1758 0478 Department of Geriatrics, Fujian Medical University Union Hospital, 29 Xinquan Road, Fuzhou, 350001 China
2 https://ror.org/050s6ns64 grid.256112.3 0000 0004 1797 9307 Fujian Key Laboratory of Vascular Aging, Fujian Medical University, Fuzhou, 350001 China
9 8 2024
9 8 2024
10 2024
13 5 14311451
31 5 2024
2 7 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.
Introduction

The systemic inflammatory response index (SIRI) is a novel indicator of systemic inflammation derived from the absolute counts of neutrophils, monocytes, and lymphocytes. The aim of this meta-analysis was to evaluate the association between SIRI and functional outcome in patients with acute ischemic stroke (AIS).

Methods

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed in this meta-analysis. Relevant cohort studies were retrieved by a search of electronic databases including PubMed, Web of Science, Embase, Wanfang, and China National Knowledge Infrastructure from database inception to February 9, 2024. A poor functional outcome was defined as a modified Rankin Scale ≥ 3 within 3 months after disease onset. A random-effects model was used to combine the data by incorporating the influence of between-study heterogeneity. The protocol of the meta-analysis was not prospectively registered in PROSPERO.

Results

Fourteen cohort studies were included. Pooled results showed that a high SIRI at admission was associated with increased risk of poor functional outcome within 3 months (odds ratio [OR]: 1.57, 95% confidence interval: 1.39 to 1.78, p < 0.001; I2 = 0%). Results of the meta-regression analysis suggested that the cutoff for defining a high SIRI was positively related to the OR for the association between SIRI and the risk of poor functional outcome (coefficient = 0.13, p = 0.03), while other variables including sample size, mean age, severity of stroke at admission, percentage of men, current smokers, or patients with diabetes did not significantly modify the results. Subgroup analyses according to study design, main treatments, and study quality scores showed similar results.

Conclusion

A high SIRI may be associated with a poor functional outcome in patients after AIS.

Keywords

Acute ischemic stroke
Systemic inflammatory response index
Prognosis
Functional outcome
Meta-analysis
issue-copyright-statement© Springer Healthcare Ltd., part of Springer Nature 2024
==== Body
pmcKey Summary Points

Why carry out this study?	
Acute ischemic stroke (AIS) is a significant cause of disability and mortality, with inflammation playing a critical role in its progression and outcomes.	
The study hypothesized that a higher systemic inflammatory response index (SIRI) at admission is associated with a poorer functional outcome in patients with acute ischemic stroke.	
What was learned from the study?	
The meta-analysis found that a high SIRI at admission is significantly associated with an increased risk of poor functional outcome within 3 months.	
The study suggests that SIRI could be a valuable prognostic marker for short-term functional outcomes in patients after AIS, aiding in early identification of those at higher risk.	

Introduction

Acute ischemic stroke (AIS) continues to be a leading cause of death and long-term disability on a global scale, imposing a significant burden on healthcare systems and society [1–3]. The aging of the global population is expected to lead to a continuous increase in AIS cases worldwide over the coming years [4]. Despite progress in acute stroke management, accurately predicting short-term functional outcomes of patients with AIS remains difficult [5, 6]. Growing evidence indicates that systemic inflammation plays a role in the decline of neurological function after AIS; accordingly, recent research has increasingly emphasized the significance of systemic inflammation as a primary factor influencing stroke severity and recovery [7].

The systemic inflammatory response index (SIRI) is a newly developed marker based on peripheral blood counts, and it has been identified as a potential prognostic tool for various medical conditions such as cancer and cardiovascular diseases [8, 9]. By definition, SIRI indicates the equilibrium between systemic inflammation and host immune response by incorporating neutrophil, lymphocyte, and monocyte counts [10]. In the context of AIS, SIRI shows promise as a predictor of short-term functional outcomes, providing clinicians with important insights into patient prognosis to guide personalized treatment approaches [11–17]. Although individual studies have investigated the link between SIRI and AIS outcomes, the findings have been diverse, highlighting the need for a comprehensive review of existing evidence. Two prior meta-analyses have sought to investigate the link between SIRI and the functional outcome of patients who have had a stroke [18, 19]. However, these analyses were based on 6–7 studies with diverse patient groups and varying definitions of functional outcomes after a stroke, leading to challenges in interpreting the findings [18, 19]. Given that several relevant studies have been published since these meta-analyses [20–26], our aim in this study was to systematically assess the correlation between SIRI levels and functional outcomes in patients with AIS through an updated meta-analysis. Additionally, with a sufficient number of included studies, we also explored potential characteristics of the studies related to this association.

Materials and Methods

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (2020) [27, 28] were followed in this study. The Cochrane Handbook for Systematic Reviews of Interventions [29] was referenced throughout the study. This article is based on previously conducted studies and does not contain any new studies with human participants or animals performed by any of the authors.

Literature Analysis

Five main electronic databases including PubMed, Web of Science, Embase, Wanfang, and China National Knowledge Infrastructure (CNKI) were used for the literature search with a predefined combined search term: (“Systemic inflammation response index” OR “System inflammation response index” OR “Systemic inflammatory response index” OR “System inflammatory response index” OR “SIRI”) AND (“stroke” OR “transient ischemic stroke” OR “TIA” OR “cerebral infarction” OR “cerebrovascular infarction”). We incorporated the keyword “stroke” rather than “acute ischemic stroke” to broaden the search results, and because the search with the word “stroke” covered the results for “acute ischemic stroke.” This search strategy was also carried out to avoid missing studies which included patients with overall stroke, and reported subgroup data in patients with AIS. Only studies with human subjects published in English or Chinese were included. A second-round check-up for the references of the relevant articles was also conducted. The final database search was completed on February 9, 2024.

Inclusion and Exclusion Criteria

The inclusion criteria were determined according to the PICOS principle:

(1) P (patients): Patients with confirmed diagnosis of AIS, with no limitations of the main treatments.

(2) I (exposure): Total white blood cells, including absolute neutrophil count (ANC), absolute monocyte count (AMC), and absolute lymphocyte count (ALC), were collected from admission blood work, and the SIRI was measured at baseline according to the formula: SIRI = ANC × AMC/ALC. A high SIRI at admission was considered as the exposure. The cutoff for defining a high SIRI was consistent with the value used in the original studies.

(3) C (comparison): Patients with a low SIRI at baseline were considered as the controls.

