The predictive value of the ratio of multi-dimensional inflammatory biomarkers in pediatric diseases from the perspective of pro-inflammatory/anti-inflammatory balance: a systematic review

Introduction

Inflammation protects hosts against pathogen invasion, eliminates damaged tissues and cells, establishes a microenvironment conducive to the repair of injured tissues, and mediates a series of adaptive physiological changes (1). When there is an imbalance in inflammatory regulation, either an overactivated pro-inflammatory response or an inadequate anti-inflammatory response can trigger a “cytokine storm”, causing damage to tissues and organs. This imbalance is a common mechanism underlying various diseases, including infectious diseases and autoimmune disorders, in children.

The developmental course of the pediatric immune system is unique, with notable stage-specific differences. During the neonatal period, cellular hyporesponsiveness, coupled with overactivation of immunosuppressive and tissue-protective mechanisms, may contribute to impaired innate immune function, rendering neonates susceptible to infections, sepsis, brain injury, and neurodevelopmental disorders (2). Infants and toddlers often have a predominantly Th2-skewed immune response, which may predispose them to allergic reactions and recurrent infections (3). In slightly older children (school-aged), the immune system matures progressively, and the immunoregulatory network becomes increasingly sophisticated; however, it remains functionally less efficient than the adult immune system. These developmental characteristics may render the pediatric immune system more vulnerable to external disturbances, leading to a homeostatic imbalance between pro-inflammatory and anti-inflammatory responses, accelerated disease progression, and greater heterogeneity in clinical outcomes.

Although traditional single inflammatory biomarkers may have some clinical value in pediatrics, they have substantial limitations. For example, C-reactive protein (CRP) appears to be convenient and inexpensive to measure. However, its elevation often exhibits a 4–6-hour lag phase and may also occur in non-infectious inflammatory conditions, resulting in insufficient specificity (4). Procalcitonin (PCT) may have high specificity for bacterial infections, but it often yields false-positive results in the neonatal period and may also be elevated in some children during viral infections. Interleukin (IL)-6 is a sensitive indicator of early inflammation, but it has a short half-life and high cost of detection, making it unsuitable for routine monitoring. Compared to single markers, inflammatory ratio indexes may better reflect the balance between pro-inflammatory and anti-inflammatory responses and thus warrant further validation and application in large-scale population cohort studies (5). For example, even when the level of the anti-inflammatory factor IL-10 is high, if the level of the pro-inflammatory factor IL-6 is significantly higher, the IL-6/IL-10 ratio will still increase, suggesting a risk of uncontrolled inflammation. Single biomarkers reflect the level of inflammation at a given time point, whereas ratios of inflammatory markers can dynamically represent the pro-inflammatory/anti-inflammatory balance and help predict the evolutionary trend of inflammation, thereby providing more comprehensive information for clinical decision-making.

The ratios of multi-dimensional inflammatory markers can be categorized into two major groups based on the detection principle and biological significance, covering information on inflammation at the molecular level and the cellular/protein level, thereby helping to forming a comprehensive assessment system: Class A (cytokine ratios): highly specific, it often helps reflect the balance between pro-inflammatory and anti-inflammatory responses at the molecular level, as well as the regulatory mechanisms of upstream molecules. including three types of core ratios. These ratios include classical pro-inflammatory/anti-inflammatory factor ratios [e.g., IL-6/IL-10, tumor necrosis factor-α (TNF-α)/IL-10], T-cell subpopulation balance ratios [e.g., interferon-γ (IFN-γ)/IL-4, IL-17A/IL-10], and specific pathway ratios [e.g., IL-1β/IL-1 receptor antagonist (IL-1Ra), IL-12/IL-10]. Category B [systemic inflammation ratio (SIR)]: easily accessible, it is calculated from routine blood test indicators and reflects the overall downstream pro-inflammatory and anti-inflammatory balance of inflammation, including three core indicators: leukocyte-derived ratios [e.g., neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR)], composite inflammation indices [e.g., Systemic Immune-Inflammation Index (SII), Systemic Inflammatory Response Index (SIRI)], and protein-related ratios [e.g., C-reactive protein-to-albumin ratio (CAR), fibrinogen-to-albumin ratio (FAR)]. While prior reviews have separately examined cytokine ratios or systemic inflammation indices, the present classification framework—distinguishing Class A (cytokine-based, molecular-level) from Class B (cell/protein-based, systemic-level) ratios—is proposed by the authors to provide a unified conceptual structure for comparing indicators across different biological levels. This classification is intended to complement, rather than replace, existing biomarker taxonomies. To our knowledge, this is the first systematic review to integrate both cytokine-based ratios (Class A) and SIRs (Class B) within a unified framework of pro-inflammatory/anti-inflammatory balance, providing a comprehensive, mechanistically grounded reference for precision pediatric diagnosis and treatment. We present this article in accordance with the PRISMA reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0189/rc).

Methods

We systematically searched the following databases: PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Data Knowledge Service Platform, and VIP Chinese Science and Technology Journal Database. We ensured that relevant research findings from around the world were comprehensively covered. All relevant published studies from the construction of each database to December 2025 were evaluated to ensure the timeliness and comprehensiveness of the study. The core search terms included inflammatory biomarker ratio, cytokine ratio, NLR, PLR, SII, CAR, children, pediatric, infant, neonate, sepsis, Kawasaki disease, juvenile idiopathic arthritis (JIA), pediatric multisystem inflammatory syndrome (MIS), and pro-inflammatory/anti-inflammatory balance. Search strategy: we searched the databases using a combination of subject headings and free terms, with search formulae constructed via the logical operators AND and OR.

The inclusion criteria of this review were as follows: (I) study types: randomized controlled trials (RCTs), cohort studies, case-control studies, cross-sectional studies, systematic reviews, meta-analyses, and basic experimental studies; (II) study population: only children (≤18 years old), including neonates, infants, school-age children, and adolescents; (III) research content: studies on the correlation between multi-dimensional inflammatory marker ratios (class A cytokine ratio or class B systemic inflammatory ratio) and childhood diseases, including disease prediction, assessment, prognosis, and treatment response monitoring; (IV) data integrity: literature providing clear study design, detection methods, main data results, and statistical analysis methods; (V) language: both Chinese and English were acceptable.

