Diagnostic Accuracy of Presepsin, sMR, and Established Inflammatory Biomarkers in Critically Ill Children with Sepsis or Systemic Inflammatory Response Syndrome

Abstract

Background: Pediatric sepsis is a life-threatening emergency and remains complex to diagnose promptly due to the absence of universally reliable biomarkers. C-reactive protein (CRP) and procalcitonin (PCT) are widely used but have limited effectiveness. We evaluated the diagnostic reliability of presepsin and soluble mannose receptor (sMR) and identified optimal biomarker combinations for distinguishing sepsis from non-infectious systemic inflammatory response syndrome (SIRS) in children. Methods: A total of 80 children were enrolled in this prospective study, including 53 consecutive admissions to the pediatric intensive care unit (PICU) (sepsis, n = 42; non-infectious SIRS, n = 11) and 27 healthy controls. The serum levels of new biomarkers presepsin and soluble mannose receptor (sMR) levels were quantified by ELISA methods and their diagnostic reliability (both individually and combined with CRP and PCT) was assessed using receiver operating characteristic (ROC) curves and multivariate logistic regression. Results: Significantly higher concentrations of all measured markers were found both in septic and other critically ill patients than in healthy controls (p < 0.05). No single biomarker reliably differentiated sepsis from non-infectious SIRS. The sMR + CRP + PCT combination demonstrated the highest diagnostic accuracy (AUC = 0.78, p = 0.0007), surpassing the CRP + PCT model (AUC = 0.71, p = 0.0087). Conclusions: The addition of sMR to the established markers CRP and PCT improves the diagnostic effectiveness in pediatric sepsis. Larger multicenter studies are warranted to confirm clinical utility.

1. Introduction

Sepsis remains a major contributor to morbidity and mortality worldwide, with an estimated 20 million cases occurring annually among children under five years of age [1]. This burden highlights the imperative for more reliable and objective strategies for early diagnosis. Research has focused primarily on laboratory biomarkers with high sensitivity and specificity that can reduce diagnostic errors and unnecessary antibiotic therapy [2]. Although more than 200 biochemical markers have been studied to date, none has demonstrated sufficient reliability for distinguishing and confirming the condition [3].

Organ dysfunction is a defining feature of sepsis, and its timely recognition is critical for accurate diagnosis and effective intervention. Infectious sepsis is driven by pathogen-associated molecular patterns (PAMPs), whereas non-infectious SIRS results from sterile tissue injury (e.g., trauma, pancreatitis) and the release of damage-associated molecular patterns (DAMPs), such as high mobility group box 1 (HMGB1), mitochondrial DNA, and heat shock proteins. Both PAMPs and DAMPs are sensed by pattern recognition receptors (PRRs), initiating inflammatory cascades that activate innate immune cells and induce secretion of cytokines including interleukin-1β, interleukin-6, interleukin-8, and tumor necrosis factor-α [4,5,6]. These mediators stimulate the synthesis of acute-phase proteins such as C-reactive protein (CRP) and procalcitonin (PCT), both widely recognized inflammatory biomarkers. They are widely used in clinical practice but lack specificity for differentiating sepsis from non-infectious SIRS, as both PAMP- and DAMP-driven pathways converge on similar inflammatory responses [7,8,9].

The rapid and often unpredictable progression of sepsis requires reliable diagnostic markers capable of reflecting dynamic changes in clinical status and supporting timely therapeutic decisions, either alone or in combination. In this context, multi-marker approaches—particularly those incorporating macrophage-specific markers like soluble mannose receptor (sMR; soluble CD206) and monocyte-activation indicators such as presepsin (soluble CD14 subtype, sCD14-ST)—provide superior discriminatory and prognostic value, positioning these molecules as promising early biomarkers of pediatric sepsis [10,11,12].

Interest in presepsin and sMR as subjects of scientific research is growing, but their interpretation remains difficult due to the lack of standardized analytical methods and validated reference values.

The aim of this study is to evaluate the diagnostic reliability of presepsin and sMR by determining the most effective combinations of biomarkers for distinguishing sepsis from non-infectious SIRS in children.

