Combination biomarkers to diagnose sepsis in the critically ill patient

Heparin-binding protein as a biomarker for the diagnosis of sepsis in the intensive care unit: a retrospective cross-sectional study in China

OBJECTIVES

This study aims to investigate the diagnostic value of heparin-binding protein (HBP) in sepsis and develop a sepsis diagnostic model incorporating HBP with key biomarkers and disease-related scores for rapid, and accurate diagnosis of sepsis in the intensive care unit (ICU).

DESIGN

Clinical retrospective cross-sectional study.

SETTING

A comprehensive teaching tertiary hospital in China.

PARTICIPANTS

Adult patients (aged ≥18 years) who underwent HBP testing or whose blood samples were collected when admitted to the ICU.

MAIN OUTCOME MEASURES

HBP, C reactive protein (CRP), procalcitonin (PCT), white blood cell count (WBC), interleukin-6 (IL-6), lactate (LAC), Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) score were recorded.

RESULTS

Between March 2019 and December 2021, 326 patients were enrolled in this study. The patients were categorised into a non-infection group (control group), infection group, sepsis group and septic shock group based on the final diagnosis. The HBP levels in the sepsis group and septic shock group were 45.7 and 69.0 ng/mL, respectively, which were significantly higher than those in the control group (18.0 ng/mL) and infection group (24.0 ng/mL) (p<0.001). The area under the curve (AUC) value of HBP for diagnosing sepsis was 0.733, which was lower than those corresponding to PCT, CRP and SOFA but higher than those of IL-6, LAC and APACHE II. Multivariate logistic regression analysis identified HBP, PCT, CRP, IL-6 and SOFA as valuable indicators for diagnosing sepsis. A sepsis diagnostic model was constructed based on these indicators, with an AUC of 0.901, a sensitivity of 79.7% and a specificity of 86.9%.

CONCLUSIONS

HBP could serve as a biomarker for the diagnosis of sepsis in the ICU. Compared with single indicators, the sepsis diagnostic model constructed using HBP, PCT, CRP, IL-6 and SOFA further enhanced the diagnostic performance of sepsis.

Dynamic Changes in Soluble Triggering Receptor Expressed on Myeloid Cells-1 in Sepsis with Respect to Antibiotic Susceptibility

Purpose

Proper antibiotic administration is crucial for sepsis management. Given the escalating incidence of antimicrobial resistance, there is a pressing need for indicators of antimicrobial susceptibility with short turnaround times. This study aimed to investigate the potential of soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) as an early biomarker for in vivo antibiotic susceptibility in patients with sepsis.

Patients and Methods

We conducted a retrospective analysis of plasma samples from patients enrolled in a pre-established study designed to investigate prognostic biomarkers in patients with sepsis or septic shock. Baseline and 6 h sTREM-1 levels were examined using enzyme-linked immunosorbent assays. The primary outcome of the study was the comparison of percentage changes in sTREM-1 levels at the 6 h relative to baseline with respect to antibiotic susceptibility.

Results

Of the 596 patients enrolled in the pre-established study, 29 with a median age of 75.8 and a 28-day mortality rate of 17.2% were included in the present analysis. Among these patients, 24 were classified into the susceptible group, whereas the remaining five were classified into the resistant group. The trend in plasma sTREM-1 levels differed with respect to antibiotic susceptibility. Moreover, percentage change in sTREM-1 levels at the 6 h relative to baseline was significantly higher in the resistant group (P = 0.028).

Conclusion

The trend in plasma sTREM-1 levels in patients with sepsis differed with respect to antibiotic susceptibility, with a higher percentage change in patients treated with inappropriate antibiotics. These findings indicate the potential utility of sTREM-1 as an early biomarker of antibiotic susceptibility.

A biomarker panel of C-reactive protein, procalcitonin and serum amyloid A is a predictor of sepsis in severe trauma patients

Severe trauma could induce sepsis due to the loss of control of the infection, which may eventually lead to death. Accurate and timely diagnosis of sepsis with severe trauma remains challenging both for clinician and laboratory. Combinations of markers, as opposed to single ones, may improve diagnosis. We compared the diagnostic characteristics of routinely used biomarkers of sepsis alone and in combination, trying to define a biomarker panel to predict sepsis in severe patients. This prospective observational study included patients with severe trauma (Injury severity score, ISS = 16 or more) in the emergency intensive care unit (EICU) at a university hospital. Blood samples were collected and plasma levels of procalcitonin (PCT), C-reactive protein (CRP), interleukin-6 (IL-6) and serum amyloid A (SAA) were measured using commercial enzyme linked immunosorbent assay (ELISA) kits. A total of 100 patients were eligible for analysis. Of these, 52 were diagnosed with sepsis. CRP yielded the highest discriminative value followed by PCT. In multiple logistic regression, SAA, CRP, and PCT were found to be independent predictors of sepsis. Bioscore which was composed of SAA, CRP, and PCT was shown to be far superior to that of each individual biomarker taken individually. Therefore, compared with single markers, the biomarker panel of PCT, CRP, and SAA was more predictive of sepsis in severe polytrauma patients.

Obesity Alters cytokine signaling and gut microbiome in septic mice

Sepsis is a leading cause of mortality. Plasma cytokine levels may identify those at increased risk of mortality from sepsis. Our aim was to understand how obesity alters cytokine levels during early sepsis and its correlation with survival. Six-week-old C57BL/6 male mice were randomized to control (non-obese) or high fat diet (obese) for 5-7 weeks. Sepsis was induced by cecal ligation and perforation (CLP). Cytokine levels were measured from cheek bleeds 8 h after CLP, and mice were monitored for survival. Other cohorts were sacrificed 1 h after CLP for plasma and tissue. Septic obese mice had higher survival. At 8 h after sepsis, obese mice had higher adiponectin, leptin, and resistin but lower TNFα and IL-6 compared to non-obese mice. When stratified by 24-h survival, adipokines were not significantly different in obese and non-obese mice. TNFα and IL-6 were higher in non-obese, compared to obese, mice that died within 24 h of sepsis. Diet and to sepsis significantly impacted the cecal microbiome. IL-6 is a prognostic biomarker during early sepsis in non-obese and obese mice. A plausible mechanism for the survival difference in non-obese and obese mice may be the difference in gut microbiome and its evolution during sepsis.

Monocyte chemoattractant protein-1 as a potential marker for patients with sepsis: a systematic review and meta-analysis

Objective

To investigate the diagnostic value of monocyte chemoattractant protein-1 (MCP-1) as a biomarker for adult patients with sepsis.

Methods

Related studies on the diagnostic value of MCP-1 in adult patients with sepsis were searched in PubMed, Cochrane Library, Embase, CNKI, CBM, Web of Science, Scopus, and Wanfang Data databases (published to February 20, 2023) was performed if studies assessed the diagnostic accuracy of MCP-1 in adult patients with sepsis and provided appropriate information sufficient to construct a 2 × 2 linked table, studies were included.

Results

Data from 8 studies with a total of 805 patients were included. The combined sensitivity was 0.84 (95% CI 0.70-0.92), the specificity was 0.82 (95% CI 0.67-0.91), the combined positive likelihood ratio was 3.711 (2.119-6.500), the negative likelihood ratio was 0.287 (0.198-0.415), and the area under the working characteristic curve for combined subjects was 0.88. The diagnostic odds ratio (DOR) was 16.508 (7.632-35.706). Meta-regression analysis showed that the results were not significant. Deeks' funnel plot showed that there was no publication bias.

Conclusion

According to our meta-analysis, MCP-1 is a valuable biomarker and may provide evidence for the diagnosis of sepsis in adults.

Significance of sTREM-1 and sST2 combined diagnosis for sepsis detection and prognosis prediction

The diagnosis of sepsis still lacks a practical and reliable gold standard. The purpose of this study was to confirm the effect of soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) combined with soluble suppression of tumorigenicity 2 (sST2) in the diagnosis of sepsis through the correlation between sTREM-1, sST2, and sequential organ failure assessment (SOFA) scores. Baseline data of 91 patients with sepsis in the intensive care unit were collected, sTREM-1 and sST2 were detected, and the correlation between markers and SOFA score was analyzed. Besides, the prognostic value of baseline and postadmission indicators for sepsis was analyzed with death as the outcome. The results showed that the expressions of sST2 and sTREM-1 in death group and survival group were higher than those in the survival group (p < 0.05). Correlation analysis showed that sST2, sTREM-1, and the joint diagnosis model had a high correlation with SOFA score (p < 0.05), but poor correlation with Acute Physiology and Chronic Health Evaluation Ⅱ score (p > 0.05). Among them, joint diagnosis model has the highest correlation. Receiver operating characteristic curve analysis showed that combined diagnosis had higher area under curve values. sTREM-1/sST2 can be better used in the diagnosis of sepsis than the single biomarker detection, and the combination of the above two biomarkers has potential application value in the detection and prognosis prediction of sepsis.

One biomarker does not fit all: tailoring anti-infective therapy through utilization of procalcitonin and other specific biomarkers

INTRODUCTION

Considering the ongoing increase in antibiotic resistance, the importance of judicious use of antibiotics through reduction of exposure is crucial. Adding procalcitonin (PCT) and other biomarkers to pathogen-specific tests may help to further improve antibiotic therapy algorithms and advance antibiotic stewardship programs to achieve these goals.

