Combined use of biomarkers for distinguishing between bacterial and viral etiologies in pediatric lower respiratory tract infections

Diagnostic value of serum CRP, PCT and IL-6 in children with nephrotic syndrome complicated by infection: a single center retrospective study

OBJECTIVE

The purpose was to look into the diagnostic value of serum CRP, PCT and IL-6 in children with nephrotic syndrome co-infection.

METHODS

One hundred and forty-nine children with nephrotic syndrome who met the inclusion and exclusion criteria were included in this study. The children were divided into three groups: bacterial infection group, non-bacterial infection group, and non-infection group. The diagnostic value was analyzed and compared using the ROC curve.

RESULTS

There was no statistically significant difference in the Leukocyte counts among three groups. The mean results of serum CRP, PCT and IL-6 were significantly higher in the bacterial infection group compared to those in the non-infection group (p < 0.05). AUC of CRP, PCT, IL-6 in bacterial infection were 0.791, 0.859, 0.783. The following combinations CRP + PCT + IL-6, IL-6 + PCT, CRP + PCT significantly increased the efficiency of bacterial infection diagnosis, the AUCs were 0.881, 0.884, and 0.884, respectively. AUC of PCT in non-bacterial infection was 0.663. The combinations of these three clinical indicators performed no better than PCT in ROC analysis.

CONCLUSION

Normal CRP or IL-6 levels do not rule out the diagnosis of bacterial infection in children on long-term glucocorticoid therapy. The appropriate combination of two or three indicators can improve the diagnostic value.

IMPACT

This study evaluated the diagnostic value of the serum concentrations of CRP, PCT and IL-6 and assessed whether the value of their combined application is better than when used alone for diagnosing primary nephrotic syndrome complicated by infection. The elevation in leukocyte count cannot be used to diagnose children with nephrotic syndromes on long-term glucocorticoid treatment who have bacterial infections. Normal CRP or IL-6 levels do not rule out the diagnosis of bacterial infection in children on long-term glucocorticoid therapy. The appropriate combination of two or three indicators can improve diagnostic value, sensitivity, and specificity.

Epidemiologic, clinical, and serum markers may improve discrimination between bacterial and viral etiologies of childhood pneumonia

Background

Discrimination of bacterial and viral etiologies of childhood community-acquired pneumonia (CAP) is often challenging. Unnecessary antibiotic administration exposes patients to undue risks and may engender antimicrobial resistance. This study aimed to develop a prediction model using epidemiological, clinical and laboratory data to differentiate between bacterial and viral CAP.

Methods

Data from 155 children with confirmed bacterial or mixed bacterial and viral infection (N = 124) and viral infection (N = 31) were derived from a comprehensive assessment of causative pathogens [Partnerships for Enhanced Engagement in Research-Pneumonia in Pediatrics (PEER-PePPeS)] conducted in Indonesia. Epidemiologic, clinical and biomarker profiles (hematology and inflammatory markers) were compared between groups. The area under the receiver operating characteristic curve (AUROC) for varying biomarker levels was used to characterize performance and determine cut-off values for discrimination of bacterial and mixed CAP versus viral CAP. Diagnostic predictors of bacterial and mixed CAP were assessed by multivariate logistic regression.

Results

Diarrhea was more frequently reported in bacterial and mixed CAP, while viral infections more frequently occurred during Indonesia's rainy season. White blood cell counts (WBC), absolute neutrophil counts (ANC), neutrophil-lymphocyte ratio (NLR), C-reactive protein (CRP), and procalcitonin (PCT) were significantly higher in bacterial and mixed cases. After adjusting for covariates, the following were the most important predictors of bacterial or mixed CAP: rainy season (aOR 0.26; 95% CI 0.08-0.90; p = 0.033), CRP ≥5.70 mg/L (aOR 4.71; 95% CI 1.18-18.74; p = 0.028), and presence of fever (aOR 5.26; 95% CI 1.07-25.91; p = 0.041). The model assessed had a low R-squared (Nagelkerke R² = 0.490) but good calibration (p = 0.610 for Hosmer Lemeshow test). The combination of CRP and fever had moderate predictive value with sensitivity and specificity of 62.28 and 65.52%, respectively.