2. Materials and Methods

2.1. Patients and Study Design

A prospective observational study was conducted from 1 June 2022 to 31 January 2024, including 80 pediatric patients aged between 7 days and 18 years (mean age 78 ± 71 days), admitted to the First Pediatric Clinic and the Pediatric Intensive Care Unit (PICU) at University Hospital “St. Marina,” Varna. The study population was stratified into three groups:

• Group I (n = 42): Septic patients presenting with systemic inflammatory response syndrome (SIRS) of confirmed or suspected infectious etiology, fulfilling at least two diagnostic criteria, one of which was an abnormal body temperature or leukocyte count.
• Group II (n = 11): Critical patients with SIRS attributed to non-infectious causes.
• Group III (n = 27): Patients without a history or clinical evidence of infectious syndrome or SIRS, serving as controls.

For the purposes of the study, the terms “Group I” and “septic patients” as well as “Group II” and “critical and non-infectious SIRS” are interchangeable.

Patients with traumatic injuries, oncohematological diseases, and other forms of immune deficiency, as well as patients undergoing surgical interventions, newborns in the early neonatal period (<7 days), admissions over 15 days, and pregnant patients were excluded from the study. The definition adopted by the International Consensus on Pediatric Sepsis in 2005 was used to categorize septic patients [13].

A structured interview with each patient and their parent or legal guardian was conducted to obtain a detailed medical history relevant to the study objectives. Participation required written informed consent from parents or guardians. The study was approved by the Ethics Committee of the Medical University of Varna (Protocol No. 115/31.03.2022).

2.2. Physical Examination

Standard diagnostic methods were applied for clinical assessment. Within the first 24 h after PICU admission, patient status was evaluated using the Pediatric Risk of Mortality III (PRISM III), Pediatric Sequential Organ Failure Assessment (pSOFA), Pediatric Logistic Organ Dysfunction-2 (PELOD-2), and Phonix Sepsis Score (PSS). PRISM III and PELOD-2 were calculated through the Pediatric Scores Plus application (version 7) based on publicly accessible scoring criteria. PSS was derived retrospectively, with both PSS and pSOFA applied only to patients in the sepsis group. No scoring was performed for the control group [14,15].

2.3. Laboratory Methods

At admission and before the initiation of antibiotic therapy, venous blood samples were obtained from all study participants for complete blood count, blood gas analysis, coagulation studies, and biochemical parameters, including measurement of CRP and PCT. By centrifuging 2 mL of venous blood at room temperature (6000 rpm for 15 min), serum was separated (~1 mL), aliquoted in two eppendorf tubes and stored according to the manufacturer’s requirements until the simultaneous testing of innovative biomarkers of inflammation (presepsin, sMR) at a later stage of the study. The following analytical methods were used.

2.3.1. Hematological Analysis

Blood count parameters were determined using a 5-diff hematology analyzer Sysmex XN 1000 (Sysmex Corporation, Kobe, Japan), based on the principles of fluorescent flow cytometry using a semiconductor laser and hydrodynamic focusing. Reference ranges appropriate for age were used to interpret the leukocyte count [16].

2.3.2. Biochemical Indicators

CRP was determined by a latex-enhanced immunoturbidimetric method using a Siemens Advia 1800 biochemical analyzer (Siemens Healthineers, Erlangen, Germany, Wide range C-reactive protein) with reference values: 0.00–5.00 mg/L and cut-off for possible bacterial infection—20 mg/L; PCT was determined on a Maglumi^®X3 immunochemical analyzer using a chemiluminescent immunoassay (Maglumi PCT (CLIA), Snibe, Shenzhen, China) with reference values: 0.00–0.05 ng/mL and cut-off for possible bacterial infection—0.5 ng/mL, and for high risk of sepsis development—>2.0 ng/mL. The cut-off values were adopted according to international recommendations in Europe and the United States of America and compared with the literature [17,18,19].