AREAS COVERED

In recent years, several trials have investigated the inclusion of biomarkers such as PCT into clinical decision-making algorithms. For adult patients, findings demonstrated improvements in the individualization of antibiotic treatment, particularly for patients with respiratory tract infections and sepsis. While most trials were performed in hospitals with central laboratories, point-of-care testing might further advance the field by providing a cost-effective and rapid diagnostic tool in upcoming years. Furthermore, novel biomarkers including CD-64, presepsin, Pancreatic stone and sTREM-1, have all shown promising results for increased accuracy of sepsis diagnosis. Availability of these markers however is currently still limited and there is insufficient evidence for their routine use in clinical care.

EXPERT OPINION

In addition to new host-response markers, combining such biomarkers with pathogen-directed diagnostics present a promising strategy to increase algorithm accuracy in differentiating between bacterial and viral infections. Recent advances in microbiologic testing using PCR or nucleic amplification tests may further improve the diagnostic yield and promote more targeted pathogen-specific antibiotic therapy.

sTREM-1 and TNF-α levels are associated with the clinical outcome of leprosy patients

Leprosy reaction (LR) and physical disability (PD) are the most significant clinical complications of leprosy. Herein, we assessed the circulating serum-sTREM-1 and TNF-α levels and their genetic polymorphisms in leprosy. Serum-sTREM-1 and TNF-α levels were measured in leprosy patients (LP) before treatment (n = 51) and from their household contacts (HHCs; n = 25). DNA samples were genotyped using TREM-1 rs2234246 and TNF-α rs1800629-SNP in 210 LPs and 168 endemic controls. The circulating sTREM-1 and TNF-α levels are higher in the multibacillary form. The ROC curve of the serum-sTREM-1 levels was able to differentiate LR from non-LR and PD from non-PD. Similarly, LPs with serum-sTREM-1 levels >210 pg/ml have 3-fold and 6-fold higher chances of presenting with LR and PD, respectively. Genotypes CC+CT of the TREM-1 were associated with leprosy. Taken together, our analyses indicated that sTREM-1 and TNF-α play an important role in the pathogenesis of leprosy and provide promising biomarkers to assist in the diagnosis of leprosy complications.

Diagnostic Value of Neutrophil CD64 in Sepsis Patients in the Intensive Care Unit: A Cross-Sectional Study

Little is known about the role of neutrophil CD64 (nCD64) in detecting sepsis early in Asian populations. We examined the cut-off and predictive values of nCD64 for diagnosing sepsis in Vietnamese intensive care units (ICU) patients. A cross-sectional study was conducted at the ICU of Cho Ray Hospital between January 2019 and April 2020. All 104 newly admitted patients were included. Sensitivity (Sens), specificity (Spec), positive and negative predictive values (PPV and NPV), and receiver operating characteristic (ROC) curves were calculated to compare the diagnostic values of nCD64 with those of procalcitonin (PCT) and white blood cell (WBC) for sepsis. The median nCD64 value in sepsis patients was statistically higher than that of non-sepsis patients (3106 [1970-5200] vs. 745 [458-906] molecules/cell, p < 0.001). ROC analysis found that the AUC value of nCD64 was 0.92, which was higher than that of PCT (0.872), WBC (0.637), and nCD64 combined, with WBC (0.906) and nCD64 combined with WBC and PCT (0.919), but lower than that of nCD64 combined with PCT (0.924). With an AUC value of 0.92, the nCD64 index of 1311 molecules/cell-detected sepsis with 89.9% Sens, 85.7% Spec, 92.5% PPV, and 81.1% NPV. nCD64 can be a useful marker for early sepsis diagnosis in ICU patients. nCD64 combined with PCT may improve the diagnostic accuracy.

Point-of-care neutrophil CD64 as a rule in diagnostic test for bacterial infections in the emergency department

INTRODUCTION

Bacterial infections are frequently seen in the emergency department (ED), but can be difficult to distinguish from viral infections and some non-infectious diseases. Common biomarkers such as c-reactive protein (CRP) and white blood cell (WBC) counts fail to aid in the differential diagnosis. Neutrophil CD64 (nCD64), an IgG receptor, is suggested to be more specific for bacterial infections. This study investigated if nCD64 can distinguish bacterial infections from other infectious and non-infectious diseases in the ED.

METHODS

All COVID-19 suspected patients who visited the ED and for which a definitive diagnosis was made, were included. Blood was analyzed using an automated flow cytometer within 2 h after presentation. Patients were divided into a bacterial, viral, and non-infectious disease group. We determined the diagnostic value of nCD64 and compared this to those of CRP and WBC counts.

RESULTS

Of the 291 patients presented at the ED, 182 patients were included with a definitive diagnosis (bacterial infection n = 78; viral infection n = 64; non-infectious disease n = 40). ROC-curves were plotted, with AUCs of 0.71 [95%CI: 0.64-0.79], 0.77 [0.69-0.84] and 0.64 [0.55-0.73] for nCD64, WBC counts and CRP, respectively. In the bacterial group, nCD64 MFI was significantly higher compared to the other groups (p < 0.01). A cut-off of 9.4 AU MFI for nCD64 corresponded with a positive predictive value of 1.00 (sensitivity of 0.27, a specificity of 1.00, and an NPV of 0.64). Furthermore, a diagnostic algorithm was constructed which can serve as an example of what a future biomarker prediction model could look like.

CONCLUSION

For patients in the ED presenting with a suspected infection, nCD64 measured with automatic flow cytometry, has a high specificity and positive predictive value for diagnosing a bacterial infection. However, a low nCD64 cannot rule out a bacterial infection. For future purposes, nCD64 should be combined with additional tests to form an algorithm that adequately diagnoses infectious diseases.

Elevated HMGB1 and sRAGE levels in cerebrospinal fluid of aneurysmal subarachnoid hemorrhage patients

BACKGROUND

Neuroinflammation after aneurysmal subarachnoid hemorrhage (aSAH) leads to poor outcome of patients. High mobility group box 1 (HMGB1) contributes to inflammation through binding to receptors for advanced glycation end-products (RAGE) in various diseases. We aimed to determine the production of these two factors after aSAH and their relationship with clinical features.

METHODS

HMGB1 and soluble RAGE (sRAGE) levels in cerebrospinal fluid (CSF) of aSAH patients and controls were measured, and their temporal courses were observed. The correlation between early concentrations (days 1-3) and clinical symptoms assessed by disease severity scores, neuroinflammation estimated by CSF IL-6 levels, as well as prognosis evidenced by delayed cerebral ischemia (DCI) and 6-month adverse outcome was investigated. Finally, combined analysis of early levels for predicting prognosis was confirmed.

RESULTS

CSF HMGB1 and sRAGE levels were higher in aSAH patients than in controls (P < 0.05), and the levels decreased from higher early to lower over time. Their early concentrations were positively associated with disease severity scores, IL-6 levels, DCI and 6-month poor outcome (P < 0.05). HMGB1 ≥ 6045.5 pg/ml (OR = 14.291, P = 0.046) and sRAGE ≥ 572.0 pg/ml (OR = 13.988, P = 0.043) emerged as independent predictors for DCI, while HMGB1 ≥ 5163.2 pg/ml (OR = 7.483, P = 0.043) and sRAGE ≥ 537.3 pg/ml (OR = 12.653, P = 0.042) were predictors for 6-month poor outcome. Combined analysis of them improved predictive values of adverse prognosis.

CONCLUSION

CSF HMGB1 and sRAGE levels of aSAH patients were increased early and then varied dynamically, which might act as potential biomarkers for poor outcome, especially when co-analyzed.

Combining Serum Procalcitonin Level, Thromboelastography, and Platelet Count to Predict Short-term Development of Septic Shock in Intensive Care Unit

OBJECTIVE

Despite the recent advances in diagnosis and treatment, sepsis continues to lead to high morbidity and mortality. Early diagnosis and prompt treatment are essential to save lives. However, most biomarkers can only help to diagnose sepsis, but cannot predict the development of septic shock in high-risk patients. The present study determined whether the combined measurement of procalcitonin (PCT), thromboelastography (TEG) and platelet (PLT) count can predict the development of septic shock.

METHODS

A retrospective study was conducted on 175 septic patients who were admitted to the intensive care unit between January 2017 and February 2021. These patients were divided into two groups: 73 patients who developed septic shock were assigned to the septic shock group, while the remaining 102 patients were assigned to the sepsis group. Then, the demographic, clinical and laboratory data were recorded, and the predictive values of PCT, TEG and PLT count for the development of septic shock were analyzed.

RESULTS

Compared to the sepsis group, the septic shock group had statistically lower PLT count and TEG measurements in the R value, K value, α angle, maximum amplitude, and coagulation index, but had longer prothrombin time (DT), longer activated partial thromboplastin time (APTT), and higher PCT levels. Furthermore, the Sequential Organ Failure Assessment (SOFA) score was higher in the septic shock group. The multivariate logistic regression analysis revealed that PCT, TEG and PLT count were associated with the development of septic shock. The area under the curve analysis revealed that the combined measurement of PCT, TEG and PLT count can be used to predict the development of septic shock with higher accuracy, when compared to individual measurements.

CONCLUSION

The combined measurement of PCT, TEG and PLT count is a novel approach to predict the development of septic shock in high-risk patients.

[Sepsis during pregnancy: Key points in 2022]

Sepsis is a severe affection, that requires an urgent and specific treatment sequence. Physiological changes occurring during pregnancy make the diagnosis of sepsis more challenging in this setting, with possible delay in treatment initiation, that in turn is responsible for poorer maternal and fetal outcome. This review aims to summarize current knowledge on the diagnosis and treatment of maternal sepsis, as well as persistent knowledge gaps in the field.