Conclusion

Combining clinical and laboratory profiles is potentially valuable for discriminating bacterial and mixed from viral pediatric CAP and may guide antibiotic use. Further studies with a larger sample size should be performed to validate this model.

Diagnostic models predicting paediatric viral acute respiratory infections: a systematic review

OBJECTIVES

To systematically review and evaluate diagnostic models used to predict viral acute respiratory infections (ARIs) in children.

DESIGN

Systematic review.

DATA SOURCES

PubMed and Embase were searched from 1 January 1975 to 3 February 2022.

ELIGIBILITY CRITERIA

We included diagnostic models predicting viral ARIs in children (<18 years) who sought medical attention from a healthcare setting and were written in English. Prediction model studies specific to SARS-CoV-2, COVID-19 or multisystem inflammatory syndrome in children were excluded.

DATA EXTRACTION AND SYNTHESIS

Study screening, data extraction and quality assessment were performed by two independent reviewers. Study characteristics, including population, methods and results, were extracted and evaluated for bias and applicability using the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies and PROBAST (Prediction model Risk Of Bias Assessment Tool).

RESULTS

Of 7049 unique studies screened, 196 underwent full text review and 18 were included. The most common outcome was viral-specific influenza (n=7; 58%). Internal validation was performed in 8 studies (44%), 10 studies (56%) reported discrimination measures, 4 studies (22%) reported calibration measures and none performed external validation. According to PROBAST, a high risk of bias was identified in the analytic aspects in all studies. However, the existing studies had minimal bias concerns related to the study populations, inclusion and modelling of predictors, and outcome ascertainment.

CONCLUSIONS

Diagnostic prediction can aid clinicians in aetiological diagnoses of viral ARIs. External validation should be performed on rigorously internally validated models with populations intended for model application.

PROSPERO REGISTRATION NUMBER

CRD42022308917.

Cellular analysis and metagenomic next-generation sequencing of bronchoalveolar lavage fluid in the distinction between pulmonary non-infectious and infectious disease

Background

The aim of the current study was to investigate the clinical value of cellular analysis and metagenomic next-generation sequencing (mNGS) of bronchoalveolar lavage fluid (BALF) in differentiating pulmonary non-infectious and infectious diseases in immunocompetent patients.

Methods

The present retrospective study was conducted from December 2017 to March 2020, and included immunocompetent patients with suspected pulmonary infection. High-resolution computed tomography, total cell counts and classification of BALF, conventional microbiological tests (CMTs), laboratory tests and mNGS of BALF were performed. Patients were assigned to pulmonary non-infectious disease (PNID) and pulmonary infectious disease (PID) groups based on final diagnoses. PNID-predictive values were analyzed via areas under receiver operating characteristic curves (AUCs). Optimal cutoffs were determined by maximizing the sum of sensitivity and specificity.

Results

A total of 102 patients suspected of pulmonary infection were enrolled in the study, 23 (22.5%) with PNID and 79 (77.5%) with PID. The diagnostic efficiency of BALF mNGS for differentiating PID from PNID was better than that of CMTs. Neutrophil percentage (N%) and the ratio of neutrophils to lymphocytes (N/L) in BALF were significantly lower in the PNID group than in the PID group. The AUCs for distinguishing PNID and PID were 0.739 (95% confidence interval [CI] 0.636-0.825) for BALF N%, 0.727 (95% CI 0.624-0.815) for BALF N/L, and 0.799 (95% CI 0.702-0.876) for BALF mNGS, with respective cutoff values of 6.7%, 0.255, and negative. Joint models of BALF mNGS combined with BALF N/L or BALF N% increased the respective AUCs to 0.872 (95% CI 0.786-0.933) and 0.871 (95% CI 0.784-0.932), which were significantly higher than those for BALF mNGS, BALF N%, and BALF N/L alone.

