Systemic immune-inflammation index as a risk factor for acute kidney injury in patients with neonatal jaundice

Introduction

Jaundice is one of the most common conditions during the neonatal period, affecting about 60% of newborns within their first week (1). It mainly results from abnormal bilirubin metabolism in neonates, causing elevated total bilirubin levels in the blood. When bilirubin exceeds 85 µmol/L, jaundice can become visible through the skin, mucous membranes, and sclera (2). Usually, neonatal jaundice is mild and short-lived, often resolving on its own within 1–2 weeks. However, in some infants, it can develop into severe hyperbilirubinemia, which not only risks damaging the central nervous system but may also harm other organs such as the kidneys and liver (3,4). Acute kidney injury (AKI) is a serious complication in patients with neonatal jaundice, and its incidence is about 38 % in those patients (5). Research indicates that neonatal AKI is related to higher mortality, emphasizing the importance of identifying risk factors for AKI in jaundiced neonates and adopting effective prevention and treatment approaches (6).

Numerous studies have shown that inflammation is crucial in the development and progression of AKI (7). When the kidney encounters insults such as ischemia, toxins, or infections, the innate immune system quickly activates, releasing pro-inflammatory cytokines like tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6). These inflammatory substances promote the infiltration of immune cells, such as neutrophils and macrophages, into the kidney tissue, worsening tubular cell apoptosis and necrosis. Furthermore, inflammation damages the renal tubular epithelial barrier, causes endothelial dysfunction, and impairs microcirculation, creating a continuous cycle that increasingly worsens AKI (8,9). Previous research has identified certain inflammatory markers, like interleukin-18 (IL-18), as being related to neonatal kidney injury (10). However, a single inflammatory indicator cannot accurately assess the inflammatory state in the body and may be restrictive in distinguishing high-risk AKI in patients with neonatal jaundice. Therefore, more comprehensive inflammatory biomarkers need to be found to better identify jaundiced neonates at high risk for AKI.

The systemic immune-inflammation index (SII), calculated from counts of platelets, neutrophils, and lymphocytes, is a recently proposed composite inflammatory marker that reflects patients’ inflammatory and immune status. It is known for its simplicity, accessibility, and comprehensive nature (11). Extensive research has shown a relationship between SII and the occurrence or prognosis of various diseases, including germ-cell tumors (12), sepsis (13), colorectal cancer (14), stroke (15), periodontitis (16), and non-alcoholic fatty liver disease (17). Studies on the connection between SII and AKI have found that higher SII levels are independently linked to an increased risk of AKI in adults undergoing cardiac surgery (18). Furthermore, Jia et al. reported a J-shaped relationship between SII and mortality in AKI patients (19). However, the association between SII and AKI in neonates with jaundice remains unclear. Therefore, this study aims to explore the relationship between SII and AKI using data from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database, providing vital evidence for establishing SII as a potential risk factor for AKI in neonates with jaundice. We present this article in accordance with the STROBE reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0310/rc).

Methods

Study design and participants

This study was a retrospective study based on the MIMIC-IV database. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The database, which is publicly available and approved by the institutional review boards of Beth Israel Deaconess Medical Center and the Massachusetts Institute of Technology, comprises clinical records of intensive care unit (ICU) patients admitted between 2008 and 2019. Patient data were anonymized, eliminating the need for informed consent from the patients’ legal guardian. Trained personnel who completed the Collaborative Institutional Training Initiative (CITI) program and obtained MIMIC-IV database access credentials performed the data extraction. PostgreSQL facilitated the retrieval process. We first collected data on 7,870 newborns in the Neonatal Intensive Care Unit (NICU) from the database. We screened 2,836 jaundiced newborns, all of whom had information related to the diagnosis of AKI. Then, we excluded 335 patients with a NICU duration of less than 24 hours and further excluded 175 patients with missing SII. The remaining 2,326 patients were included in this study.