Combination of Interleukin-6, C-Reactive Protein and Procalcitonin Values as Predictive Index of Sepsis in Course of Fever Episode in Adult Haematological Patients: Observational and Statistical Study

Haematological patients represent a vulnerable population to opportunistic infections, mainly due to the disease itself and chemotherapy-induced neutropenia. The level of immune suppression strongly increases the importance of timely antibiotic treatment in order to prevent sepsis-related mortality. During the initial fever episode, serum biomarkers are usually used to estimate the probability of blood stream infection prior to the results of microbial diagnosis. A new serum biomarker combination study on a febrile haematological population, including C-reactive protein (CRP), interleukin-6 (IL-6) and procalcitonin (PCT), is proposed in order to improve their predictive accuracy. In our prospective study, CRP, IL-6 and PCT were evaluated in 34 immunosuppressed haematological patients immediately after the onset of 51 fever episodes, either during the course of standard chemotherapy or high-dose chemotherapy and autologous stem cell transplant. The fever episodes were divided into documented infections and fever alone. Receiver operating characteristic analysis (ROC) was performed for each biomarker and a combination of all three biomarkers (multiROC) to define a new predictive index. Significant differences were evidenced between the two groups (documented infection and no infection) for both PCT and IL-6 (p = 0.03 and p = 0.035, respectively), but none for CRP (p = 0.1). The composite parameter is more reliable than any single biomarker alone, with an area under the curve (AUC) of 79% and with high sensitivity and specificity. IL-6 gave the closest response compared to the composite index. Composite parameters of serum biomarkers could be used for an early diagnosis of infection at fever onset in haematological patients.

Recent advances in neutrophil chemotaxis abnormalities during sepsis

Sepsis remains one of the leading causes of death globally, in spite of advanced developments in intensive care and better understandings of pathophysiology related to sepsis. There is no special treatment or drug available for sepsis, currently. Under normal circumstances, neutrophil is a major player in acute infection control. However, during sepsis, the migration abilities and antimicrobial functions of neutrophils are impaired, resulting in a dysregulated immune response. Recent studies have indeed demonstrated that blocking or reversing neutrophil migration and impaired antibacterial function can improve the outcomes in septic animal models. This article systemically synthesized information regarding related factors and signaling involved in the functions of neutrophils in sepsis. This review also discussed the possibility that neutrophils be used as a marker for specific diagnosis and/or prediction of the outcomes of sepsis.

Monocyte HLADR and Immune Dysregulation Index as Biomarkers for COVID-19 Severity and Mortality

Immune dysregulation in COVID-19 is the major causal factor associated with disease progression and mortality. Role of monocyte HLA-DR (mHLA-DR), neutrophil CD64 (nCD64) and Immune dysregulation index (IDI) were studied in COVID-19 patients for assessing severity and outcome. Results were compared with other laboratory parameters. Antibody bound per cell for mHLA-DR, nCD64 and IDI were measured in 100 COVID-19 patients by flow cytometry within 12 h of hospital admission. Thirty healthy controls (HC) were included. Clinical and laboratory parameters like C - reactive protein (CRP), Procalcitonin (PCT), Absolute Lymphocyte count (ALC), Absolute Neutrophil count (ANC) and Neutrophil to Lymphocyte ratio (NLR) were recorded. Patients were followed up until recovery with discharge or death. Parameters from 54 mild (MCOV-19), 46 severe (SCOV-19) and 30 HC were analysed. mHLA-DR revealed significant and graded down regulation in MCOV-19 and SCOV-19 as compared to HC whereas IDI was lowest in HC with increasing values in MCOV-19 and SCOV-19. For diagnostic discrimination of MCOV-19 and SCOV-19, IDI revealed highest AUC (0.99). All three immune parameters revealed significant difference between survivors (n = 78) and non-survivors (n = 22). mHLA-DR < 7010 and IDI > 12 had significant association with mortality. Four best performing parameters to identify patients with SCOV-19 at higher risk of mortality were IDI, NLR, ALC and PCT. mHLA-DR and IDI, in addition to NLR and ALC at admission and during hospital stay can be utilized for patient triaging, monitoring, early intervention, and mortality prediction. IDI reported for the first time in this study, appears most promising. Immune monitoring of ‘in hospital’ cases may provide optimized treatment options.

Prognostic value of heparin-binding protein for mortality in severe COVID-19 pneumonia

Aim: The study investigated heparin-binding protein (HBP) levels in patients with severe COVID-19 pneumonia and their relation to prognosis. Methods: A total of 134 patients with serious COVID-19 pneumonia were prospectively analyzed. HBP levels were statistically compared between both the patient and healthy control groups and within the patient group itself. Results: HBP was defined to be significantly higher in the patient group compared with the control group. There was a statistically significant distinction between the patients who survived and those who died with regard to HBP levels. When the cutoff value of HBP was >13.47, sensitivity (89.8%), specificity (74.1%) had area under the curve values of 0.806 (p < 0.001). Conclusion: HBP level may be used for prognosis prediction of patients with COVID-19.

Application of Biomarkers in the Diagnostic Distinction of Bacterial and Viral Infections

Infectious diseases, which pose a great threat worldwide, have a significant impact on public health and the world economy. It contributes to increased healthcare costs, unnecessary drug-related side effects, and increased antimicrobial resistance. It is not always easy to distinguish the etiological differentiation of diseases that can develop with bacteria and viruses. Therefore, one of the biggest challenges in medicine is how to correctly distinguish between the different causes of these infections and how to manage the patient. Because bacterial and viral infections often present similar symptoms. The real decision is whether the infection is caused by bacteria or viruses and whether to treat the patient with antibiotics. There are many different methodological approaches to diagnosing infections. Biomarkers have been used in the diagnosis of diseases and other conditions for many years. Biomarkers are molecules found in blood and body fluids in measurable amounts, which can evaluate biological and pathological processes. These key indicators can provide vital information in determining disease prognosis, predicting response to treatments, adverse events and drug interactions, and identifying key risks. An effective biomarker is extremely important for the early diagnosis of various diseases. The explosion of interest in biomarker research is driving the development of new predictive, diagnostic, and prognostic products in modern medical practice. The purpose of this review is to demonstrate the use and diagnostic potential of current and investigational biomarkers in the distinction between bacterial and viral infections.

Changes in Biomarkers and Hemodynamics According to Antibiotic Susceptibility in a Model of Bacteremia

Proper selection of susceptible antibiotics in drug-resistant bacteria is critical to treat bloodstream infection. Although biomarkers that guide antibiotic therapy have been extensively evaluated, little is known about host biomarkers targeting in vivo antibiotic susceptibility. Therefore, we aimed to evaluate the trends of hemodynamics and biomarkers in a porcine bacteremia model treated with insusceptible antibiotics compared to those in susceptible models. Extended-spectrum β-lactamase (ESBL)-producing Escherichia coli (E. coli, 5.0 * 10^9 CFU) was intravenously administered to 11 male pigs. One hour after bacterial infusion, pigs were assigned to two groups of antibiotics, ceftriaxone (n = 6) or ertapenem (n = 5). Pigs were monitored up to 7 h after bacterial injection with fluid and vasopressor support to maintain the mean arterial blood pressure over 65 mmHg. Blood sampling for blood culture and plasma acquisition was performed before and every predefined hour after E. coli injection. Cytokine (tumor necrosis factor-α, interleukin [IL]-1β, IL-6, IL-8, IL-10, C-reactive protein, procalcitonin, presepsin, heparan sulfate, syndecan, and soluble triggering receptor expressed on myeloid cells-1 [sTREM-1]) levels in plasma were analyzed using enzyme-linked immunosorbent assays. Bacteremia developed after intravenous injection of E. coli, and negative conversion was confirmed only in the ertapenem group. While trends of other biomarkers failed to show differences, the trend of sTREM-1 was significantly different between the two groups (P = 0.0001, two-way repeated measures analysis of variance). Among hemodynamics and biomarkers, the sTREM-1 level at post 2 h after antibiotics administration represented a significant difference depending on susceptibility, which can be suggested as a biomarker candidate of in vivo antibiotics susceptibility. Further clinical studies are warranted for validation.

IMPORTANCE Early and appropriate antibiotic treatment is a keystone in treating patients with sepsis. Despite its importance, blood culture which requires a few days remains as a pillar of diagnostic method for microorganisms and their antibiotic susceptibility. Whether changes in biomarkers and hemodynamics indicate treatment response of susceptible antibiotic compared to resistant one is not well understood to date. In this study using extended-spectrum β-lactamase -producing E. coli bacteremia porcine model, we have demonstrated the comprehensive cardiovascular hemodynamics and trends of plasma biomarkers in sepsis and compared them between two groups with susceptible and resistant antibiotics. While other hemodynamics and biomarkers have failed to differ, we have identified that levels of soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) significantly differed between the two groups over time. Based on the data in this study, trends of sTREM-1 obtained before the antibiotics and 2~4 h after the antibiotics could be a novel host biomarker that triggers the step-up choice of antibiotics.

ARG1 as a promising biomarker for sepsis diagnosis and prognosis: evidence from WGCNA and PPI network

Background

Sepsis is a life-threatening multi-organ dysfunction caused by the dysregulated host response to infection. Sepsis remains a major global concern with high mortality and morbidity, while management of sepsis patients relies heavily on early recognition and rapid stratification. This study aims to identify the crucial genes and biomarkers for sepsis which could guide clinicians to make rapid diagnosis and prognostication.