Exclusion criteria were as follows: (I) studies involving adults (>18 years old) or animals; (II) studies assessing only a single inflammatory marker without ratio analysis; (III) duplicate publications, conference abstracts, dissertation drafts, non-systematic reviews, and studies with unavailable full text; (IV) studies with serious flaws in study design, contradictory data, or no statistical analysis; (V) case reports and small-sample studies on rare diseases with a final effective sample size <10 (rare diseases were defined in accordance with the latest official National Catalogue of Rare Diseases).

The studies were screened independently by two researchers using the aforementioned inclusion and exclusion criteria. Any disagreement between the researchers was resolved through negotiation or arbitration by another researcher. The data were extracted on basic information of the study (authors, year of publication, and country of origin), the participants involved in the study (age, gender, sample size, and disease type), types of inflammatory marker ratios and detection methods, the main findings of the study (diagnostic efficacy, correlation analysis, predictive value, etc.), the statistical methods used, and the conclusions drawn. The quality of the included studies was assessed using appropriate tools. The Cochrane risk-of-bias assessment tool was used for RCT; the Newcastle-Ottawa Scale (NOS) was used for cohort and case-control studies; the AMSTAR2 scale was used for systematic reviews and meta-analyses; and the ARRIVE guideline evaluation criteria were used for basic experimental studies. Basic research was used solely to supplement the biological mechanisms and interpretative rationale of inflammatory marker ratios, with no extraction of clinical predictive or diagnostic data. All clinical conclusions are derived exclusively from clinical studies. Only studies of moderate quality and above were included for review and analysis. Articles that did not meet the inclusion criteria, such as research design flaws, incomplete data, or low quality, were excluded, leaving 32 articles included in the systematic review. The literature screening process is shown in Figure 1.

Figure 1 Literature screening process. CNKI, China National Knowledge Infrastructure.

Results

Category A: cytokine-based specific ratios and their clinical applications

As core signaling molecules between immune cells, cytokines often reflect an imbalance between pro- and anti-inflammatory responses via alterations in their ratio, which may be of great importance for precise phenotyping and targeted therapeutic guidance in pediatric diseases. Based on their biological functions and signaling pathway characteristics, specific cytokine-based ratio indicators can be classified into three major categories, upon which comprehensive comparisons are conducted. Classic ratios, such as IL-6/IL-10, TNF-α/IL-10, and IL-18/IL-10, often help reflect the balance between the body’s overall inflammatory burden and immune homeostasis by quantifying the dynamic antagonistic relationship between pro-inflammatory and anti-inflammatory cytokines, and thus may serve as core parameters for assessing the severity of cytokine storms. T-cell subset balance ratios, including IFN-γ/IL-4 and IL-17A/IL-10, may capture the functional antagonism among different effector subsets to reveal the polarization direction and regulatory imbalance of adaptive immune responses, providing important evidence for determining the orientation of immune responses. Specific inflammatory pathway ratios, such as IL-1β/IL-1Ra, enable precise quantification of the agonist and antagonist components in key signaling axes, which may more specifically reflect the activation intensity and regulatory status of a particular inflammatory pathway, thereby offering direct molecular-level references for the formulation of targeted therapeutic regimens. Compared with the absolute concentrations of individual cytokines, the aforementioned ratio indicators may effectively eliminate interference from interindividual differences in baseline inflammatory levels. They exhibit higher sensitivity and specificity in dynamically monitoring disease progression, evaluating therapeutic responses, and predicting clinical outcomes, and have become an important research direction in the field of precise assessment of pediatric inflammatory diseases.

IL-6/IL-10 ratio

IL-6 is mainly secreted by monocytes/macrophages and T cells. It is the core driver of the inflammatory cascade, inducing the acute-phase response, promoting B cell differentiation, and triggering fever. IL-10 is mainly derived from regulatory T cells (Treg) and Th2 cells, and may play an endogenous anti-inflammatory role by inhibiting the release of pro-inflammatory factors and limiting the activation of immune cells. A high IL-6/IL-10 ratio may indicate that the intensity of pro-inflammatory response greatly exceeds the anti-inflammatory ability, which may suggest that the risk of uncontrolled inflammation is notably increased.

Several studies on pediatric diseases have supported the predictive value of such cytokine ratios. In childhood pneumonia, the IL-6/IL-10 ratio may help predict coinfection, with a diagnostic sensitivity of approximately 94%, and may be clinically useful for early identification of patients with severe Mycoplasma pneumoniae pneumonia at risk of coinfection (6). The IL-6/IL-10 ratio is often higher in children affected with pediatric sepsis than in those not affected by sepsis, and a high ratio may indicate the development of sepsis in infected children (7).

TNF-α/IL-10 ratio

TNF-α is an early pro-inflammatory cytokine that induces the apoptosis of cells, activates vascular endothelial cells, and may exacerbate tissue damage. IL-10 may mitigate inflammation by inhibiting TNF-α secretion. A high ratio of TNF-α/IL-10 reflects the early loss of control of acute inflammatory responses. In neonatal sepsis, this ratio may be positively correlated with disease severity and may serve as an indicator for the early identification of neonatal infections (8). In pediatric trauma, an early increase in the TNF-α/IL-10 ratio may indicate an increase in the risk of multiple organ dysfunction, thus providing an early warning for preventing post-traumatic complications (9).

IL-18/IL-10 ratio

IL-18 serves as a specific marker of inflammasome activation, promoting Th1 cell differentiation and IFN-γ release while exacerbating cell-mediated inflammatory damage. IL-10 counteracts the pro-inflammatory effects of IL-18. This ratio may hold diagnostic value in macrophage activation syndrome (MAS). Pediatric MAS patients frequently exhibit considerably high levels of IL-18, accompanied by an often high IL-18/IL-10 ratio, which may serve as a distinguishing indicator between MAS and other autoimmune disorders (10).

Notably, the significant elevation of IL-18 may be associated with a relatively specific pathological background. The ratio of IL-18 to IL-10 not only reflects the activation level of the inflammasome pathway but also quantifies, to some extent, the imbalance between cellular immune-mediated pro-inflammatory and anti-inflammatory regulation. This may provide a mechanistically based biological marker for the early identification of MAS and the assessment of its disease severity.