Assessment of exposure variable and outcome variable

The exposure variable in this study, SII, was calculated using the formula: SII = (platelet count × neutrophil count)/lymphocyte count. Automated hematology analyzers were used to determine the values of the three cell types, measured from the first laboratory test obtained within 24 hours of NICU admission (20). The primary outcome was whether AKI occurred, while the secondary outcome was the NICU duration. The diagnostic criteria for neonatal AKI were based on the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines: a rise in creatinine to 0.3 mg/dL within 48 hours, or an increase of ≥1.5 times the initial level, or urine output <0.5 mL/kg/h for at least 6 hours (21).

Covariables

In this study, we included the following covariates: phototherapy (no vs. yes), gestational week <28 weeks (no vs. yes), intrauterine growth retardation (no vs. yes), gender (male vs. female), race (white vs. other), acidosis (no vs. yes), asphyxia (no vs. yes), sepsis (no vs. yes), vancomycin (no vs. yes), mechanical ventilation (no vs. yes), respiratory distress (no vs. yes), weight (kg), age (hours), sequential organ failure assessment (SOFA), acute physiology score-III (APS-III), heart rate (bpm), lymphocytes (%), neutrophils (%), platelet count (K/µL), red blood cell count (RBC, m/µL), red blood cell distribution width (RDW, %), white blood cell count (WBC, K/µL), hemoglobin (g/dL), and bilirubin (mg/dL).

Statistical analysis

Data analysis in this study was conducted using R software version 4.2.2. P<0.05 was considered statistically significant. Neonates with jaundice were divided into a non-AKI group and an AKI group. Mann-Whitney U tests and chi-square tests were employed to compare continuous and categorical variables between groups, respectively. Continuous variables and categorical variables were expressed as medians (quartiles) and n (%), respectively. Continuous variables with a missing rate greater than 25% were converted to categorical variables, while those with a missing rate of 25% or less were imputed using a multiple imputation method via the “mice” package (22). Notably, due to the skewed distribution of SII, the SII variable was transformed to the logarithm base 2 (logSII) before analysis (except for baseline comparison). Collinearity between variables was assessed using collinearity analysis, with a variance inflation factor (VIF) >5 indicating collinearity.

Logistic regression analyses were conducted to explore the relationship between logSII (quartile of logSII) and AKI, with adjustments made in different models (Model 1 without adjustment; Model 2 adjusting for SOFA, APS-III, sepsis, acidosis, phototherapy, and gestational week <28 weeks; Model 3: adjusting for RBC, hemoglobin, heart rate, and bilirubin group; Model 4: adjusting for SOFA, APS-III, sepsis, acidosis, phototherapy, gestational week <28 weeks, RBC, hemoglobin, heart rate, and bilirubin group). Trend regression analysis was used to assess the relationship between quartile logSII and AKI risk. Confounding factors were selected a priori based on clinical knowledge and established risk factors for neonatal AKI, rather than based on statistical significance testing. The E-value was calculated to quantify the strength of unmeasured confounding that would be required to explain away the association. Given its clinical importance, bilirubin, despite a higher proportion of missing values (34.7%), was multiply imputed and analysed as a continuous variable in sensitivity analysis, and a complete-case analysis restricted to neonates with measured bilirubin was also performed as a sensitivity analysis.

Restricted cubic splines (RCS) with four knots were used to evaluate nonlinear relationships between logSII and AKI. Subgroup analysis was conducted to examine the sensitivity of the relationship, while interaction analysis was used to explore interactions between logSII and subgroup variables on AKI. The correlation between logSII and NICU duration was additionally assessed using Spearman correlation analysis. Competing risks analysis was further performed as an exploratory analysis using the Fine and Gray subdistribution hazard approach. A univariable competing risks regression model was employed, with transfer out of the NICU defined as the event of interest and in-hospital death as the competing event. Cumulative incidence functions were estimated and plotted to visualize the probability of NICU transfer over time, stratified by the median logSII level (high vs. low). Given the small number of in-hospital deaths (n=24) and the potential misclassification inherent in defining NICU transfer based on the temporal order of ICU transfer events relative to hospital discharge (i.e., transfer out of the NICU was defined as ICU transfer occurring earlier than hospital discharge), this analysis was considered exploratory. Therefore, the results should be interpreted with caution.