Methods

Preliminary analysis of multiple global datasets, including 170 samples from patients with sepsis and 110 healthy control samples, revealed common differentially expressed genes (DEGs) in peripheral blood of patients with sepsis. After Gene Oncology (GO) and pathway analysis, the Weighted Gene Correlation Network Analysis (WGCNA) was used to screen for genes most related with clinical diagnosis. Also, the Protein-Protein Interaction Network (PPI Network) was constructed based on the DEGs and the hub genes were found. The results of WGCNA and PPI network were compared and one shared gene was discovered. Then more datasets of 728 experimental samples and 355 control samples were used to prove the diagnostic and prognostic value of this gene. Last, we used real-time PCR to confirm the bioinformatic results.

Results

Four hundred forty-four common differentially expressed genes in the blood of sepsis patients from different ethnicities were identified. Fifteen genes most related with clinical diagnosis were found by WGCNA, and 24 hub genes with most node degrees were identified by PPI network. ARG1 turned out to be the unique overlapped gene. Further analysis using more datasets showed that ARG1 was not only sharply up-regulated in sepsis than in healthy controls, but also significantly high-expressed in septic shock than in non-septic shock, significantly high-expressed in severe or lethal sepsis than in uncomplicated sepsis, and significantly high-expressed in non-responders than in responders upon early treatment. These all demonstrate the performance of ARG1 as a key biomarker. Last, the up-regulation of ARG1 in the blood was confirmed experimentally.

Conclusions

We identified crucial genes that may play significant roles in sepsis by WGCNA and PPI network. ARG1 was the only overlapped gene in both results and could be used to make an accurate diagnosis, discriminate the severity and predict the treatment response of sepsis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-022-00240-1.

Diagnostic and prognostic value of new bioscore in critically ill septic patients

OBJECTIVE

To evaluate the diagnostic and prognostic value of biomarkers and new bioscore in septic patients in intensive care unit (ICU).

MATERIALS AND METHODS

A study was conducted on septic and non-septic patients in ICU. Diagnostic and prognostic values of C-reactive protein (CRP), procalcitonin (PCT), Sequential Organ Failure Assessments (SOFA) score and new bioscore were analysed statistically.

RESULTS

A total of 226 patients were enrolled in the study. In septic patients, PCT, SOFA and bioscore were found significantly increased (p = .007, p = .001 and p = .001, respectively). The AUC value of bioscore was higher than PCT and SOFA in septic patients. SOFA was found to be more significant prognostic marker than bioscore in predicting 28-day mortality. The prognostic value of bioscore and SOFA was similar for predicting 90-day mortality.

CONCLUSIONS

The new bioscore formed by combination of CRP, PCT and SOFA score may be useful in early diagnosis of sepsis.

Heparin Binding Protein for the Early Diagnosis and Prognosis of Sepsis in the Emergency Department: The Prompt Multicenter Study

BACKGROUND

The validation of new biomarkers for the diagnosis and risk stratification of patients with sepsis at an early point is essential for successful treatment. Recent publications prompted us to investigate of heparin binding protein (HBP) for the emergency department (ED) admissions.

MATERIALS AND METHODS

In this multicenter, cross-sectional study, HBP and procalcitonin (PCT) were measured within the first hour upon admission to the ED in plasma samples of 371 patients with signs of infection. Patients were classified into non-sepsis and sepsis by the Sepsis-3 definitions and were followed up for outcome.

RESULTS

HBP was significantly higher in patients with sepsis and was positively correlated to PCT and C-reactive protein, absolute neutrophil and monocyte counts, creatinine, bilirubin and lactate. Sensitivity, specificity, positive predictive value, and negative predictive value of HBP more than 19.8 ng/mL for the diagnosis of sepsis was 66.3%, 44.9%, 49.3%, and 62.2%, respectively; and for prediction of early death was 100%, 41.0%, 4.5%, and 100%, respectively. Single HBP and PCT could not predict 28-day mortality; this was performed with sensitivity, specificity, positive predictive value, and negative predictive value 44.8%, 81.8%, 17.3%, and 94.6% when used in combination.

CONCLUSION

Admission HBP can be used as a tool for the early diagnosis of sepsis and for the risk of early death in the ED.

Comparison of CRP, Procalcitonin, Neutrophil Counts, Eosinophil Counts, sTREM-1, and OPN between Pneumonic and Nonpneumonic Exacerbations in COPD Patients

Introduction

The patients with community-acquired pneumonia (CAP) and acute exacerbations of COPD (AECOPD) could have a higher risk of acute and severe respiratory illness than those without CAP in AECOPD. Consequently, early identification of pneumonia in AECOPD is quite important. Methods. 52 subjects with AECOPD + CAP and 93 subjects with AECOPD from two clinical centers were enrolled in this prospective observational study. The values of osteopontin (OPN), soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), C-reactive protein (CRP), procalcitonin (PCT), eosinophil (EOS) counts, and neutrophil (Neu) counts in blood on the first day of admission and clinical symptoms were compared in AECOPD and AECOPD + CAP. In addition, subgroup analyses of biomarker difference were conducted based on the current use of inhaled glucocorticoids (ICS) or systemic corticosteroids (SCS).

Results

Patients with AECOPD + CAP had increased sputum volume, sputum purulence, diabetes mellitus, and longer hospital stays than AECOPD patients (p < 0.05). A clinical logistic regression model showed among the common clinical symptoms, purulent sputum can independently predict pneumonia in AECOPD patients after adjusting for a history of diabetes. At day 1, AECOPD + CAP patients had higher values of Neu, CRP, PCT, and OPN, while serum sTREM-1 levels and EOS counts were similar in the two groups. CRP fared best at predicting AECOPD with CAP (p < 0.05 for the test of difference), while OPN had similar accuracy with Neu, PCT, and purulent sputum (p > 0.05 for the test of difference). Multivariate analysis, including clinical symptoms and biomarkers, suggested that CRP ≥15.8 mg/dL at day 1 was a only promising predictor of pneumonia in AECOPD. CRP and OPN were not affected by ICS or SCS.

Conclusions

CRP ≥15.8 mg/dL is an ideal promising predictor of pneumonia in AECOPD, and its plasma level is not affected by ICS or SCS. The diagnostic performance of CRP is not significantly improved when combined with clinical symptoms or other markers (OPN, PCT, and Neu).

Biomarkers Predicting Tissue Pharmacokinetics of Antimicrobials in Sepsis: A Review

The pathophysiology of sepsis alters drug pharmacokinetics, resulting in inadequate drug exposure and target-site concentration. Suboptimal exposure leads to treatment failure and the development of antimicrobial resistance. Therefore, we seek to optimize antimicrobial therapy in sepsis by selecting the right drug and the correct dosage. A prerequisite for achieving this goal is characterization and understanding of the mechanisms of pharmacokinetic alterations. However, most infections take place not in blood but in different body compartments. Since tissue pharmacokinetic assessment is not feasible in daily practice, we need to tailor antibiotic treatment according to the specific patient’s pathophysiological processes. The complex pathophysiology of sepsis and the ineffectiveness of current targeted therapies suggest that treatments guided by biomarkers predicting target-site concentration could provide a new therapeutic strategy. Inflammation, endothelial and coagulation activation markers, and blood flow parameters might be indicators of impaired tissue distribution. Moreover, hepatic and renal dysfunction biomarkers can predict not only drug metabolism and clearance but also drug distribution. Identification of the right biomarkers can direct drug dosing and provide timely feedback on its effectiveness. Therefore, this might decrease antibiotic resistance and the mortality of critically ill patients. This article fills the literature gap by characterizing patient biomarkers that might be used to predict unbound plasma-to-tissue drug distribution in critically ill patients. Although all biomarkers must be clinically evaluated with the ultimate goal of combining them in a clinically feasible scoring system, we support the concept that the appropriate biomarkers could be used to direct targeted antibiotic dosing.

Identification of a novel four-gene diagnostic signature for patients with sepsis by integrating weighted gene co-expression network analysis and support vector machine algorithm

Sepsis is a life-threatening condition in which the immune response is directed towards the host tissues, causing organ failure. Since sepsis does not present with specific symptoms, its diagnosis is often delayed. The lack of diagnostic accuracy results in a non-specific diagnosis, and to date, a standard diagnostic test to detect sepsis in patients remains lacking. Therefore, it is vital to identify sepsis-related diagnostic genes. This study aimed to conduct an integrated analysis to assess the immune scores of samples from patients diagnosed with sepsis and normal samples, followed by weighted gene co-expression network analysis (WGCNA) to identify immune infiltration-related genes and potential transcriptome markers in sepsis. Furthermore, gene regulatory networks were established to screen diagnostic markers for sepsis based on the protein-protein interaction networks involving these immune infiltration-related genes. Moreover, we integrated WGCNA with the support vector machine (SVM) algorithm to build a diagnostic model for sepsis. Results showed that the immune score was significantly lower in the samples from patients with sepsis than in normal samples. A total of 328 and 333 genes were positively and negatively correlated with the immune score, respectively. Using the MCODE plugin in Cytoscape, we identified four modules, and through functional annotation, we found that these modules were related to the immune response. Gene Ontology functional enrichment analysis showed that the identified genes were associated with functions such as neutrophil degranulation, neutrophil activation in the immune response, neutrophil activation, and neutrophil-mediated immunity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed the enrichment of pathways such as primary immunodeficiency, Th1- and Th2-cell differentiation, T-cell receptor signaling pathway, and natural killer cell-mediated cytotoxicity. Finally, we identified a four-gene signature, containing the hub genes LCK, CCL5, ITGAM, and MMP9, and established a model that could be used to diagnose patients with sepsis.

