The Role of the Systemic Immune Inflammation Index (SII) as an Indicator of the Hospital Admission Rate among Pediatric Patients with Acute Exacerbation of Asthma: A Retrospective Cohort Study

The Role of the Systemic Immune Inflammation Index (SII) as an Indicator of the Hospital Admission Rate among Pediatric Patients with Acute Exacerbation of Asthma: A Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Role of the Systemic Immune Inflammation Index (SII) as an Indicator of the Hospital Admission Rate among Pediatric Patients with Acute Exacerbation of Asthma: A Retrospective Cohort Study Ahmed Sobhi, Baha Aldeen Alshareif, Ahmed Ghoname, Abdulelah Bisher Yakti, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7023956/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background: Asthma is the most common chronic condition among children; it typically involves emergency room visits and stays in hospitals during severe recurrence. Derived from neutrophil, lymphocyte, and platelet counts, the systemic immune inflammation index (SII) may also indicate systemic inflammation and predict clinical outcomes. Objective: This study sought to investigate the correlation between the SII and hospital admissions in children experiencing acute asthma exacerbations and to assess the predictive value of the SII with respect to other hematological indicators over the course of the study. Methods: A total of 172 children (≤14 years) presenting with asthma exacerbations from 2018--2024 were included in a retrospective cohort study at Saudi German Hospital, Medina. Within twenty-four hours of emergency presentation, the SII was computed via CBC data. Assessments of relationships with hospital admission used logistic and Poisson regression methods. Results: With respect to the SII values (2,162 vs. 1,095), admitted patients had noticeably higher values (p < 0.001). For predicting admission, ROC analysis revealed an SII cut-off of 735 (sensitivity 72%, specificity 62%). Independent of age, sex, and BMI, a high SII was associated with doubled admission rates (IRR = 2.22, p = 0.001) and a greater likelihood of hospitalisation (OR = 4.78, 95% CI: 2.47–9.57, p <0.001). Conclusion: In paediatric asthma exacerbations, an elevated SII is an independent predictor of hospital admission; hence, it is valuable for early risk assessment and therapy choices. Asthma Children Hospital admission Systemic immune-inflammation index (SII) Biomarkers Figures Figure 1 Background Asthma is a chronic inflammatory condition of the airways characterised by fluctuating airflow restriction, heightened airway reactivity, and respiratory symptoms, including wheezing, coughing, chest tightness, and dyspnoea. Affecting more than 5–10% of children worldwide, asthma is among the most common chronic conditions in paediatric populations. Although suitable medication and preventative actions help to effectively control asthma, acute exacerbations remain a major source of morbidity and death, especially in children with either poorly controlled or severe disease [1,2]. Asthma exacerbation pathogenesis involves complicated combinations of immune-mediated inflammation, environmental stimuli, and genetic predispositions.Airway inflammation becomes more noticeable during exacerbations, which causes bronchoconstriction, mucus hypersecretion, and airway edema that ultimately results in airflow limitation and respiratory compromise [3]. From mild episodes controlled in the outpatient environment to severe exacerbations requiring hospitalisation and critical care assistance, the degree of asthma aggravation can vary greatly. The ability to maximise clinical decision-making and enhance patient outcomes depends on the identification of biomarkers able to predict the risk of severe exacerbations and the need for hospital admission [4]. Researchers have now started looking at several markers to gauge the degree of asthma severity and predict the likelihood of an exacerbation [5]. Although conventional measures, including pulmonary function tests, fractional exhaled nitric oxide (FeNO), and blood eosinophil counts, are helpful in particular situations, these tests cannot exactly reflect the systemic inflammatory response associated with asthma episodes. Reflecting the balance between pro- and anti-inflammatory processes, the SII—calculated as the platelet count × neutrophil count/lymphocyte count—offers a composite estimate of systemic inflammation and the immune state [6]. In many inflammatory disorders, including cardiovascular diseases, cancers, and infectious diseases, elevated SII values have been linked to poor prognosis and adverse events [7, 8,9]. There has been limited research on the role that the SII plays in predicting hospital admission rates for paediatric children experiencing an acute asthma attack. This is true even if the SII is relevant in revealing immune dysregulation and systemic inflammation in asthma. Knowing the link between the degree of asthma exacerbation (SII) and the likelihood of hospitalisation could help doctors identify high-risk patients early in the course of the disease and provide an important understanding of the pathophysiology of severe asthma exacerbations [3]. The objective of this retrospective cohort study was to assess the predictive power of the SII for hospital admission rates in paediatric patients who experienced acute asthma exacerbation. The findings of this study will affect therapeutic management, risk classification, and the distribution of medical resources. Objectives 1. To conduct a retrospective analysis of the correlation between the Systemic Immune Inflammation Index and hospital admissions in paediatric patients experiencing acute asthma exacerbations. 2. To assess the correlation between the SII and the probability of hospital admission in paediatric patients experiencing acute asthma exacerbation. 3. To evaluate the predictive significance of the SII in relation to other hematological indices (such as the NLR and PLR) for predicting disease severity and hospitalisation. 