(4) O (outcome): The primary outcome of the meta-analysis was the incidence of poor functional outcome during follow-up, defined as a modified Rankin Scale (mRS) score ≥ 3 [30], compared between patients with AIS having a higher versus a lower SIRI at admission.

(5) S (study design): Cohort studies, including the prospective and retrospective cohort studies, which were published as full-length articles in peer-reviewed journals.

We excluded reviews, meta-analyses, studies including patients with hemorrhagic stroke, those with SIRI analyzed as a continuous variable only, or studies that did not report the outcome of poor functional outcome. In cases where there was potential overlap in patient population across multiple studies, only the study with the largest sample size was included in this analysis.

Data Collection and Quality Assessment

Two authors conducted a thorough search of the academic literature, performed data collection and analysis, and independently assessed the quality of the studies. Any discrepancies that arose were resolved by discussion and consensus between the two authors. Data were gathered on study information, design, diagnosis of the patients, sample size, age, sex, main treatments, mean National Institutes of Health Stroke Scale (NIHSS) at baseline, diabetes and smoking status of the patients, methods for defining cutoffs of SIRI, values of SIRI cutoffs, follow-up duration, number of patients with AIS who developed poor functional outcome during follow-up, and variables adjusted in the regression model for studying the association between SIRI and functional outcome of patients with AIS. The NIHSS is a widely used impairment scale for evaluating stroke severity recommended by the National Stroke Foundation [31]. Study quality was assessed using the Newcastle–Ottawa Scale (NOS) [32], which evaluates criteria such as the participant selection process, group comparability, and outcome validity. The scale employs a rating system from 1 to 9 stars, with higher scores indicating better study quality.

Statistical Methods

The relationship between SIRI and functional outcomes in patients with AIS was assessed using odds ratios (OR) and 95% confidence intervals (CI), comparing those with higher versus lower baseline SIRI levels. ORs and their standard errors were derived from the 95% CIs or p-values and then logarithmically transformed to stabilize variance and achieve a normalized distribution [29]. The heterogeneity among studies was assessed using the Cochrane Q test and I2 statistic [33, 34], with I2 > 50% indicating significant statistical heterogeneity. A random-effects model was used for result aggregation considering the influence of clinical heterogeneity of the included studies (different treatments and cutoff for SIRI, etc.), even if the statistical heterogeneity was low [29]. The sensitivity analyses by omitting one study at a time were performed to evaluate the robustness of the findings. The influences of study characteristics as continuous variables on the outcome of the meta-analysis was evaluated with the univariate meta-regression analyses [29], which involved study characteristics such as sample size, mean age, percentage of men, severity of stoke at baseline as reflected by the mean NIHSS at admission, percentage of patients with diabetes, percentage of current smokers, and SIRI cutoff values. Additionally, multiple subgroup analyses were performed to evaluate the influence of study characteristics presented as categorical variables on the outcome, such as the differences in study design (prospective or retrospective cohorts), main treatments for AIS, and study quality scores with NOS [29]. To estimate publication bias, funnel plots were constructed and visually inspected for symmetry. This was followed by Egger’s regression test for further analysis [35]. These assessments were carried out using RevMan version 5.1 (Cochrane Collaboration, Oxford, UK) and Stata software version 17 (StataCorp LLC, College Station, TX). A p-value of less than 0.05 was considered statistically significant.

Results

Study Inclusion

The process for selecting relevant studies for the meta-analysis is outlined in Fig. 1. Initially, 493 potential records were identified through extensive searches across five databases. After removing 176 duplicates, titles and abstracts were screened, resulting in the exclusion of 286 studies that did not meet the meta-analysis criteria. The full texts of the remaining 31 records were independently reviewed by two authors, leading to the exclusion of an additional nine studies for various reasons specified in Fig. 1. Ultimately, 14 cohort studies [11–17, 20–26] were deemed suitable for the quantitative analyses.Fig. 1 Process of literature search and study identification

Overview of the Study Characteristics

Table 1 summarizes the characteristics of the included studies. No effort was made to contact the authors of the original studies because there were no missing baseline data in the included studies, as shown in Table 1. In total, the meta-analysis included 4062 patients with AIS from two prospective cohorts [14, 15] and 12 retrospective cohort studies [11–13, 16, 17, 20–26]. These studies, conducted in Italy, Korea, and China, were published between 2021 and 2024. All of the studies included adult populations with AIS. The mean patient age was 61–75 years. The mean NIHSS at admission was 3–19. The percentage of patients with diabetes was 12.5–44.8%, and the percentage of current smokers was 18.5–59.6%. The cutoffs of SIRI were determined using the receiver operating characteristic curve analysis in 11 studies [11–14, 16, 17, 20–23, 25], and using the medians of SIRI in three studies [15, 24, 26]. The cutoff values of SIRI for defining a high SIRI varied from 1.00 to 4.96 ×109/L. The follow-up duration was within the period of hospitalization for two studies [17, 25], 1 month for one study [13], and 3 months for the other 11 studies [11, 12, 14–16, 20–24, 26]. Accordingly, 1389 (34.2%) patients developed poor functional outcome within 3-month follow-up. Multivariate analyses were performed in all of the included studies, and variables such as age, sex, admission NIHSS, comorbidities, cardiovascular risk factors, and main treatments were adjusted to a varying extent among the included studies. The NOS scores of the included studies were seven to nine stars, suggesting overall moderate to good study quality (Table 2).Table 1 Characteristics of the included studies