Precision medicine in sepsis and septic shock: From omics to clinical tools

Sepsis is a heterogeneous disease with variable clinical course and several clinical phenotypes. As it is associated with an increased risk of death, patients with this condition are candidates for receipt of a very well-structured and protocolized treatment. All patients should receive the fundamental pillars of sepsis management, which are infection control, initial resuscitation, and multiorgan support. However, specific subgroups of patients may benefit from a personalized approach with interventions targeted towards specific pathophysiological mechanisms. Herein, we will review the framework for identifying subpopulations of patients with sepsis, septic shock, and multiorgan dysfunction who may benefit from specific therapies. Some of these approaches are still in the early stages of research, while others are already in routine use in clinical practice, but together will help in the effective generation and safe implementation of precision medicine in sepsis.

Immunomonitoring of Monocyte and Neutrophil Function in Critically Ill Patients: From Sepsis and/or Trauma to COVID-19

Immune cells and mediators play a crucial role in the critical care setting but are understudied. This review explores the concept of sepsis and/or injury-induced immunosuppression and immuno-inflammatory response in COVID-19 and reiterates the need for more accurate functional immunomonitoring of monocyte and neutrophil function in these critically ill patients. in addition, the feasibility of circulating and cell-surface immune biomarkers as predictors of infection and/or outcome in critically ill patients is explored. It is clear that, for critically ill, one size does not fit all and that immune phenotyping of critically ill patients may allow the development of a more personalized approach with tailored immunotherapy for the specific patient. In addition, at this point in time, caution is advised regarding the quality of evidence of some COVID-19 studies in the literature.

Diagnostic Value of Neutrophil CD64 in Burn Patients With Infection in Chinese Population: A Systematic Review and Meta-analysis

Infection is one of the leading causes of death in burn patients. Many researchers regard neutrophil CD64 (nCD64) as a biomarker in the early diagnosis of burn patients with infection. Nevertheless, the conclusions are controversial. A comprehensive analysis of the diagnostic value of nCD64 for burn infection was performed in China using a meta-analysis method. Pubmed, Cochrane Library, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), and China Wanfang databases were searched for studies on nCD64 as a diagnostic biomarker of burn patients with infection from the establishment of the databases to September 29, 2020. The data were analyzed by Stata 15.0 software. Six studies were identified. The results showed that the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.92 (95% confidence interval [CI]: 0.88~0.95), 0.82 (95% CI: 0.76~0.87), 5.10 (95% CI: 3.90~6.80), 0.10 (95% CI: 0.06~0.15), and 52 (95% CI: 29~94), respectively. The area under the curve was 0.94 (95% CI: 0.92~0.94). According to the analysis of the sepsis subgroup, it showed that nCD64 had good diagnostic value in the patients with burn sepsis in Chinese population. Neutrophil CD64 is highly efficient to diagnose burn infection in Chinese population. Therefore, nCD64 could be regarded as a valuable biomarker for the early diagnosis of burn infection in China, especially in patients with burn sepsis. Combined with other diagnostic indexes, nCD64 can be clinically used in the early diagnosis of burn infection to improve the sensitivity and specificity.

Diagnostic and prognostic predictive values of circulating sTREM-1 in sepsis: A meta-analysis

BACKGROUND

With the increasing studies regarding the diagnostic value of soluble triggering receptor expressed on myeloid cells (sTREM)-1 in sepsis in recent years, it is essential to make an updated meta-analysis to explore the sepsis differentiation value of circulating sTREM-1 from systemic inflammatory response syndrome (SIRS). Recently, no meta-analysis was made to explore the prognostic predictive value of circulating sTREM-1 in sepsis. Thus, the present aimed to make meta-analyses to explore the diagnostic and prognostic predictive values of circulating sTREM-1 in sepsis.

METHODS

Articles published before March 2021 were searched in databases: PubMed, Web of Science, EMBASE, Medline and Google Scholar. After a summary of sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic odds ratio (DOR), the receive-operating characteristics (SROC) curve were performed to summarize true positive (TP) and false positive (FP) rates. Q test and I² were used to explore heterogeneity between studies.

RESULTS

Circulating sTREM-1 showed a high sensitivity (0.85 (95% confidence interval (CI): 0.76-0.91)) and moderate specificity (0.79 (95% CI: 0.70-0.86)) to differentiate sepsis from SIRS. The study showed a high sensitivity (0.80 (95% CI: 0.66-0.89)) and moderate specificity (0.75 (95% CI: 0.69-0.81)) to predict 28-day mortality in sepsis.

CONCLUSION

In conclusion, the present study suggested that circulating sTREM-1 showed diagnostic and prognostic predictive values in sepsis.

Diagnostic, Prognostic, Predictive, and Monitoring Role of Neutrophil CD11b and Monocyte CD14 in Neonatal Sepsis

Background

Sepsis is a critical medical condition that requires additional diagnostic considerations. Recently, focus has shifted to the diagnosis of sepsis using new markers to overcome the limitations of traditional laboratory diagnostic modalities. Neutrophil CD11b (nCD11b) and monocyteCD14 (mCD14) cell surface antigens have been shown to be useful in such diagnostic consideration.

Aim

To investigate the diagnostic, monitoring, prognostic, and predictive roles of nCD11b and mCD14 as sepsis biomarkers in comparison to each other and to traditional laboratory sepsis parameters in order to select the best fit for routine daily use in neonatal intensive care units (NICUs).

Subject

The study included 188 neonates from Ain Shams University Hospitals' NICUs, who were divided into two groups: the control group (n = 100) and the sepsis group (n = 88). Highly sensitive CRP (hs-CRP), complete blood count (CBC), blood culture, and nCD11b and mCD14 evaluations were all part of the laboratory sepsis evaluation (done by flow cytometry technology). Positive blood culture results (BACT/ALERT system) confirmed the sepsis diagnosis. Twenty-four enrolled sepsis neonates were subjected to follow-up assessments, and they were divided into two groups based on clinical improvement: improved sepsis and sepsis without improvement. In order to predict performance evaluation, the subjected neonates were reclassified according to their outcome into survivors' and nonsurvivors' group.

Results

Sepsis patients had a significant increase in mCD14 MFI values when compared to controls. With sensitivity 75.4 percent, specificity 71.9 percent, efficacy 73.3 percent, and AUC 0.703, mCD14 MFI at cutoff 9.36 could distinguish the presence of septicemia. Significant increases in both mCD14 MFI and nCD11b MFI (P = 0.001) were observed in the severe sepsis/septic shock group compared to the nonsevere sepsis group. The combined measurement of CD14 MFI at cutoff 9.97 and CD14 percent at cutoff 44.7 percent yielded the best predictive performance.

Conclusion

Sepsis patients had a significant increase in mCD14 MFI comparable to the controls. mCD14 MFI demonstrated better diagnostic, prognostic, and predictive results than nCD11b. hs-CRP outperformed mCD14 and nCD11b in terms of diagnostic efficacy and AUC. In the monitoring of sepsis patients, both mCD14 and nCD11b produced unsatisfactory results. Currently, the routine use of mCD14 or nCD11b as sepsis biomarkers in neonatal ICUs is not justified.

The Use of Artificial Neural Networks to Forecast the Behavior of Agent-Based Models of Pathophysiology: An Example Utilizing an Agent-Based Model of Sepsis

Introduction: Disease states are being characterized at finer and finer levels of resolution via biomarker or gene expression profiles, while at the same time. Machine learning (ML) is increasingly used to analyze and potentially classify or predict the behavior of biological systems based on such characterization. As ML applications are extremely data-intensive, given the relative sparsity of biomedical data sets ML training of artificial neural networks (ANNs) often require the use of synthetic training data. Agent-based models (ABMs) that incorporate known biological mechanisms and their associated stochastic properties are a potential means of generating synthetic data. Herein we present an example of ML used to train an artificial neural network (ANN) as a surrogate system used to predict the time evolution of an ABM focusing on the clinical condition of sepsis. Methods: The disease trajectories for clinical sepsis, in terms of temporal cytokine and phenotypic dynamics, can be interpreted as a random dynamical system. The Innate Immune Response Agent-based Model (IIRABM) is a well-established model that utilizes known cellular and molecular rules to simulate disease trajectories corresponding to clinical sepsis. We have utilized two distinct neural network architectures, Long Short-Term Memory and Multi-Layer Perceptron, to take a time sequence of five measurements of eleven IIRABM simulated serum cytokine concentrations as input and to return both the future cytokine trajectories as well as an aggregate metric representing the patient's state of health. Results: The ANNs predicted model trajectories with the expected amount of error, due to stochasticity in the simulation, and recognizing that the mapping from a specific cytokine profile to a state-of-health is not unique. The Multi-Layer Perceptron neural network, generated predictions with a more accurate forecasted trajectory cone. Discussion: This work serves as a proof-of-concept for the use of ANNs to predict disease progression in sepsis as represented by an ABM. The findings demonstrate that multicellular systems with intrinsic stochasticity can be approximated with an ANN, but that forecasting a specific trajectory of the system requires sequential updating of the system state to provide a rolling forecast horizon.