2.3.3. Innovative Markers of Inflammation

Serum concentrations of presepsin were quantified by enzyme-linked immunosorbent assay (ELISA) using a commercial kit (Hycult Biotech, Uden, The Netherlands). The method is a non-competitive immunoassay with linearity 3.1–200 ng/mL and sensitivity of 3.1 ng/mL. Quantitative analysis of sMR in serum was performed using the same method, using an ELISA kit (Reagent Genie, Dublin, Ireland), with a working range of 31.2–2000 pg/mL and a sensitivity of 11.64 pg/mL. Both analyses were performed according to the manufacturer’s instructions. Due to expected high serum values, the samples were diluted beforehand: 10-fold for sMR and 5-fold for presepsin. The final results were calculated by multiplying the measured values obtained from the standard curve by the corresponding dilution factor. The control serum samples from healthy individuals were tested without prior dilution. The reference ranges for presepsin and sMR were determined experimentally using a robust statistical method.

2.3.4. Microbiological Tests

The automated BACTEC 9050 system (BD, Franklin Lakes, NJ, USA) was used for microbial isolation from blood, with samples incubated for 5 days and, in cases of suspected mycotic infection, for up to 14 days. When microbial growth was detected, positive blood cultures underwent rapid identification using mass spectrometry (MALDI-TOF-MS Biotyper and MBT Sepsityper IVD, Bruker, Bremen, Germany).

2.4. Statistical Analysis

Data analysis was performed with IBM SPSS Statistics, version 24 (SPSS Inc., Chicago, IL, USA), GraphPad Prism, version 10.4.0 (GraphPad Software, San Diego, CA, USA), Python, version 3.13.0 (Python Software Foundation, Wilmington, DE, USA), and MedCalc, version 23.1.6 (MedCalc Software Ltd, Oostende, Belgium). To analyse the normality of data distribution the Kolmogorov–Smirnov and Shapiro–Wilk tests were used. The descriptive statistics for normally distributed quantitative variables included mean, standard deviation (SD), and range (minimum–maximum) and, for non-normally distributed data, median and interquartile range (IQR). Comparisons of non-parametric (non-normally distributed) data were performed using the Mann–Whitney test. Statistical significance was set at p ≤ 0.05. The diagnostic reliability of the tested biomarkers was evaluated using receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC). Optimal cut-off points were determined by Youden’s Index to achieve maximum sensitivity and specificity [20]. Positive predictive value (PPV), negative predictive value (NPV), and 95% confidence intervals (CI) for AUC were calculated. The diagnostic performance of the optimal biomarker combination was further assessed using multiple logistic regression supplemented by ROC analysis. Comparison of AUC values was calculated using the method described by Hanley and McNeil [21]. To determine whether each AUC was statistically significantly greater than 0.5 (the value of chance), Z-tests were performed based on the calculated standard errors. The AUC was considered statistically significant at a p-value less than 0.05. As new biomarkers, presepsin and sMR are characterized by a lack of standardized analytical methods, and the published reference values for them are method-dependent, which further emphasizes the need for local validation of the results. The reference ranges for presepsin and sMR were determined experimentally for the purposes of the study by applying a robust statistical method (95% right-sided reference interval) suitable for small samples of less than 120 individuals [22]. The results obtained for the control group of children were compared with existing literature data [23,24].

3. Results

3.1. Baseline Characteristics of the Study Population

During the 18-month study period, 53 children, aged 44 ± 56 months, fulfilled the inclusion criteria for Groups I and II (sepsis and non-infectious SIRS). The majority (42/53) had sepsis, while the remaining 11 were diagnosed with non-infectious SIRS. Infections of the lower respiratory tract were the predominant diagnosis, occurring in 41.5% of cases, and were linked to Streptococcus pneumoniae, Mycobacterium tuberculosis, and SARS-CoV-2. Gastrointestinal infections accounted for approximately one in 10 cases, with causative agents including Rotavirus, Salmonella Group D, and Clostridioides difficile. A single case of bloodstream infection of urinary origin due to Escherichia coli was recorded. Non-infectious SIRS was most often due to intoxications (n = 4) or metabolic disorders, including type 1 diabetes mellitus with initial ketoacidosis (n = 2). The mean length of PICU stay was 11 ± 8 days. Chronic comorbidities were present in roughly one-quarter of patients. Clinical deterioration occurred in 43.4% of the cohort, with one fatal outcome. Complications affected 28.2% of patients, predominantly respiratory (18.8%), with pleural effusion being the most common (5.6%), followed by neurological complications (9.4%), which were more frequent in non-infectious SIRS (3.8%).

