Diagnostic accuracy of a TRAIL, IP-10 and CRP combination for discriminating bacterial and viral etiologies at the Emergency Department

Differentiating viral and bacterial infections: A machine learning model based on routine blood test values

The growing threat of antibiotic resistance necessitates accurate differentiation between bacterial and viral infections for proper antibiotic administration. In this study, a Virus vs. Bacteria machine learning model was developed to distinguish between these infection types using 16 routine blood test results, C-reactive protein concentration (CRP), biological sex, and age. With a dataset of 44,120 cases from a single medical center, the model achieved an accuracy of 82.2 %, a sensitivity of 79.7 %, a specificity of 84.5 %, a Brier score of 0.129, and an area under the ROC curve (AUC) of 0.905, outperforming a CRP-based decision rule. Notably, the machine learning model enhanced accuracy within the CRP range of 10-40 mg/L, a range where CRP alone is less informative. These results highlight the advantage of integrating multiple blood parameters in diagnostics. The "Virus vs. Bacteria" model paves the way for advanced diagnostic tools, leveraging machine learning to optimize infection management.

Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance

Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.

Diagnostic Accuracy of a Real-Time Host-Protein Test for Infection

OBJECTIVE

Determining infection etiology can be difficult because viral and bacterial diseases often manifest similarly. A host protein test that computationally integrates the circulating levels of TNF-related apoptosis-induced ligand, interferon γ-induced protein-10, and C-reactive protein to differentiate between bacterial and viral infection (called MMBV) demonstrated high performance in multiple prospective clinical validation studies. Here, MMBV's diagnostic accuracy is evaluated in febrile children for whom physicians were uncertain about etiology when applied at the physician's discretion.

METHODS

Patients aged 3 months to 18 years were retrospectively recruited (NCT03075111; SPIRIT study; 2014-2017). Emergency department physician's etiological suspicion and certainty level were recorded in a questionnaire at blood-draw. MMBV results are based on predefined score thresholds: viral/non-bacterial etiology (0 ≤ score <35), equivocal (35 ≤ score ≤65), and bacterial or coinfection (65 < score ≤100). Reference standard etiology (bacterial/viral/indeterminate) was adjudicated by 3 independent experts based on all available patient data. Experts were blinded to MMBV. MMBV and physician's etiological suspicion were assessed against the reference standard.

RESULTS

Of 3003 potentially eligible patients, the physicians were uncertain about infection etiology for 736 of the cases assigned a reference standard (128 bacterial, 608 viral). MMBV performed with sensitivity 89.7% (96/107; 95% confidence interval 82.4-94.3) and specificity 92.6% (498/538; 95% confidence interval 90.0-94.5), significantly outperforming physician's etiological suspicion (sensitivity 49/74 = 66.2%, specificity 265/368 = 72.0%; P < .0001). MMBV equivocal rate was 12.4% (91/736).

CONCLUSIONS

MMBV was more accurate in determining etiology compared with physician's suspicion and had high sensitivity and specificity according to the reference standard.

Host biomarkers and combinatorial scores for the detection of serious and invasive bacterial infection in pediatric patients with fever without source

BACKGROUND

Improved tools are required to detect bacterial infection in children with fever without source (FWS), especially when younger than 3 years old. The aim of the present study was to investigate the diagnostic accuracy of a host signature combining for the first time two viral-induced biomarkers, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and interferon γ-induced protein-10 (IP-10), with a bacterial-induced one, C-reactive protein (CRP), to reliably predict bacterial infection in children with fever without source (FWS) and to compare its performance to routine individual biomarkers (CRP, procalcitonin (PCT), white blood cell and absolute neutrophil counts, TRAIL, and IP-10) and to the Labscore.

METHODS

This was a prospective diagnostic accuracy study conducted in a single tertiary center in children aged less than 3 years old presenting with FWS. Reference standard etiology (bacterial or viral) was assigned by a panel of three independent experts. Diagnostic accuracy (AUC, sensitivity, specificity) of host individual biomarkers and combinatorial scores was evaluated in comparison to reference standard outcomes (expert panel adjudication and microbiological diagnosis).

RESULTS

241 patients were included. 68 of them (28%) were diagnosed with a bacterial infection and 5 (2%) with invasive bacterial infection (IBI). Labscore, ImmunoXpert, and CRP attained the highest AUC values for the detection of bacterial infection, respectively 0.854 (0.804-0.905), 0.827 (0.764-0.890), and 0.807 (0.744-0.869). Labscore and ImmunoXpert outperformed the other single biomarkers with higher sensitivity and/or specificity and showed comparable performance to one another although slightly reduced sensitivity in children < 90 days of age.