Machine learning identification of specific changes in myeloid cell phenotype during bloodstream infections

The early identification of bacteremia is critical for ensuring appropriate treatment of nosocomial infections in intensive care unit (ICU) patients. The aim of this study was to use flow cytometric data of myeloid cells as a biomarker of bloodstream infection (BSI). An eight-color antibody panel was used to identify seven monocyte and two dendritic cell subsets. In the learning cohort, immunophenotyping was applied to (1) control subjects, (2) postoperative heart surgery patients, as a model of noninfectious inflammatory responses, and (3) blood culture-positive patients. Of the complex changes in the myeloid cell phenotype, a decrease in myeloid and plasmacytoid dendritic cell numbers, increase in CD14⁺CD16⁺ inflammatory monocyte numbers, and upregulation of neutrophils CD64 and CD123 expression were prominent in BSI patients. An extreme gradient boosting (XGBoost) algorithm called the “infection detection and ranging score” (iDAR), ranging from 0 to 100, was developed to identify infection-specific changes in 101 phenotypic variables related to neutrophils, monocytes and dendritic cells. The tenfold cross-validation achieved an area under the receiver operating characteristic (AUROC) of 0.988 (95% CI 0.985–1) for the detection of bacteremic patients. In an out-of-sample, in-house validation, iDAR achieved an AUROC of 0.85 (95% CI 0.71–0.98) in differentiating localized from bloodstream infection and 0.95 (95% CI 0.89–1) in discriminating infected from noninfected ICU patients. In conclusion, a machine learning approach was used to translate the changes in myeloid cell phenotype in response to infection into a score that could identify bacteremia with high specificity in ICU patients.

Which Biomarkers Can Be Used as Diagnostic Tools for Infection in Suspected Sepsis?

The diagnosis of infection in patients with suspected sepsis is frequently difficult to achieve with a reasonable degree of certainty. Currently, the diagnosis of infection still relies on a combination of systemic manifestations, manifestations of organ dysfunction, and microbiological documentation. In addition, the microbiologic confirmation of infection is obtained only after 2 to 3 days of empiric antibiotic therapy. These criteria are far from perfect being at least in part responsible for the overuse and misuse of antibiotics, in the community and in hospital, and probably the main drive for antibiotic resistance. Biomarkers have been studied and used in several clinical settings as surrogate markers of infection to improve their diagnostic accuracy as well as in the assessment of response to antibiotics and in antibiotic stewardship programs. The aim of this review is to provide a clear overview of the current evidence of usefulness of biomarkers in several clinical scenarios, namely, to diagnose infection to prescribe antibiotics, to exclude infection to withhold antibiotics, and to identify the causative pathogen to target antimicrobial treatment. In recent years, new evidence with "old" biomarkers, like C-reactive protein and procalcitonin, as well as new biomarkers and molecular tests, as breathomics or bacterial DNA identification by polymerase chain reaction, increased markedly in different areas adding useful information for clinical decision making at the bedside when adequately used. The recent evidence shows that the information given by biomarkers can support the suspicion of infection and pathogen identification but also, and not less important, can exclude its diagnosis. Although the ideal biomarker has not yet been found, there are various promising biomarkers that represent true evolutions in the diagnosis of infection in patients with suspected sepsis.

Le dosage de la procalcitonine peut-il être utile à la prise en charge d’une infection à SARS-CoV-2 aux urgences et en réanimation ?

De nombreuses études d’impact ont validé l’intérêt du dosage de la procalcitonine pour rationaliser les antibiothérapies dans les infections respiratoires basses. En l’absence d’étude prospective interventionnelle spécifiquement chez les patients atteints de Covid-19, le dosage de la procalcitonine peut cependant être utilisé aux urgences comme dans les autres IRB pour l’aide à la décision d’antibiothérapie. La majorité des infections à SARS-CoV-2 non compliquées ont des valeurs de procalcitonine inférieures à 0,25 μg/l. Parallèlement, des concentrations supérieures à 0,5 μg/l peuvent traduire un risque d’évolution vers une forme grave et/ou une co-infection bactérienne. En soins critiques, la procalcitonine est prometteuse chez les patients avec un syndrome de détresse respiratoire aiguë lié à la Covid. Chez ces patients, la pertinence de l’antibiothérapie est à reconsidérer quotidiennement, compte tenu du risque d’infection bactérienne qui évolue tout au long de séjours souvent prolongés, afin de réduire la sélection d’espèces résistantes et de limiter les toxicités.

Prognostic Value of Procalcitonin, C-Reactive Protein, and Lactate Levels in Emergency Evaluation of Cancer Patients with Suspected Infection

Simple Summary

Cancer patients are at increased risk of infections and related complications, including sepsis. We developed a scoring system for mortality prediction based on readily available clinical and laboratory data, including the quick sequential organ failure assessment (qSOFA) score, cancer subtype, and several laboratory markers (procalcitonin, C-reactive protein, lactate dehydrogenase, and albumin) that can be used in emergency departments for cancer patients with suspected infection. The prediction score, which stratifies patients into four different risk groups (from low risk to very high risk), achieved excellent performance in predicting 14-day mortality, with an area under the receiver operating characteristic curve value of 0.88 (95% confidence interval 0.85–0.91). The score was also effective in predicting intensive care unit admission and 30-day mortality.

Abstract

Cancer patients have increased risk of infections, and often present to emergency departments with infection-related problems where physicians must make decisions based on a snapshot of the patient’s condition. Although C-reactive protein, procalcitonin, and lactate are popular biomarkers of sepsis, their use in guiding emergency care of cancer patients with infections is unclear. Using these biomarkers, we created a prediction model for short-term mortality in cancer patients with suspected infection. We retrospectively analyzed all consecutive patients who visited the emergency department of MD Anderson Cancer Center between 1 April 2018 and 30 April 2019. A clinical decision model was developed using multiple logistic regression for various clinical and laboratory biomarkers; coefficients were used to generate a prediction score stratifying patients into four groups according to their 14-day mortality risk. The prediction score had an area under the receiver operating characteristic curve value of 0.88 (95% confidence interval 0.85–0.91) in predicting 14-day mortality. The prediction score also accurately predicted intensive care unit admission and 30-day mortality. Our simple new scoring system for mortality prediction, based on readily available clinical and laboratory data, including procalcitonin, C-reactive protein, and lactate, can be used in emergency departments for cancer patients with suspected infection.

Predictors of plasma leakage among dengue patients in Thailand: A plasma-leak score analysis

Delayed plasma leakage recognition could lead to improper fluid administration resulting in dengue shock syndrome, subsequently, multi-organ failure, and death. This prospective observational study was conducted in Bangkok, Thailand, between March 2018 and February 2020 to determine predictors of plasma leakage and develop a plasma leakage predictive score among dengue patients aged ≥15 years. Of 667 confirmed dengue patients, 318 (47.7%) developed plasma leakage, and 349 (52.3%) had no plasma leakage. Multivariate analysis showed three independent factors associated with plasma leakage, including body mass index ≥25.0 kg/m2 (odds ratio [OR] = 1.784; 95% confidence interval [CI] = 1.040-3.057; P = 0.035), platelet count <100,000/mm3 on fever days 3 to 4 (OR = 2.151; 95% CI = 1.269-3.647; P = 0.004), and aspartate aminotransferase or alanine aminotransferase ≥100 U/l on fever days 3 to 4 (OR = 2.189; 95% CI = 1.231-3.891; P = 0.008). Because these three parameters had evidence of equality, each independent factor was weighted to give a score of 1 with a total plasma-leak score of 3. Higher scores were associated with increased plasma leakage occurrence, with ORs of 2.017 (95% CI = 1.052-3.869; P = 0.035) for score 1, 6.158 (95% CI = 2.914-13.015; P <0.001) for score 2, and 6.300 (95% CI = 2.419-16.407; P <0.001) for score 3. The area under the receiver operating characteristics curves for predicting plasma leakage was good (0.677 [95% CI = 0.616-0.739]). Patients with a plasma-leak score ≥1 had high sensitivity (88.8%), and those with a plasma-leak score of 3 had high specificity (93.4%) for plasma leakage occurrence. This simple and easily accessible clinical score might help physicians provide early and timely appropriate clinical dengue management in endemic areas.

The Surviving Sepsis Campaign: research priorities for the administration, epidemiology, scoring and identification of sepsis

Objective

To identify priorities for administrative, epidemiologic and diagnostic research in sepsis.

Design

As a follow-up to a previous consensus statement about sepsis research, members of the Surviving Sepsis Campaign Research Committee, representing the European Society of Intensive Care Medicine and the Society of Critical Care Medicine addressed six questions regarding care delivery, epidemiology, organ dysfunction, screening, identification of septic shock, and information that can predict outcomes in sepsis.

Methods

Six questions from the Scoring/Identification and Administration sections of the original Research Priorities publication were explored in greater detail to better examine the knowledge gaps and rationales for questions that were previously identified through a consensus process.

Results

The document provides a framework for priorities in research to address the following questions: (1) What is the optimal model of delivering sepsis care?; (2) What is the epidemiology of sepsis susceptibility and response to treatment?; (3) What information identifies organ dysfunction?; (4) How can we screen for sepsis in various settings?; (5) How do we identify septic shock?; and (6) What in-hospital clinical information is associated with important outcomes in patients with sepsis?

Conclusions

There is substantial knowledge of sepsis epidemiology and ways to identify and treat sepsis patients, but many gaps remain. Areas of uncertainty identified in this manuscript can help prioritize initiatives to improve an understanding of individual patient and demographic heterogeneity with sepsis and septic shock, biomarkers and accurate patient identification, organ dysfunction, and ways to improve sepsis care.

Diagnostic value of neutrophil CD64, procalcitonin, and interleukin-6 in sepsis: a meta-analysis

Background

The aim of the study was to conduct a meta-analysis to evaluate the accuracy of neutrophil CD64, procalcitonin (PCT), and interleukin-6 (IL-6) as markers for the diagnosis of sepsis in adult patients.