4. To investigate the efficacy of the SII as a mechanism for risk assessment and tailored management approaches in paediatric asthma exacerbations. Methods Study Design and Setting: This retrospective cohort study was performed at the Emergency and Pediatric Departments of Saudi German Hospital, Medina, a tertiary care facility in Saudi Arabia. The trial duration extended from January 1, 2018, until February 29, 2024. Study population: Eligible participants were paediatric patients who experienced acute aggravation of asthma during the research period, as determined by electronic health records. Inclusion criteria: Children aged 14 years or younger. Clinical diagnosis of acute asthma exacerbation at presentation. A complete blood count (CBC) was performed within the first 24 hours of presentation to the emergency department (ED). Exclusion criteria: Presence of concurrent infections or other inflammatory diseases. The diagnosis of hematological disorders or the use of immunosuppressive therapy could influence inflammatory indices. Incomplete or missing medical records. Calculation of the systemic immune inflammation index (SII): The SII was calculated via the following formula: SII = (platelet count × neutrophil count)/lymphocyte count. Values identified from CBC were obtained from the first laboratory assessment 24 hours following ED presentation. Analysed as a continuous variable, the SII was then dichotomised on the basis of the ideal threshold found via ROC curve analysis. Sample size determination: The sample size estimation was based on the following assumption: Anticipated odds ratio for hospital admission associated with an elevated SII: 1.5 Level of significance (α): 0.05 (two-tailed) Statistical power (1–β): 80% Estimated prevalence of hospital admission: 30% By applying a standard logistic regression sample size computation formula, the minimum needed sample size was approximated to be over 200 cases. There were ultimately 172 paediatric patients included, which, although somewhat below the target, still provided enough statistical power for the main analyses. Data collection and variables: The following variables were extracted from the electronic health records: Laboratory parameters: Absolute counts of neutrophils, lymphocytes, and platelets, as well as the derived SII. Clinical outcome: Hospital admission status (admitted vs. not admitted) following ED presentation. Additional variables: Age, sex, body mass index (BMI), Pediatric Respiratory Assessment (PRAM) score, medication adherence, history of previous admissions, and C-reactive protein (CRP) levels. Statistical analysis: Baseline characteristics were compiled via descriptive statistics; continuous variables, means and standard deviations; and categorical variables, frequencies and percentages. For continuous variables, group comparisons were performed with the Wilcoxon rank-sum test; for categorical variables, Pearson's chi-square test or Fisher's exact test was used. The ideal SII threshold for hospital admission prediction was determined via receiver operating characteristic (ROC) curve analysis. After adjustment for possible confounders (age, sex, BMI), multivariate logistic regression was used to evaluate the relationship between increased SII and hospital admission. Poisson regression was also used to project incidence rate ratios (IRRs) for admission rates among high-SII patients. A p value < 0.05 was considered statistically significant. All the statistical analyses were performed via R software, version 4.4.3 (R software: fundamentals of programming and statistical analysis. (Statistics and Computing) [10]. Results This study investigated the role of the systemic immune inflammatory index (SII) in predicting hospital admission rates among pediatric patients with acute asthma exacerbations. Key findings from the demographic and clinical characteristics (Table 1) revealed that admitted patients had significantly higher total admission counts due to asthma (2.80 vs. 0.71, p <0.001), poorer medication adherence (37% vs. 74%, *p*<0.001), and higher PRAM scores (9.19 vs. 5.42, p <0.001). Age, sex, and BMI did not differ significantly between the admitted and nonadmitted groups (Table 1). The laboratory results (Table 2) highlighted significant inflammatory differences: admitted patients presented elevated total white blood cells (12.3 vs. 9.7 ×10³/μL), neutrophils (8.9 vs. 5.3 ×10³/μL), and neutrophil‒lymphocyte ratios (6.7 vs. 2.9, p <0.001). Additionally, the SII was markedly greater in admitted patients (2,162 vs. 1,095, p <0.001), as were the levels of CRP (14 vs. 4 mg/L) and liver enzymes (Table 2). The ROC curve revealed an SII threshold of 735 (sensitivity 72%, specificity 62%) for predicting admission (Figure 1). Regression analyses reinforced the predictive value of the SII. Logistic regression revealed a high SII (>735) with approximately fivefold increased odds of admission (OR = 4.78, 95% CI: 2.47–9.57, p <0.001), independent of age, sex, or BMI (Table 3). Similarly, Poisson regression demonstrated that a high SII doubled admission rates (IRR = 2.22, 95% CI: 1.39–3.68, p = 0.001) (Table 4). In summary, the SII is an independent predictor of hospitalisation in pediatric asthma exacerbations, reflecting systemic inflammation. However, while the SII alone has moderate accuracy, its integration with clinical factors such as prior admissions, medication adherence, and PRAM scores could enhance risk stratification. Table 1: Demographic and clinical characteristics of the study groups Characteristic Overall N = 172 1 Not admitted N = 86 1 Admitted N = 86 1 p value 2 Age 5.26 ± 3.12 5.43 ± 3.44 5.09 ± 2.77 >0.9 Gender 0.7 Male 118 (69%) 58 (67%) 60 (70%) Female 54 (31%) 28 (33%) 26 (30%) BMI 17.10 ± 3.29 17.38 ± 3.34 16.81 ± 3.23 0.3 Admitted to PICU 48 (56%) 0 (NA%) 48 (56%) >0.9 Length of admission 3.71 ± 1.69 NA ± NA 3.71 ± 1.69 Total admission count due to asthma 1.76 ± 1.95 0.71 ± 0.84 2.80 ± 2.18 <0.001 Other allergies 61 (35%) 31 (36%) 30 (35%) 0.9 adherent to medications 96 (56%) 64 (74%) 32 (37%) <0.001 PRAM score (ON PRESENTATION) 7.30 ± 2.29 5.42 ± 1.00 9.19 ± 1.53 <0.001 1 Mean ± SD; n (%) 2 Wilcoxon rank sum test; Pearson's Chi-squared test; Fisher's exact test Table 2: Summary of laboratory results among the study groups Characteristic Overall N = 172 1 Not admitted N = 86 1 Admitted N = 86 1 p value 2 Total WBCs 11.0 ± 4.8 9.7 ± 4.2 12.3 ± 5.1 <0.001 Neutrophils count 7.1 ± 4.9 5.3 ± 3.9 8.9 ± 5.1 <0.001 Lymphocytes count 2.80 ± 2.12 3.34 ± 2.49 2.27 ± 1.49 <0.001 Monocyte count 0.71 ± 0.59 0.68 ± 0.36 0.73 ± 0.76 0.8 Eosinophils count 0.27 ± 0.43 0.30 ± 0.48 0.24 ± 0.38 0.2 Neutrophils/Lymphocyte 4.8 ± 5.8 2.9 ± 3.9 6.7 ± 6.6 <0.001 Monocyte/Lymphocytes 0.32 ± 0.24 0.28 ± 0.19 0.37 ± 0.28 0.003 Platelet count 332 ± 85 339 ± 81 326 ± 88 0.2 Systemic Immune Inflammation index (SII) 1,629 ± 2,013 1,095 ± 1,537 2,162 ± 2,283 <0.001 Hemoglobin 13.00 ± 2.16 12.69 ± 1.14 13.32 ± 2.80 0.077 CRP 9 ± 14 4 ± 5 14 ± 18 <0.001 AST 22 ± 11 19 ± 11 25 ± 10 <0.001 ALT 22 ± 11 26 ± 11 19 ± 9 735) Characteristic OR 95% CI p value SII Low SII — — High SII 4.78 2.47, 9.57 <0.001 Age 0.94 0.84, 1.05 0.3 Gender Male — — Female 1.08 0.53, 2.22 0.8 BMI 0.96 0.86, 1.06 0.4 Abbreviations: CI = Confidence Interval, OR = Odds Ratio Table 4: Poisson regression for predicting the RR at admission among patients with high SII va lues (> 735) Characteristic IRR 95% CI p value SII Low SII — — High SII 2.22 1.39, 3.68 0.001 Age 0.97 0.90, 1.05 0.5 Gender Male — — Female 1.03 0.63, 1.63 >0.9 BMI 0.98 0.91, 1.05 0.6 Abbreviations: CI = Confidence Interval, IRR = Incidence Rate Ratio Discussion The systemic immune-inflammation index (SII) was assessed in this retrospective cohort study as a predictor of hospital admission in young patients with acute asthma exacerbations. Our results revealed a strong, independent correlation between an increased SII and increased hospital admission rates, highlighting the clinical value of the SII as a biomarker for disease severity and systemic inflammation in this population. Children hospitalised for asthma exacerbations had significantly elevated SII values compared with those observed during outpatient care (2,162 vs. 1,095; p < 0.001). Regardless of age, sex, and BMI, an elevated SII was associated with a nearly fivefold increase in hospitalisation risk (OR = 4.78, 95% CI: 2.47–9.57). An SII threshold of 735 had a sensitivity of 72% and specificity of 62% for predicting admission. These results are in line with new data showing that the SII, which combines neutrophil, lymphocyte, and platelet counts, is a strong indicator of systemic inflammation and immunological activation in children with asthma [12,16]. The clinical significance of the SII in juvenile respiratory disorders is corroborated by an expanding body of research. A study conducted in 2025 demonstrated that children experiencing acute asthma episodes exhibit significantly elevated SII values compared with healthy controls and that increased SII values correlate with poorer short-term prognosis; furthermore, underlining its sensitivity to systemic inflammatory responses in respiratory diseases, a recent study by Wang S et al. (2024) confirmed the SII as a predictive marker in paediatric pneumonia [12, 17]. Additionally, a study conducted in 2024 highlighted the important role of the SII in the risk assessment of paediatric asthma, particularly in people under 20 years of age, by demonstrating a robust linear correlation between the SII and asthma persistence [15]. Although traditional biomarkers such as the CRP level and NLR have been used for evaluating inflammation, our findings indicate that the SII has superior predictive capability for hospital admission. Even though hospitalised patients had substantially higher CRP levels and NLRs, after adjusting for confounding variables, only the SII remained the main predictor. Recent studies have shown that composite indicators such as the SII and NLR outperform single markers in both paediatric and adult asthma patients and COPD patients in terms of exacerbation severity [11,12]. SII strength resides in its unique ability to regulate both innate (neutrophils, platelets) and adaptive (lymphocytes) immune responses, providing a more thorough representation of the immunologic dysregulation typical of acute asthma exacerbations [12]. This comprehensive approach might explain why the SII exceeds isolated markers such as CRP, which are more reactive and less specific to the fundamental immune system. Our results also support a multidimensional strategy for risk stratification that combines the SII with clinical severity scores (e.g., PRAM), patient history, and medication adherence. An increased likelihood of hospitalisation was independently linked with higher PRAM scores, a history of several past admissions, and poor medication adherence, confirming recognised predictors of poor asthma outcomes [13,14]. Combining the SII with these clinical criteria should enable the identification of high-risk populations that may benefit from early, forceful intervention. Children with both high SII and high PRAM scores, for example, may be particularly vulnerable to clinical deterioration, which justifies a quick increase in treatment. This method fits present trends in precision medicine, which stresses the need to use biomarker data in customised treatment plans [14]. Limitations: Numerous limitations must be recognised. First, the retroactive design introduces possible confusing elements that could not be completely under control: the effect of past corticosteroid use or concurrent infections on haematologic indices. Second, the SII does not discriminate between eosinophilic and neutrophilic asthma phenotypes, so the clinical consequences may differ. Third, the study was carried out at a single center, which may restrict the generalizability of the findings. Ultimately, even if the SII has great predictive power for hospital admission, its value in predicting other outcomes, such as recurrence or long-term control, is yet unknown [15]. Conclusion This study offers convincing evidence that, in paediatric patients with acute asthma attacks, the systemic immune inflammation index is a powerful, independent predictor of hospital admission. When paired with clinical criteria, the SII improves risk categorisation and supports tailored treatment over traditional inflammatory indicators. Prospective multicenter investigations are justified to confirm these conclusions and define the function of the SII in more general asthma management strategies. Declarations Ethical approval and consent to participate This research was approved by the Institutional Review Board (IRB) of Saudi German Hospital, Medina (IRB log No: 24-037). The Institutional Review Board waived the requirement for informed permission because of the retrospective design of the study and the utilisation of anonymized patient data. All methods involving human subjects adhered to the ethical norms established by the institutional and national research committees, as well as the 1964 Helsinki Declaration and its subsequent revisions or equivalent ethical guidelines. Consent for publication Not applicable. Availability of data and materials All the data generated or analysed during this study are included in this published article and in the supplementary information files. Competing interest The authors declare that they have no competing interests. Funding Not applicable. Author contributions Conceptualisation, visualisation, validation and methodology, A.S. and B.A.; software and investigation, A.G., A.B.Y. and A.I.; resources and curation, F.M.M. and K.A.Q.; writing original draft, A.M.B., A.E. and R.A.E.; project administration, A.S.; supervision, B.A.; All the authors have read and approved the final manuscript. Acknowledgements Not applicable. Clinical trial number Not applicable. References Fleming M, et al. Educational and health outcomes of children treated for asthma: Scotland-wide record linkage study of 683 716 children. Eur Respir J. 2019;54(3):1802309. 10.1183/13993003.02309–2018 . Asher MI, Montefort S, Björkstén B, Lai CK, Strachan DP, Weiland SK, Williams H, ISAAC Phase Three Study Group. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7023956","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":503214409,"identity":"bf3f08b6-125e-44e2-b2f9-2d1c9f676c79","order_by":0,"name":"Ahmed Sobhi","email":"","orcid":"","institution":"Cairo University","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"","lastName":"Sobhi","suffix":""},{"id":503214413,"identity":"151c5132-9206-47d9-b100-e58eff68dfb7","order_by":1,"name":"Baha Aldeen Alshareif","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYBACAwYeIFnADOElMNgAScbGA4S1GMC1pIG0NJCghYHhMJjEq8Wc/ezBDz8MrOX4pZsff3jw57zd2vbDQFtqbKJxabHsyUuW7DFIN5acc8zAIIHndvK2M4lALcfSchtwOexAjoEEj8HhxA03EgwSEiRuJ5sdAGphbDiMW8v5N8Y//xgcrt9/I/3DgQSDc8lm5x8S0HIjx0waaEuCgUSOYUNCwgE7sxsEbLGc8cbMWsYg3XDGjZxihoQDyQlmN4C2JODxizl/jvHNNxXW8vwz0jd//PHHzt7sfPrDBx9qbHBqwQCJYJUJxCoHAXtSFI+CUTAKRsHIAAAXQ2Tlq9rAVwAAAABJRU5ErkJggg==","orcid":"","institution":"Alzaiem Alazhari University","correspondingAuthor":true,"prefix":"","firstName":"Baha","middleName":"Aldeen","lastName":"Alshareif","suffix":""},{"id":503214414,"identity":"b1737319-18d3-4289-b71a-1aa9c8c4b274","order_by":2,"name":"Ahmed Ghoname","email":"","orcid":"","institution":"Saudi German Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"","lastName":"Ghoname","suffix":""},{"id":503214416,"identity":"086d75f0-2314-48c5-84a1-e57f459f531d","order_by":3,"name":"Abdulelah Bisher Yakti","email":"","orcid":"","institution":"Saudi German Hospital","correspondingAuthor":false,"prefix":"","firstName":"Abdulelah","middleName":"Bisher","lastName":"Yakti","suffix":""},{"id":503214417,"identity":"9fa7774d-2c9d-4c80-b6cd-28cd47c2c6ca","order_by":4,"name":"Fatimah Moaz Mansour","email":"","orcid":"","institution":"Alnoor Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fatimah","middleName":"Moaz","lastName":"Mansour","suffix":""},{"id":503214418,"identity":"836d15cd-0cff-4af7-b9b8-1519393d134f","order_by":5,"name":"Khulood A. Qasem","email":"","orcid":"","institution":"Saudi German Hospital","correspondingAuthor":false,"prefix":"","firstName":"Khulood","middleName":"A.","lastName":"Qasem","suffix":""},{"id":503214419,"identity":"78c66ce5-95c3-4a6f-96bb-a58101b0d2e6","order_by":6,"name":"Abdulrahman Mohammed Baroom","email":"","orcid":"","institution":"Saudi German Hospital","correspondingAuthor":false,"prefix":"","firstName":"Abdulrahman","middleName":"Mohammed","lastName":"Baroom","suffix":""},{"id":503214420,"identity":"a7b23480-c4e1-495a-a873-b792df64e118","order_by":7,"name":"Abdullah Esmail","email":"","orcid":"","institution":"Almoosa Specialist Hospital","correspondingAuthor":false,"prefix":"","firstName":"Abdullah","middleName":"","lastName":"Esmail","suffix":""},{"id":503214421,"identity":"e917f713-3169-4e7d-a395-f3c2128d7270","order_by":8,"name":"Ramzi Ahmed Elamaireh","email":"","orcid":"","institution":"Bugshan Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ramzi","middleName":"Ahmed","lastName":"Elamaireh","suffix":""},{"id":503214422,"identity":"ba892ade-680e-44d3-a55d-a239a0323e7c","order_by":9,"name":"Amany Ibrahim","email":"","orcid":"","institution":"Cairo University","correspondingAuthor":false,"prefix":"","firstName":"Amany","middleName":"","lastName":"Ibrahim","suffix":""}],"badges":[],"createdAt":"2025-07-02 00:53:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7023956/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7023956/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89630577,"identity":"60d2c724-fa04-4050-9573-3f0de4e4cf86","added_by":"auto","created_at":"2025-08-22 06:39:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":6169,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eROC curve showing the best threshold of the SII for predicting admission (threshold = 735, specificity = 0.62 and sensitivity = 0.72)\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7023956/v1/508b7bf8de41b63c90322ac6.png"},{"id":89630937,"identity":"f54eb549-b741-498e-9b5f-5adaada017b7","added_by":"auto","created_at":"2025-08-22 06:47:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":972610,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7023956/v1/9904fd87-51e2-417e-a7bd-e4bfeeef8cc6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Role of the Systemic Immune Inflammation Index (SII) as an Indicator of the Hospital Admission Rate among Pediatric Patients with Acute Exacerbation of Asthma: A Retrospective Cohort Study","fulltext":[{"header":"Background","content":"\u003cp\u003eAsthma is a chronic inflammatory condition of the airways characterised by fluctuating airflow restriction, heightened airway reactivity, and respiratory symptoms, including wheezing, coughing, chest tightness, and dyspnoea. Affecting more than 5–10% of children worldwide, asthma is among the most common chronic conditions in paediatric populations. Although suitable medication and preventative actions help to effectively control asthma, acute exacerbations remain a major source of morbidity and death, especially in children with either poorly controlled or severe disease [1,2]. Asthma exacerbation pathogenesis involves complicated combinations of immune-mediated inflammation, environmental stimuli, and genetic predispositions.Airway inflammation becomes more noticeable during exacerbations, which causes bronchoconstriction, mucus hypersecretion, and airway edema that ultimately results in airflow limitation and respiratory compromise [3]. From mild episodes controlled in the outpatient environment to severe exacerbations requiring hospitalisation and critical care assistance, the degree of asthma aggravation can vary greatly. The ability to maximise clinical decision-making and enhance patient outcomes depends on the identification of biomarkers able to predict the risk of severe exacerbations and the need for hospital admission [4].\u003c/p\u003e\n\u003cp\u003eResearchers have now started looking at several markers to gauge the degree of asthma severity and predict the likelihood of an exacerbation [5]. Although conventional measures, including pulmonary function tests, fractional exhaled nitric oxide (FeNO), and blood eosinophil counts, are helpful in particular situations, these tests cannot exactly reflect the systemic inflammatory response associated with asthma episodes. Reflecting the balance between pro- and anti-inflammatory processes, the SII—calculated as the platelet count × neutrophil count/lymphocyte count—offers a composite estimate of systemic inflammation and the immune state [6]. In many inflammatory disorders, including cardiovascular diseases, cancers, and infectious diseases, elevated SII values have been linked to poor prognosis and adverse events [7, 8,9].