CONCLUSION

Labscore and ImmunoXpert demonstrate high diagnostic accuracy for safely discriminating bacterial infection in children with FWS aged under and over 90 days, supporting their adoption in the assessment of febrile patients.

Rapid identification of sepsis in the emergency department

Objectives

Recent research has helped define the complex pathways in sepsis, affording new opportunities for advancing diagnostics tests. Given significant advances in the field, a group of academic investigators from emergency medicine, intensive care, pathology, and pharmacology assembled to develop consensus around key gaps and potential future use for emerging rapid host response diagnostics assays in the emergency department (ED) setting.

Methods

A modified Delphi study was conducted that included 26 panelists (expert consensus panel) from multiple specialties. A smaller steering committee first defined a list of Delphi statements related to the need for and future potential use of a hypothetical sepsis diagnostic test in the ED. Likert scoring was used to assess panelists agreement or disagreement with statements. Two successive rounds of surveys were conducted and consensus for statements was operationally defined as achieving agreement or disagreement of 75% or greater.

Results

Significant gaps were identified related to current tools for assessing risk of sepsis in the ED. Strong consensus indicated the need for a test providing an indication of the severity of dysregulated host immune response, which would be helpful even if it did not identify the specific pathogen. Although there was a relatively high degree of uncertainty regarding which patients would most benefit from the test, the panel agreed that an ideal host response sepsis test should aim to be integrated into ED triage and thus should produce results in less than 30 minutes. The panel also agreed that such a test would be most valuable for improving sepsis outcomes and reducing rates of unnecessary antibiotic use.

Conclusion

The expert consensus panel expressed strong consensus regarding gaps in sepsis diagnostics in the ED and the potential for new rapid host response tests to help fill these gaps. These finding provide a baseline framework for assessing key attributes of evolving host response diagnostic tests for sepsis in the ED.

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.

A point-of-need platform for rapid measurement of a host-protein score that differentiates bacterial from viral infection: analytical evaluation

The objective was to evaluate the analytical performance of a new point-of-need platform for rapid and accurate measurement of a host-protein score that differentiates between bacterial and viral infection. The system comprises a dedicated test cartridge (MeMed BV®) and an analyzer (MeMed Key®). In each run, three host proteins (TRAIL, IP-10 and CRP) are measured quantitatively and a combinational score (0-100) computed that indicates the likelihood of Bacterial versus Viral infection (BV score). Serum samples collected from patients with acute infection representing viral (0 ≤ score < 35), equivocal (35 ≤ score ≤ 65), or bacterial (65 < score ≤ 100) scores based on pre-defined score cutoffs were employed for the analytical evaluation studies as well as samples from healthy individuals. To assess reproducibility, triplicate runs were conducted at 3 different sites, on 2 analyzers per site over 5 non-consecutive days. Lower limit of quantitation (LLoQ) and analytical measurement range were established utilizing recombinant proteins. Sample stability was evaluated using patient samples representative of BV score range (0-100). MeMed Key® and MeMed BV® passed the acceptance criteria for each study. In the reproducibility study, TRAIL, IP-10 and CRP measurements ranged with coefficient of variation from 9.7 to 12.7%, 4.6 to 6.2% and 5.0 to 11.6%, respectively. LLoQ concentrations were established as 15 pg/mL, 100 pg/mL and 1 mg/L for TRAIL, IP-10 and CRP, respectively. To date, sample stability when frozen is 14 months. In summary, the analytical performance reported here, along with diagnostic accuracy established in the Apollo clinical validation study (NCT04690569), supports that MeMed BV® run on MeMed Key® can serve as a tool to assist clinicians in differentiating between bacterial and viral infection.

BV score differentiates viral from bacterial-viral co-infection in adenovirus PCR positive children

BACKGROUND AND OBJECTIVES

Adenovirus causes acute respiratory illness that can mimic bacterial infection, making it challenging to differentiate adenoviral infection from adenoviral-bacterial co-infection. A host-protein score (BV score) for differentiating bacterial from viral infection that combines the expression levels of TNF-related apoptosis-induced ligand, interferon gamma-induced protein-10, and C-reactive protein exhibited a negative predictive value (NPV) of 98% in prior studies. Here we evaluate BV score's diagnostic accuracy in pediatrics with adenovirus PCR detection.