Study	Design	Country	Sample size	Main treatment	Mean age (years)	Male (%)	Mean NIHSS at admission	DM (%)	Current smoking (%)	Methods for defining SIRI cutoff	Cutoff value of SIRI (109/L)	Follow-up duration	No. of patients with poor functional outcome	Variables adjusted	
Lattanzi 2021	RC	Italy	184	EVT	75	47.3	15.7	12.5	21.2	ROC curve analysis	3.8	3 months	110	Age, sex, history of hypertension, baseline NIHSS score, and ASPECTS	
Yi 2021	RC	Korea	440	MT	70	59.1	9.9	26.1	19.8	ROC curve analysis	2.9	3 months	195	Age, sex, baseline NIHSS score, ASPECTS, first-pass reperfusion, and successful recanalization	
Zhou 2022	PC	China	287	NR	61.6	69	3	35.9	59.6	Median	1.26	3 months	79	Age, sex, race, BMI, smoking, drinking, hypertension, diabetes, CAD, AF, PAD, LDL-C, FPG, Hcy, NIHSS score at admission	
Ma 2022	PC	China	63	IVT	66.2	41.3	10.8	NR	NR	ROC curve analysis	1.01	3 months	18	Age, sex, race, NIHSS at baseline, wallowing function score, SUA, blood lipids, and FPG	
Huang 2022	RC	China	50	NR	61	54	19	18	30	ROC curve analysis	4.96	1 month	38	Age, sex, BMI, and NIHSS at baseline	
Liu 2023	RC	China	272	NR	70	61.4	3	37.1	34.6	ROC curve analysis	1.17	3 months	76	Age, sex, BMI, NIHSS at baseline, diabetes, smoking, hypertension, and TG	
Guo 2023	RC	China	125	NR	65	64	3	44.8	35.2	ROC curve analysis	1.76	3 months	32	Age, sex, comorbidities, baseline NIHSS, blood lipids level, SCr, and main treatment	
Li 2023	RC	China	303	IVT	69	58.7	6	26.7	18.5	ROC curve analysis	1.59	3 months	69	Age, sex, AF, HF, baseline NIHSS, and TG	
Zhang 2023	RC	China	861	NR	63.4	64.1	3	28.5	34.5	ROC curve analysis	1.55	At discharge	194	Age, sex, NIHSS at admission, TG, smoking, hypertension, AF, diabetes, and IVT	
Ma 2023	RC	China	190	IVT	70.4	64.2	4	29.5	26.8	ROC curve analysis	1.29	3 months	28	Age, sex, random BG, admission NIHSS scores, smoking, drinking history, TOAST, and comorbidities	
Chen 2023	RC	China	161	IVT	64.7	69.5	9.5	36.6	43.5	ROC curve analysis	2.54	3 months	81	Age, sex, comorbidities, baseline NIHSS score, ASPECTS, and blood lipids level	
Huang 2023	RC	China	234	NR	69	50.4	5	22.6	35.9	ROC curve analysis	1.79	At discharge	97	Age, sex, NIHSS at admission, and CRP	
Shen 2023	RC	China	426	EVT	65	66.2	16	28.6	32.6	Median	2	3 months	274	Age, sex, NIHSS at admission, SBP at admission, CAD, and PSP	
Wang 2024	RC	China	466	IVT	65.5	62.4	4.7	29.8	39.1	Median	1	3 months	98	Age, sex, admission NIHSS, BG at admission	
DM diabetes mellitus, SIRI systemic inflammation response index, RC retrospective cohort, PC prospective cohort, NR not reported, EVT endovascular treatment, MT mechanical thrombectomy, IVT intravenous thrombolysis, ROC receiver operating characteristic, HF heart failure, BMI body mass index, SBP systolic blood pressure, CRP C-reactive protein, AF atrial fibrillation, SUA serum uric acids, LDL-C low-density lipoprotein cholesterol, CAD coronary artery disease, ASPECTS Alberta Stroke Program Early CT Score, NIHSS National Institutes of Health Stroke Scale, TOAST Trial of ORG 10172 in Acute Stroke Treatment, FPG fasting plasma glucose, BG blood glucose, TG triglyceride, PSP post-stroke pneumonia, PAD peripheral artery disease, Hcy homocysteine, SCr serum creatinine

Table 2 Study quality evaluation via the Newcastle–Ottawa Scale

Study	Representativeness of the exposed cohort	Selection of the non-exposed cohort	Ascertainment of exposure	Outcome not present at baseline	Control for age and sex	Control for other confounding factors	Assessment of outcome	Sufficiently long follow-up duration	Adequacy of follow-up of cohorts	Total	
Lattanzi 2021	1	1	1	1	1	1	1	1	1	9	
Yi 2021	0	1	1	1	1	1	1	1	1	8	
Zhou 2022	1	1	1	1	1	1	1	1	1	9	
Ma 2022	1	1	1	1	1	1	1	1	1	9	
Huang 2022	0	1	1	1	1	1	1	0	1	7	
Liu 2023	0	1	1	1	1	1	1	1	1	8	
Guo 2023	0	1	1	1	1	1	1	1	1	8	
Li 2023	1	1	1	1	1	1	1	1	1	9	
Zhang 2023	0	1	1	1	1	1	1	0	1	7	
Ma 2023	0	1	1	1	1	1	1	1	1	8	
Chen 2023	0	1	1	1	1	1	1	1	1	8	
Huang 2023	0	1	1	1	1	1	1	0	1	7	
Shen 2023	1	1	1	1	1	1	1	1	1	9	
Wang 2024	0	1	1	1	1	1	1	1	1	8	

Meta-analysis Results

The pooled results for 14 cohorts [11–17, 20–26] using a random-effects model showed that, compared to patients with a low SIRI at admission, those with a high SIRI had an increased risk of poor functional outcome within 3 months (OR: 1.57, 95% CI 1.39–1.78, p < 0.001; Fig. 2A) without significant statistical heterogeneity (p < 0.001; I2 = 0%). Sensitivity analysis by excluding one study at a time did not significantly change the results (OR: 1.55–1.60, p all < 0.05; Fig. 2B). Results of the meta-regression analysis suggested that the cutoff for defining a high SIRI was positively related to the OR for the association between SIRI and the risk of poor functional outcome (coefficient = 0.13, p = 0.03; Table 3 and Fig. 2C), while other variables such as sample size, mean age, NIHSS at admission, percentage of men, current smokers, or patients with diabetes did not significantly modify the results (p all > 0.05; Table 3). Finally, the results of the subgroup analyses showed consistent results in prospective and retrospective studies (p for subgroup difference = 0.94; Fig. 3A), in studies with different main treatments for AIS (p for subgroup difference = 0.13; Fig. 3B), and in studies with different quality scores (p for subgroup difference = 0.49; Fig. 3C).Fig. 2 Main results for the meta-analysis of the association between SIRI and short-term functional outcome of patients after AIS: A forest plots for the overall meta-analysis; B results of sensitivity analysis by excluding one study at a time; and C results of meta-regression analysis for the influence of SIRI cutoff on the association between SIRI and the risk of poor functional outcome

Table 3 Results of univariate meta-regression analysis

Variables	OR for the association between SIRI and poor functional outcome after stroke	
Coefficient	95% CI	P values	
Sample size	0.000034	−0.000718 to 0.000786	0.92	
Mean age (years)	−0.0057	−0.0492 to 0.0377	0.78	
Men (%)	−0.0046	−0.0240 to 0.0148	0.62	
NIHSS at baseline	0.018	−0.016 to 0.053	0.27	
Diabetes (%)	−0.0055	−0.0281 to 0.0171	0.61	
Current smokers (%)	−0.0022	−0.0161 to 0.0116	0.74	
Cutoff for SIRI (109/L)	0.13	0.02–0.24	0.03	
OR odds ratio, SIRI systemic inflammation response index, CI confidence interval; NIHSS National Institutes of Health Stroke Scale