Methods

Various databases were searched to collect published studies on the diagnosis of sepsis in adult patients using neutrophil CD64, PCT, and IL-6 levels. Utilizing the Stata SE 15.0 software, forest plots and the area under the summary receiver operating characteristic curves were drawn. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the curve (AUC) were calculated.

Results

Fifty-four articles were included in the study. The pooled sensitivity, specificity, and AUC of neutrophil CD64 for the diagnosis of sepsis were 0.88 (95% confidence interval [CI], 0.81–0.92), 0.88 (95% CI, 0.83–0.91), and 0.94 (95% CI, 0.91–0.96), respectively. The pooled sensitivity, specificity, and AUC of PCT for the diagnosis of sepsis were 0.82 (95% CI, 0.78–0.85), 0.78 (95% CI, 0.74–0.82), and 0.87 (95% CI, 0.83–0.89), respectively. Subgroup analysis showed that the AUC for PCT diagnosis of intensive care unit (ICU) sepsis was 0.86 (95% CI, 0.83–0.89) and the AUC for PCT diagnosis of non-ICU sepsis was 0.82 (95% CI, 0.78–0.85). The pooled sensitivity, specificity, and AUC of IL-6 for the diagnosis of sepsis were 0.72 (95% CI, 0.65–0.78), 0.70 (95% CI, 0.62–0.76), and 0.77 (95% CI, 0.73–0.80), respectively.

Conclusions

Of the three biomarkers studied, neutrophil CD64 showed the highest diagnostic value for sepsis, followed by PCT, and IL-6. On the other hand, PCT showed a better diagnostic potential for the diagnosis of sepsis in patients with severe conditions compared with that in patients with non-severe conditions.

Soluble triggering receptor expressed on myeloid cells-1 is a marker of organ injuries in cardiogenic shock: results from the CardShock Study

AIMS

Optimal outcome after cardiogenic shock (CS) depends on a coordinated healing response in which both debris removal and extracellular matrix tissue repair play a crucial role. Excessive inflammation can perpetuate a vicious circle, positioning leucocytes as central protagonists and potential therapeutic targets. High levels of circulating Triggering Receptor Expressed on Myeloid cells-1 (TREM-1), were associated with death in acute myocardial infarction confirming excessive inflammation as determinant of bad outcome. The present study aims to describe the association of soluble TREM-1 with 90-day mortality and with various organ injuries in patients with CS.

METHODS AND RESULTS

This is a post-hoc study of CardShock, a prospective, multicenter study assessing the clinical presentation and management in patients with CS. At the time of this study, 87 patients had available plasma samples at either baseline, and/or 48 h and/or 96-120 h for soluble TREM-1 (sTREM-1) measurements. Plasma concentration of sTREM-1 was higher in 90-day non-survivors than survivors at baseline [median: 1392 IQR: (724-2128) vs. 621 (525-1233) pg/mL, p = 0.008), 48 h (p = 0.019) and 96-120 h (p = 0.029). The highest tertile of sTREM-1 at baseline (threshold: 1347 pg/mL) was associated with 90-day mortality with an unadjusted HR 3.08 CI 95% (1.48-6.42). sTREM-1 at baseline was not associated to hemodynamic parameters (heart rate, blood pressure, use of vasopressors or inotropes) but rather with organ injury markers: renal (estimated glomerular filtration rate, p = 0.0002), endothelial (bio-adrenomedullin, p = 0.018), myocardial (Suppression of Tumourigenicity 2, p = 0.002) or hepatic (bilirubin, p = 0.008).

CONCLUSION

In CS patients TREM-1 pathway is highly activated and gives an early prediction of vital organ injuries and outcome.

Diagnostic Value of Plasma Soluble Triggering Receptor Expressed on Myeloid Cells-1 in Children with Urinary Tract Infections

Objective The aim of the present study was to evaluate the diagnostic value of soluble triggering receptor on myeloid cells-1 as a novel marker for diagnosis of childhood urinary tract infections (UTI).

Methods This study enrolled 30 pediatric patients diagnosed with acute febrile UTIs; 30 healthy children were included as the control group. The blood samples from the patients and healthy controls were collected for a soluble triggering receptor on myeloid cells-1 (sTREM-1) test.

Results The study group was composed of 9 males and 21 females, and the mean age of the study population was 6.6 ± 3.2 (range = 1–14) years. sTREM-1 levels were significantly higher in UTI patients than in the controls (592 ± 323 vs. 490 ± 299 pg/mL, p = 0.04). The receiver operating curve analysis revealed a cut-off value of soluble triggering receptor expressed on myeloid cells-1 of 514 ng/mL (area under the curve = 0.562). When the cut-off value was taken 514 pg/mL, soluble triggering receptor expressed on myeloid cells-1 had a sensitivity of 57% and a specificity of 50% for the diagnosis of UTI.

Conclusion The present study revealed that plasma sTREM-1 level may be elevated in UTI and may therefore serve as a useful predictive tool for the diagnosis of UTI.

Optimal combination of early biomarkers for infection and sepsis diagnosis in the emergency department: The BIPS study

OBJECTIVE

To define the best combination of biomarkers for the diagnosis of infection and sepsis in the emergency room.

METHODS

In this prospective study, consecutive patients with a suspicion of infection in the emergency room were included. Eighteen different biomarkers measured in plasma, and twelve biomarkers measured on monocytes, neutrophils, B and T-lymphocytes were studied and the best combinations determined by a gradient tree boosting approach.

RESULTS

Overall, 291 patients were included and analysed, 148 with bacterial infection, and 47 with viral infection. The best biomarker combination which first allowed the diagnosis of bacterial infection, included HLA-DR (human leukocyte antigen DR) on monocytes, MerTk (Myeloid-epithelial-reproductive tyrosine kinase) on neutrophils and plasma metaloproteinase-8 (MMP8) with an area under the curve (AUC) = 0.94 [95% confidence interval (IC95): 0.91;0.97]. Among patients in whom a bacterial infection was excluded, the combination of CD64 expression, and CD24 on neutrophils and CX3CR1 on monocytes ended to an AUC = 0.98 [0.96;1] to define those with a viral infection.

CONCLUSION

In a convenient cohort of patients admitted with a suspicion of infection, two different combinations of plasma and cell surface biomarkers were performant to identify bacterial and viral infection.

Diagnostic Accuracy of Infection Markers to Diagnose Infections in Neonates and Children Receiving Extracorporeal Membrane Oxygenation

BACKGROUND

Infections represent one of the most common complications in patients managed on Extracorporeal Membrane Oxygenation (ECMO) and are associated with poorer outcomes. Clinical signs of infection in patients on ECMO are non-specific. We assessed the diagnostic accuracy of Procalcitonin (PCT), C-reactive protein (CRP) and White cell count (WCC) to diagnose infection on ECMO.

METHODS

Retrospective single center observational study including neonates and children <18 years treated with ECMO in 2015 and 2016. Daily data on PCT, CRP and WCC were assessed in relation to microbiologically confirmed, and clinically suspected infection on ECMO using operating characteristics (ROC) curves.

RESULTS

Sixty-five ECMO runs in 58 patients were assessed. CRP had the best accuracy with an area under the ROC curve (AUC) of 0.79 (95%-CI 0.66-0.92) to diagnose confirmed infection and an AUC of 0.72 (0.61-0.84) to diagnose confirmed and suspected infection. Abnormal WCC performed slightly worse with an AUC of 0.70 (0.59-0.81) for confirmed and AUC of 0.66 (0.57-0.75) for confirmed and suspected infections. PCT was non-discriminatory.

CONCLUSION

The diagnosis of infections acquired during ECMO remains challenging. Larger prospective studies are needed that also include novel infection markers to improve recognition of infection in patients on ECMO.

Neutrophil CD64 a Diagnostic and Prognostic Marker of Sepsis in Adult Critically Ill Patients: A Brief Review

INTRODUCTION

Sepsis is a life-threatening organ dysfunction with increased incidence of morbidity and mortality. Early diagnosis and prompt therapeutic intervention is the cornerstone of sepsis care. Biomarkers play an important role in sepsis having both diagnostic and prognostic implications. Neutrophil CD64 (nCD64) is a useful candidate biomarker for sepsis. Neutrophil CD64 also known as Fc receptor 1 (FcR1), is a high-affinity receptor present on neutrophils for Fc part of immunoglobulin-G (IgG) heavy chain. Its expression gets strongly upregulated in response to proinflammatory cytokines of infection within 4-6 hours. Neutrophil CD64 integrates function involving both innate and adaptive immune responses. The aim of this review is to present literature about nCD64 as a diagnostic and prognostic marker in patients with sepsis/septic shock.

BACKGROUND

The authors searched articles over 13 years, i.e., from 2006 to 2019. They included articles written in English only and further reviewed the reference list of selected articles to obtain potentially relevant articles. Reviews, letters, commentaries, correspondences, case reports, conference abstracts, expert opinions, editorials, and animal experiments were excluded. Articles involving pediatric patients (≤18 years) were also excluded.

REVIEW RESULTS

Several studies have indicated that nCD64 is a highly sensitive and specific marker for the diagnosis of sepsis. Various combinations of biomarkers have been used with nCD64 for a better diagnostic value. Neutrophil CD64 as a prognostic marker in critically ill patients needs to be explored more. Most of the existing literatures have highlighted its prognostic utility based on single value at enrolment. There are limited literatures on prognostic implications of serial trend and kinetics of nCD64.