Results

General attributes of the study participant

This study enrolled 2,326 patients with neonatal jaundice, including 201 cases with AKI. Table 1 demonstrates significant intergroup differences in phototherapy, gestational week <28 weeks, acidosis, sepsis, SOFA, APS-III, heart rate, lymphocytes, RBC, hemoglobin, bilirubin, and SII (all P<0.05). Compared to the AKI group, the non-AKI group exhibited higher phototherapy utilization (84.518% vs. 78.109%) and a higher proportion of gestational weeks <28 weeks (88.706% vs. 83.085%). Conversely, the AKI group showed elevated rates of acidosis (8.458% vs. 3.765%) and sepsis (15.920% vs. 6.824%). Compared to the non-AKI group, SOFA, APS-III, heart rate, and SII were significantly increased in AKI patients (all P<0.05), while lymphocyte counts, RBC, hemoglobin, and bilirubin were significantly reduced (all P<0.05).

Among the continuous variables analyzed, weight, heart rate, RBC, RDW, and hemoglobin exhibited missing data ratios ≤25%, which we addressed through multiple imputation. Bilirubin, with a missing ratio >25%, was transformed into a categorical variable. Post-processing analysis confirmed that variables initially showing significant differences retained these differences, while those without significant differences remained unchanged (Table 2).

The association of logSII with AKI in patients with neonatal jaundice

Since SII exhibited a skewed distribution, SII was converted to a logarithm base 2. To investigate the relationship between logSII and AKI, we initially assessed collinearity among the candidate covariates. All VIFs <5 confirmed the absence of multicollinearity among variables (Table S1).

Logistic regression analyses were further used to assess the independent relationship between the logSII and AKI. Table 3 demonstrates that logSII is significantly associated with AKI [Model 1: OR (95% CI): 1.226 (1.109, 1.356), P<0.001], with consistent results across adjustment models [Model 2: OR (95% CI): 1.220 (1.099,1.356), P<0.001; Model 3:OR (95% CI): 1.250 (1.128, 1.387), P<0.001; Model 4: OR (95% CI): 1.230 (1.107, 1.369), P<0.001]. Based on Model 4, the E-value for this association was 1.76 (1.45 for the lower confidence limit). In sensitivity analyses also based on Model 4, when bilirubin was multiply imputed and analysed as a continuous variable, the association remained significant [OR = 1.227 (95% CI: 1.105, 1.364), P<0.001]. Furthermore, a complete-case analysis restricted to neonates with measured bilirubin yielded consistent results [OR (95% CI): 1.256 (1.103, 1.431), P<0.001].

Trend analyses revealed that there were trends in all models [Model 1: OR (95% CI): 1.307 (1.145, 1.493), P for trend <0.001; Model 2: OR (95% CI): 1.287 (1.122, 1.478), P for trend <0.001; Model 3: OR (95% CI): 1.350 (1.180, 1.545), P for trend <0.001; Model 4: OR (95% CI): 1.308 (1.138, 1.503), P for trend =0.003], but only the highest logSII quartile (Q4) showed a significant association with AKI compared to the reference (Q1) (Table 3). In summary, logSII was independently associated with AKI.

The linearity and stability of the relationship between logSII and AKI in patients with neonatal jaundice

In a logistic regression analysis of quartiles of logSII and AKI, with Q1 as the reference, the quartile estimates were non-monotonic, and only the highest (Q4) quartile was significantly associated with AKI, with the confidence intervals for Q2 and Q3 crossing 1, indicating limited precision. To formally assess the shape of the association, we performed an RCS analysis. The RCS curve visually exhibited a pattern of first decreasing and then increasing. However, the RCS curve revealed no significant departure from linearity (P for overall <0.001, P for non-linear =0.14, Figure 1A), and this finding persisted after full covariate adjustment (P for overall <0.001, P for non-linear =0.51, Figure 1B). Formal testing did not support a statistically significant departure from linearity. Consequently, logSII was entered into the model as a linear term.

Figure 1 The RCS analysis between logSII and AKI with different adjustments. (A) without adjustment, (B) adjusting for phototherapy, bilirubin group, gestational week <28 weeks, acidosis, sepsis, SOFA, APS-III, heart rate, RBC, and hemoglobin. AKI, acute kidney injury; APS-III, acute physiology score-III; CI, confidence interval; RBC, red blood cell; RCS, restricted cubic spline; SII, systemic immune-inflammation index; SOFA, sequential organ failure assessment.

