Systemic inflammation response index as a clinical outcome evaluating tool and prognostic indicator for hospitalized stroke patients: a systematic review and meta-analysis

Background Stroke, which is the main element of cerebrovascular disease (CVD), has become the foremost reason for death and disability on a global scale. The systemic inflammation response index (SIRI), a newly developed and comprehensive indicator, has demonstrated promise in forecasting clinical results for diverse ailments. Nevertheless, the uncertainty surrounding the assessment and prediction of clinical outcomes for stroke patients by SIRI persists, and the conflicting findings from the limited studies conducted on this matter further complicate the situation. Consequently, we performed a thorough systematic review and meta-analysis to explore the correlation between SIRI and the clinical results in individuals suffering from stroke. Methods This research was registered in PROSPERO and carried out following the PRISMA guidelines. A thorough investigation was carried out on PubMed, Embase, the Cochrane Library, Web of Science, and Scopus databases. Furthermore, we conducted a manual search in Chinese databases, such as China national Knowledge Infrastructure (CNKI), WanFang, VIP, and China Biology Medicine (CBM). We assessed the potential for bias in the studies included by utilizing the Newcastle–Ottawa Scale (NOS) tool. Adverse clinical outcomes were the main focus of the study, with secondary endpoints including mortality, the predictive value of SIRI, SIRI values across various endpoints, and clinical parameters associated with subarachnoid hemorrhage (SAH) in relation to low and high SIRI group. Results Following rigorous evaluation, a grand total of 22 investigations, encompassing a populace of 12,737 individuals, were considered suitable for incorporation in the final analysis. The findings from our meta-analysis indicate a strong and consistent correlation between elevated SIRI levels and adverse functional outcomes, irrespective of the method used to evaluate unfavorable outcomes. Furthermore, increased SIRI values have a strong correlation with mortality rates in both the short and long term. Besides, SIRI is a useful indicator of the severity of SAH. SIRI demonstrates strong predictive ability in identifying unfavorable outcomes and stroke-related pneumonia (SAP), as higher SIRI values are typically linked to negative endpoints. Nevertheless, the meta-analysis indicated that there was no significant increase in the risk of early neurological deterioration (END) and acute hydrocephalus (AHC) in high SIRI group when comparing to low SIRI. Conclusion This study could potentially pave the way for groundbreaking insights into the relationship between SIRI and stroke patient outcomes, as it appears to be the first meta-analysis to explore this association. Given the critical role of the inflammatory response in stroke recovery, closely monitoring patients with high SIRI levels could represent a promising strategy for mitigating brain damage post-stroke. Thus, further investigation into SIRI and its impact on clinical outcomes is essential. While our initial findings offer valuable insights into this area, continued research is necessary to fully elucidate the potential of SIRI, ideally through dynamic monitoring and large-scale, multi-center studies. Ultimately, this research has the potential to inform clinical decision-making and improve patient outcomes following stroke. Systematic review registration: https://www.crd.york.ac.uk/prospero/; Identifier CRD42023405221. Supplementary Information The online version contains supplementary material available at 10.1186/s40001-023-01446-3.


Introduction
Studies in epidemiology have shown that the prevalence of cerebrovascular disease (CVD) has exceeded that of heart disease, emerging as the primary factor for death and impairment in the adult population [1,2].The occurrence of stroke is increasing as it is the main element of CVD.Accounting for 84.4% of all strokes, ischemic stroke (IS) is a prevalent sub-type [3].Hemorrhagic stroke (HS), a more severe sub-type, consists of intracerebral hemorrhage (ICH) and subarachnoid hemorrhage (SAH).ICH experiences an annual increase of 3.41 million cases [4], while SAH contributes to 5% of total stroke cases [5].Both IS and HS result in elevated mortality rates and prolonged disability [6][7][8].With the population getting older, there will be a substantial rise in the burden of stroke in the coming years.Hence, it is imperative to create a straightforward, user-friendly, economical indicator that can anticipate the likelihood of unfavorable results and offer supplementary details grounded in clear pathophysiological principles for subsequent treatment.Since blood routine tests are essential for every admitted patient, a new indicator that relies on the absolute values of blood cell counts demonstrates potential.
The SIRI, an innovative and comprehensive indicator, relies on the absolute counts of neutrophils, monocytes, and lymphocytes (N × M/L) in the peripheral blood as a measure.The body's inflammatory status can be more comprehensively reflected by these three blood cells, which represent distinct pathways of inflammation and immunity, as compared to peripheral blood cell ratios like neutrophil/lymphocyte ratio (NLR), lymphocyte/ monocyte ratio (LMR), and platelet/lymphocyte ratio (PLR) [9][10][11][12].Previous studies have extensively utilized SIRI to evaluate the regression of tumor patients and forecast unfavorable clinical treatment regression in pancreatic, gastric, and hepatocellular cancers [13].Moreover, research has indicated that SIRI additionally mirrors the extent of atherosclerosis and forecasts the medical results in individuals with ICH, SAH, and those receiving intravascular mechanical thrombectomy for large artery occlusive stroke [14][15][16].In patients with rheumatoid arthritis, there has been a connection between SIRI and the potential for developing acute ischemic stroke (AIS) [17].Nevertheless, despite certain research indicating that SIRI holds promise as a valuable instrument for diagnosing and forecasting results in individuals with stroke, its ability to anticipate functional outcomes in stroke patients is restricted, and the results are contradictory, leaving the connection between SIRI and clinical outcomes uncertain.Hence, we conducted a comprehensive review and meta-analysis to investigate the correlation between SIRI and the clinical results in individuals affected by stroke.