Fig. 3 Forest plots for the subgroup analyses of the association between SIRI and short-term functional outcome in patients after AIS: A subgroup analysis according to study design; B subgroup analysis according to main treatment; and C subgroup analysis according to study quality scores

Publication Bias

The funnel plots for the meta-analysis of the association between SIRI and functional outcome of patients with AIS are shown in Fig. 4. The symmetrical nature of the funnel plots suggests a low possibility of publication bias. The results of Egger's regression test also showed a low risk of publication bias (p = 0.43).Fig. 4 Funnel plots for the publication bias underlying the meta-analysis of the association between SIRI and short-term functional outcome of patients after AIS

Discussion

In this research, we conducted an updated meta-analysis to comprehensively assess the correlation between SIRI and short-term functional outcomes in patients with AIS. By combining data from 14 cohort studies, our findings indicate that a high SIRI upon admission is linked to an increased likelihood of poor functional outcomes for patients with AIS. Notably, we observed a positive relationship between the cutoff value of SIRI used in each study and the odds ratio for association with poor functional outcome, which helps explain result variability. Furthermore, through multiple analyses including meta-regression, sensitivity, and subgroup assessments, we found consistent evidence indicating that the association between elevated SIRI at admission and poor functional outcome after AIS was not significantly influenced by individual study characteristics such as sample size or patient demographics. Overall, our results suggest that higher levels of systemic inflammation are connected to inferior short-term functional outcomes in patients with AIS. This conclusion aligns with growing insights into the role of systemic inflammation in stroke pathophysiology and its impact on neurological recovery processes triggered by ischemic brain injury [36, 37].

To our knowledge, only two meta-analyses have been conducted to assess the link between SIRI and functional outcome in patients who have had a stroke. One previous analysis involved seven cohort studies and indicated that SIRI might be a risk factor for poor functional outcomes after acute stroke [19]. However, this analysis included both patients who have had an AIS and patients who have had a hemorrhagic stroke, with varying definitions of poor functional outcomes leading to significant heterogeneity [19]. The other meta-analysis focused on six studies of patients with AIS, suggesting that a high SIRI could be associated with poorer functional outcomes [18]. Similar variations in defining poor functional outcomes were observed among these studies, and limited dataset availability prevented further exploration of heterogeneity sources [18]. Our meta-analysis presents several methodological improvements compared to previous studies. Firstly, we limited the study population to patients with AIS and focused on outcome mRS ≥ 3 to minimize potential differences in patient and outcome selection across studies. Additionally, we conducted an updated literature search using five commonly used electronic databases. This search yielded 14 cohort studies, seven of which were not included in previous meta-analyses. Furthermore, all included studies underwent multivariate analyses indicating that the relationship between a high SIRI and poor functional outcome in patients with AIS was likely independent of confounding factors such as age, sex, and NIHSS at admission. Lastly, multiple sensitivity analyses along with meta-regression and subgroup analyses were performed to assess the impact of various study characteristics on outcomes. These analyses revealed a positive correlation between the cutoff for defining a high SIRI and the OR for the association between SIRI and risk of poor functional outcome in patients with AIS, thus explaining much of the variance in the results.

The link between SIRI and AIS outcomes highlights the significance of considering systemic inflammation as a crucial factor in stroke severity and recovery. Previous research has demonstrated that elevated SIRI levels in patients with AIS were associated with an increased risk of early neurological deterioration [38, 39], stroke-related pneumonia [40, 41], and cognitive impairment [42]. These findings partly explain the connection between high SIRI levels and poor functional outcomes in these individuals. Furthermore, a recent study indicated that higher SIRI levels may adversely impact intracranial plaque vulnerability, leading to more severe ischemic events and their recurrence in patients with cerebral ischemia [43]. In addition, NIHSS at admission has been related to the 3-month functional outcome of patients after AIS [44]. The results of meta-regression analyses in our study suggested that NIHSS did not significantly affect the relationship between SIRI and poor functional outcome after AIS. These findings suggested that the association between SIRI and poor functional outcome after AIS was likely independent of baseline NIHSS. Our meta-analysis also underscores the potential use of SIRI as a prognostic biomarker for guiding treatment decisions and optimizing resource allocation in stroke care. Including SIRI in prognostic models may enhance risk stratification, allowing clinicians to identify high-risk individuals who may benefit from more aggressive therapeutic interventions or closer monitoring during the acute phase of stroke. Early identification of patients at increased risk of poor outcomes based on elevated SIRI levels could facilitate timely intervention strategies, such as targeted anti-inflammatory therapies or intensive rehabilitation programs, aimed at improving functional recovery and reducing disability burden.

However, several limitations should be considered when interpreting the results of our meta-analysis. Firstly, the protocol of the meta-analysis was not prospectively registered in PROSPERO. Secondly, the majority of studies were retrospective in nature, raising concerns about potential biases and confounding factors that were not adequately addressed. However, subgroup analysis showed similar results in prospective and retrospective studies, and in studies with different quality scores. Moreover, 12 of the included studies were from China, and the included studies exhibited heterogeneity in terms of patient comorbidities, cutoff for SIRI, and main treatments for AIS, which may have influenced the overall effect size and generalizability of our findings. In addition, although we found that the cutoff value for SIRI may significantly modify the association between SIRI and poor functional outcome after AIS, the optimal cutoff value for defining high SIRI levels in these patients remains to be determined for standardized criteria to ensure consistency and reproducibility in future research. Moreover, it is important to determine whether the association between SIRI and poor functional outcome was consistent in patients with different ischemic stroke subtypes. This is important because the pathophysiology, prognosis, and clinical features of ischemic small vessel strokes are different from other cerebral infarcts [45]. Also, it is important to know whether there is a relationship between the location of vascular cerebral topography and its impact on the SIRI after AIS. A previous study suggested that cerebral infarcts in the territory of the anterior cerebral artery have a better prognosis than infarcts in the territory of the middle cerebral artery [46]. Studies are warranted for further investigation into the potential influences of different locations and subtypes of cerebral infarcts on the association between SIRI and functional outcome after AIS. Finally, only SIRI at admission was considered. Further investigations into the dynamic changes in SIRI levels over time and their association with functional recovery trajectories could provide valuable insights into the temporal dynamics of inflammation in stroke evolution.