Conclusions

BALF N% ≤ 6.7% or BALF N/L ≤ 0.255 combined with a negative BALF mNGS result can effectively distinguish PNID from PID in immunocompetent patients with suspected pulmonary infection. BALF mNGS outperforms CMTs for identifying pathogens in immunocompetent patients, and the combination of mNGS and CMTs may be a better diagnostic strategy.

Machine Learning Approaches for Discriminating Bacterial and Viral Targeted Human Proteins

Infectious diseases are one of the core biological complications for public health. It is important to recognize the pathogen-specific mechanisms to improve our understanding of infectious diseases. Differentiations between bacterial- and viral-targeted human proteins are important for improving both prognosis and treatment for the patient. Here, we introduce machine learning-based classifiers to discriminate between the two groups of human proteins. We used the sequence, network, and gene ontology features of human proteins. Among different classifiers and features, the deep neural network (DNN) classifier with amino acid composition (AAC), dipeptide composition (DC), and pseudo-amino acid composition (PAAC) (445 features) achieved the best area under the curve (AUC) value (0.939), F1-score (94.9%), and Matthews correlation coefficient (MCC) value (0.81). We found that each of the selected top 100 of the bacteria- and virus-targeted human proteins from a candidate pool of 1618 and 3916 proteins, respectively, were part of distinct enriched biological processes and pathways. Our proposed method will help to differentiate between the bacterial and viral infections based on the targeted human proteins on a global scale. Furthermore, identification of the crucial pathogen targets in the human proteome would help us to better understand the pathogen-specific infection strategies and develop novel therapeutics.

The Clinical Diagnostic Values of SAA, PCT, CRP, and IL-6 in Children with Bacterial, Viral, or Co-Infections

Background

Bacterial, viral, and bacterial and viral co-infections generally lead to inflammatory-related diseases. The aim of this study is to assess the clinical diagnostic values of serum amyloid A (SAA), procalcitonin (PCT), C-reactive protein (CRP), and interleukin (IL)-6 in children with bacterial, viral, or co-infections.

Methods

A total of 181 children with infection symptoms (bacterial infection (Bac group), n = 46; viral infection (Vir group), n = 7; co-infections (Bac + Vir group), n = 128) were enrolled in our hospital from December 2019 to April 2020. Meanwhile, 42 healthy children without any infections were used as the controls. Venous blood samples were collected and the levels of serum SAA, PCT, CRP, and IL-6 were determined by immunoluminometric assay under an IMMAGE^® analyzer. The diagnostic values of these biomarkers were assessed using the receiver operating characteristic (ROC) curves.

Results

The results indicated that IL-6 level was increased in three infection groups compared to the controls. Both SAA and CRP were significantly elevated in Vir and Bac + Vir groups. High level of PCT was observed in Bac and Bac + Vir goups. In addition, PCT (0.9281, 95% CI = 0.8645-0.9916) alone is an effective method for identifying bacterial infections. SAA in combination with CRP may distinguish co-infection from bacterial infection. Simultaneous positive of SAA, PCT, IL-6, and CRP can discriminate co-infection from the healthy controls.

Conclusion

In a word, the levels of serum SAA, PCT, CRP, and IL-6 are increased to varying degrees in different infection situations. Our findings may provide early diagnosis for patients with different infections.

Pilot Study Analysis of Serum Cytokines to Differentiate Pediatric Septic Arthritis and Transient Synovitis

BACKGROUND

In pediatric patients, the presentation of the nontraumatic acutely painful joint/limb poses a diagnostic dilemma due to the similarity of presentations of the most likely diagnoses [septic arthritis (SA), transient synovitis (TS), osteomyelitis]. Current tools employed to differentiate these diagnoses rely on nonspecific inflammatory markers, radiologic imaging, and arthrocentesis. Diagnostic algorithms utilizing these clinical, radiographic, and biochemical parameters have produced conflicting results. The purpose of this study was to identify a serum-based inflammatory signature which can differentiate SA from TS in pediatric patients.