Search strategy
The systematic review and meta-analysis followed the PRISMA guidelines [18] and was registered on PROS-PERO with the identifier CRD42023405221 (https //www.crd.york.ac.uk/ PROSP ERO/) [19].Additional file 1: Table S1 contains the PRISMA checklist.PubMed was searched using the keywords ("Systemic inflammation response index" OR "System inflammation response index" OR "Systemic inflammatory response index" OR "SIRI") AND ("Patients").We used the identical search approach for Embase, Cochrane Library, Web of Science, and Scopus.Furthermore, we conducted a manual search in Chinese databases, such as China national Knowledge Infrastructure (CNKI), WanFang, VIP, and China Biology Medicine (CBM).To minimize selection bias, articles in both English and Chinese were taken into account during the search, which spanned from the beginning to February 12, 2023.Additional file 1: Table S2 presents the detailed search strategy.

Study selection
We included studies that satisfied the following PICO criteria: (1)  or Glasgow Outcome Score [GOS] at follow-up), mortality, predictive value of SIRI, SIRI values between poor and good outcomes, stroke-associated pneumonia (SAP) and non-SAP, early neurological deterioration (END) and non-END; SAH-associated clinical parameters between high SIRI and low SIRI, including Hunt-Hess Scale (HHS), modified Fisher Scale (mFS), delayed cerebral ischemia (DCI), vasospasm, and acute hydrocephalus (AHC).We did not include reviews, editorials, commentaries, case reports, letters to the editor, systematic reviews and meta-analyses, notes, replies, and conference abstracts because these types of records are insufficient for data.
Both reviewers (H Y-W and Z Y) individually examined the titles and abstracts of all the records that were obtained.Two reviewers independently assessed the relevant studies in their entirety and made decisions on article inclusion or exclusion according to the eligibility criteria.In case of discordance, the corresponding authors (L Z-P and Y X-S) would adjudicate.

Data extraction
Data were independently extracted into separate Excel spreadsheets by two reviewers, namely F C and A Y-H.To ensure accuracy, the source material and the spreadsheets were cross-checked with each other.Data collection included the first author's name, year of publication, country, study design, sample size, age, range, gender, stroke type, intervention type, SIRI cutoff (× 10 9 /L), primary and secondary endpoints, as well as the duration of follow-up.If any discrepancies were found, they were resolved by the corresponding author (L Z-P and Y X-S).

Study outcomes
The primary outcome of this study was the assessment of functional outcomes, as measured by the mRS or GOS at follow-up.The definition of mRS and GOS is presented in Additional file 1: Table S3.The secondary outcomes included mortality, the predictive value of SIRI, SIRI values between poor/good outcomes, the SAP/non-SAP, and END/non-END.Additionally, the study analyzed the differences in HHS, mFS, DCI, vasospasm, and AHC between patients with low SIRI and high SIRI.

Bias assessment
Two independent reviewers (H Y-W and F C) assessed the risk of bias of the included studies using the Newcastle-Ottawa Scale (NOS) tool [20] in a blind manner.The risk of bias summaries was then cross-checked, and any unresolved discrepancies were resolved by the corresponding author (LZ-P and YX-S).

