ROLE OF SYSTEMIC INFLAMMATORY INDICES IN IDENTIFYING SEPSIS IN PICU PATIENTS IN A TERTIARY HEALTHCARE CENTRE OF INDIA

Summary of evidence

Zhu et al. conducted a thorough investigation. SII had the highest predictive value, while the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio could also accurately predict pediatric sepsis. SII yielded the highest AUC value at 0.82, with a sensitivity of 78% and specificity of 87% at optimal cutoff concentrations of approximately 936. The AUC value was 0.74, with an optimal cut-off concentration of 4.2, sensitivity of 75%, and specificity of 72% for NLR. PLR yielded an AUC value of 0.66 with an optimal cut-off concentration of 59.6, exhibiting a sensitivity of 73% and 63% specificity.¹⁰

An accessible and credible systemic inflammatory index for the diagnosis of Early Onset Sepsis in very low birth weight preterm newborns is SIRI when combined with other indicators, as per a study by Cakir et al. The AUC value of SIRI for predicting EOS was 0.803.¹¹

A study by Seda Aydogan et al. found that SII and NLR have predictive power to identify neonatal sepsis in infants with CHD. The AUC for SII was 0.76 (70% sensitivity, 70.5% specificity).¹² Güngör et al. showed that SII is a predictor of UTIs in babies. AUC for SII was 0.84 (95% CI: 0.78-0.89).¹³

Research by Runqiang Liang et al. found that the SII was crucial for diagnosing serious bacterial infections in newborns. The AUC was 0.805 (95%CI: 0.759–0.852). At a cutoff value of 0.082, the maximum specificity and sensitivity were 0.809 (95%CI: 0.787–0.831) and 0.719 (95%CI: 0.641–0.797), respectively.¹⁴

Cakir et al. found that a higher SII level (≥78.2) may be a predictor of the development of RDS in premature infants. The AUC value of the SII was 0.842.¹⁵ It was found that SII, SIRI, PIV, and NLR were significantly increased in infants with hypoxic-ischemic encephalopathy when compared to the control group in a study by Burak Ceran et al. The areas under the curve for NLR, PLR, MLR, SII, SIRI, and PIV to predict HIE were 0.808, 0.597, 0.653, 0.763, 0.686, and 0.663, respectively.¹⁶

Another study by Kawalec et al. showed that the SII and NLR were promising prognostic markers in children with burns, and higher NLR and SII values were related to longer hospitalization.¹⁷ A study by Mathews et al. showed that the SII has been used frequently as a biomarker to determine the load of inflammation in certain illnesses, like diabetic kidney injury and severe COVID-19. It was observed that the non-The survivor group had a higher SII than the survivor group. Interestingly, the pattern of the SII was consistent with that of the NLR and PLR. These are believed to provide more comprehensive assessment of patient inflammatory status. NLR increase predicted mortality of 61.1%, and a PLR increase of 77.8%. Decreasing trends in the NLR and PLR were both closely related to better survival. Rise in PLR had higher sensitivity, specificity, PPV, NPV, and an overall accuracy of 72.73% (p < 0.001) for predicting mortality.¹⁸

Frans et al. used NLR, PLR, MLR, and MPV as indicators of mortality in sepsis in the pediatric population. This study indicated that NLR was the best indicator of sepsis-related mortality. The cut-off value of NLR as a diagnostic marker for sepsis was 3.52 with a sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and odds ratio (OR) of 82.50%, 47.50%, 61.11%, 73.08%, and 4.26 (p < 0.004), respectively.¹⁹

Need for study

The early identification of sepsis is key to managing and reducing morbidity and mortality. The extent of sepsis also aids treatment modalities and provides insights into the course of antibiotics required. Bedside parameters will also help reduce the need to wait for a culture report before starting the course of treatment.

Study design and setting

This prospective, observational study was conducted in the pediatric intensive care unit (PICU) at the Regional Advanced Pediatric Care Center, Mangalore, a tertiary care referral hospital. This study was conducted between November 2024 and March 2025 after obtaining approval from institutional ethics committee at Kasturba Medical College in Mangalore granted ethical clearance on 21/11/24 (Protocol No: IECKMCMLR-11/2024/644). The study is done as per STROBE guidelines for observational study ( Figure 1). We adhered to all ethical parameters as per Declaration of Helsinki.

Figure 1. Strobe flow diagram.

