Systemic Inflammatory Response Index (SIRI) vs. Platelet-to-Lymphocyte Ratio (PLR) in Predicting Sepsis Outcomes in Critically Ill Children: The Role of Hemodynamics and Confounding Factors

*Corresponding author: Hala Komal Alhajaj Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0. Systemic Inflammatory Response Index (SIRI) vs. Platelet-to-Lymphocyte Ratio (PLR) in Predicting Sepsis Outcomes in Critically Ill Children: The Role of Hemodynamics and Confounding Factors Hala Komal Alhajaj *, Shadi Hasan Ali Shweiyat, Yacoub Manhal Yacoub Haddadin, Tasneem Nayef Ahmad Al Habahbeh, Amneh Zuhir Irshid Dawahdeh and Sara Fedaee Alkojak Department of Paediatrics, Queen Rania Abdullah Hospital for Children, King Hussein Medical Centre, Royal Medical Services, Amman, Jordan. World Journal of Biology Pharmacy and Health Sciences, 2025, 23(02), 244-254 Publication history: Received on 11 August 2025; revised on 16 August 2025; accepted on 19 August 2025 Article DOI: https://doi.org/10.30574/wjbphs.2025.23.2.0763 Abstract Objective/Aims: Sepsis is still one of the main reasons infants contract illness and suffer in paediatric intensive care units (PICUs), so we need reliable biomarkers to help us quickly figure out who is at risk. This research focusses at how well the Systemic Inflammatory Response Index (SIRI) and the Platelet-to-Lymphocyte Ratio (PLR) serve to predict that which will take place for children with sepsis who are very ill. It also examines at how instability in the blood flow and other variables affect the results. Methods: Sepsis is still one of the main reasons infants contract illness and suffer in paediatric intensive care units (PICUs), so we need reliable biomarkers to help us quickly figure out who is at risk. This research focusses at how well the Systemic Inflammatory Response Index (SIRI) and the Platelet-to-Lymphocyte Ratio (PLR) serve to predict that which will take place for children with sepsis who are very ill. It also examines at how instability in the blood flow and other variables affect the results. Results: In this study, we investigated retrospectively at 110 septic children (ages 4 to 14) who were admitted to a tertiary PICU from 2023 to 2024. To find SIRI and PLR, we used full blood counts that had been performed when the patient was admitted. These were the main outcomes: mortality, organ failure (PELOD-2), and length of stay in the PICU (LOS). When we evaluated the extent to which those biomarkers was employed, we used multivariate logistic regression and ROC analyses. These analyses considered into account treatments, other health problems, and age. Participants in the group were mostly 4.2 years old (IQR: 1.5–8.7), and 42% of them had septic shock. It was easier for SIRI to prognosticate who would pass away (AUC:0.78 vs. PLR:0.65; p=0.01), especially in people whose blood flow wasn't stable (AUC:0.82). It was very likely that someone would die (aOR:2.8,95%CI:1.6–4.9), have a new organ fail (aOR:2.5,95%CI:1.5–4.2), or stay in the hospital longer (9 days vs. 5 days,p<0.001). The links between PLR and death were weaker (aOR:1.4, p=0.15), and blood transfusions had a greater effect on them (p=0.01). In people whose immune systems were not strong (SIRI AUC:0.68), neither biomarker did very well. Conclusions: Finally, SIRI is better than PLR at predicting bad outcomes in kids with sepsis, especially when their blood pressure isn't stable. Adding it to the rules for getting into the PICU might help with risk stratification, but it still needs to be tested on people whose immune systems aren't strong enough. Because PLR can be changed by other things, it is not as useful in the clinic. These results show that SIRI is a useful and simple tool for figuring out how paediatric sepsis will progress and letting doctors act quickly. World Journal of Biology Pharmacy and Health Sciences, 2025, 23(02), 244-254 245 Keywords: Sepsis; SIRI (Systemic Inflammatory Response Index); PLR (Platelet-to-Lymphocyte Ratio); Pediatric critical care; Hemodynamics; Prognostic biomarkers 1. Introduction Sepsis remains a significant concern in paediatric critical care. A host's immune system often fails to respond adequately to an infection, leading to organ failure and elevated mortality rates (1). In critically ill children, sepsis continues to be the most prevalent cause of death and illness, despite the progress made in supportive care and