In the multivariable model, logSII remained independently associated with AKI after adjustment (Table S2). To further examine the robustness of this association, pre-specified subgroup analyses were performed across clinically relevant variables (phototherapy, illness severity (SOFA, APSIII), and RBC) (Table 4). The association between logSII and AKI was generally consistent across most subgroups, although the association did not reach statistical significance in the RBC ≥5 subgroup (P=0.07). No significant interaction was detected [all P for interaction >0.05, including phototherapy (P=0.21), SOFA (P=0.42, APS-III (P=0.09), and RBC (P=0.71)], supporting the overall robustness of the relationship.

The correlation between logSII and NICU duration in patients with neonatal jaundice

Based on the significant relationship between logSII and AKI, we further explored the relationship between logSII and NICU duration. Spearman correlation analysis revealed a statistically significant inverse association between logSII and NICU duration in the overall study patients (r=−0.174, P<0.001; Figure 2A). Subgroup analyses demonstrated that this negative correlation remained significant in both non-AKI patients (r=−0.169, P<0.001; Figure 2B) and AKI patients (r=−0.227, P=0.001; Figure 2C). Notably, patients with NICU duration >7 days exhibited significantly lower SII levels compared to those with NICU duration ≤7 days (P<0.001; Figure 2D), providing additional evidence for the inverse relationship between logSII and NICU duration.

Figure 2 The relationship between logSII and NICU duration in patients with neonatal jaundice. Spearman correlation analysis between SII and NICU duration in (A) all patients; (B) patients without AKI; (C) patients with AKI. (D) Comparison of SII between NICU duration >7 days and NICU duration ≤7 days. AKI, acute kidney injury; NICU, neonatal intensive care unit; SII, systemic immune-inflammation index.

To account for in-hospital death as a competing event, a univariable competing risks regression model was performed with transfer out of the NICU as the event of interest. The results showed that logSII, as a continuous variable, was significantly associated with an increased subdistribution hazard of NICU transfer [subdistribution hazard ratio (SHR) =1.49 (95% CI: 1.34, 1.65), P<0.001], suggesting that higher logSII levels corresponded to a shorter NICU duration. When patients were stratified by the median logSII level (high vs. low), the cumulative incidence function curves (Figure S1) consistently showed that the high logSII group had a higher cumulative incidence of NICU transfer compared to the low logSII group, whereas the cumulative incidence of in-hospital death remained low and comparable between the two groups. Taken together, these competing risks analyses indicate an inverse relationship between higher logSII levels and NICU length of stay.

Discussion

In this study, we found a positive and approximately linear relationship between logSII and AKI in patients with neonatal jaundice, and logSII was a significant independent risk factor for AKI. Furthermore, logSII was negatively correlated with the length of stay in the NICU. This negative correlation was found to be robust following validation using the Fine-Gray model (with in-hospital death as the competing event) (SHR =1.49, P<0.001).

Our study found that in patients with neonatal jaundice, the logSII was elevated and significantly positively correlated with AKI. In patients with neonatal jaundice, pathologically high bilirubin levels are associated with pro-oxidative effects, disrupting the oxidative balance in the newborn and increasing the body’s inflammatory level (23,24). Inflammation is more likely to trigger multi-organ dysfunction in newborns, and the kidneys are particularly sensitive to inflammatory stimuli (25), making AKI more likely. Furthermore, elevated SII indicates neutrophilia and lymphocytopenia, reflecting an imbalance in the body’s immune response and an active inflammatory state. Activated neutrophils release large amounts of reactive oxygen species, proteases, and proinflammatory cytokines (such as TNF-α and IL-6). These substances can directly damage renal tubular epithelial cells, causing cast necrosis and loss of barrier function. Furthermore, platelet activation also contributes to the inflammatory process, promoting microthrombosis and leading to impaired peritubular microcirculation, exacerbating the ischemic and hypoxic state (26). Although neonatal kidneys are structurally intact, their function is not yet fully mature. Renal parenchymal cells have limited anaerobic metabolic capacity, making them highly sensitive to hypoxia and have poorer tolerance to it, making them more susceptible to AKI (27). Therefore, an increase in logSII is positively correlated with AKI. This association suggests that logSII may serve as a supportive indicator to help flag neonates at higher risk of AKI, although it cannot replace established diagnostic assessment.