IFN-γ/IL-4 ratio (Th1/Th2 balance)

IFN-γ, secreted by Th1 cells, primarily mediates cellular immunity, enhances macrophage phagocytosis, and helps combat intracellular pathogens. IL-4 is secreted by Th2 cells; it drives humoral immunity, helps promote antibody production by B cells, and participates in anti-parasitic infections and allergic reactions. The IFN-γ/IL-4 ratio reflects the equilibrium between Th1 and Th2 cells, with a low ratio indicating Th2 polarization and a high ratio suggesting Th1 dominance.

In pediatric allergic and infectious diseases, this ratio may have potentially significant clinical importance. In childhood allergic asthma, a low IFN-γ/IL-4 ratio before treatment and its subsequent recovery following specific immunotherapy serve as objective indicators for helping evaluate efficacy (11). In the acute phase of Henoch-Schönlein purpura, an imbalance between Th1 and Th2 cells is observed, characterized by a predominant Th2 response. IL-4-mediated immunity suppresses the production of the Th1-type cytokine IFN-γ, thereby leading to a reduced IFN-γ/IL-4 ratio. Accumulating evidence indicates that restoring the IFN-γ/IL-4 ratio to normal levels may serve as a valuable immunological marker of disease remission (12). In atopic dermatitis, the IFN-γ/IL-4 ratio may reflect the degree of Th2 polarization, which helps optimize anti-allergic treatment regimens.

Based on the aforementioned evidence, the IFN-γ/IL-4 ratio serves as a useful quantitative parameter for the Th1/Th2 immune balance and reflects not only the current immune polarization status of the disease but also dynamically tracks the transformation of the immune response direction. Compared with the detection of a single cytokine, this ratio offers greater directionality and interpretability in therapeutic efficacy assessment and disease monitoring, and is expected to become an important auxiliary indicator for individualized treatment decisions in pediatric allergic diseases.

IL-17A/IL-10 ratio (Th17/Treg balance)

IL-17A, secreted by Th17 cells, recruits neutrophils, activates inflammatory pathways, and contributes to the development of autoimmune diseases and infectious inflammation. IL-10, secreted by Treg cells, helps maintain immune tolerance by suppressing the activation of Th17 cells. Elevated IL-17A/IL-10 ratio, which may be a critical molecular indicator of Th17 cell hyperactivation and defective Treg cell immunosuppressive function, contributes to the disruption of pro-inflammatory and anti-inflammatory immune network homeostasis and the impairment of peripheral immune tolerance.

This ratio may have potentially significant clinical value in pediatric autoimmune diseases. In JIA, high levels of IL-17A/IL-10 in both serum and synovial fluid are positively correlated with the Juvenile Arthritis Disease Activity Score (JADAS), serving as markers for disease monitoring and helping assess treatment responses (13). In asthma, the IL-17A/IL-10 ratio may help predict disease activity. IL-17A was downregulated by four-fold and seven-fold in mild and severe asthma groups, respectively. This finding contradicts the conventional understanding that IL-17A levels are high in individuals with severe asthma. Upon analyzing the potential mechanisms, researchers found that all pediatric asthma patients included in that study presented with allergic asthma (predominantly Th2-mediated). The expression of IL-17A may be suppressed by Th2 cytokines, such as IL-4 and IL-13. Moreover, the proportion of neutrophilic asthma cases in this study was extremely low, contributing to the overall downregulation of IL-17A expression (14). In pediatric systemic lupus erythematosus (SLE), high levels of IL-17A are accompanied by low levels of IL-10. The IL-17A/IL-10 ratio is correlated with the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI), providing a reference for immunomodulatory therapy in SLE.

It should be emphasized that the clinical interpretation of the IL-17A/IL-10 ratio should generally be combined with the immunophenotypic background of the disease. As illustrated in the aforementioned asthma study, the direction of change in this ratio may differ across disease subtypes with distinct immune polarization patterns. The simplistic application of a uniform threshold may lead to misjudgment. Therefore, when applying the IL-17A/IL-10 ratio to clinical decision‑making, it is often advisable to fully consider the child’s disease subtype, dominant immune pathways, and the overall characteristics of the accompanying cytokine profile, so as to achieve accurate evaluation of Th17/Treg imbalance and its individualized clinical application.

IL-1β/IL-1Ra ratio

IL-1β is a key pro-inflammatory factor in the IL-1 family; it can activate the NF-κB pathway to exacerbate inflammatory responses. The IL-1Ra functions as an endogenous blocker of the IL-1 receptor, competitively binding to IL-1 receptors to inhibit the pro-inflammatory effects of IL-1β. A high IL-1β/IL-1Ra ratio may indicate overactivation of the IL-1 pathway, serving as a hallmark feature of autoinflammatory diseases.

In children affected with Systemic Juvenile Idiopathic Arthritis (sJIA), the IL-1β/IL-1Ra ratio is often elevated, which may indicate that sJIA is an IL-1-driven autoinflammatory disorder. This ratio may serve as a diagnostic marker for sJIA and provides support for the rationale for IL-1 inhibitor therapy (e.g., anakinra, canakinumab) (15). In neonatal-onset multisystem inflammatory disease (NOMID), persistent activation of the IL-1 pathway increases the IL-1β/IL-1Ra ratio, which may serve as an indicator for both diagnosis and treatment monitoring. As IL-1β levels are considerably elevated and the IL-1β/IL-1Ra ratio is high in patients with MAS, IL-1-targeted therapy may be effective (16).

From the perspective of translational medicine, the clinical value of the IL-1β/IL-1Ra ratio lies not only in disease diagnosis and classification but also in its ability to help quantify the net activation intensity of the IL-1 pathway, thereby offering objective molecular evidence for determining the timing of targeted therapy initiation and adjusting treatment doses. Compared with other inflammatory ratio indicators, this ratio shows a more direct correlation with specific therapeutic targets and may play a unique role in guiding precision treatment decision-making for pediatric autoinflammatory diseases.

A comprehensive comparison of Category A ratio indicators is presented in Table 1.