Future research on the SIRI and its relationship with the short-term functional outcomes in patients with AIS could explore several promising directions. One potential avenue is the investigation of the long-term prognostic value of SIRI, extending beyond short-term outcomes to understand its impact on recovery and recurrence of stroke over months or years. Additionally, integrating SIRI with other biomarkers and imaging techniques could provide a more comprehensive understanding of its role in stroke pathology and patient stratification. Another valuable direction would be examining the interplay between SIRI and various treatment modalities, such as thrombolysis or mechanical thrombectomy, to determine how systemic inflammation influences therapeutic efficacy and recovery. Furthermore, exploring the genetic and environmental factors that modulate SIRI levels in diverse populations could yield insights into personalized medicine approaches for stroke management. Lastly, interventional studies aiming to modulate SIRI through pharmacological or lifestyle interventions could assess the potential for improving stroke outcomes by targeting systemic inflammation directly.

Conclusions

In conclusion, our meta-analysis supports the notion that SIRI is a promising prognostic marker for short-term functional outcomes in patients with AIS. Despite the limitations inherent in the available evidence, our findings underscore the potential clinical utility of SIRI in risk stratification and personalized management of AIS. Further research is needed to refine our understanding of the role of systemic inflammation in stroke pathophysiology and to translate these insights into improved outcomes for patients who have had a stroke.

Acknowledgements

Medical Writing and Editorial Assistance

The authors did not use any medical writing or editorial assistance for this article.

Author Contribution

Ying Han and Nan Lin designed the study. Ying Han and Nan Lin performed the database search, study identification, study quality evaluation, and data collection. Ying Han and Nan Lin performed statistical analyses and interpreted the results. Ying Han drafted the manuscript. Nan Lin revised the manuscript. Ying Han and Nan Lin approved the submission.

Funding

No funding or sponsorship was received for this study or publication of this article. The Rapid Service Fee was funded by the authors.

Data Availability

The data supporting the findings of this study are available within the article.

Declarations

Conflict of Interest

Ying Han and Nan Lin have nothing to disclose.

Ethical Approval

This article is based on previously conducted studies and does not contain any new studies with human participants or animals performed by any of the authors.
==== Refs
References