\u003c/p\u003e\n\u003cp\u003eThere has been limited research on the role that the SII plays in predicting hospital admission rates for paediatric children experiencing an acute asthma attack. This is true even if the SII is relevant in revealing immune dysregulation and systemic inflammation in asthma. Knowing the link between the degree of asthma exacerbation (SII) and the likelihood of hospitalisation could help doctors identify high-risk patients early in the course of the disease and provide an important understanding of the pathophysiology of severe asthma exacerbations [3]. The objective of this retrospective cohort study was to assess the predictive power of the SII for hospital admission rates in paediatric patients who experienced acute asthma exacerbation. The findings of this study will affect therapeutic management, risk classification, and the distribution of medical resources.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1. To conduct a retrospective analysis of the correlation between the Systemic Immune Inflammation Index and hospital admissions in paediatric patients experiencing acute asthma exacerbations.\u003c/p\u003e\n\u003cp\u003e2. To assess the correlation between the SII and the probability of hospital admission in paediatric patients experiencing acute asthma exacerbation.\u003c/p\u003e\n\u003cp\u003e3. To evaluate the predictive significance of the SII in relation to other hematological indices (such as the NLR and PLR) for predicting disease severity and hospitalisation.\u003c/p\u003e\n\u003cp\u003e4. To investigate the efficacy of the SII as a mechanism for risk assessment and tailored management approaches in paediatric asthma exacerbations.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Design and Setting:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective cohort study was performed at the Emergency and Pediatric Departments of Saudi German Hospital, Medina, a tertiary care facility in Saudi Arabia. The trial duration extended from January 1, 2018, until February 29, 2024.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy population:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEligible participants were paediatric patients who experienced acute aggravation of asthma during the research period, as determined by electronic health records.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion criteria:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChildren aged 14 years or younger.\u003c/p\u003e\n\u003cp\u003eClinical diagnosis of acute asthma exacerbation at presentation.\u003c/p\u003e\n\u003cp\u003eA complete blood count (CBC) was performed within the first 24 hours of presentation to the emergency department (ED).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion criteria:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePresence of concurrent infections or other inflammatory diseases.\u003c/p\u003e\n\u003cp\u003eThe diagnosis of hematological disorders or the use of immunosuppressive therapy could influence inflammatory indices.\u003c/p\u003e\n\u003cp\u003eIncomplete or missing medical records.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCalculation of the systemic immune inflammation index (SII):\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe SII was calculated via the following formula:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSII = (platelet count × neutrophil count)/lymphocyte count.\u003c/em\u003e Values identified from CBC were obtained from the first laboratory assessment 24 hours following ED presentation. Analysed as a continuous variable, the SII was then dichotomised on the basis of the ideal threshold found via ROC curve analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size determination:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe sample size estimation was based on the following assumption:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnticipated odds ratio for hospital admission associated with an elevated SII: 1.5\u003c/p\u003e\n\u003cp\u003eLevel of significance (α): 0.05 (two-tailed)\u003c/p\u003e\n\u003cp\u003eStatistical power (1–β): 80%\u003c/p\u003e\n\u003cp\u003eEstimated prevalence of hospital admission: 30%\u003c/p\u003e\n\u003cp\u003eBy applying a standard logistic regression sample size computation formula, the minimum needed sample size was approximated to be over 200 cases. There were ultimately 172 paediatric patients included, which, although somewhat below the target, still provided enough statistical power for the main analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection and variables:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following variables were extracted from the electronic health records:\u003c/p\u003e\n\u003cp\u003eLaboratory parameters: Absolute counts of neutrophils, lymphocytes, and platelets, as well as the derived SII.\u003c/p\u003e\n\u003cp\u003eClinical outcome: Hospital admission status (admitted vs. not admitted) following ED presentation.\u003c/p\u003e\n\u003cp\u003eAdditional variables: Age, sex, body mass index (BMI), Pediatric Respiratory Assessment (PRAM) score, medication adherence, history of previous admissions, and C-reactive protein (CRP) levels.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBaseline characteristics were compiled via descriptive statistics; continuous variables, means and standard deviations; and categorical variables, frequencies and percentages. For continuous variables, group comparisons were performed with the Wilcoxon rank-sum test; for categorical variables, Pearson's chi-square test or Fisher's exact test was used.\u003c/p\u003e\n\u003cp\u003eThe ideal SII threshold for hospital admission prediction was determined via receiver operating characteristic (ROC) curve analysis. After adjustment for possible confounders (age, sex, BMI), multivariate logistic regression was used to evaluate the relationship between increased SII and hospital admission. Poisson regression was also used to project incidence rate ratios (IRRs) for admission rates among high-SII patients. A p value \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e\n\u003cp\u003eAll the statistical analyses were performed via R software, version 4.4.3 (R software: fundamentals of programming and statistical analysis. (Statistics and Computing) [10].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThis study investigated the role of the systemic immune inflammatory index (SII) in predicting hospital admission rates among pediatric patients with acute asthma exacerbations. Key findings from the demographic and clinical characteristics (Table 1) revealed that admitted patients had significantly higher total admission counts due to asthma (2.80 vs. 0.71, p \u0026lt;0.001), poorer medication adherence (37% vs. 74%, *p*\u0026lt;0.001), and higher PRAM scores (9.19 vs. 5.42, p \u0026lt;0.001). Age, sex, and BMI did not differ significantly between the admitted and nonadmitted groups (Table 1).