Table 1. Serum levels of five laboratory parameters in septic patients, non-infectious critically ill patients, and controls.

Parameter	Group I Median (IQR)	Group II Median (IQR)	Group III Median (IQR)	p (I vs II)	p (II vs III)	p (I vs III)
Leukocytes (109/L)	12.79 (8.60–17.41)	12.29 (11.02–23.85)	6.66 (5.67–8.12)	0.4387	<0.0001	<0.0001
CRP (mg/L)	17.20 (1.43–101.80)	6.73 (0.12–21.00)	0.60 (0.12–0.60)	0.1515	0.0111	<0.0001
Procalcitonin (ng/mL)	1.57 (0.38–5.78)	0.95 (0.43–1.67)	0.05 (0.04–0.06)	0.1344	<0.0001	<0.0001
Presepsin (pg/mL)	228.10 (145.30–351.70)	347.00 (59.43–1136.00)	15.97 (3.52–51.10)	>0.9999	0.0009	<0.0001
sMR (ng/mL)	231.90 (191.20–307.20)	238.80 (138.90–349.60)	117.70 (106.50–125.60)	0.7547	0.0024	<0.0001

Group I, septic; Group II, noninfectious SIRS; Group III, controls; IQR, interquartile range. The Mann–Whitney test was used, and statistical significance was set at p < 0.05.

presents the values of the laboratory parameters examined in the three patient groups.

3.2. Diagnostic Applicability of Presepsin and sMR: Reference Values and Comparative Analysis

• Comparison of results of sick children with a control group

In both groups of patients, a statistically significant increase in all examined parameters was observed compared to the control group. The most pronounced differences were observed in septic patients (Group I)—p < 0.0001 for the five laboratory parameters. In critically ill children (Group II), statistical significance ranged from 0.0111 for CRP to < 0.0001 for leukocytes and PCT (Table 1).

The following reference limits were established for presepsin—up to 107.47 pg/mL—and for sMR—up to 152.81 ng/mL (95% right-sided reference interval).

When performing ROC analysis to assess the diagnostic reliability of the studied parameters, high AUC values were found (from 0.86 for leukocytes to 0.974 for sMR, at p < 0.0001) (Supplementary File S1). High AUC values were also found in the discrimination of critically ill children from healthy children (Supplementary File S2).

During the study, three out of seven newborns with clinical signs of sepsis showed elevated PCT levels, but only one of them also had CRP levels above the reference range.

• Comparison between patients from Group I and Group II

When comparing septic and non-infectious cases, CRP and PCT values that were approximately twice as high were observed in the septic group but with no statistical significance. The values for leukocytes, presepsin, and sMR did not differ significantly between the two patient groups: (p = 0.4387, p > 0.9999, p = 0.7547, respectively (Table 1).

The graphical distribution of serum levels of the five laboratory parameters in the three groups of children studied is presented in (Supplementary File S3).

Independent assessment of each parameter using ROC analysis highlights PCT with the highest AUC value (0.649), but without statistical significance (p = 0.1344). The results for CRP are similar (p = 0.1515). Leukocytes, sMR, and presepsin did not demonstrate the ability to successfully discriminate between septic and critically ill children (AUC values close to 0.5 and p > 0.05). The results of the ROC analysis are shown in

Table 2. Diagnostic performance of laboratory biomarkers studied in septic and critical patients.