1. Zhang R Liu H Pu L Zhao T Zhang S Han K Global burden of ischemic stroke in young adults in 204 countries and territories Neurology 2023 100 4 e422 e434 10.1212/WNL.0000000000201467 36307222
Zhang R, Liu H, Pu L, Zhao T, Zhang S, Han K, et al. Global burden of ischemic stroke in young adults in 204 countries and territories. Neurology. 2023;100(4):e422–34. 10.1212/WNL.0000000000201467.36307222 10.1212/WNL.0000000000201467
2. Tu WJ Zhao Z Yin P Cao L Zeng J Chen H Estimated burden of stroke in China in 2020 JAMA Netw Open 2023 6 3 e231455 10.1001/jamanetworkopen.2023.1455 36862407
Tu WJ, Zhao Z, Yin P, Cao L, Zeng J, Chen H, et al. Estimated burden of stroke in China in 2020. JAMA Netw Open. 2023;6(3): e231455. 10.1001/jamanetworkopen.2023.1455.36862407 10.1001/jamanetworkopen.2023.1455
3. Ding Q Liu S Yao Y Liu H Cai T Han L Global, regional, and National Burden of Ischemic Stroke, 1990–2019 Neurology 2022 98 3 e279 e290 10.1212/WNL.0000000000013115 34911748
Ding Q, Liu S, Yao Y, Liu H, Cai T, Han L. Global, regional, and National Burden of Ischemic Stroke, 1990–2019. Neurology. 2022;98(3):e279–90. 10.1212/WNL.0000000000013115.34911748 10.1212/WNL.0000000000013115
4. Global, regional, and national burden of stroke and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol. 2021;20(10):795–820. 10.1016/S1474-4422(21)00252-0.
5. Mosconi MG Paciaroni M Treatments in ischemic stroke: current and future Eur Neurol 2022 85 5 349 366 10.1159/000525822 35917794
Mosconi MG, Paciaroni M. Treatments in ischemic stroke: current and future. Eur Neurol. 2022;85(5):349–66. 10.1159/000525822.35917794 10.1159/000525822
6. Phipps MS Cronin CA Management of acute ischemic stroke BMJ 2020 368 l6983 10.1136/bmj.l6983 32054610
Phipps MS, Cronin CA. Management of acute ischemic stroke. BMJ. 2020;368: l6983. 10.1136/bmj.l6983.32054610 10.1136/bmj.l6983
7. DeLong JH Ohashi SN O'Connor KC Sansing LH Inflammatory responses after ischemic stroke Semin Immunopathol 2022 44 5 625 648 10.1007/s00281-022-00943-7 35767089
DeLong JH, Ohashi SN, O’Connor KC, Sansing LH. Inflammatory responses after ischemic stroke. Semin Immunopathol. 2022;44(5):625–48. 10.1007/s00281-022-00943-7.35767089 10.1007/s00281-022-00943-7
8. Zhou Q Su S You W Wang T Ren T Zhu L Systemic inflammation response index as a prognostic marker in cancer patients: a systematic review and meta-analysis of 38 cohorts Dose Response 2021 19 4 15593258211064744 10.1177/15593258211064744 34987341
Zhou Q, Su S, You W, Wang T, Ren T, Zhu L. Systemic inflammation response index as a prognostic marker in cancer patients: a systematic review and meta-analysis of 38 cohorts. Dose Response. 2021;19(4):15593258211064744. 10.1177/15593258211064744.34987341 10.1177/15593258211064744
9. Zhao S Dong S Qin Y Wang Y Zhang B Liu A Inflammation index SIRI is associated with increased all-cause and cardiovascular mortality among patients with hypertension Front Cardiovasc Med 2022 9 1066219 10.3389/fcvm.2022.1066219 36712259
Zhao S, Dong S, Qin Y, Wang Y, Zhang B, Liu A. Inflammation index SIRI is associated with increased all-cause and cardiovascular mortality among patients with hypertension. Front Cardiovasc Med. 2022;9:1066219. 10.3389/fcvm.2022.1066219.36712259 10.3389/fcvm.2022.1066219
10. Islam MM Satici MO Eroglu SE Unraveling the clinical significance and prognostic value of the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, systemic immune-inflammation index, systemic inflammation response index, and delta neutrophil index: An extensive literature review Turk J Emerg Med 2024 24 1 8 19 10.4103/tjem.tjem_198_23 38343523
Islam MM, Satici MO, Eroglu SE. Unraveling the clinical significance and prognostic value of the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, systemic immune-inflammation index, systemic inflammation response index, and delta neutrophil index: An extensive literature review. Turk J Emerg Med. 2024;24(1):8–19. 10.4103/tjem.tjem_198_23.38343523 10.4103/tjem.tjem_198_23
11. Lattanzi S Norata D Divani AA Di Napoli M Broggi S Rocchi C Systemic Inflammatory Response Index and Futile Recanalization in Patients with Ischemic Stroke Undergoing Endovascular Treatment Brain Sci 2021 10.3390/brainsci11091164 34573185
Lattanzi S, Norata D, Divani AA, Di Napoli M, Broggi S, Rocchi C, et al. Systemic Inflammatory Response Index and Futile Recanalization in Patients with Ischemic Stroke Undergoing Endovascular Treatment. Brain Sci. 2021. 10.3390/brainsci11091164.34573185 10.3390/brainsci11091164
12. Yi HJ Sung JH Lee DH Systemic inflammation response index and systemic immune-inflammation index are associated with clinical outcomes in patients treated with mechanical thrombectomy for large artery occlusion World Neurosurg 2021 153 e282 e289 10.1016/j.wneu.2021.06.113 34217857
Yi HJ, Sung JH, Lee DH. Systemic inflammation response index and systemic immune-inflammation index are associated with clinical outcomes in patients treated with mechanical thrombectomy for large artery occlusion. World Neurosurg. 2021;153:e282–9. 10.1016/j.wneu.2021.06.113.34217857 10.1016/j.wneu.2021.06.113
13. Huang BC Li L Zhang AW Sun J Fan MC Zhang X Prognostic value of pre-operation systemic inflammation response index in decompressive craniectomy for massive cerebral infarction caused by middle cerebral artery embolization Clin Med China 2022 38 5 441 447 10.3760/cma.j.cn101721-20220505-000160
Huang BC, Li L, Zhang AW, Sun J, Fan MC, Zhang X. Prognostic value of pre-operation systemic inflammation response index in decompressive craniectomy for massive cerebral infarction caused by middle cerebral artery embolization. Clin Med China. 2022;38(5):441–7. 10.3760/cma.j.cn101721-20220505-000160.10.3760/cma.j.cn101721-20220505-000160
14. Ma X Yang J Wang X Chai S The clinical value of systemic inflammatory response index and inflammatory prognosis index in predicting 3-month outcome in acute ischemic stroke patients with intravenous thrombolysis Int J Gen Med 2022 15 7907 7918 10.2147/IJGM.S384706 36314038
Ma X, Yang J, Wang X, Chai S. The clinical value of systemic inflammatory response index and inflammatory prognosis index in predicting 3-month outcome in acute ischemic stroke patients with intravenous thrombolysis. Int J Gen Med. 2022;15:7907–18. 10.2147/IJGM.S384706.36314038 10.2147/IJGM.S384706
15. Zhou Y Zhang Y Cui M Shang X Prognostic value of the systemic inflammation response index in patients with acute ischemic stroke Brain Behav 2022 12 6 e2619 10.1002/brb3.2619 35588444
Zhou Y, Zhang Y, Cui M, Shang X. Prognostic value of the systemic inflammation response index in patients with acute ischemic stroke. Brain Behav. 2022;12(6): e2619. 10.1002/brb3.2619.35588444 10.1002/brb3.2619
16. Chen YF Qi S Yu ZJ Li JT Qian TT Zeng Y Systemic inflammation response index predicts clinical outcomes in patients with acute ischemic stroke (AIS) after the treatment of intravenous thrombolysis Neurologist 2023 28 6 355 361 10.1097/NRL.0000000000000492 37027178