Category B—systemic inflammatory ratios based on routine blood tests and their clinical applications

Category B ratios are calculated based on routine indicators, including complete blood count and biochemical tests, acting as simple surrogate markers for the systemic pro‑inflammatory/anti-inflammatory balance. Characterized by easy detection, low cost, and high accessibility, they are suited for rapid screening in primary care hospitals and emergency departments and have been widely applied for the early identification and severity stratification of pediatric diseases. Based on their indicator composition and information integration dimensions, Class B ratios can be categorized into three major types, and a comprehensive comparison is performed across them. Leukocyte-derived ratios, such as the NLR, PLR, and monocyte-to-lymphocyte ratio (MLR), often help reflect the dynamic balance between innate and adaptive immune responses by quantifying the relative proportions of different immune cell subsets, and may serve as fundamental parameters for evaluating the degree of systemic inflammation and immunosuppression. Comprehensive inflammatory indices, including the SII and SIRI, further integrate multiple cellular parameters (e.g., platelets and monocytes) based on single-leukocyte ratios. Through the synergistic superposition of multi-dimensional information, these indices more comprehensively capture the interactive disorders among the three axes of inflammatory response, thrombosis activation, and immune regulation, and thus may possess greater information integration advantages in the severity assessment of complex critical illnesses. Protein-related ratios, such as the CAR and FAR, combine the dynamic changes of acute-phase proteins with nutritional reserve status. From a unique perspective of inflammation-nutrition interaction, they help quantify the intensity of the body’s overall stress response and its reserve capacity, thereby providing important supplementary value in the comprehensive evaluation of children with chronic diseases, critical illnesses, and tumors. These three types of indicators exhibit distinct characteristics in terms of clinical application scenarios and predictive focuses. Their rational combination is expected to provide a more comprehensive basis for early identification and precise stratification of inflammatory diseases in children.

NLR

Under stress or inflammatory states, cortisol and catecholamines released by the body help promote neutrophil mobilization and de-marginalization, leading to an increase in neutrophil counts. Concurrently, cortisol induces the apoptosis of lymphocytes and promotes the redistribution of lymphocytes to tissues, thereby decreasing lymphocyte counts. NLR, calculated as the ratio of absolute neutrophil count to absolute lymphocyte count, acts as a simple surrogate marker for the overall pro‑inflammatory/anti-inflammatory balance. An elevated NLR may indicate a combined state of systemic inflammation and stress.

Pediatric NLR reference values exhibit age specificity, and researchers have established age-stratified and gender-stratified reference ranges from birth to 18 years. Neonatal NLR levels are physiologically elevated and decrease gradually with age. The predictive value of NLR in pediatric diseases has been extensively validated. Prospective studies on childhood sepsis have demonstrated that initial NLR is a significant biomarker for predicting severe sepsis, and that the combined use of PCT may enhance the efficacy of early identification (17). Meta-analyses suggest that NLR values are significantly higher in septic neonates than in healthy controls [standardized mean difference (SMD) =1.81, 95% confidence interval (CI): 1.14–2.48, P<0.001]. NLR is a promising biomarker that can be readily integrated into clinical practice to aid in diagnosing neonatal sepsis (18). In Kawasaki disease, systematic reviews and meta-analyses have supported that high NLR may be an independent risk factor for predicting non-response to intravenous immunoglobulin (IVIG) and coronary artery lesions (CAL) (19).

Based on the existing evidence, NLR, a ratio derived from routine blood tests, has several key advantages, including low detection cost, high clinical utility, and the ability to integrate dynamic information on innate and adaptive immune responses. However, the non-specificity of NLR is its inherent limitation—physiological stress, glucocorticoid use, and age-related physiological fluctuations in lymphocytes can all affect its value. During clinical interpretation, comprehensive judgment should be made in combination with age-stratified reference intervals for children and accompanying clinical indicators, to avoid misjudgment arising from over-reliance on NLR thresholds.

PLR

Platelets participate in hemostasis and serve as a significant source and carrier of inflammatory mediators. During inflammatory states, platelet activation increases and lymphocyte counts decrease concurrently, leading to an increase in PLR (calculated as platelet count divided by absolute lymphocyte count). This may reflect the presence of a synergistic interaction between thrombosis and inflammation.

In pediatric diseases, PLR is primarily used for neonatal infections and trauma. In individuals with early-onset neonatal sepsis, PLR is significantly elevated with an area under the curve (AUC) of 0.89–0.93. At a cut-off value of 39.5–57.7, sensitivity ranges from 88.9% to 91.3%, and specificity ranges from 94.7% to 97.6% (20). In individuals suffering from pediatric trauma, PLR demonstrated an AUC of 0.764 for helping predict the severity of injuries, with 90% sensitivity and 85% specificity at a cut-off value of 61.83 (21). Significant variation in PLR cut-off values across different diseases may be related to differences in the maturation of the immune system and disease pathophysiology between neonates and children. For clinical application, appropriate cut-off values tailored to specific conditions need to be selected.

In addition, compared with the NLR, PLR has distinct advantages in situations involving synergistic activation of thrombosis and inflammation, particularly in disease states with platelet activation. However, platelet count is easily affected by multiple factors, such as infection, nutritional status, and bone marrow hematopoietic function, and its independent predictive value remains to be further verified in large-sample, multicenter studies.

MLR and lymphocyte-to-monocyte ratio (LMR)

Monocytes are the core cells of innate immunity and can differentiate into macrophages and dendritic cells, thereby participating in inflammatory responses and antigen presentation. The MLR (calculated as absolute monocyte count divided by absolute lymphocyte count) reflects activation of the monocyte-macrophage system when elevated. As the reciprocal of MLR, LMR provides mutually supportive clinical significance with MLR. In neonatal sepsis, LMR is valuable for differentiating early‑onset sepsis from lateonset sepsis (with an LMR cut-off value ≥10.92, specificity 98.7%, and sensitivity 8.1%) (22). In pediatric Hodgkin lymphoma, MLR is associated with prognosis and may serve as a monitoring indicator for tumor progression (23).

Notably, research evidence for MLR and LMR in pediatric diseases remains relatively limited. Most available data are derived from adult oncology and critical care settings. The reference intervals and clinical cut-off values for these ratios across different pediatric age groups have not been systematically established. Larger-scale prospective studies in pediatric populations are warranted to explore their independent predictive value.

SII

SII = (platelet count × neutrophil count)/lymphocyte count. This index integrates three key indicators, including platelets (thrombotic inflammation), neutrophils (inflammatory response), and lymphocytes (immune regulation), to comprehensively reflect systemic pro‑inflammatory/anti-inflammatory balance and immune status, with predictive performance superior to any single ratio alone.