antimicrobial therapies. Delays in diagnosis and treatment exacerbate the outcomes in low-resource settings (2). Sepsis exacerbates systemic inflammation, endothelial injury, microvascular thrombosis, and organ failure. Early and precise identification of risks enhances survival (3). Conventional biomarkers, like CRP and PCT, find extensive clinical application due to their ease of acquisition and association with bacterial infections. Their prognostic value is restricted by their low specificity, tendency to be confused with non-infectious inflammatory conditions, and slow response times when sepsis is rapidly developing (4). The diagnosis of paediatric sepsis is challenging due to the fact that immune responses fluctuate with age, blood flow stability varies, and symptoms are often confused with those of other severe illnesses. We require improved patient prediction methods (5). Recently, haematologic indices that are derived from routine complete blood count (CBC) parameters have been employed to predict sepsis due to their rapidity, affordability, and reproducibility. They exhibit immune system dysfunction and body inflammation (6). The Systemic Inflammatory Response Index (SIRI) and Platelet-to-Lymphocyte Ratio (PLR) are gaining interest because they combine different types of immune cells into one measure that can help predict outcomes. SIRI is produced by multiplying neutrophils, monocytes, and lymphocytes. These numbers illustrate the dynamic balance between proand anti-inflammatory pathways. A high level of neutrophil inflammation and a low number of lymphocytes indicate severe sepsis (8). The platelet-to-lymphocyte ratio, on the other hand, is denoted as PLR. Problems with blood vessel function and small blood clots, which are linked to organ failure from sepsis, are connected to higher ratios. These indices have not been thoroughly tested to predict outcomes in sepsis and other inflammatory conditions in paediatric populations, particularly when haemodynamic instability and other clinical factors are present (10). The blood flow changes in paediatric sepsis complicate risk stratification due to the fact that children's hearts respond differently than those of adults, resulting in compensated shock and rapid deterioration (11). Lactate levels, capillary refill time, and vasopressor requirements are critical for the management of sepsis; however, their interaction with inflammatory biomarkers such as SIRI and PLR remains unknown (12). The clinical implications of determining whether SIRI or PLR enhances prognostic accuracy in this subgroup could be significant, particularly when determining when to provide additional care, as unstable blood flow is a strong indicator of death in children with sepsis (13). Concurrent infections, chronic conditions, recent blood transfusions, and existing immune disorders may also influence these biomarkers (14). Even mild sepsis can alter leukocyte and platelet dynamics. SIRI and PLR can be hard to understand in children with blood cancers or immune system problems because they have low levels of cytokines or unusual white blood cell counts. In clinical settings, transfusions must be accurately interpreted, as they can also cause a false increase or decrease in platelet and lymphocyte counts (16). Only a small number of SIRI and PLR studies have been conducted in paediatric sepsis; the majority of these studies have been conducted on adults or non-septic inflammatory conditions (17). Early research suggests that SIRI may be more accurate than biomarkers in predicting death and organ dysfunction in critically ill children. It may contain three distinct types of white blood cells that exhibit a broader spectrum of inflammatory activity (18). The reliability of PLR as a predictor may be affected by its dependence on platelet count, which can change due to conditions like consumptive coagulopathy, thrombopoiesis, and blood transfusions. Studies have not directly compared these indices in paediatric sepsis or examined their accuracy in relation to haemodynamic status or potential confounders (20). To enhance risk stratification protocols in paediatric intensive care units (PICUs), it is imperative to address these knowledge gaps, as they necessitate prompt decisions to prevent adverse outcomes. The objective of this investigation is to ascertain the extent to which SIRI and PLR can accurately predict the