Chen YF, Qi S, Yu ZJ, Li JT, Qian TT, Zeng Y, et al. Systemic inflammation response index predicts clinical outcomes in patients with acute ischemic stroke (AIS) after the treatment of intravenous thrombolysis. Neurologist. 2023;28(6):355–61. 10.1097/NRL.0000000000000492.37027178 10.1097/NRL.0000000000000492
17. Huang L Increased systemic immune-inflammation index predicts disease severity and functional outcome in acute ischemic stroke patients Neurologist 2023 28 1 32 38 10.1097/NRL.0000000000000464 36125980
Huang L. Increased systemic immune-inflammation index predicts disease severity and functional outcome in acute ischemic stroke patients. Neurologist. 2023;28(1):32–8. 10.1097/NRL.0000000000000464.36125980 10.1097/NRL.0000000000000464
18. Han J Yang L Lou Z Zhu Y Association between systemic immune-inflammation index and systemic inflammation response index and outcomes of acute ischemic stroke: a systematic review and meta-analysis Ann Indian Acad Neurol 2023 26 5 655 662 10.4103/aian.aian_85_23 38022472
Han J, Yang L, Lou Z, Zhu Y. Association between systemic immune-inflammation index and systemic inflammation response index and outcomes of acute ischemic stroke: a systematic review and meta-analysis. Ann Indian Acad Neurol. 2023;26(5):655–62. 10.4103/aian.aian_85_23.38022472 10.4103/aian.aian_85_23
19. Huang YW Zhang Y Feng C An YH Li ZP Yin XS Systemic inflammation response index as a clinical outcome evaluating tool and prognostic indicator for hospitalized stroke patients: a systematic review and meta-analysis Eur J Med Res 2023 28 1 474 10.1186/s40001-023-01446-3 37915088
Huang YW, Zhang Y, Feng C, An YH, Li ZP, Yin XS. Systemic inflammation response index as a clinical outcome evaluating tool and prognostic indicator for hospitalized stroke patients: a systematic review and meta-analysis. Eur J Med Res. 2023;28(1):474. 10.1186/s40001-023-01446-3.37915088 10.1186/s40001-023-01446-3
20. Guo XN Wang QG Han BJ Tao TT Systemic inflammatory response index predicts early neurological deterioration and outcome in patients with branch atheromatous disease Int J Cerebrovasc Dis 2023 31 12 901 906 10.3760/cma.j.issn.1673-4165.2023.12.004
Guo XN, Wang QG, Han BJ, Tao TT. Systemic inflammatory response index predicts early neurological deterioration and outcome in patients with branch atheromatous disease. Int J Cerebrovasc Dis. 2023;31(12):901–6. 10.3760/cma.j.issn.1673-4165.2023.12.004.10.3760/cma.j.issn.1673-4165.2023.12.004
21. Li LL Chen ZB Lin YJ Cao J Chen XL Systemic inflammatory response index predicts outcomes after intravenous thrombolysis in patients with acute ischemic stroke Int J Cerbrovasc Dis 2023 30 5 321 326 10.3760/cma.j.issn.1673-4165.2022.05.001
Li LL, Chen ZB, Lin YJ, Cao J, Chen XL. Systemic inflammatory response index predicts outcomes after intravenous thrombolysis in patients with acute ischemic stroke. Int J Cerbrovasc Dis. 2023;30(5):321–6. 10.3760/cma.j.issn.1673-4165.2022.05.001.10.3760/cma.j.issn.1673-4165.2022.05.001
22. Liu HM Han Y Liu Y Jiang JX Inflammatory markers based on blood cell count predict functional outcomes in patients with acute ischemic stroke: construction and validation of a nomogram model Int J Cerebrovasc Dis 2023 31 10 728 735 10.3760/cma.j.issn.1673-4165.2023.10.002
Liu HM, Han Y, Liu Y, Jiang JX. Inflammatory markers based on blood cell count predict functional outcomes in patients with acute ischemic stroke: construction and validation of a nomogram model. Int J Cerebrovasc Dis. 2023;31(10):728–35. 10.3760/cma.j.issn.1673-4165.2023.10.002.10.3760/cma.j.issn.1673-4165.2023.10.002
23. Ma F Li L Xu L Wu J Zhang A Liao J The relationship between systemic inflammation index, systemic immune-inflammatory index, and inflammatory prognostic index and 90-day outcomes in acute ischemic stroke patients treated with intravenous thrombolysis J Neuroinflammation 2023 20 1 220 10.1186/s12974-023-02890-y 37777768
Ma F, Li L, Xu L, Wu J, Zhang A, Liao J, et al. The relationship between systemic inflammation index, systemic immune-inflammatory index, and inflammatory prognostic index and 90-day outcomes in acute ischemic stroke patients treated with intravenous thrombolysis. J Neuroinflammation. 2023;20(1):220. 10.1186/s12974-023-02890-y.37777768 10.1186/s12974-023-02890-y
24. Shen HX Sun W Wu X Song HQ Chen F Huang XQ Influence of inflammatory markers on predicting prognosis in patients with acute ischemic stroke after endovascular treatment Chin J Cerebrovasc Dis 2023 20 6 382 391 10.3969/j.issn.1672-5921.2023.06.004
Shen HX, Sun W, Wu X, Song HQ, Chen F, Huang XQ. Influence of inflammatory markers on predicting prognosis in patients with acute ischemic stroke after endovascular treatment. Chin J Cerebrovasc Dis. 2023;20(6):382–91. 10.3969/j.issn.1672-5921.2023.06.004.10.3969/j.issn.1672-5921.2023.06.004
25. Zhang YX Shen ZY Jia YC Guo X Guo XS Xing Y The association of the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio and systemic inflammation response index with short-term functional outcome in patients with acute ischemic stroke J Inflamm Res 2023 16 3619 3630 10.2147/JIR.S418106 37641703
Zhang YX, Shen ZY, Jia YC, Guo X, Guo XS, Xing Y, et al. The association of the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio and systemic inflammation response index with short-term functional outcome in patients with acute ischemic stroke. J Inflamm Res. 2023;16:3619–30. 10.2147/JIR.S418106.37641703 10.2147/JIR.S418106
26. Wang N Wang L Zhang M Deng B Wu T Correlations of 2 novel inflammation indexes with the risk for early neurological deterioration in acute ischemic stroke patients after intravenous thrombolytic therapy Neurologist 2024 10.1097/NRL.0000000000000557 38853723
Wang N, Wang L, Zhang M, Deng B, Wu T. Correlations of 2 novel inflammation indexes with the risk for early neurological deterioration in acute ischemic stroke patients after intravenous thrombolytic therapy. Neurologist. 2024. 10.1097/NRL.0000000000000557.38853723 10.1097/NRL.0000000000000557
27. Page MJ McKenzie JE Bossuyt PM Boutron I Hoffmann TC Mulrow CD The PRISMA 2020 statement: an updated guideline for reporting systematic reviews BMJ 2021 372 n71 10.1136/bmj.n71 33782057
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372: n71. 10.1136/bmj.n71.33782057 10.1136/bmj.n71
28. Page MJ Moher D Bossuyt PM Boutron I Hoffmann TC Mulrow CD PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews BMJ 2021 372 n160 10.1136/bmj.n160 33781993
Page MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 2021;372: n160. 10.1136/bmj.n160.33781993 10.1136/bmj.n160
29. Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page M, et al. Cochrane Handbook for Systematic Reviews of Interventions version 6.2. The Cochrane Collaboration. 2021;www.training.cochrane.org/handbook. Accessed 23 Mar 2024