Statistical analysis
We computed odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) for binary variables.Continuous variables were used to calculate the mean difference (MD) along with their corresponding 95% CIs.If there is a substantial difference in the values of continuous variables, we employed the standard mean difference (SMD) for conducting meta-analysis.We extracted ORs and their corresponding 95% CIs from studies that had adjusted for confounding factors.The mean and standard deviation (SD) were estimated by utilizing the sample size, median, and interquartile range.These estimates were obtained using the optional estimation techniques described in McGrath et al. 's publication [21], which can be accessed at https:// smcgr ath.shiny apps.io/ estme ansd/.To consider the variation in clinical characteristics, we performed meta-analyses and subgroup analyses utilizing the random-effects approach if the heterogeneity exceeds 50%, or the fixed-effects approach if the heterogeneity is less than 50% [22].When there were more than five studies included, subgroups analyses were conducted based on the sub-type stroke.Significant heterogeneity was assessed by conducting the Cochrane Q test (P < 0.1 or I 2 > 50%) [23].Statistical significance was determined using a significance level of P < 0.05.Funnel plots were utilized to evaluate publication bias.The statistical analyses were conducted using Review Manager software (version 5.3.3),which can be found at https:// train ing.cochr ane.org/ online-learn ing/ core-softw areco chrane-revie ws/ revman.

Functional outcomes assessed by the GOS or mRS
Two studies [15,38] reported functional outcomes assessed by GOS.The meta-analysis showed that individuals with high SIRI had a 3.17-fold higher risk of poor outcomes compared to those with low SIRI (odds ratio [OR] 3.17, 95% confidence interval [CI] 1.51-6.65,P = 0.002, I 2 = 0%, Fig. 2A), and the SIRI value was 0.72 higher in those with poor outcomes compared to those with good outcomes (standard mean difference [SMD] 0.72, 95%CI 0.47-0.97,P < 0.00001, I 2 = 42%, Fig. 2B).The predictive value of SIRI for poor outcome was 0.72 with a 95%CI of 0.63 to 0.82, P < 0.00001, and I 2 = 54% (Fig. 2C).After combining with clinical data, the predictive value for poor outcome was 0.88 with a 95%CI of 0.83 to 0.94, P < 0.0001, and I 2 = 55% (Fig. 2D), indicating that SIRI had a reasonably good predictive accuracy and a potential predictive ability.The results are summarized in Table 2.
The predictive value of SIRI for poor outcome was 0.72 with a 95% CI 0.69 to 0.76, P < 0.00001, and I 2 = 78% (Fig. 3D).The results are summarized in Table 2.In summary, despite the use of different assessment tools for poor outcome, it was consistently found that high SIRI was strongly associated with poor outcomes.In other words, there was a significant correlation between high SIRI and poor outcome.

SIRI and END after stroke
Two studies [26,36] provided data on END.The SIRI value of END was found to be 0.37 higher than that of non-END with a 95% CI of 0.34 to 0.40, P < 0.00001 and I 2 = 0% (Fig. 6A).However, the meta-analysis revealed that high SIRI did not significantly increase the risk of END compared to low SIRI (OR 1.78, 95% CI 0.95-3.34,P = 0.07, I 2 = 85%, Fig. 6B).The results are summarized in Table 2.

Analyses of subgroups based on sub-type of stroke
Subgroup analyses were conducted based on the subtype of stroke (IS and HS) for (i) the difference in SIRI values between the poor outcome group and the good outcome group, (ii) predicting poor outcome when SIRI was regarded as a continuous variable or dichotomous variable, and (iii) the predictive value of SIRI for poor outcome.Subgroup analysis demonstrated that the SIRI values were higher in the poor outcome group than in the good outcome group for both IS (SMD: 0.62; 95% CI 0.49-0.75,P < 0.00001, I 2 = 14%) and HS (SMD: 0.65; 95% CI 0.33-0.67,P < 0.00001, I 2 = 84%) (Fig. 8A).When SIRI was regarded as a continuous variable, subgroup analysis demonstrated that for each standard deviation increase in SIRI, the risk of poor outcome increased by 19% for IS (OR: 1.19; 95% CI 1.04-1.37,P = 0.01, and I 2 = 50%), whereas no statistically significant difference was found for HS (OR: 1.28; 95% CI 0.94-1.74,P = 0.12, and I 2 = 83%) (Fig. 8B).Similarly, when SIRI was regarded as a dichotomous variable, subgroup analysis demonstrated that the risk of a poor outcome at a high SIRI level was 3.73 times greater than that at a low SIRI level for IS (OR: 3.73; 95% CI 2.19-6.34,P < 0.00001, and I 2 = 74%) and 2.04 times greater for HS (OR: 2.04; 95% CI 1.50-2.77,P < 0.00001, I 2 = 0%) (Fig. 8C).Lastly, the predictive value of SIRI for poor outcomes was 0.72 for IS (AUC: 0.72; 95% CI 0.67-0.76)and 0.73 for HS (AUC: 0.73; 95% CI 0.67-0.80)(Fig. 8D).The results are summarized in Table 3.