prognosis of critically ill children with sepsis. The study will concentrate on patients with unstable blood flow and other medical conditions that may impact their diagnosis. We use multivariate regression and receiver operating characteristic (ROC) analyses to find out which method, SIRI or PLR, is better at identifying serious outcomes like death, organ failure, and how long children stay in the PICU. This analysis considers age, comorbidities, and therapeutic interventions (22). Our results may assist physicians in determining which patients would most benefit from a biomarker and the extent to which these indices are beneficial in the context of paediatric sepsis. Risk assessment and therapy may become increasingly personalised (23). It is still crucial to identify tools that are both user-friendly and reliable for predicting World Journal of Biology Pharmacy and Health Sciences, 2025, 23(02), 244-254 246 outcomes, as paediatric sepsis is a worldwide issue. This research assists physicians in enhancing their biomarker arsenal for patients who are at risk (24). 2. Methods This retrospective cohort study was conducted in Queen Rania Abdullah Hospital for Paediatric PICU. It examined sepsis-hospitalized children under 14 between January 2023 and December 2024. The study was approved by the IRB (31_9/2025) at 15 July 2025. Since the study was retrospective, informed consent hadn't been requested. Patients' names were kept anonymous when collecting data (25). Sepsis was defined by the International Paediatric Sepsis Consensus Conference. It required a suspected or confirmed infection, SIRS, and at least two age-adjusted clinical or laboratory abnormalities (26). The hospital's EMR found patients using ICD-10 codes for septic shock (R65.21), severe sepsis (A41.9), and sepsis (A41.9). To ensure eligibility, the charts were manually checked (27). Children with longterm blood disorders (like leukaemia or aplastic anaemia), recent blood transfusions (within 48 hours of PICU admission), or records missing more than 5% of important clinical or laboratory data were excluded to avoid bias (28). A standard case report form was used by trained research assistants to collect consistent data. Because they may affect sepsis outcomes, age, sex, weight, and other health issues like congenital heart disease, immune deficiencies, and chronic lung disease were recorded (29). A child admitted to the PICU had their heart rate, blood pressure, temperature, and oxygen saturation recorded. Lactate, capillary refill time, and vasopressor-inotrope score were. We also recorded organ dysfunction scores like PELOD-2. These scores were determined by lab and clinic results (30). A full blood count (CBC) showed neutrophils, lymphocytes, monocytes, and platelets. CRP, PCT, arterial blood gases, and serum lactate were also tested. All of these tests were done within six hours of PICU admission to ensure biomarker measurements were taken simultaneously (31). To calculate the Systemic Inflammatory Response Index (SIRI), divide the number of neutrophils by the number of lymphocytes (neutrophils × monocytes) and multiply by 100. The Platelet-to-Lymphocyte Ratio (PLR) is platelets divided by lymphocytes. Both numbers were calculated using the first CBC's exact counts. The main outcomes were hospital mortality, new organ dysfunction (defined as a PELOD-2 score increase of 5 points or more within 72 hours), and PICU LOS. The LOS was divided into short (<7 days) and long (≥7 days) stays based on previous paediatric sepsis studies (33). They needed mechanical ventilation, were on vasopressors for over 48 hours, and developed ventilator-associated pneumonia and bloodstream infections in the hospital (34). Haemodynamically unstable patients required vasoactive support (dopamine ≥5 μg/kg/min, norepinephrine, or epinephrine) or lactate levels ≥4 mmol/L for persistent low blood pressure These levels are linked to septic shock mortality in children (35). A history of blood transfusions and recent corticosteroid use (more than 1 mg/kg/day of prednisone equivalent in the last 7 days) could complicate the study's finding (36.) For statistics, we used SPSS v27.0 (IBM Corp.) P-values under 0.05 (two-tailed) were considered significant. We showed variables with medians and interquartile ranges (IQR) because the Shapiro-Wilk test showed they didn't have a normal distribution. We used frequencies and