METHODS

Serum samples were collected from 22 pediatric patients presenting with joint/extremity pain whose working diagnosis included SA or TS. Each sample was analyzed for serum abundance of 72 distinct biomarkers and cytokines using enzyme linked immunosorbent assay based arrays. Linear discriminant analysis was performed to identify a combinatorial biomarker panel to predict a diagnosis of SA or TS. Efficacy of the biomarker panel was compared with definitive diagnoses as based on laboratory tests, arthrocentesis results, and clinical scenario.

RESULTS

At the time of presentation: (1) mean erythrocyte sedimentation rate in the SA group was 56.6 mm/h and 12.4 mm/h in the TS group (P<0.001), (2) mean C-reactive protein was 55.9 mg/dL in the SA group and 13.7 mg/dL in the TS group (P=0.12), and (3) mean white blood cell was 10.9 k/mm3 in the SA group and 11.0 k/mm3 in the TS group (P=0.95). A combined panel of 72 biomarkers was examined using discriminant analysis to identify a limited set of predictors which could accurately predict whether a patient was diagnosed with SA or TS. A diagnostic algorithm consisting of transforming growth factor alpha, interleukin (IL)-7, IL-33, and IL-28A serum concentration correctly classified 20 of the 22 cases with a sensitivity and specificity of 90.9% (95% confidence interval: 73.9%-100.0%).

CONCLUSION

This study identifies a novel serum-based 4-cytokine panel that accurately differentiates SA from TS in pediatric patients with joint/limb pain.

LEVEL OF EVIDENCE

Level II-diagnostic study.

Distinguishing bacterial versus non-bacterial causes of febrile illness - A systematic review of host biomarkers

BACKGROUND

Acute febrile illnesses (AFIs) represent a major disease burden globally; however, the paucity of reliable, rapid point-of-care testing makes their diagnosis difficult. A simple tool for distinguishing bacterial versus non-bacterial infections would radically improve patient management and reduce indiscriminate antibiotic use. Diagnostic tests based on host biomarkers can play an important role here, and a target product profile (TPP) was developed to guide development.

OBJECTIVES

To qualitatively evaluate host biomarkers that can distinguish bacterial from non-bacterial causes of AFI.

DATA SOURCES

The PubMed database was systematically searched for relevant studies published between 2015 and 2019.

STUDY ELIGIBILITY CRITERIA

Studies comparing diagnostic performances of host biomarkers in patients with bacterial versus non-bacterial infections were included.

PARTICIPANTS

Studies involving human participants and/or human samples were included.

METHODS

We collected information following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A risk of bias assessment was performed, based on a modified QUADAS-2 (Quality Assessment of Diagnostic Accuracy Score 2).

RESULTS

We identified 1107 publications. Following screening, 55 publications were included, with 265 biomarker entries. Entries mostly comprised protein biomarkers (58.9%), followed by haematological, RNA, and metabolite biomarkers (15.5%, 8.7%, 12.5%). Sensitivity/specificity was reported for 45.7% of biomarker entries. We assessed a high overall risk of bias for most entries (75.8%). In studies with low/medium risk of bias, four biomarker entries tested in blood samples had sensitivity/specificity of more than 0.90/0.80. Only 12 additional biomarker entries were identified with sensitivity/specificity of more than 0.65/0.65.

CONCLUSIONS

Most recently assessed biomarkers represent well-known biomarkers, e.g. C-reactive protein and procalcitonin. Some protein biomarkers with the highest reported performances include a combined biomarker signature (CRP, IP-10, and TRAIL) and human neutrophil lipocalin (HNL). Few new biomarkers are in the pipeline; however, some RNA signatures show promise. Further high-quality studies are needed to confirm these findings.

Consensus Document on Community-Acquired Pneumonia in Children. SENP-SEPAR-SEIP

Community-acquired pneumonia (CAP) is a prevalent disease among children and is frequently associated with both diagnostic and therapeutic uncertainties. Consensus has been reached between SEPAR, SENP and SEIP, and their conclusions are as follows.