\u003c/p\u003e\n\u003cp\u003eThe laboratory results (Table 2) highlighted significant inflammatory differences: admitted patients presented elevated total white blood cells (12.3 vs. 9.7 \u0026times;10\u0026sup3;/\u0026mu;L), neutrophils (8.9 vs. 5.3 \u0026times;10\u0026sup3;/\u0026mu;L), and neutrophil‒lymphocyte ratios (6.7 vs. 2.9, p \u0026lt;0.001). Additionally, the SII was markedly greater in admitted patients (2,162 vs. 1,095, p \u0026lt;0.001), as were the levels of CRP (14 vs. 4 mg/L) and liver enzymes (Table 2).\u003c/p\u003e\n\u003cp\u003eThe ROC curve revealed an SII threshold of 735 (sensitivity 72%, specificity 62%) for predicting admission (Figure 1). Regression analyses reinforced the predictive value of the SII. Logistic regression revealed a high SII (\u0026gt;735) with approximately fivefold increased odds of admission (OR = 4.78, 95% CI: 2.47\u0026ndash;9.57, p \u0026lt;0.001), independent of age, sex, or BMI (Table 3). Similarly, Poisson regression demonstrated that a high SII doubled admission rates (IRR = 2.22, 95% CI: 1.39\u0026ndash;3.68, p = 0.001) (Table 4). In summary, the SII is an independent predictor of hospitalisation in pediatric asthma exacerbations, reflecting systemic inflammation. However, while the SII alone has moderate accuracy, its integration with clinical factors such as prior admissions, medication adherence, and PRAM scores could enhance risk stratification.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 1: Demographic and clinical characteristics of the study groups\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 261px;\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eOverall \u0026nbsp;N = 172\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eNot admitted \u0026nbsp;N = 86\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eAdmitted \u0026nbsp;N = 86\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003ep value\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e5.26 \u0026plusmn; 3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e5.43 \u0026plusmn; 3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e5.09 \u0026plusmn; 2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026gt;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e118 (69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e58 (67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e60 (70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e54 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e28 (33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e26 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e17.10 \u0026plusmn; 3.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e17.38 \u0026plusmn; 3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e16.81 \u0026plusmn; 3.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eAdmitted to PICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e48 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0 (NA%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e48 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026gt;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eLength of admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e3.71 \u0026plusmn; 1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003eNA \u0026plusmn; NA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e3.71 \u0026plusmn; 1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eTotal admission count due to asthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.76 \u0026plusmn; 1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.71 \u0026plusmn; 0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e2.80 \u0026plusmn; 2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eOther allergies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e61 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e31 (36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e30 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eadherent to medications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e96 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e64 (74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e32 (37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003ePRAM score (ON PRESENTATION)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e7.30 \u0026plusmn; 2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e5.42 \u0026plusmn; 1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e9.19 \u0026plusmn; 1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 624px;\"\u003e\n \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eMean \u0026plusmn; SD; n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 624px;\"\u003e\n \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eWilcoxon rank sum test; Pearson\u0026apos;s Chi-squared test; Fisher\u0026apos;s exact test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 2: Summary of laboratory results among the study groups\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 263px;\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eOverall \u0026nbsp;N = 172\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eNot admitted \u0026nbsp;N = 86\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eAdmitted \u0026nbsp;N = 86\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003ep value\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eTotal WBCs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e11.0 \u0026plusmn; 4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e9.7 \u0026plusmn; 4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e12.3 \u0026plusmn; 5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eNeutrophils count\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e7.1 \u0026plusmn; 4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e5.3 \u0026plusmn; 3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e8.9 \u0026plusmn; 5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eLymphocytes count\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e2.80 \u0026plusmn; 2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e3.34 \u0026plusmn; 2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e2.27 \u0026plusmn; 1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eMonocyte count\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.71 \u0026plusmn; 0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.68 \u0026plusmn; 0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.73 \u0026plusmn; 0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eEosinophils count\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.27 \u0026plusmn; 0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.30 \u0026plusmn; 0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.24 \u0026plusmn; 0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eNeutrophils/Lymphocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e4.8 \u0026plusmn; 5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e2.9 \u0026plusmn; 3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e6.7 \u0026plusmn; 