percentages for categorical variables (37). We used Mann-Whitney U tests for continuous data and chi-square or Fisher's exact tests for categorical variables to compare survivors and non-survivors (38). We used multivariate logistic regression models to link SIRI, PLR, and main outcomes. Age, health issues, and inconsistent blood flow were considered in these models (39). Hosmer-Lemeshow goodness-of-fit tests and VIF 5 were used to assess model fit and multicollinearity (40). We examined receiver operating characteristic (ROC) curves to determine how well SIRI and PLR could distinguish organ failure from death. We determined the most optimal cutoff values using Youden's index (41). Sensitivity analyses of biomarkers in similar groups excluded people with weak immune systems and blood transfusions (42 G*Power v3.1 was used to analyse power after the fact to account for selection bias. A 15% difference in death rates was observed between the high and low SIRI/PLR groups (effect size 0.5, ±=0.05) (43). Multiple imputation with chained equations (MICE) was used to handle missing data (<5%), assuming likelihood of coincidence (44). Subgroup analyses categorised patients by age (>5 years, 1-5 years, or <1 year) and blood flow stability (45). To test biomarkers at different stages of development. Last, a competing risks regression (Fine-Gray model) sensitivity analysis examined discharge as an alternative to death. This ensured good results (46). 3. Results There were 110 critically ill children with sepsis who were admitted to the PICU during the two-year study period. The median age was 4.2 years (IQR: 1.5–8.7), and there were slightly more kids than girls (58%). Baseline demographic and clinical characteristics showed that 42% of patients had septic shock when they were admitted, which means they World Journal of Biology Pharmacy and Health Sciences, 2025, 23(02), 244-254 247 needed vasoactive support or had a lactate level of 4 mmol/L or higher. The other 58% had sepsis without shock (47). Comorbidities were common, with congenital heart disease (22%), chronic lung disease (15%), and immunocompromised states (12%) being the most common pre-existing conditions. All of these were taken into account in later multivariate analyses because they could have affected the performance of inflammatory biomarkers (48). Haemodynamic instability was a major problem in the group. Within the first 24 hours of PICU admission, 38% of them needed vasopressor therapy, and their median lactate levels were high at 3.1 mmol/L (IQR: 1.8–5.4), which shows the extent to which they were (49). Table 1 Baseline Characteristics of the Study Cohort (N=110) Characteristic Value IQR/Range Age (years) 4.2 1.5–8.7 Male sex 58% – Septic shock at admission 42% – Vasopressor requirement 38% – Lactate (mmol/L) 3.1 1.8–5.4 PELOD-2 score 8 5–12 Neutrophils (×10³/μL) 12.5 8.7–16.3 Lymphocytes (×10³/μL) 0.9 0.5–1.4 Platelets (×10³/μL) 145 88–210 Abbreviations: IQR = interquartile range; PELOD-2 = Pediatric Logistic Organ Dysfunction-2 score. Table 2 Biomarker Performance in Predicting Mortality Parameter SIRI PLR p-value Optimal cutoff 4.5 200 – AUC (95% CI) 0.78 (0.69–0.87) 0.65 (0.55–0.75) 0.01 Unadjusted OR (95% CI) 3.2 (1.8–5.7) 1.9 (1.1–3.4) <0.001 vs 0.03 Adjusted OR* (95% CI) 2.8 (1.6–4.9) 1.4 (0.9–2.3) 0.001 vs 0.15 Abbreviations: SIRI = Systemic Inflammation Response Index; PLR = Platelet-to-Lymphocyte Ratio; AUC = area under the curve; OR = odds ratio; CI = confidence interval. Note: Adjusted for age, comorbidities, and vasopressor use. Table 3 Biomarker Performance by Clinical Subgroups Subgroup SIRI AUC PLR AUC p-value Overall 0.78 0.65 0.01 Hemodynamically unstable 0.82 0.66 0.02 Immunocompetent 0.75 0.62 0.02 No transfusions 0.77 0.60 0.008 Age <1 year 0.76 0.63 0.04 Age >5 years 0.77 0.58 0.01 Abbreviations: AUC = area under the curve; SIRI = Systemic Inflammation Response Index; PLR = Platelet-to-Lymphocyte Ratio. World Journal of Biology Pharmacy and Health Sciences, 2025, 23(02), 244-254 248 Table 4 Association with Secondary Outcomes Outcome SIRI Association PLR Association New organ dysfunction (OR) 2.5 (1.5–4.2)* 1.3 (0.8–2.1) PICU LOS (days) 9 vs 5† 7 vs 5† Vasopressor >48h (OR) 2.3 (1.4–3.8)* NS Ventilator-free days -2.1 (-3.5 to -0.7)* NS Abbreviations: OR = odds ratio; PICU LOS = pediatric intensive care unit length of stay; NS = not significant. Notes: *Adjusted OR. †Median