In pediatric diseases, SII appears to show greater predictive value than isolated white blood cell ratios. Retrospective studies on MIS-C have reported that SII outperforms NLR and PLR in helping predict disease severity and cardiovascular involvement. In pediatric pneumonia caused by Mycoplasma pneumoniae, SII could serve as an auxiliary indicator to help evaluate the severity of hospitalized children and guide the selection of treatment intensity (24). In pediatric acute appendicitis, SII demonstrates high diagnostic accuracy, reducing unnecessary surgery (25). In pediatric chronic kidney disease, SII serves as a candidate biomarker for predicting dialysis requirement, with high predictive efficacy when incorporated into random forest classifiers (26).

By integrating three dimensions—thrombotic inflammation, innate immunity, and adaptive immunity—into a single index, SII may offer more comprehensive information integration than binary ratio indicators such as NLR and PLR. This partially accounts for its superior predictive performance compared with single leukocyte ratio indices across various pediatric diseases. However, the calculation of SII involves the product of three hematological parameters, leading to a wide range of numerical values and significant variations in cut-off values across different diseases. Currently, standardized reference intervals for the pediatric population have not been established, and cautious interpretation in clinical practice remains necessary, taking into account the specific disease context and age stratification.

Other composite indices

SIRI = (neutrophil count × monocyte count)/lymphocyte count. Incorporating monocyte metrics provides a more precise reflection of monocyte-macrophage activation and helps predict cardiovascular involvement in MIS-C. Aggregate Inflammatory Systemic Index (AISI) = (neutrophil count × monocyte count × platelet count)/lymphocyte count. By integrating four cellular markers, it may offer the greatest information content, but has been studied less frequently in pediatric settings. Neutrophil-lymphocyte-platelet ratio (NLPR) = NLR × platelet count. In pediatric sepsis, NLPR demonstrated the highest AUC (0.748), comparable to the Pediatric Critical Illness Score (PCIS), and may serve as a supplementary prognostic indicator (27).

A common characteristic of the above-mentioned composite indices is their attempt to enhance information integration by including more cellular parameters. Nevertheless, the expansion of information dimensions does not necessarily result in a proportional improvement in predictive efficacy. Currently, research on the application of these indicators in pediatric diseases is still in its initial stage. Most of the evidence comes from single‑center retrospective studies with limited sample sizes, and systematically established age‑stratified reference intervals for children are still lacking. In the future, high-quality prospective multicenter studies are required to clarify further the applicable scenarios and clinical positioning of each indicator.

CAR

CRP is a positive acute-phase protein whose hepatic synthesis increases during inflammatory states. Albumin is a negative acute-phase protein whose synthesis decreases during inflammation and whose levels further decrease due to capillary leakage and increased consumption. CAR = CRP (mg/L)/albumin (g/L). An increase in CAR may reflect the dual effects of inflammatory response and nutritional depletion, offering greater predictive value than CRP or albumin alone.

In pediatric diseases, CAR application includes critical illness, infections, and autoimmune disorders. In critically ill children, elevated CAR levels are significantly correlated with increased 28-day mortality, with the highest quartile relative risk (RR) =1.51 (95% CI: 1.07–2.13) (28). In pediatric severe burns, CAR shows a significant positive correlation with the length of hospital stay (r=0.529, P<0.001) and may help predict the duration of hospitalization (29).

CAR integrates inflammatory intensity and nutritional reserve into a single ratio. Its biological logic lies in the fact that isolated elevation of CRP can be observed in various mild to moderate inflammatory conditions, whereas elevated CRP accompanied by a simultaneous decrease in albumin may indicate that the body has entered a synergistic deteriorating phase of inflammation and catabolism. This complex pathological state has greater clinical early-warning significance than abnormalities in a single indicator. However, albumin levels are influenced by multiple non-inflammatory factors, including nutritional status, liver function, and fluid resuscitation. When interpreting CAR, these confounding factors should generally be fully taken into account to avoid over-reliance on a single ratio threshold and neglect of the overall clinical background of the child.

Other protein-related ratios

In the FAR, fibrinogen may serve as a positive acute-phase protein involved in coagulation and inflammation. A high FAR may reflect a combined disturbance of inflammation, coagulation, and nutrition. In pediatric neuroblastoma, the albumin-to-fibrinogen ratio (AFR) may serve as a prognostic factor. The Prognostic Nutritional Index (PNI) = albumin (g/L) + 5 × lymphocyte count (×10⁹/L). By integrating nutritional status and immune function, it helps assess the nutritional-immune interaction state in pediatric oncology and critical care, guiding nutritional support therapy.

A common characteristic of the above-mentioned protein-related ratios is that they combine the dynamic changes of acute-phase proteins with nutritional or coagulation status, helping quantify the degree of interactive disorders among the three axes of inflammation, nutrition, and coagulation from different perspectives. Compared with single inflammatory ratio indicators, these indices have unique advantages in reflecting the body’s overall reserve capacity and disease tolerance and may be particularly suitable for the comprehensive assessment of children with chronic diseases or critical illnesses characterized by a long disease course and significant nutritional requirements. However, high-quality research evidence on the above indicators in the pediatric field is still limited, and determining their clinical cut-off values and applicability across different diseases requires further systematic verification.

A comprehensive comparison of Category B ratio indicators is summarized in Table 2.

Age‑stratified reference ranges for common inflammatory biomarkers in children are listed in Table 3.

Discussion

Application in infectious diseases

Sepsis is a major cause of critical illness in children, and multi-dimensional ratios may be used to help assess the condition in different dimensions. For example, the IL-6/IL-10 ratio reflects the inflammatory balance and may help predict mortality; the NLR may aid early sepsis identification, and meta-analyses have confirmed its sensitivity and specificity to be 79% and 91%, respectively. The PLR has excellent diagnostic efficacy in neonatal sepsis (AUC =0.89–0.93). CAR may help predict 28-day mortality (RR =1.51), while NLPR aids in prognostic assessment (AUC =0.748). In clinical practice, early screening can be performed by combining NLR with PCT; when used along with CAR, it may help assess the severity of the disease and dynamically monitor the change in the ratio to guide the therapeutic adjustment (30).

Notably, although the combined application of the above multi-dimensional ratio indicators in sepsis has theoretical advantages, there is currently no uniform evidence-based standard for weight assignment among indicators or determination of combined cut-off values. Mechanical superposition should be avoided in clinical practice; instead, individualized comprehensive judgment should be made based on the child’s age, underlying diseases, and dynamic changes in clinical condition.