CONCLUSION

Neutrophil CD64 is a useful diagnostic and prognostic marker of sepsis in critically ill patients. Additional studies are needed on nCD64 in sepsis based on sepsis-3 criteria. Further trials with large sample size are needed to establish prognostic implications of serial nCD64 trend.

HOW TO CITE THIS ARTICLE

Patnaik R, Azim A, Agarwal V. Neutrophil CD64 a Diagnostic and Prognostic Marker of Sepsis in Adult Critically Ill Patients: A Brief Review. Indian J Crit Care Med 2020;24(12):1242-1250.

Current Evidence and Limitation of Biomarkers for Detecting Sepsis and Systemic Infection

Sepsis was recently redefined as a life-threatening disease involving organ dysfunction caused by a dysregulated host response to infection. Biomarkers play an important role in early detection, diagnosis, and prognostication. We reviewed six promising biomarkers for detecting sepsis and systemic infection, including C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), CD64, presepsin, and sTREM-1. Among the recent studies, we found the following risks of bias: only a few studies adopted the random or consecutive sampling strategy; extensive case-control analysis, which worsened the over-estimated performance; most of the studies used post hoc cutoff values; and heterogeneity with respect to the inclusion criteria, small sample sizes, and different quantitative synthesis methods applied in meta-analyses. We recommend that CD64 and presepsin should be considered as the most promising biomarkers for diagnosing sepsis. Future studies should enroll a larger sample size with a cohort rather than a case-control study design. A random or consecutive study design with a pre-specified laboratory threshold, consistent sampling timing, and an updated definition of sepsis will also increase the reliability of the studies. Further investigations of appropriate specimens, testing assays, and cutoff levels for specific biomarkers are also warranted.

Differential expression of CD64 in patients with Mycobacterium tuberculosis infection: A potential biomarker for clinical diagnosis and prognosis

To evaluate the clinical utility of neutrophil (n)CD64 index to diagnose pulmonary tuberculosis (PTB) and extrapulmonary TB (ePTB) and to predict the outcome of Mycobacterium tuberculosis infection. We recruited 189 patients with active TB and 140 controls and measured the differential expression of nCD64 index using flow cytometry. The receiver operating characteristics (ROC) curve analysis was performed to estimate the diagnostic performance of the nCD64 index and T‐SPOT.TB assay for the diagnosis of TB. Furthermore, we analysed whether the nCD64 index in patients with TB was correlated with inflammatory indicators. Finally, we assessed the prognosis of patients by following the dynamic changes of the nCD64 index once a week. The nCD64 index was significantly higher in active TB group (PTB and ePTB), than in the anti‐TB and healthy controls (HC) groups. The sensitivity and specificity of nCD64 index for the differential diagnosis of PTB and pneumonia (PN) patients were 68.33% and 77.55%, respectively. The sensitivity and specificity of nCD64 index for the diagnosis of tuberculous meningitis (TBM) were 53.85% and 100%, respectively. Furthermore, there was a weak correlation between the nCD64 index and inflammatory indicators. More importantly, with the improvement in patient condition, the nCD64 index started to decline in the first week of anti‐TB therapy and significantly decreased at 4 weeks after treatment. Our study demonstrated that the CD64 assay is a rapid, non‐invasive and stable method for clinical application, and the nCD64 index can serve as a potential biomarker for the diagnosis and prognosis of TB.

The Utility of Neutrophil CD64 and Presepsin as Diagnostic, Prognostic, and Monitoring Biomarkers in Neonatal Sepsis

Background

Neonatal septicemia is a critical medical situation; current conventional laboratory methods still have many limitations and diagnostic obstacles. For this purpose, last decades have witnessed a challenge between the battery of sepsis biomarkers including many leukocyte surface antigens, not only for early diagnostic purposes but also for better follow-up and good management of sepsis patients.

Aim

To evaluate the diagnostic, prognostic, and monitoring performance of both neutrophil CD64 (nCD64) and presepsin as sepsis biomarkers compared to each other and to the conventional laboratory sepsis parameters aiming to decide which is the best fitting for routine daily use in neonatal intensive care units (NICUs).

Methods

235 neonates were enrolled from three Egyptian neonatal ICUs, during the period from November 2015 till March 2018; they were classified into two main groups: the control group (n = 102) and the sepsis group (n = 133). Laboratory sepsis evaluation included highly sensitive CRP (hs-CRP), CBC, in addition to nCD64 (flow cytometry technique), and presepsin measurement (CLEIA technique combined with Magtration® technology); the diagnosis was confirmed thereafter by positive blood culture results (BacT/Alert system). Sixty-two of the enrolled sepsis neonates were subjected to follow-up assessment; they were reclassified according to their clinical improvement at the second time assessment into (group 1: sepsis group without improvement) (n = 20) and (group 2: improved sepsis group) (n = 42).

Results

Significant increase in nCD64 and presepsin values was found in sepsis groups compared to the controls. At cutoff 41.6%, nCD64% could discriminate the presence of septicemia with sensitivity 94.7%, specificity 93.6 %, and AUC 0.925, while presepsin at cutoff 686 pg/ml achieves sensitivity 82.7%, specificity 95.5%, and AUC 0.887, respectively. Significant increase in nCD64 (P < 0.001) and hs-CRP (P=0.018) values was observed in severe sepsis/septic shock patients compared to nonsevere sepsis patients. Delta change percentage (dC%) between initial and follow-up evaluations for both improved and nonimproved sepsis patients was dC Z value −5.904 for nCD64% followed by dC Z value −4.494 for presepsin.

Conclusion

nCD64 and presepsin are valuable early diagnostic and monitoring sepsis biomarkers; the highest sensitivity could be achieved by a univariant sepsis marker in this study was recorded by the nCD64% biomarker, while the highest specificity was documented by presepsin. Combined measurement of both achieves the highest diagnostic performance in sepsis neonates. Either of CD64 or presepsin combined with hs-CRP associated with better performance than any of them alone. nCD64 carries an additional promising role in reflecting sepsis prognosis.

Comprehensive analysis of multiple cytokines and blood parameters for the diagnosis of bacterial infections in rheumatoid arthritis

Patients with rheumatoid arthritis (RA) are more susceptible to infections, which elevate the levels of relative cytokines. However, the ability of the cytokines levels to predicate bacterial infections in RA patients remains unclear. Here, we assessed the ability of the combination of serum cytokine levels and blood parameters to diagnose bacterial infections in RA patients. We measured the levels of a panel of serum cytokine and blood parameters in 168 RA patients and 81 healthy individuals. RA patients were divided into the bacterial infection (INFE) group (n = 76) and RA flare without INFE group (n = 92). Bacterial infection was confirmed by microbial culture, imaging, antibiotic response, and typical clinical symptoms. The discriminative ability of the combination of the cytokine levels and inflammatory parameters was assessed using the receiver-operating characteristic (ROC) curves analysis and a novel bioscore system. The levels of interleukin (IL)-6 (p = 0.006), IL-10 (p = 0.019), interferon (IFN)-γ (p = 0.033), CRP (p < 0.001), and ESR (p < 0.001) were higher in patients of the INFE group than in patients with RA flare, and the absolute numbers of CD19⁺ B cells (p < 0.001) and CD4⁺ T cells (p = 0.009) were lower. For discriminating bacterial infection, the combination of IL-6, IL-10, IFN-γ, ESR, CRP, CD19⁺ B cells, and CD4⁺ T cells, provided an area under the curve (AUC) of 0.827 [(95% confidence interval (CI): 0.760-0.881)], which was profoundly larger than that of IL-6, IL-10, IFN-γ, ESR, CRP, CD19⁺ B cells, or CD4⁺ T cells alone. In addition, we also developed a bioscore system based on the combination of these seven biomarkers. Seventeen (100%) patients with a bioscore of 0 were non-infected, while seven (100%) patients with a score of 7 had bacterial infections. The bioscore based on the combination of ESR, CRP, IL-6, IL-10, IFN-γ, CD19⁺ B cells and CD4⁺ T cells may be a promising and robust tool to diagnose bacterial infections in RA patients.

Identification of progranulin as a novel diagnostic biomarker for early-onset sepsis in neonates

Neonatal early-onset sepsis (EOS) is associated with high morbidity and mortality. Accurate early diagnosis is crucial for prompt treatment and a better clinical outcome. We aimed to identify new biomarkers for the diagnosis of EOS. A total of 152 neonates with a risk of EOS were divided into an EOS group and a non-EOS group according to the conventional diagnostic criteria. Blood samples were collected within 0-24, 24-48, and 48-72 h after birth. Serum levels of progranulin (PGRN), interleukin (IL)-33, IL-17a, IL-23, IL-6, tumor necrosis factors α (TNF-α), interferon γ (IFN-γ), granulocyte-macrophage colony-stimulating factor (GM-CSF), procalcitonin (PCT), and C-reactive protein (CRP) were determined. PGRN levels were significantly elevated in the EOS neonates compared with the levels in the non-EOS neonates (1.53 vs. 0.77 ng/ml (median), P < 0.001), with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.76 (P < 0.001). Compared with PGRN, IL-33, IL-17a, IL-23, IL-6, PCT, and CRP showed significant (AUC > 0.70) but slightly less predictive power for EOS within the same time range. Stepwise multivariate regression analysis identified PGRN, IL-33, and PCT as independent predictors of EOS. In addition, the combined measurements of PGRN, IL-33, and PCT showed significantly higher predictive power for EOS than any of the three markers alone. PGRN showed greater efficacy for predicting EOS than the traditional markers PCT and CRP as well as other potential markers tested in this study. PGRN may serve as an effective biomarker for the early diagnosis of EOS.