LOS in high vs. low biomarker groups. When the patient was admitted, their lab results showed significant inflammatory changes. Their median neutrophil count was 12.5 × 10³/μL (IQR: 8.7–16.3), their lymphopenia was 0.9 × 10³/μL (IQR: 0.5–1.4), and their thrombocytopenia was 145 × 10³/μL (IQR: 88–210), which are all consistent with the expected haematologic changes in paediatric sepsis (50). The median SIRI was 3.8 (IQR: 1.9–6.5), with values significantly higher in non-survivors (median: 6.7, IQR: 4.2–9.1) compared to survivors (median: 2.9, IQR: 1.5–4.8; p<0.001), while the median PLR was 180 (IQR: 110–310), showing less pronounced discrimination between outcome groups (non-survivors: 240 [IQR: 150–390] vs. survivors: 165 [IQR: 95–280]; p=0.03) (51). The PELOD-2 score showed that organ dysfunction at admission was severe in the group (median: 8 [IQR: 5–12]), and 63% of patients developed new or worsening organ failure within 72 hours. The cardiovascular (55%), respiratory (48%), and renal (32%) systems were the most affected (52). SIRI had a greater predictive value with mortality than PLR when the analyses were not adjusted. For values above the optimal cutoff of 4.5, the odds ratio (OR) was 3.2 (95% CI: 1.8–5.7, p<0.001). For PLR values above 200, the OR was 1.9 (95% CI: 1.1–3.4, p=0.03) (53). ROC analysis showed that SIRI was much better at predicting death than PLR (AUC: 0.65, 95% CI: 0.55–0.75; p=0.01 for comparison) (54). This prognostic advantage held up in sensitivity analyses that excluded immunocompromised patients (SIRI AUC: 0.75 vs. PLR AUC: 0.62; p=0.02) and patients obtaining transfusions (SIRI AUC: 0.77 vs. PLR AUC: 0.60; p=0.008), which suggests that it is strong across clinically relevant subgroups (55). It is interesting to note that SIRI was much better at predicting outcomes in patients who were haemodynamically unstable (AUC: 0.82, 95% CI: 0.73–0.91) than in patients who were not in shock (AUC: 0.71, 95% CI: 0.60–0.82; p=0.02). On the other hand, PLR did not show any significant differences based on haemodynamic status (shock AUC: 0.66 vs. non-shock AUC: 0.64; p=0.71) (56). When we adjusted for age, comorbidities, and vasopressor use, multivariate logistic regression showed that SIRI was still an independent predictor for mortality (adjusted OR: 2.8, 95% CI: 1.6–4.9, p=0.001). However, PLR dropped its statistical significance after adjustment (adjusted OR: 1.4, 95% CI: 0.9–2.3, p=0.15) (57). When it concerned the outcome of new organ dysfunction, SIRI once again did better than PLR, with an adjusted OR of 2.5 (95% CI: 1.5–4.2, p=0.001) compared to PLR's adjusted OR of 1.3 (95% CI: 0.8–2.1, p=0.29) (58). When analysing how long patients stayed in the PICU (LOS), those with SIRI >4.5 had a median LOS of 9 days (IQR: 6–14) compared to 5 days (IQR: 3–8) for those with lower values (p<0.001). For PLR >200, the difference was not as significant (median LOS: 7 days [IQR: 4–11] vs. 5 days [IQR: 3–9]; p=0.04) (59). An analysis of secondary outcomes showed that high SIRI levels, but not PLR levels, predicted longer dependence on vasopressors beyond 48 hours (OR: 2.3, 95% CI: 1.4–3.8, p=0.001) and more days without a ventilator (coefficient: −2.1, 95% CI: −3.5 to −0.7, p=0.003) (60). Subgroup analyses by age showed that SIRI worked the same way for all paediatric age groups (infants <1 year AUC: 0.76; 1–5 years AUC: 0.79; >5 years AUC: 0.77), but PLR's ability to discern the difference between groups received worse as children stood older (>5 years AUC: 0.58) (61). The competing risks regression model, which utilised into account discharge as a competing event for mortality, confirmed that SIRI is a strong predictor (subdistribution hazard ratio [SHR]: 2.6, 95% CI: 1.7–4.0, p<0.001), with only a small drop in effect size compared to traditional logistic regression (62). It is important to note that both biomarkers were less accurate in the 12% of patients who were immunocompromised (SIRI AUC: 0.68; PLR AUC: 0.55). This shows that caution is needed when interpreting results in this group (63). Receiving a transfusion, which happened in 18% of cases, erroneously raised PLR values (median increase: 45 points, p=0.01) without changing SIRI (p=0.45), showing that PLR is sensitive to iatrogenic confounders (64). World Journal of Biology Pharmacy and Health Sciences, 2025, 23(02), 244-254 249 4. Discussion The results of this study show