30. Banks JL Marotta CA Outcomes validity and reliability of the modified Rankin scale: implications for stroke clinical trials: a literature review and synthesis Stroke 2007 38 3 1091 1096 10.1161/01.STR.0000258355.23810.c6 17272767
Banks JL, Marotta CA. Outcomes validity and reliability of the modified Rankin scale: implications for stroke clinical trials: a literature review and synthesis. Stroke. 2007;38(3):1091–6. 10.1161/01.STR.0000258355.23810.c6.17272767 10.1161/01.STR.0000258355.23810.c6
31. Kwah LK Diong J National Institutes of Health Stroke Scale (NIHSS) J Physiother 2014 60 1 61 10.1016/j.jphys.2013.12.012 24856948
Kwah LK, Diong J. National Institutes of Health Stroke Scale (NIHSS). J Physiother. 2014;60(1):61. 10.1016/j.jphys.2013.12.012.24856948 10.1016/j.jphys.2013.12.012
32. Wells GA, Shea B, O'Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. 2010;http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Accessed 23 Mar 2024
33. Higgins JP Thompson SG Quantifying heterogeneity in a meta-analysis Stat Med 2002 21 11 1539 1558 10.1002/sim.1186 12111919
Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21(11):1539–58. 10.1002/sim.1186.12111919 10.1002/sim.1186
34. Patsopoulos NA Evangelou E Ioannidis JP Sensitivity of between-study heterogeneity in meta-analysis: proposed metrics and empirical evaluation Int J Epidemiol 2008 37 5 1148 1157 10.1093/ije/dyn065 18424475
Patsopoulos NA, Evangelou E, Ioannidis JP. Sensitivity of between-study heterogeneity in meta-analysis: proposed metrics and empirical evaluation. Int J Epidemiol. 2008;37(5):1148–57. 10.1093/ije/dyn065.18424475 10.1093/ije/dyn065
35. Egger M Davey Smith G Schneider M Minder C Bias in meta-analysis detected by a simple, graphical test BMJ 1997 315 7109 629 634 10.1136/bmj.315.7109.629 9310563
Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.9310563 10.1136/bmj.315.7109.629
36. Simats A Liesz A Systemic inflammation after stroke: implications for post-stroke comorbidities EMBO Mol Med 2022 14 9 e16269 10.15252/emmm.202216269 35971650
Simats A, Liesz A. Systemic inflammation after stroke: implications for post-stroke comorbidities. EMBO Mol Med. 2022;14(9): e16269. 10.15252/emmm.202216269.35971650 10.15252/emmm.202216269
37. Anrather J Iadecola C Inflammation and stroke: an overview Neurotherapeutics 2016 13 4 661 670 10.1007/s13311-016-0483-x 27730544
Anrather J, Iadecola C. Inflammation and stroke: an overview. Neurotherapeutics. 2016;13(4):661–70. 10.1007/s13311-016-0483-x.27730544 10.1007/s13311-016-0483-x
38. Wang J Zhang X Tian J Li H Tang H Yang C Predictive values of systemic inflammatory responses index in early neurological deterioration in patients with acute ischemic stroke J Integr Neurosci 2022 21 3 94 10.31083/j.jin2103094 35633175
Wang J, Zhang X, Tian J, Li H, Tang H, Yang C. Predictive values of systemic inflammatory responses index in early neurological deterioration in patients with acute ischemic stroke. J Integr Neurosci. 2022;21(3):94. 10.31083/j.jin2103094.35633175 10.31083/j.jin2103094
39. Zhao J Dong L Hui S Lu F Xie Y Chang Y Prognostic values of prothrombin time and inflammation-related parameter in acute ischemic stroke patients after intravenous thrombolysis with rt-PA Clin Appl Thromb Hemost 2023 29 10760296231198042 10.1177/10760296231198042 37670481
Zhao J, Dong L, Hui S, Lu F, Xie Y, Chang Y, et al. Prognostic values of prothrombin time and inflammation-related parameter in acute ischemic stroke patients after intravenous thrombolysis with rt-PA. Clin Appl Thromb Hemost. 2023;29:10760296231198042. 10.1177/10760296231198042.37670481 10.1177/10760296231198042
40. Yan D Dai C Xu R Huang Q Ren W Predictive ability of systemic inflammation response index for the risk of pneumonia in patients with acute ischemic stroke Gerontology 2023 69 2 181 188 10.1159/000524759 35584610
Yan D, Dai C, Xu R, Huang Q, Ren W. Predictive ability of systemic inflammation response index for the risk of pneumonia in patients with acute ischemic stroke. Gerontology. 2023;69(2):181–8. 10.1159/000524759.35584610 10.1159/000524759
41. Li J Luo H Chen Y Wu B Han M Jia W Comparison of the predictive value of inflammatory biomarkers for the risk of stroke-associated pneumonia in patients with acute ischemic stroke Clin Interv Aging 2023 18 1477 1490 10.2147/CIA.S425393 37720840
Li J, Luo H, Chen Y, Wu B, Han M, Jia W, et al. Comparison of the predictive value of inflammatory biomarkers for the risk of stroke-associated pneumonia in patients with acute ischemic stroke. Clin Interv Aging. 2023;18:1477–90. 10.2147/CIA.S425393.37720840 10.2147/CIA.S425393
42. Chu M Luo Y Wang D Liu Z Niu H Wu X Prediction of poststroke cognitive impairment based on the systemic inflammatory response index Brain Behav 2024 14 1 e3372 10.1002/brb3.3372 38376025
Chu M, Luo Y, Wang D, Liu Z, Niu H, Wu X, et al. Prediction of poststroke cognitive impairment based on the systemic inflammatory response index. Brain Behav. 2024;14(1): e3372. 10.1002/brb3.3372.38376025 10.1002/brb3.3372
43. Wei X Cheng J Zhang L Xu R Zhang W Association of systemic inflammatory response index and plaque characteristics with the severity and recurrence of cerebral ischemic events J Stroke Cerebrovasc Dis 2024 33 3 107558 10.1016/j.jstrokecerebrovasdis.2024.107558 38262100
Wei X, Cheng J, Zhang L, Xu R, Zhang W. Association of systemic inflammatory response index and plaque characteristics with the severity and recurrence of cerebral ischemic events. J Stroke Cerebrovasc Dis. 2024;33(3): 107558. 10.1016/j.jstrokecerebrovasdis.2024.107558.38262100 10.1016/j.jstrokecerebrovasdis.2024.107558
44. Hendrix P Melamed I Collins M Lieberman N Sharma V Goren O NIHSS 24 h after mechanical thrombectomy predicts 90-day functional outcome Clin Neuroradiol 2022 32 2 401 406 10.1007/s00062-021-01068-4 34402916
Hendrix P, Melamed I, Collins M, Lieberman N, Sharma V, Goren O, et al. NIHSS 24 h after mechanical thrombectomy predicts 90-day functional outcome. Clin Neuroradiol. 2022;32(2):401–6. 10.1007/s00062-021-01068-4.34402916 10.1007/s00062-021-01068-4
45. Rudilosso S Rodriguez-Vazquez A Urra X Arboix A The potential impact of neuroimaging and translational research on the clinical management of lacunar stroke Int J Mol Sci 2022 10.3390/ijms23031497 35163423
Rudilosso S, Rodriguez-Vazquez A, Urra X, Arboix A. The potential impact of neuroimaging and translational research on the clinical management of lacunar stroke. Int J Mol Sci. 2022. 10.3390/ijms23031497.35163423 10.3390/ijms23031497
46. Arboix A Garcia-Eroles L Sellares N Raga A Oliveres M Massons J Infarction in the territory of the anterior cerebral artery: clinical study of 51 patients BMC Neurol 2009 9 30 10.1186/1471-2377-9-30 19589132
Arboix A, Garcia-Eroles L, Sellares N, Raga A, Oliveres M, Massons J. Infarction in the territory of the anterior cerebral artery: clinical study of 51 patients. BMC Neurol. 2009;9:30. 10.1186/1471-2377-9-30.19589132 10.1186/1471-2377-9-30