Study population

Participants who fulfilled the following criteria were included in the study: (1) admission to the PICU during the study period and (2) diagnosis of sepsis or septic shock according to the Third International Consensus Definitions (2016). Patients were excluded if they had (1) severe non-infectious life-threatening conditions (e.g., trauma, congenital malformations), (2) were on long-term medications such as antibiotics or immunosuppressants, or if (3) they were not willing to participate.

Sample size

Based on previous research, it was found that the mean PLR in the sepsis group was 62.5, with a standard deviation of 37.3, whereas for the non-sepsis group, the average PLR was 80.4 with a Standard deviation of 26.2. Considering the same 80% power and 95% confidence interval, the sample size was estimated to be 69 patients in each group. Thus, there were 138 PICU patients, 69 patients with sepsis, and 69 patients without sepsis. Consecutive sampling was used to select the participants from the sepsis group. Open Epi Version 3.01 was used to calculate the sample size.¹⁰ Figure 1 shows the STROBE flow diagram for recruitment of cases.

Data collection and laboratory assays

Data were collected at the time of PICU admission after obtaining written informed consent from parents/guardians. Blood tests, including a complete blood count (CBC) which were sent as part of the PICU protocol, were considered for the study. CBC was calculated using the Sysmex XN 1000 automator used in our laboratory. For patients who had multiple CBC reports within 24 hours, only the first value was considered for consistency. The collected data included demographic information (age and sex) and clinical diagnosis. All tests were performed in the hospital’s central diagnostic laboratory following standardized protocols. From the collected data, the SII, SIRI, PIV, NLR, MLR, and PLR were calculated using the following formulae:

Operational definitions

Sepsis and septic shock were defined according to the 3^rd International Consensus Definition of 2016. Sepsis is defined as a suspected or documented infection with an acute increase of ≥ 2 Sequential Organ Failure Assessment (SOFA) points. Septic Shock is diagnosed when sepsis and vasopressor therapy are needed to elevate MAP ≥ 65 mmHg and lactate >2 mmol/L (18 mg/dL) after adequate fluid resuscitation. The definitions of the systemic inflammatory indices were based on previously validated formulas.

Statistical analysis

The data was entered and analysed using IBM SPSS (Statistical Package for Social Sciences) Statistics for Windows Version 29.0. Armonk, NY: IBM Corp. Descriptive statistics were presented as medians and standard deviations. The scores between the case and control arms were compared using an independent-sample t-test. Statistical significance was set at P < 0.05. to assess the predictive ability of the diagnostic markers ROC analysis was done. Additionally, the optimum cut-off values were determined using the Youden Index.

Critical reflection

Systemic inflammatory indices play a significant role in predicting sepsis in critically ill pediatric patients. These findings highlight a peculiar inflammatory signature in sepsis patients with grossly elevated NLR, PLR, MLR, SII, SIRI, and PIV underscoring the immune system dysregulation inherent in sepsis. NLR’s strikingly high AUC value of 1.000 suggests extremely severe infection and systemic inflammation in septic patients, reflective of an extreme immune response. Such perfect discriminatory power may be largely attributed to the inclusion of patients with advanced or fulminant sepsis, in which neutrophilia and lymphopenia manifest quite pronouncedly. SIRI with an AUC of 0.950 and SII with an AUC value of 0.944 showed remarkably excellent predictive ability beyond the NLR, reinforcing their role as robust markers. The predictive strength of PLR, MLR, and PIV further supports their potential utility in sepsis diagnosis quite early on. The cut-off values identified here provide actionable thresholds aiding clinical decision-making, thereby facilitating prompt intervention and resulting in markedly improved outcomes. These findings underscore the potential of systemic inflammatory indices to serve as swiftly deployable biomarkers for early sepsis detection in pediatric ICU settings. Implementation of their diagnostics could facilitate earlier treatment initiation in critically ill pediatric patients, thereby significantly improving survival rates and markedly reducing morbidity.

Limitations

The generalizability of the findings may be limited because this study was conducted in a single center setting. Results may differ significantly between adult and neonatal populations, whereas study population populations may differ in spopulation, spopulation, spopulation, spopulation, spopulation, spopulation, spopulation, spopulation, and spopulation. Systemic inflammatory indices showed strong predictive ability, yet external validation with a fairly large multicenter cohort remains necessary to confirm clinical applicability. Future research should rigorously incorporate such indices into sepsis screening protocols and evaluate their effectiveness in real-world clinical settings.