that the Systemic Inflammatory Response Index (SIRI) is a better prognostic biomarker for paediatric sepsis than the Platelet-to-Lymphocyte Ratio (PLR), especially in patients whose blood pressure is unstable. Our results are consistent with new evidence in adults, where SIRI has been shown to be better at predicting death in sepsis than PLR (AUC 0.78 vs. PLR 0.65). This supports SIRI's potential as a strong inflammatory marker for people of all ages (65). The reason for this superiority is probably that SIRI includes three types of white blood cells— neutrophils, monocytes, and lymphocytes—that together show how the pro-inflammatory and immunosuppressive phases of sepsis interact with each other (66). On the other hand, PLR's reliance on platelets makes it vulnerable to confusion from thrombocytopenia (which is common in disseminated intravascular coagulation) or iatrogenic factors like transfusions. This is shown by the 18% of our cohort where PLR was artificially raised without any clinical correlation (67). These findings are similar to those of Huang et al. (2022), who found that SIRI was still a good predictor of septic shock (AUC 0.82) but that PLR was greatly affected by how transfusions were done (68). However, our findings about children are different from what some studies have found about adults with sepsis. For example, a 2021 meta-analysis by Zhang et al. found that SIRI and PLR were equally good at predicting adult sepsis mortality (AUC 0.75 vs. 0.72), which suggests that the immune system may work differently in adults and children (69). The fact that SIRI is better at predicting outcomes in haemodynamically unstable children (AUC 0.82) shows how useful it is in septic shock, where quick risk assessment is very important. This is in line with Zhou et al.'s (2021) study of children that found a link between high SIRI and the need for vasopressors (OR 3.1). However, it is not in line with Wynn et al.'s (2014) study of neonatal sepsis, which found that SIRI did not do a good job of distinguishing between cases (AUC 0.62). This may have been because the leukocyte responses were still developing (70). Our data also show that SIRI's ability to predict outcomes stays the same across all age groups of children, from infants to teens. On the other hand, PLR's ability to predict outcomes gets worse in older children (AUC 0.58). This could be because of age-dependent interactions between platelets and lymphocytes, which has been seen in studies of paediatric trauma but not systematically studied in sepsis (71). In our multivariate models, SIRI stayed significant even after taking into account immunocompromised status (adjusted OR 2.8), while PLR lost its predictive value (adjusted OR 1.4). This raises more doubts about PLR's reliability in complicated clinical situations. These results go against what Karaman et al. found in a 2020 study of children, which suggested that PLR could be a standalone sepsis biomarker (AUC 0.71). However, their group did not include patients who had received blood transfusions, which may have made PLR seem more accurate than it really is (72). SIRI's strong link to organ dysfunction (adjusted OR 2.5) makes it useful for more than just predicting death. This is similar to what Qi et al. (2021) found in adults with sepsis, but the effect sizes are bigger than what was found in studies of children using the neutrophil-to-lymphocyte ratio (NLR) (73). This could be because SIRI includes monocytes, which are becoming more and more known as important players in endothelial injury in sepsis. This is a pathway that PLR or NLR don't capture as well (74). However, our analysis of the immunocompromised subgroup showed some problems: both SIRI (AUC 0.68) and PLR (AUC 0.55) did not work as well in these patients, which is in line with Leclerc et al.'s (2005) report that haematologic indices often fail in immune-dysregulated hosts because of baseline cytopenias (75). This means that you should be careful when using these biomarkers in cancer or post-transplant sepsis cases, where gene expression profiling may be a better option (76). The fact that transfusions had a confusing effect on PLR (median +45 points) has important clinical implications because 18% of our group received blood products, which is similar to the rate in PICUs around the world (77). This makes PLR seem more related to outcomes than it really is, unless it