Disease stratification may serve as a key reference for clinical therapeutic decision-making in pediatric community-acquired pneumonia. For children with mild disease, the NLR can be used as a rapid screening marker. In one study, an IL-6/IL-10 ratio greater than 5 was associated with an increased risk of severe pneumonia. For the assessment of treatment response, changes in the IL-6/IL-10 ratio may be monitored on day 3 of antibiotic therapy: a declining ratio generally may indicate a favorable response to treatment, whereas a persistently elevated ratio suggests a poor response and could support prompt adjustment of the antibiotic regimen or evaluation for concurrent complications.

This stratified application strategy demonstrates the complementary value of multi-dimensional ratio-based biomarkers in the adjunctive management of childhood community-acquired pneumonia. NLR is advantageous for its rapid availability and suitability for initial screening, while the IL-6/IL-10 ratio excels in mechanistic specificity, making it may be useful for severe disease identification and therapeutic response monitoring. Rational combined use of these two markers is expected to reduce unnecessary hospitalizations and excessive antibiotic use, while lowering the risk of missed severe cases, thereby providing a more robust decision-making framework for precise severity-stratified management of pediatric pneumonia.

Applications in immune/inflammatory diseases

The diagnosis and treatment of Kawasaki disease may facilitate auxiliary disease management by multi-dimensional ratios. To elaborate, NLR and PLR may be helpful for early recognition in the diagnostic stage; CAR and SII may be useful for predicting IVIG non-response at the risk stratification stage; NLR and CAR are rechecked to determine the efficacy of IVIG at the treatment response assessment stage. In refractory cases, the IL-6/IL-10 and IL-17A/IL-10 ratios are determined to help elucidate the immunopathological mechanism and guide second-line therapy (e.g., infliximab vs. tocilizumab). The combination of NLR + PLR and CAR alone can effectively help predict IVIG non-response, and NLR may help predict CAL (31).

Notably, the application of the aforementioned multi-dimensional ratio indicators in the whole-course management of Kawasaki disease is not isolated but forms a sequential decision-making chain covering early identification, risk stratification, and therapeutic efficacy evaluation. The application of IL-6/IL-10 and IL-17A/IL-10 ratios is particularly crucial in refractory cases. These ratios can not only help reveal individual differences in immunopathological mechanisms but also provide a mechanistic basis for selecting targeted drugs such as infliximab and tocilizumab, thereby promoting the development of precision-based second-line treatment for Kawasaki disease.

MIS-C is often characterized by an extremely high IL-6/IL-10 ratio, which helps facilitate the differentiation of MIS-C from KDSS. SII and SIRI are predictive of cardiovascular involvement and may provide a reference for risk stratification in intensive care settings (32). Dynamic monitoring of the IL-6/IL-10 ratio and SII enables the assessment of treatment response and disease remission.

As a newly recognized pediatric inflammatory syndrome, research on the application of multi-dimensional ratios in MIS-C is currently accumulating rapidly. Most existing evidence comes from small-sample retrospective studies, and the diagnostic thresholds and predictive efficacy of various indicators require further validation by large-sample prospective studies. With a deeper understanding of the immunopathological mechanisms of MIS-C, precise immune stratification based on cytokine ratios may provide more robust evidence-based support for formulating individualized therapeutic strategies for this disease.

Clinical integration strategy

Given the characteristics of Class A and Class B ratios, a stratified diagnosis and treatment strategy could be established. Nevertheless, the proposed strategy in this study is merely a theoretical model and requires further validation in prospective studies. Specifically, in primary care/emergency settings, type B ratios (NLR, PLR, SII, and CAR) should be prioritized for rapidly screening children at high risk. In tertiary hospital/specialty settings, type A ratios (IL-6/IL-10, IL-17A/IL-10, etc.) should be incorporated for precise subtyping and guiding targeted therapy. In complex and critical cases, dynamic monitoring of combined type A and type B ratios should be adopted to comprehensively assess changes in the inflammatory status and optimize treatment regimens. A hierarchical diagnosis and treatment strategy needs to be developed based on the characteristics of type A and type B ratios, with the specific process illustrated in Figure 2.

Figure 2 Flowchart of clinically stratified diagnosis and treatment for multi-dimensional inflammatory marker ratios. CAR, C-reactive protein-to-albumin ratio; IL, interleukin; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; SII, Systemic Immune-Inflammation Index.

Challenges and prospects

Currently, the clinical application of multi-dimensional inflammatory ratios still faces three core challenges. First, reference ranges for most ratio-based indicators originate from studies on adults. Only NLR, PLR, and LMR possess age-stratified pediatric reference intervals. Pediatric-specific reference values for other indicators (e.g., SII, CAR) remain unestablished, leading to biases in clinical interpretation. The lack of a pediatric reference value system is the core bottleneck hindering the clinical adoption of the aforementioned ratio indicators, particularly in neonates and young infants. The resolution of this problem depends on the systematic accumulation and sharing of multicenter, large-sample data from healthy pediatric cohorts. Second, cytokine ratios are greatly affected by detection kits, detection time, and sample processing methods, and the results of different laboratories are poorly comparable. Although Class B ratios are based on routine testing, differences in routine blood testing instruments may lead to deviations in cell counts. The essence of the detection standardization issue is that the clinical value of ratio indicators depends heavily on data reproducibility. If test results lack comparability across institutions, cut-off values established based on single-center data will be difficult to disseminate and apply. This, to a certain extent, hinders the effective translation of existing research achievements into clinical practice. Third, factors such as age, comorbidities, medications (e.g., glucocorticoids, immunosuppressants), nutritional status, and timing of blood collection, among others, may affect the ratio results. In clinical application, it is often advisable to consider the condition of the child to avoid reliance on a single ratio index, which may lead to misjudgment.