6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eMonocyte/Lymphocytes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.32 \u0026plusmn; 0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.28 \u0026plusmn; 0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e0.37 \u0026plusmn; 0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003ePlatelet count\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e332 \u0026plusmn; 85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e339 \u0026plusmn; 81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e326 \u0026plusmn; 88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eSystemic Immune Inflammation index (SII)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1,629 \u0026plusmn; 2,013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e1,095 \u0026plusmn; 1,537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e2,162 \u0026plusmn; 2,283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eHemoglobin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e13.00 \u0026plusmn; 2.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e12.69 \u0026plusmn; 1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e13.32 \u0026plusmn; 2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e9 \u0026plusmn; 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e4 \u0026plusmn; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e14 \u0026plusmn; 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eAST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e22 \u0026plusmn; 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e19 \u0026plusmn; 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e25 \u0026plusmn; 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eALT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e22 \u0026plusmn; 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e26 \u0026plusmn; 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e19 \u0026plusmn; 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 624px;\"\u003e\n \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 624px;\"\u003e\n \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eWilcoxon rank sum test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 3: Logistic regression model for predicting the OR at admission among patients with high SII values (\u0026gt; 735)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 139px;\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eLow SII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eHigh SII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e4.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e2.47, 9.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.84, 1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.53, 2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.86, 1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 392px;\"\u003e\n \u003cp\u003eAbbreviations: CI = Confidence Interval, OR = Odds Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 4: Poisson regression for predicting the RR at admission among patients with high SII\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eva\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003elues (\u0026gt; 735)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003eIRR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eLow SII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eHigh SII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e1.39, 3.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e0.90, 1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e0.63, 1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026gt;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003e0.91, 1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 458px;\"\u003e\n \u003cp\u003eAbbreviations: CI = Confidence Interval, IRR = Incidence Rate Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe systemic immune-inflammation index (SII) was assessed in this retrospective cohort study as a predictor of hospital admission in young patients with acute asthma exacerbations. Our results revealed a strong, independent correlation between an increased SII and increased hospital admission rates, highlighting the clinical value of the SII as a biomarker for disease severity and systemic inflammation in this population.\u003c/p\u003e\n\u003cp\u003eChildren hospitalised for asthma exacerbations had significantly elevated SII values compared with those observed during outpatient care (2,162 vs. 1,095; p \u0026lt; 0.001). Regardless of age, sex, and BMI, an elevated SII was associated with a nearly fivefold increase in hospitalisation risk (OR = 4.78, 95% CI: 2.47–9.57). An SII threshold of 735 had a sensitivity of 72% and specificity of 62% for predicting admission. These results are in line with new data showing that the SII, which combines neutrophil, lymphocyte, and platelet counts, is a strong indicator of systemic inflammation and immunological activation in children with asthma [12,16].\u003c/p\u003e\n\u003cp\u003eThe clinical significance of the SII in juvenile respiratory disorders is corroborated by an expanding body of research. A study conducted in 2025 demonstrated that children experiencing acute asthma episodes exhibit significantly elevated SII values compared with healthy controls and that increased SII values correlate with poorer short-term prognosis; furthermore, underlining its sensitivity to systemic inflammatory responses in respiratory diseases, a recent study by Wang S et al. (2024) confirmed the SII as a predictive marker in paediatric pneumonia [12, 17]. Additionally, a study conducted in 2024 highlighted the important role of the SII in the risk assessment of paediatric asthma, particularly in people under 20 years of age, by demonstrating a robust linear correlation between the SII and asthma persistence [15].\u003c/p\u003e\n\u003cp\u003eAlthough traditional biomarkers such as the CRP level and NLR have been used for evaluating inflammation, our findings indicate that the SII has superior predictive capability for hospital admission. Even though hospitalised patients had substantially higher CRP levels and NLRs, after adjusting for confounding variables, only the SII remained the main predictor. Recent studies have shown that composite indicators such as the SII and NLR outperform single markers in both paediatric and adult asthma patients and COPD patients in terms of exacerbation severity [11,12].\u003c/p\u003e\n\u003cp\u003eSII strength resides in its unique ability to regulate both innate (neutrophils, platelets) and adaptive (lymphocytes) immune responses, providing a more thorough representation of the immunologic dysregulation typical of acute asthma exacerbations [12]. This comprehensive approach might explain why the SII exceeds isolated markers such as CRP, which are more reactive and less specific to the fundamental immune system.