Biomarker	Leukocytes (109/L)	CRP (mg/L)	Procalcitonin (ng/mL)	Presepsin (pg/mL)	sMR (ng/mL)
AUC 95% CI	0.422 (0.22–0.61)	0.643 (0.47–0.82)	0.649 (0.47–0.82)	0.471 (0.27–0.66)	0.530 (0.34–0.72)
Cut-off	29.75	34.33	2.33	147.97	112.63
Sensitivity %	11	42	40	81	100
Specificity %	100	90	100	36	18
PPV %	100	82	100	56	55
NPV %	53	61	62	65	100
p	0.4387	0.1515	0.1344	>0.9999	0.7547

AUC—area under the curve, CI—confidence interval, PPV—positive predictive value, NPV—negative predictive value, Cut-off—cut-off point.

and visualized in Figure 1.

• Diagnostic potential through modeling combinations of biomarkers

To identify a superior combination of inflammatory markers in terms of their discriminatory power, we performed ROC analysis of different models of the investigated parameters.

The combined analysis of biomarkers revealed the highest diagnostic efficacy in the combination PCT + sMR (AUC = 0.74), followed by the combination CRP + PCT (AUC = 0.71). The lowest discriminatory potential was reported for CRP + presepsin (AUC = 0.56). Among the triple combinations, the sMR + CRP + PCT model showed the best efficacy for distinguishing sepsis (AUC = 0.78). The results of this analysis are illustrated in Figure 2 and

Table 3. Diagnostic performance of biomarker combinations.

Model	AUC	95% CI	p
CRP + procalcitonin	0.71	0.55–0.87	0.0087
CRP + sMR	0.68	0.52–0.84	0.0322
CRP + presepsin	0.56	0.37–0.75	0.5300
Procalcitonin + sMR	0.74	0.59–0.89	0.0015
Procalcitonin + presepsin	0.64	0.47–0.81	0.1142
Presepsin + CRP + procalcitonin	0.69	0.53–0.86	0.0133
sMR + CRP + procalcitonin	0.78	0.63–0.93	0.0007

Hanley and McNeil test, p < 0.05.

.

4. Discussion

This study fills a gap in the literature regarding the effectiveness of presepsin and sMR in children. In addition, it contributes to the implementation of international experience in laboratory diagnostics with biomarkers in a busy clinical setting. Its main contributions include establishing reference ranges for presepsin and sMR in children using the analytical methods employed, as well as identifying the most effective combination of inflammatory biomarkers with high discriminatory ability in distinguishing between septic and non-septic conditions.

The main challenge facing clinicians treating critically ill children is the lack of a universal and highly reliable biomarker or method that can provide sufficient diagnostic accuracy and rapid identification of septic patients. As part of the CBC, elevated white blood cell counts are one of the oldest indicators of inflammation. Various studies have investigated the diagnostic potential of this indicator in patients with suspected sepsis. For example, Marik et al. [25] find that the leukocyte count has very low prognostic value, with an AUROC (area under the ROC curve) of only 0.52. The present research shows similar results, confirming the limited diagnostic value of leukocytes as a single marker.

Currently, one of the most widely used markers of inflammation is CRP. De Rop et al. [26] have observed that patients with complicated infections tend to have higher CRP levels, but cases of severe infections with CRP < 5 mg/L have also been reported. In support of these observations, the study by Pontrelli et al. shows that PCT has moderate diagnostic value for sepsis in newborns with suspected infection at borderline levels between 2.0 and 2.5 ng/mL [27]. This was confirmed in the present analysis, despite the relatively small number of newborns. These data highlight the differences in the sensitivity of the two biomarkers and their uncertainty in recognizing septic conditions. The available information emphasizes their limited diagnostic potential when used alone. At the same time, a number of investigations have reported excellent diagnostic efficacy when combining RCT and CRP [28,29]. Studies such as those by Downes and Arkader have found low sensitivity and specificity of PCT and CRP, which is consistent with our results and highlights the need to combine them with additional biomarkers for more accurate diagnosis of sepsis [30,31].

Although CRP and PCT are established independent laboratory markers of inflammation and suspected sepsis, confirmed during the COVID-19 pandemic, their combined use as a routine diagnostic method is not yet widespread in hospital settings. The lack of a uniform standard approach hinders early identification of patients, which can lead to delayed treatment and increased mortality.