Risk of bias assessment and publication bias assessment
The NOS has assessed and awarded a median of 8 stars to all the research, with an inter-quartile range of 5 to 9 stars.The methodological quality of the studies included can be found in Additional file 1: Table S4.Additionally, the probability of publication bias was evaluated through funnel plot results, which are displayed in Additional file 1: Figure S1.

Discussion
Secondary brain tissue damage after AIS [43,44] is attributed to the inflammatory reaction.Inflammatory cells of the immune system secrete different substances, such as cytokines, adhesion molecules, and chemokines, which worsen the harm to tissues.Earlier research has indicated that the inflammatory reaction can be promptly initiated following a stroke and is closely associated with unfavorable consequences [45][46][47].The investigation of biomarkers is focused on various inflammatory factors linked to stroke, which are emphasized by these mechanisms.
The importance of inflammation in the development of stroke has been confirmed by many research studies.In every step of atherosclerotic plaque development, inflammation plays a crucial role and leads to the occurrence of thrombotic events [48].The beginning of early plaque formation is marked by monocyte attachment to the vascular endothelium, movement into the arterial intima, and later transformation into foamy macrophages [49,50].The occurrence of stroke is frequently a result of the disturbance of atherosclerotic plaques, which is linked to the infiltration of monocyte/macrophage and T-cells [51].Furthermore, inflammation is crucial in the pathophysiological processes of brain damage.After ischemia, white blood cells escape from the bloodstream and enter the brain and meninges [52].The brain is harmed by neutrophils when they release enzymes like metalloproteases (MMP-9), cathepsin G, reactive oxygen and nitrogen compounds, and the inflammatory IL-1β [53].The arrival of monocyte-derived macrophages (MDMs) in the ischemic brain may play a vital role in controlling the immune reaction following a stroke [54,55].Additionally, stroke can activate systemic inflammation and neurohumoral pathways, leading to immune activation, immunodepression, and functional impairment of various peripheral organs [53,[55][56][57][58][59].Therefore, markers of inflammation might suggest the prognosis after a stroke.
The SIRI is an innovative and comprehensive indicator that relies on the absolute values of neutrophil, monocyte, and lymphocyte counts in the peripheral blood.During the initiation of stroke, the activation of peripheral circulating neutrophils occurs first, leading to the release of antimicrobial enzymes and chemical substances that worsen brain damage [60,61].In the initial phase of AIS, elevated neutrophil counts were linked to greater infarction size, suggesting that the rise in neutrophil levels may worsen blood-brain barrier damage by facilitating excessive matrix metalloproteinase-9 expression [62,63].Furthermore, following AIS, monocytes serve as another crucial category of inflammatory cells capable of infiltrating infarct locations and exacerbating cerebral harm [64][65][66].Contrary to neutrophils and monocytes, certain lymphocytes have a crucial function in controlling and diminishing local inflammation during the inflammatory response after AIS, thereby providing protection [67].Hence, a substantial SIRI (N↑ × M↑/L↓) can precisely indicate the adaptive immune response and inflammation response, which play a crucial role in the occurrence of stroke and hold potential as a reliable prognostic indicator.Furthermore, these three types of blood cells symbolize distinct pathways related to inflammation and immunity within the body, thereby offering a more holistic indication of the body's inflammatory condition.
Previous studies have demonstrated that the SIRI is an effective marker for assessing the clinical prognosis of various stroke types, including AIS, ICH, and SAH.Fei et al. [36] have shown that SIRI is closely correlated with the occurrence of END in basal ganglia ICH patients and has predictive value in improving the early identification and screening of END and patient outcomes.Wang et al. [26] have reported that SIRI can serve as a new predictor of END in a more objective and reliable manner, as well as a monitor of treatment response.However, our analysis indicates that high SIRI does not increase the risk of END compared with low SIRI.As only 2 studies have focused on the relationship between SIRI and END after stroke, further research is necessary and urgent.In another study, Lin et al. [35] investigated the association between SIRI and atrial fibrillation and found that elevated SIRI values are potential biomarkers of AF among IS patients.However, as there is limited research on the relationship between SIRI and cardiovascular disease, further exploration is warranted.Yu et al. [33] studied the relationship between SIRI and SAP and demonstrated that SIRI at admission can be used as a prognostic inflammatory biomarker in ICH patients with SAP.Yan et al. [32] also reported that SIRI has a good predictive value for SAP, and stroke patients with high SIRI levels (≥ 2.74) should be aware of the risk of SAP.Our analysis showed that although there was no dose-response relationship between SIRI and SAP, high SIRI had a 2.89-fold risk for SAP compared with low SIRI.
As we are aware, SIRI has emerged as a promising prognostic indicator for stroke patients.However, it is essential to consider potential confounding factors that may affect SIRI values, such as infections that develop or coexist with stroke, especially in the elderly population who are susceptible to aspiration pneumonia and urine infections.Moreover, the ongoing COVID-19 pandemic has further complicated the situation, as almost all stroke patients have a compromised and diminished immune system, which could interfere with blood cell count and, consequently, affect SIRI values.Therefore, it is imperative to accurately document comorbidities, including infections and COVID-19 infection status, and pay closer attention to the basic conditions of elderly patients to make appropriate adjustments in data analysis.Future investigations should also consider the influence of stroke patients' histories of infection to obtain a more comprehensive understanding of SIRI as a prognostic marker for stroke outcomes.Overall, a more in-depth investigation into the relationship between SIRI, infection, and stroke outcomes, taking into account potential confounding factors, could provide more valuable insights for improving stroke management and patient outcomes.
To our knowledge, this is the first systematic review and meta-analysis to investigate the association between SIRI and clinical outcomes in stroke patients.Our analysis demonstrated that high SIRI values were associated with poor outcomes regardless of the assessment tools used.Furthermore, high SIRI values were related to both short-term and long-term mortality and could indicate the severity of SAH.In other words, higher SIRI values indicated more severe SAH.In places where CT scans are not available and medical conditions are poor, this simple index may play an important role in predicting the severity of SAH and stratifying patients.The predictive value of SIRI for poor outcomes and SAP was relatively high, with adverse endpoints typically having higher SIRI values.