Potential Trends of Point-of-Care Diagnostics-The Next Generation of the Laboratory Diagnosis

With the current worldwide outbreak of COVID-19, developing rapid, effective, and convenient detection tools has become imperative [...].

Differential Markers of Bacterial and Viral Infections in Children for Point-of-Care Testing

Children suffering from infectious diseases, both bacterial and viral, are often treated with empirical antibiotics. Keeping in mind both the menace of microorganisms and antibiotic toxicity, it is imperative to develop point-of-care testing (POCT) to discriminate bacterial from viral infections, and to define indications for antibiotic treatment. This article reviews potential protein biomarkers and host-derived gene expression signatures for differentiating between bacterial and viral infections in children, and focuses on emerging multiplex POCT devices for the simultaneous detection of sets of protein biomarkers or streamlined gene expression signatures that may provide rapid and cost-effective pathogen-discriminating tools.

Bacteria and viruses activate or inhibit different signaling pathways in the cells they infect, and further give rise to different host transcriptional signatures as well as to unique protein biomarkers.

Many of the newly evaluated protein biomarkers, especially in combination, have better discriminative value for distinguishing between bacterial and viral infections than the biomarkers that are currently used for examining infections in children.

The transcriptomes of children undergo remarkable changes when they are infected by different types of bacteria and viruses. Approaches based on host-derived DNA/RNA signatures can accurately discriminate bacterial from viral infections.

Emerging multiplex POCT techniques allow simultaneous testing of protein- or gene-based biomarkers in an outpatient setting.

CD35 and CD64 of Neutrophils Can Differentiate Between Bacterial and Viral Infections in Children by Simultaneous Quantitative Analysis

BACKGROUND The aim of this study was to determine the relationship between the expression of CD35 and CD64 from white blood cells (neutrophil, monocytes, and lymphocytes) and acute infectious diseases in children. MATERIAL AND METHODS The blood samples were collected from 104 children with infections (42 viral infections and 62 bacterial infections). Blood samples were stained with CD45-PC5, CD35-FITC, and CD64-PE, and the fluorescence intensities were measured by flow cytometer, and then the ratio of CD35 to CD64 was calculated. RESULTS The ratio of CD64/CD35 on neutrophils (NCD35/NCD64) was significantly different between the bacterial group, the virus group, and the healthy control group. According to receiver operating characteristic (ROC) analysis, a cutoff value of 7.256 (sensitivity: 90.0%, specificity: 93.7%) was determined for the NCD35/NCD64 ratio. CONCLUSIONS This study shows that NCD35/NCD64 is helpful in the differential diagnosis of acute viral infection and bacterial infection in children.

Biomarkers of Community-Acquired Pneumonia: A Key to Disease Diagnosis and Management

Community-acquired pneumonia (CAP) is a dangerous disease caused by a spectrum of bacterial and viral pathogens. The choice of specific therapy and the need for hospitalization or transfer to the intensive care unit are determined by the causative agent and disease severity. The microbiological analysis of sputum largely depends on the quality of the material obtained. The prediction of severity and the duration of therapy are determined individually, and existing prognostic scales are used generally. This review examines the possibilities of using specific serological biomarkers to detect the bacterial or viral aetiology of CAP and to assess disease severity. Particular emphasis is placed on the use of biomarker signatures and the discovery of biomarker candidates for a single multiplex analysis.

Utility of leucocyte antigens in distinguishing between bacterial and viral infection in children

Introduction

Accurate diagnosis of bacterial and viral infection is very difficult. Unfortunately, there is still no quick and discriminative diagnostic test that would help clinicians in establishing the diagnosis and taking a decision on treatment. The aim of the study was to compare the expression of antigens on phagocytes, which are involved in the first defence line during bacterial and viral infections in children, as a potential tool to distinguish the etiology of the infection.