Based on the above findings, we further investigated the relationship between logSII and length of stay in the NICU and found a negative correlation between the two. The in-hospital mortality rate in this cohort was 1.032% (24/2,326); this low mortality rate further ruled out the possibility that competing events of death had a dominant influence on the negative correlation. This finding differs from the conclusions of most studies in paediatric populations. Previous research in paediatric burn patients has reported an association between high SII and longer hospital stays, suggesting that persistent inflammation leads to prolonged illness (28). Conversely, in children undergoing cardiopulmonary bypass surgery for congenital heart disease, studies have found that SII levels are negatively correlated with the risk of postoperative infection; that is, the higher the SII, the lower the risk of infection. This phenomenon stems from the postoperative inflammatory response activating platelets, which promotes the massive recruitment and depletion of immune cells; a reduced SII also reflects a more pronounced state of immune exhaustion in the body (29). The mechanism underlying the present study is similar to the latter: low SII may reflect a relatively sluggish or depleted immune response, leading to a prolonged disease course and extended hospital stays; whereas high SII reflects an acute inflammatory response, prompting the condition to reach the clinical intervention threshold more rapidly, triggering early aggressive treatment and thereby shortening the length of hospital stay. This finding suggests that the relationship between SII and length of hospital stay exhibits significant disease heterogeneity, and its interpretation is highly dependent on the specific disease context and treatment strategy.

This study analyzed data from patients with neonatal jaundice and found that logSII was independently and positively associated with the risk of AKI, and this relationship followed an approximately linear pattern. Given the modest effect size (per-unit adjusted OR 1.23), the observational design, and potential residual confounding by illness severity, these findings should be regarded as hypothesis-generating. They suggest that logSII, derived from a routine blood count, may help identify jaundiced neonates at higher risk of AKI, but they require validation in prospective studies before any clinical application. Although the negative correlation between logSII and shorter NICU length of stay requires further investigation, overall, these findings may provide valuable insights for future research into the assessment of neonatal jaundice risk.

This retrospective study aimed to investigate the relationship between logSII and AKI in patients with neonatal jaundice. Strengths of the study include the use of the large, publicly available MIMIC-IV ICU database, which provided a sufficient sample size and reliable data quality; the retrospective design, which allows for rapid acquisition of clinical association evidence; and the focus on the unique neonatal population, which is of great clinical significance. However, this study also has several limitations: First, as a retrospective study, causality cannot be confirmed. Second, the MIMIC-IV database primarily consists of ICU patients, which may not be representative of all neonates with jaundice, thus limiting the generalizability of our findings to non-ICU settings. Third, unmeasured confounding cannot be completely excluded, although the E-value (1.76) suggests that moderate unmeasured confounding would be needed to explain away the association. Fourth, the lack of an external validation cohort limits the generalizability of the results. Fifth, while the RCS analysis showed no statistically significant nonlinear relationship (P=0.51), the quartile pattern was non-monotonic, and the true shape of the association warrants further investigation. In addition, missing data for bilirubin (34.7%) were handled using categorization with a “missing” category, which may cause some information loss; however, sensitivity analyses using multiple imputation and complete-case analysis yielded consistent results. Future prospective cohort studies are needed to further validate this association.

Conclusions

This study first found a positive and approximately linear association between logSII and AKI in patients with neonatal jaundice. This suggests that logSII may be a useful marker to help identify neonates with jaundice at higher risk of AKI; however, given the observational design and modest effect size, prospective studies are needed to confirm its value before clinical use.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0310/rc

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0310/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0310/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The database was approved by the institutional review boards of Beth Israel Deaconess Medical Center and the Massachusetts Institute of Technology. Patient data were anonymized, eliminating the need for informed consent from the patients’ legal guardian.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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