Moving forward, large-scale, multicenter prospective cohort studies should be prioritized to validate the clinical value of ratio indicators across different diseases and populations, establish high-level evidence-based medical evidence, and clarify the optimal cut-off values and applicable scenarios for each ratio. This is a critical prerequisite for promoting these ratio indicators from exploratory research to inclusion in clinical guidelines. Meanwhile, artificial intelligence (AI) technologies should be integrated with clinical data (age, sex, vital signs), inflammatory ratios (Class A + Class B), omics data (genomics, metabolomics, microbiomics), and time-series monitoring data to construct dynamic, personalized risk prediction models. These models should help improve accuracy and timeliness while ensuring clinical interpretability and feasibility for deployment in primary care settings, thereby helping support their clinical translational value. Notably, the enhancement of model complexity must be constrained by clinical interpretability and practical deployability, avoiding overemphasis on algorithmic accuracy at the cost of applicability in primary medical institutions. In addition, innovations in POCT technologies should be promoted. Microfluidic chips, biosensors, and other advanced platforms should be used to achieve real-time detection of cytokine ratios, and AI-assisted decision-making systems should be developed to extend the precision of diagnosis and treatment to primary care. Multidisciplinary collaboration among clinical medicine, engineering technology, and health policy fields is required to overcome multiple barriers to technology implementation. The ultimate goal of technological innovation and clinical translation is to realize real-time and individualized diagnosis and treatment decisions; however, the clinical implementation of related technologies still needs to address multiple practical obstacles, including data security, algorithmic regulation, and medical ethics, which necessitate cross-disciplinary collaboration between clinical medicine, engineering technology, and health policy sectors. Finally, emphasis should be placed on expanding research on neonatal diseases such as necrotizing enterocolitis (NEC) and hypoxic-ischemic encephalopathy (HIE), and on exploring the changing guidelines and clinical value of multi-dimensional inflammatory marker ratios in this special population. This will not only provide new biomarkers for early intervention in neonatal critical illnesses but also deepen understanding of the biological significance of inflammatory ratios from a developmental immunology perspective.

Limitations of this review

This study still has dual limitations regarding methodology and the indicators themselves, and the comprehensiveness and reliability of the overall conclusions remain to be further improved. From a methodological perspective, first, there is a restriction on retrieval languages: only Chinese and English literature were included in this study, which inevitably results in the omission of relevant studies published in other languages. This limitation may disproportionately affect conclusions regarding biomarkers that are more extensively studied in non-English literature. Second, there are limitations in literature types: in some sub-fields, such as neonatal diseases, the number of high-quality clinical and basic studies is relatively small, and the strength of existing evidence is insufficient to support robust conclusions. Third, there is significant heterogeneity in detection methods: the detection kits, detection instrument models, and operating procedures used in each included study all have certain differences, which directly lead to a substantial decrease in the horizontal comparability of research results. Fourth, the control of confounding factors is inadequate: some studies failed to adequately correct for key confounding factors, such as age and underlying comorbidities, further weakening the robustness of the final conclusions. Meanwhile, the inflammatory marker ratio indicators focused on in this study also have inherent conceptual limitations. First, such ratios can only unilaterally reflect the local immune status of the body, unable to fully depict the complex and interwoven inflammatory regulatory network in the body, thus making it difficult to comprehensively reflect the overall picture of the body’s inflammatory response. Second, the clinical interpretation of ratio results has strong site, time, tissue, and age specificity; a single fixed diagnostic threshold lacks clinical universality and cannot be adapted to various clinical scenarios. Third, the indicator results are highly susceptible to interference from multiple external factors, such as hormonal interventions, nutritional status, blood transfusion therapy, and body stress, so they cannot be used alone as the sole basis for disease diagnosis, condition assessment, and clinical decision-making in clinical applications. Fourth, age-specific reference intervals for the pediatric population are severely lacking; most relevant studies directly adopt adult reference data, thereby greatly reducing the accuracy and applicability of indicators in the pediatric field. Finally, the majority of conclusions in this review are hypothesis-generating rather than practice-changing, and cannot be directly adopted into clinical guidelines without further validation.

Conclusions

The multi-dimensional inflammatory marker ratio overcomes the limitations of traditional single markers from the perspective of the balance between pro-inflammatory and anti-inflammatory factors, providing a comprehensive perspective from molecular to cellular, micro to macro, to help assess childhood diseases. A cytokine ratio (e.g., IL-6/IL-10, IL-1β/IL-1Ra) has high specificity, making it suitable for accurate typing and targeted therapy. Class B systemic inflammatory ratio (e.g., NLR, SII, and CAR) is convenient and strong; therefore, it is suitable for early screening and disease stratification. In clinical practice, the synergistic integration of class A and class B ratios is expected to establish a more comprehensive decision-making framework for the stratified diagnosis and treatment of pediatric diseases. In the future, a child-specific reference value system needs to be established, prospective validation studies need to be conducted, and AI needs to be combined with POCT technology to promote the widespread application of multi-dimensional inflammation ratios for the accurate and individualized diagnosis and treatment of children, to help improve the prognosis of children’s diseases.

In summary, the establishment and optimization of a multi-dimensional inflammatory marker ratio system may help transform the traditional evaluation model of pediatric inflammatory diseases, which is characterized by overreliance on single indicators and insufficient dynamic integration. This will drive pediatric clinical decision‑making toward a precision medicine paradigm guided by pathological mechanisms and driven by objective data.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0189/rc

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0189/prf

Funding: This work was supported by Hainan Province Clinical Medical Center (No. QWYH202175).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2026-0189/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.

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/.