\u003c/p\u003e\n\u003cp\u003eOur results also support a multidimensional strategy for risk stratification that combines the SII with clinical severity scores (e.g., PRAM), patient history, and medication adherence. An increased likelihood of hospitalisation was independently linked with higher PRAM scores, a history of several past admissions, and poor medication adherence, confirming recognised predictors of poor asthma outcomes [13,14].\u003c/p\u003e\n\u003cp\u003eCombining the SII with these clinical criteria should enable the identification of high-risk populations that may benefit from early, forceful intervention. Children with both high SII and high PRAM scores, for example, may be particularly vulnerable to clinical deterioration, which justifies a quick increase in treatment. This method fits present trends in precision medicine, which stresses the need to use biomarker data in customised treatment plans [14].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNumerous limitations must be recognised. First, the retroactive design introduces possible confusing elements that could not be completely under control: the effect of past corticosteroid use or concurrent infections on haematologic indices. Second, the SII does not discriminate between eosinophilic and neutrophilic asthma phenotypes, so the clinical consequences may differ. Third, the study was carried out at a single center, which may restrict the generalizability of the findings. Ultimately, even if the SII has great predictive power for hospital admission, its value in predicting other outcomes, such as recurrence or long-term control, is yet unknown [15].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study offers convincing evidence that, in paediatric patients with acute asthma attacks, the systemic immune inflammation index is a powerful, independent predictor of hospital admission. When paired with clinical criteria, the SII improves risk categorisation and supports tailored treatment over traditional inflammatory indicators. Prospective multicenter investigations are justified to confirm these conclusions and define the function of the SII in more general asthma management strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was approved by the Institutional Review Board (IRB) of Saudi German Hospital, Medina (IRB log No: 24-037). The Institutional Review Board waived the requirement for informed permission because of the retrospective design of the study and the utilisation of anonymized patient data. All methods involving human subjects adhered to the ethical norms established by the institutional and national research committees, as well as the 1964 Helsinki Declaration and its subsequent revisions or equivalent ethical guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the data generated or analysed during this study are included in this published article and in the supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualisation, visualisation, validation and methodology, A.S. and B.A.; software and investigation, A.G., A.B.Y. and A.I.; resources and curation, F.M.M. and K.A.Q.; writing original draft, A.M.B., A.E. and R.A.E.; project administration, A.S.; supervision, B.A.; All the authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFleming M, et al. 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PMID: 38495920; PMCID: PMC10944171.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Asthma, Children, Hospital admission, Systemic immune-inflammation index (SII), Biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-7023956/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7023956/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Asthma is the most common chronic condition among children; it typically involves emergency room visits and stays in hospitals during severe recurrence. Derived from neutrophil, lymphocyte, and platelet counts, the systemic immune inflammation index (SII) may also indicate systemic inflammation and predict clinical outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e This study sought to investigate the correlation between the SII and hospital admissions in children experiencing acute asthma exacerbations and to assess the predictive value of the SII with respect to other hematological indicators over the course of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A total of 172 children (≤14 years) presenting with asthma exacerbations from 2018--2024 were included in a retrospective cohort study at Saudi German Hospital, Medina. Within twenty-four hours of emergency presentation, the SII was computed via CBC data. Assessments of relationships with hospital admission used logistic and Poisson regression methods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e With respect to the SII values (2,162 vs. 1,095), admitted patients had noticeably higher values (p \u0026lt; 0.001). For predicting admission, ROC analysis revealed an SII cut-off of 735 (sensitivity 72%, specificity 62%). Independent of age, sex, and BMI, a high SII was associated with doubled admission rates (IRR = 2.22, p = 0.001) and a greater likelihood of hospitalisation (OR = 4.78, 95% CI: 2.47–9.57, p \u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e In paediatric asthma exacerbations, an elevated SII is an independent predictor of hospital admission; hence, it is valuable for early risk assessment and therapy choices.\u003c/p\u003e","manuscriptTitle":"The Role of the Systemic Immune Inflammation Index (SII) as an Indicator of the Hospital Admission Rate among Pediatric Patients with Acute Exacerbation of Asthma: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-22 06:38:47","doi":"10.21203/rs.3.rs-7023956/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-08-26T13:40:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"289710509421087666730602242245221694140","date":"2025-08-20T15:11:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303755075038890830276700587704192163829","date":"2025-08-20T11:58:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-13T09:02:37+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-13T21:53:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-11T11:03:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-11T11:01:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-07-02T00:45:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d872fb27-bd41-4812-842e-38927c430c92","owner":[],"postedDate":"August 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-08-22T06:38:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-22 06:38:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7023956","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7023956","identity":"rs-7023956","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}