Limitations
While our study provides important insights into the association between SIRI and stroke patient outcomes, it is important to acknowledge several limitations.Firstly, due to the nature of inflammation response in stroke, most of the existing literature on this topic comprises retrospective studies, which may introduce limitations in terms of sample size, confounding variables, and selection bias.Secondly, with the exception of four prospective studies, the majority of studies included in our analysis were retrospective, resulting in considerable heterogeneity in data reporting and follow-up protocols.Therefore, further high-quality prospective studies are needed to confirm the validity and generalizability of our findings.Thirdly, based on our systematic review, the majority of included studies (86%, 19 out of 22 studies) were carried out in China, with two studies from the MIMIC database.As we know, the MIMIC database was established by the Beth Israel Deaconess Medical Center (Boston, MA, USA), and the population consisted mainly of US citizens.Therefore, these two studies reflected the relationship between SIRI and clinical outcomes in Americans.But the existing literature still lacks related studies in Europe or Africa.The broader applicability of SIRI as a predictive tool for stroke outcomes should be identified further in other ethnicities and countries.Fourthly, the high heterogeneity observed in some of our endpoints could influence the robustness of our results.Fifthly, some results are not mirrored to the total population of our studies selected, for each variable evaluated a different lesser number of studies were included.Hence, some findings are less robust.Despite these limitations, our meta-analysis provides valuable preliminary findings that could assist clinicians in making informed treatment decisions for stroke patients.Future research should aim to address these limitations and provide further insights into the association between SIRI and stroke outcomes.

Conclusion
This study could potentially pave the way for groundbreaking insights into the relationship between SIRI and stroke patient outcomes, as it appears to be the first meta-analysis to explore this association.Given the critical role of the inflammatory response in stroke recovery, closely monitoring patients with high SIRI levels could represent a promising strategy for mitigating brain damage post-stroke.Thus, further investigation into SIRI and its impact on clinical outcomes is essential.While our initial findings offer valuable insights into this area, continued research is necessary to fully elucidate the potential of SIRI, ideally through dynamic monitoring and large-scale, multi-center studies.Ultimately, this research has the potential to inform clinical decision-making and improve patient outcomes following stroke.

Fig. 2
Fig. 2 The relationship of SIRI and functional outcomes (assessed by GOS).A SIRI for predicting poor outcome; B The difference of SIRI values between poor outcome and good outcome; C The predictive value of SIRI for poor outcome; D The predictive value of SIRI combined with clinical data for poor outcome

Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8
Fig. 3 The relationship of SIRI and functional outcomes (assessed by mRS).A The difference of SIRI values between poor outcome and good outcome; B SIRI for predicting poor outcome (continuous); C SIRI for predicting poor outcome (dichotomous); D The predictive value of SIRI for poor outcome (2)ulation: individuals who have experienced a stroke, including IS and HS (ICH and SAH);(2)

Table 1
The baseline characteristics of included studies

Table 2
Meta-analysis of different outcomes

Table 3
Subgroup analyses based on sub-type of stroke * represents the data are expressed as OR § represents the data are expressed as SMD ※ represents the data are expressed as AUC