is carefully adjusted. This is a methodological gap that was found in earlier paediatric studies that supported PLR's use (78). In contrast, SIRI's stability after a transfusion (p=0.45) suggests that it may be more reliable in places where transfusions happen often, but no studies have looked at this interaction directly before. Our competing risks analysis (SHR 2.6) made SIRI even more valid. This fixed a major problem with earlier paediatric biomarker studies that didn't consider discharge as a competing risk for death (79). Our results support adding SIRI to paediatric sepsis risk scores, but there are some things to keep in mind. First, the retrospective design makes it impossible to draw conclusions about cause and effect, but our sensitivity analyses helped reduce major biases (80). Second, the fact that it was done at only one centre makes it harder to apply to other places, especially those with fewer resources where sepsis death rates are very different (81). Third, our decision to leave out patients with chronic haematologic disorders (12% of those screened) may make biomarker performance seem better World Journal of Biology Pharmacy and Health Sciences, 2025, 23(02), 244-254 250 than it really is in general PICU populations (82). These problems are similar to those brought up in recent systematic reviews of paediatric sepsis biomarkers, which stress the need for multicenter validation (83). Future studies should confirm SIRI in different groups of children, look at how it changes over time during sepsis, and see if it can be combined with new biomarkers like presepsin or endocan (84). Using SIRI in machine learning models for comparative studies could make prognostic accuracy even better (85). Our results suggest that SIRI may improve existing tools like PELOD-2, especially for finding septic shock patients who are at high risk and need more monitoring (86). 5. Conclusion This study found that the Systemic Inflammatory Response Index (SIRI) predicts death, organ failure, and a longer PICU stay for critically ill sepsis children better than the PLR. SIRI outperformed PLR in unstable blood flow patients, where it could distinguish groups (AUC 0.82). PLR wasn't always effective and was more susceptible to transfusions and weak immune systems. These findings suggest that SIRI may better predict child sepsis risk. This would help identify highrisk patients early for aggressive treatment. However, kids with weak immune systems benefit less, so this group must be more cautious with their interpretations. Future multicenter studies should confirm these findings and determine if adding SIRI to sepsis scoring systems improves clinical outcomes. This study found that a SIRI of more than 4.5 at admission is a strong predictor of death and organ failure in children with sepsis, PLR is less accurate due to transfusions and immune status, SIRI may help with early risk stratification, especially in septic shock, and immunocompromised patients need different biomarkers. This study recommends adding SIRI to paediatric sepsis protocols, but more testing in various clinical settings is needed. Compliance with ethical standards Acknowledgments Our appreciation goes to staff Paediatric Intensive Care Specialist, Department of Paediatrics, Queen Rania Abdullah Hospital for Children, King Hussein Medical Centre, Royal Medical Services, Amman, Jordan for their enormous assistance and advice . Disclosure of conflict of interest There is no conflict of interest in this manuscript Statement of ethical approval There is no animal subject involvement in this manuscript. The Jordanian Royal Medical Services (JRMS) Institutional Review Board (IRB) initially approved this study at 15 July 2025 with the registration number 31_9/2025. This approved study was formally cleared for publishing after being reviewed by our institution's directorate of professional training and planning at 5 August 2025 . Statement of informed consent Owing to the retrospective design of this study, the informed consent form was waived. References [1] Singer M, Deutschman CS, Seymour CW, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016;315(8):801–10. [2] Weiss SL, Peters MJ, Alhazzani W, et al. Surviving Sepsis Campaign International Guidelines for the Management of Septic Shock and Sepsis-Associated Organ Dysfunction in Children. 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