References

1. Harvanová G, Duranková S. Inflammatory process: Factors inducing inflammation, forms and manifestations of inflammation, immunological significance of the inflammatory reaction. Alergologia Polska-Polish Journal of Allergology 2025;12:54-61.
2. Tsafaras GP, Ntontsi P, Xanthou G. Advantages and Limitations of the Neonatal Immune System. Front Pediatr 2020;8:5. [Crossref] [PubMed]
3. León B. Understanding the development of Th2 cell-driven allergic airway disease in early life. Front Allergy 2022;3:1080153. [Crossref] [PubMed]
4. Abdelrahman ST, Omran JA, Del Castillo Miranda JC, et al. Point-of-Care Biomarkers in Pediatric Emergency Medicine: Advancing Rapid Diagnostics, Overcoming Limitations, and Shaping Future Innovations. Curr Treat Options Peds 2025;11:19.
5. You W. Roles of cytokine storm in sepsis progression: biomarkers, and emerging therapeutic strategies. Front Immunol 2025;16:1696366. [Crossref] [PubMed]
6. Dong X, Li R, Zou Y, et al. Co-detection of respiratory pathogens in children with Mycoplasma pneumoniae pneumonia: a multicenter study. Front Pediatr 2025;13:1482880. [Crossref] [PubMed]
7. Zeng G, Chen D, Zhou R, et al. Combination of C‐reactive protein, procalcitonin, IL‐6, IL‐8, and IL‐10 for early diagnosis of hyperinflammatory state and organ dysfunction in pediatric sepsis. J Clin Lab Anal 2022;36:e24505.
8. Hibbert J, Strunk T, Simmer K, et al. Plasma cytokine profiles in very preterm infants with late-onset sepsis. PLoS One 2020;15:e0232933. [Crossref] [PubMed]
9. Tsurumi A, Que YA, Ryan CM, et al. TNF-α/IL-10 Ratio Correlates with Burn Severity and May Serve as a Risk Predictor of Increased Susceptibility to Infections. Front Public Health 2016;4:216. [Crossref] [PubMed]
10. Morris G, Bortolasci CC, Puri BK, et al. The cytokine storms of COVID-19, H1N1 influenza, CRS and MAS compared. Can one sized treatment fit all? Cytokine 2021;144:155593.
11. Zhang Y, Li L, Wang R, et al. Effect of immunotherapy on T lymphocyte subsets, FOXP3 and IFN-γ/IL-4 ratio in children with allergic asthma. Tropical Journal of Pharmaceutical Research 2022;20:1529-33.
12. Liang M, Deng Z, Wu W, et al. Study on the correlation between intestinal flora and cytokines in children with Henoch-Schönlein purpura. Cytokine 2025;191:156959. [Crossref] [PubMed]
13. Möttönen M, Teräsjärvi J, Rahikkala H, et al. Association of IL-17A and IL-10 Polymorphisms with Juvenile Idiopathic Arthritis in Finnish Children. Int J Mol Sci 2024;25:8323. [Crossref] [PubMed]
14. Zonoobi E, Saeedfar K, Pourdowlat G, et al. The Study of IL-10 and IL-17A Genes Expression in Patients with Different Stages of Asthma: a Case-Control Study. Tanaffos 2018;17:146-54.
15. Malcova H, Milota T, Strizova Z, et al. Interleukin-1 Blockade in Polygenic Autoinflammatory Disorders: Where Are We now? Front Pharmacol 2020;11:619273. [Crossref] [PubMed]
16. Ruscitti P, Ursini F, Berardicurti O, et al. Cytokine profile, ferritin and multi-visceral involvement characterize macrophage activation syndrome during adult-onset Still's disease. Rheumatology (Oxford) 2022;62:321-9. [Crossref] [PubMed]
17. Zhong X, Ma A, Zhang Z, et al. Neutrophil-to-lymphocyte ratio as a predictive marker for severe pediatric sepsis. Transl Pediatr 2021;10:657-65. [Crossref] [PubMed]
18. Chen J, Yasrebinia S, Ghaedi A, et al. Meta-analysis of the role of neutrophil to lymphocyte ratio in neonatal sepsis. BMC Infect Dis 2023;23:837. [Crossref] [PubMed]
19. Zou S, Hu B. Prevalence of IVIG resistance in Kawasaki disease: a systematic review and meta-analysis. Front Pediatr 2025;13:1566590. [Crossref] [PubMed]
20. Arcagok BC, Karabulut B. Platelet to Lymphocyte Ratio in Neonates: A Predictor of Early onset Neonatal Sepsis. Mediterr J Hematol Infect Dis 2019;11:e2019055. [Crossref] [PubMed]
21. Tekin YK. Are Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios Associated with Mortality in Pediatric Trauma Patients? A Retrospective Study. Rambam Maimonides Med J 2019;10:e0022.
22. Kurt A, Tosun MS, Altuntaş N. Diagnostic accuracy of complete blood cell count and neutrophil-to-lymphocyte, lymphocyte-to-monocyte, and platelet-to-lymphocyte ratios for neonatal infection. Asian Biomed (Res Rev News) 2022;16:43-52. [Crossref] [PubMed]
23. Ertan K, Dogru A, Kara B, et al. Impact on the survival of neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, and monocyte-lymphocyte ratio on prognosis in children with Hodgkin lymphoma. Saudi Med J 2022;43:451-7. [Crossref] [PubMed]
24. Wang S, Wan Y, Zhang W. The Clinical Value of Systemic Immune Inflammation Index (SII) in Predicting the Severity of Hospitalized Children with Mycoplasma Pneumoniae Pneumonia: A Retrospective Study. Int J Gen Med 2024;17:935-42. [Crossref] [PubMed]
25. Firinci B, Aydin C, Yunluel D, et al. The Role of Systemic Immune-Inflammation Index (SII) in Diagnosing Pediatric Acute Appendicitis. Diagnostics (Basel) 2025;15:1942. [Crossref] [PubMed]
26. Kawalec A, Stojanowski J, Mazurkiewicz P, et al. Systemic Immune Inflammation Index as a Key Predictor of Dialysis in Pediatric Chronic Kidney Disease with the Use of Random Forest Classifier. J Clin Med 2023;12:6911. [Crossref] [PubMed]
27. Wang H, Guo C, Wang Y, et al. Immune cell composition and its impact on prognosis in children with sepsis. BMC Pediatr 2024;24:611. [Crossref] [PubMed]
28. Chang J, Zhang X, Wang W, et al. C-reactive protein-to-albumin ratio as a predictor of 28-day mortality in critically ill pediatric patients: a retrospective cohort study. BMC Pediatr 2025;25:864. [Crossref] [PubMed]
29. Bülbül SS, Ceylan A, Ocak M, et al. Relationship between C-reactive protein-albumin ratio and prognosis in pediatric patients with severe burns. PLoS One 2025;20:e0321215. [Crossref] [PubMed]
30. Liang P, Yu F. Value of CRP, PCT, and NLR in Prediction of Severity and Prognosis of Patients With Bloodstream Infections and Sepsis. Front Surg 2022;9:857218. [Crossref] [PubMed]
31. Liu C, Wu J. Value of blood inflammatory markers for predicting intravenous immunoglobulin resistance in Kawasaki disease: A systematic review and meta-analysis. Front Pediatr 2022;10:969502. [Crossref] [PubMed]
32. Ulu K, Çağlayan Ş, Coşkuner T, et al. Differentiating Kawasaki Disease and Multisystem Inflammatory Syndrome in Children Using Blood Composite Scores: Insights into Clinical Outcomes and Predictive Indices. Pediatr Cardiol 2025;46:1390-9. [Crossref] [PubMed]