In addition, the CRP and PCT cut-off values established in this analysis (Table 2) correspond to their international reference ranges for sepsis and severe bacterial infections in children, confirming their applicability as diagnostic indicators in the study group [17,18,19].

Presepsin and sMR were chosen as biomarkers in pediatric sepsis because they reflect distinct, critical aspects of innate immune activation and dysregulation that are central to sepsis pathophysiology, especially in children. Presepsin is a cleavage product of CD14 released during monocyte activation via the CD14/TLR4 pathway in response to bacterial infection [24]. Its levels mirror both hyperinflammatory and immunosuppressive phases of sepsis and may help identify immune paralysis, a state of monocyte hyporesponsiveness associated with poor outcomes in pediatric patients [32]. However, a 2015 meta-analysis shows that presepsin is a useful marker for sepsis, but not effective enough when used alone to confirm or rule out the diagnosis [33]. sMR is a marker of macrophage recruitment and endocytic activity, which is markedly increased in sepsis due to the strong innate immune response but can also rise in sterile inflammation [34]. Elevated levels correlate with disease severity and adverse outcomes, offering insight into immune dysregulation that is particularly relevant in pediatric patients with impaired macrophage polarization [35]. An overview of PAMP- and DAMP-driven inflammation is presented in Figure 3.

In the present study, although reference and cut-off values play a key role in the interpretation of results, the low AUC and specificity values of the innovative markers indicate their limited reliability. On the other hand, presepsin demonstrates a moderate balance between sensitivity (81%) and specificity (36%), while sMR shows high sensitivity but extremely low specificity (18%), leading to many false positive results. This reduces their standalone applicability and highlights the need to combine them with other inflammatory biomarkers.

The variation in routinely used CRP and PCT in Group II is significantly smaller than that in Group I. Conversely, for the parameters sMR and presepsin, greater variation in values is observed in Group II than in Group I. Leukocytes show wide variability in both patient groups. This observation raises the question of whether these parameters are capable of independently discriminating between septic and non-septic children. Although some studies, such as that by Hassuna et al. [24], suggest that sMR and presepsin can distinguish sepsis from non-infectious SIRS in critically ill children, our results do not support that hypothesis. This highlights the need for a larger study of these laboratory markers in large target groups to establish their applicability in the pediatric population.

This research demonstrates the importance of combining biomarkers to improve diagnostic reliability in infectious conditions. The combination of CRP and PCT confirms its clinical significance as a well-established diagnostic tool (AUC = 0.71). At the same time, the sMR, CRP, and PCT model (AUC = 0.78) performs best for distinguishing infectious sepsis from non-infectious SIRS because it captures three distinct but complementary aspects of the host response: the presence of inflammation (CRP), the suspicion of bacterial cause (PCT), and the degree of innate immune cellular engagement (sMR). In summary, our findings highlight the added value of incorporating sMR into established biomarker panels, supporting a combined approach as a more reliable framework for the early diagnosis and management of pediatric sepsis.

Study Limitations

The findings are not generalizable to the broader pediatric population, as the study involved a relatively small and specific cohort. In addition, the included patients presented with heterogeneous infectious etiologies, which may have influenced biomarker performance. Finally, the absence of external validation limits the strength of our conclusions, and larger multicenter studies will be required to confirm the diagnostic utility of presepsin and sMR in pediatric sepsis.

5. Conclusions

The present study supports the added value of a multi-biomarker approach in the diagnosis of septic and critical conditions in children, while emphasizing the importance of careful selection of markers in clinical practice. In total, CRP and PCT validate their role as an established diagnostic combination with widespread use in routine practice, providing reliability in the identification of septic conditions. Furthermore, the combination of sMR, CRP, and PCT demonstrates the best diagnostic value, suggesting its potential clinical application. Despite the promising results, the absence of standardized reference ranges for innovative biomarkers limits their diagnostic reliability, requiring further research and validation of their clinical application.