Material and methods

The expression of CD35, CD32, CD88, and MHC class I on phagocytes in 49 blood samples from children with high fever and suspected infection as well as 19 healthy children (control group) was assessed by flow cytometry. Thirty-three children were diagnosed with bacterial and 16 with viral infection. Expression of antigens was analysed on a FACSCanto II flow cytometer according to mean fluorescence intensity (MFI) and antibody binding cites (ABC).

Results

Significant differences were observed for the following: CD32, CD35, CD88, and MHCI on granulocytes; CD32, CD35, CD88 on monocytes; and MHC-I ratio between groups were observed. The obtained results did not allow us to establish valuable score points for distinguishing between bacterial and viral infections. Classification and a regression tree using CD88 expression on granulocytes and CRP was developed. It enabled us to differentiate between the origin of infection with sensitivity and specificity of more than 90%.

Conclusions

Utility of use of wide range antigens’ expression on phagocytes for distinguishing between bacterial and viral infection in children has limited value. More adequate seems to be use of CD88 expression on granulocytes linked with CRP value.

Biomarkers in Pediatric Community-Acquired Pneumonia

Community-acquired pneumonia (CAP) is an infectious disease caused by bacteria, viruses, or a combination of these infectious agents. The severity of the clinical manifestations of CAP varies significantly. Consequently, both the differentiation of viral from bacterial CAP cases and the accurate assessment and prediction of disease severity are critical for effectively managing individuals with CAP. To solve questionable cases, several biomarkers indicating the etiology and severity of CAP have been studied. Unfortunately, only a few studies have examined the roles of these biomarkers in pediatric practice. The main aim of this paper is to detail current knowledge regarding the use of biomarkers to diagnose and treat CAP in children, analyzing the most recently published relevant studies. Despite several attempts, the etiologic diagnosis of pediatric CAP and the estimation of the potential outcome remain unsolved problems in most cases. Among traditional biomarkers, procalcitonin (PCT) appears to be the most effective for both selecting bacterial cases and evaluating the severity. However, a precise cut-off separating bacterial from viral and mild from severe cases has not been defined. The three-host protein assay based on C-reactive protein (CRP), tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), plasma interferon-γ protein-10 (IP-10), and micro-array-based whole genome expression arrays might offer more advantages in comparison with former biomarkers. However, further studies are needed before the routine use of those presently in development can be recommended.

Profile of C-reactive protein, white cells and neutrophil populations in febrile children from rural north-eastern Tanzania

Introduction

C-reactive protein (CRP), white blood cell (WBC) and absolute neutrophil counts (ANC) are important inflammatory biomarkers in the early diagnosis of infections. However, little is known on their profile and usefulness in fever case management in children attending outpatient clinic in rural north-eastern Tanzania.

Methods

Patients aged between 2 and 59 months presenting with fever at Korogwe District Hospital were enrolled. Venous blood was collected for evaluation of serum CRP, WBC and ANC. Individual patient diagnosis was based on integrated management of childhood illness (IMCI) guidelines and laboratory investigations (blood and urine cultures).

Results

A total of 867 patients were enrolled, out of which 691 (79.7%) had complete clinical and laboratory data available for analysis. Acute upper respiratory tract infection 284 (41.1%), acute gastroenteritis 127 (18.4%) and pneumonia 100 (14.5%) were the most frequent diagnoses. The geometric mean levels of serum CRP, WBC and ANC were 10.4 (95% CI: 9.2 - 11.8), 11.5 (95% CI: 11.1 - 11.9) and 5.5 (95% CI: 5.2 - 5.8), respectively. CRP≤20, WBC≤15 (10³cells/µL) and ANC≤10 10³cells/µL) were observed in the majority of the patients with upper respiratory tract infection, pneumonia, acute gastroenteritis and non-specific febrile illness. Only serum CRP levels were positively correlated with positive blood cultures at a calculated cut-off value of 37.3 mg/L, giving a specificity of 77.8% and sensitivity of 74.2%.

Conclusion

CRP assessment together with IMCI guidelines may be useful in assisting the diagnosis and management of paediatric febrile infections in Tanzania.