METHODS

This is a sub-analysis of children aged 3 months to 20 years with adenovirus PCR-positive infection recruited prospectively in two previous cohort studies. Reference standard diagnosis (bacterial, viral or indeterminate) was based on expert adjudication. BV score ranges from 0 to 100 and provides three results based on predefined cutoffs: viral or other non-bacterial etiology (0 ≤ score < 35), equivocal (35 ≤ score ≤ 65), and bacterial or co-infection (65 < score ≤ 100). Experts were blinded to BV results.

RESULTS

Out of 1,779 children, 142 had an adenovirus PCR-positive nasopharyngeal swab. Median age was 1.2 years (interquartile range 0.6-1.8), 50.7% were male and 52.8% were hospitalized. 12 cases were reference standard bacterial, 115 reference standard viral and 15 were indeterminate. BV score attained sensitivity of 100.0% (no false negatives), specificity of 89.5% (95% confidence interval: 83.2-95.8), and NPV of 100.0% (92.6-100.0). Equivocal rate was 19.7%.

CONCLUSIONS

BV score accurately differentiated between adenoviral and bacterial-adenoviral co-infection in this cohort of children with PCR-positive adenovirus detection. This performance supports a potential to improve appropriate antibiotic use.

Cost impact analysis of novel host-response diagnostic for patients with community-acquired pneumonia in the emergency department

BACKGROUND

There is significant over-prescription of antibiotics for suspected community-acquired pneumonia (CAP) patients as bacterial and viral pathogens are difficult to differentiate. To address this issue, a host response diagnostic called MeMed BV (MMBV) was developed that accurately differentiates bacterial from viral infection at the point of need by integrating measurements of multiple biomarkers. A literature-based cost-impact model was developed that compared the cost impact and clinical benefits between using the standard of care diagnostics combined with MMBV relative to standard of care diagnostics alone.

METHODS

The patient population was stratified according to the pneumonia severity index, and cost savings were considered from payer and provider perspectives. Four scenarios were considered. The main analysis considers the cost impact of differences in antibiotic stewardship and resulting adverse events. The first, second, and third scenarios combine the impacts on antibiotic stewardship with changes in hospital admission probability, length of hospital stay and diagnosis related group (DRG) reallocation, and hospital admission probability, length of stay, and DRG reallocation in combination, respectively.

RESULTS

The main analysis results show overall per-patient savings of $37 for payers and $223 for providers. Scenarios 1, 2, and 3 produced savings of $137, $189, and $293 for payers, and $339, $713, and $809 for providers, respectively.

LIMITATIONS

Models are simulations of real-world clinical processes, and are not sensitive to variations in clinical practice driven by differences in physician practice styles, differences in facility-level practice patterns, and patient comorbidities expected to exacerbate the clinical impact of CAP. Hospital models are limited to costs and do not consider differences in revenue associated with each approach.

CONCLUSIONS

Introducing MMBV to the current SOC diagnostic process is likely to be cost-saving to both hospitals and payers when considering impacts on antibiotic distribution, hospital admission rate, hospital LOS, and DRG reallocation.

A comparison of host response strategies to distinguish bacterial and viral infection

OBJECTIVES

Compare three host response strategies to distinguish bacterial and viral etiologies of acute respiratory illness (ARI).

METHODS

In this observational cohort study, procalcitonin, a 3-protein panel (CRP, IP-10, TRAIL), and a host gene expression mRNA panel were measured in 286 subjects with ARI from four emergency departments. Multinomial logistic regression and leave-one-out cross validation were used to evaluate the protein and mRNA tests.

RESULTS

The mRNA panel performed better than alternative strategies to identify bacterial infection: AUC 0.93 vs. 0.83 for the protein panel and 0.84 for procalcitonin (P<0.02 for each comparison). This corresponded to a sensitivity and specificity of 92% and 83% for the mRNA panel, 81% and 73% for the protein panel, and 68% and 87% for procalcitonin, respectively. A model utilizing all three strategies was the same as mRNA alone. For the diagnosis of viral infection, the AUC was 0.93 for mRNA and 0.84 for the protein panel (p<0.05). This corresponded to a sensitivity and specificity of 89% and 82% for the mRNA panel, and 85% and 62% for the protein panel, respectively.

CONCLUSIONS

A gene expression signature was the most accurate host response strategy for classifying subjects with bacterial, viral, or non-infectious ARI.

Comparing the Diagnostic Accuracy of Clinician Judgment to a Novel Host Response Diagnostic for Acute Respiratory Illness

Background

Difficulty discriminating bacterial from viral infections drives antibacterial misuse. Host gene expression tests discriminate bacterial and viral etiologies, but their clinical utility has not been evaluated.

Methods

Host gene expression and procalcitonin levels were measured in 582 emergency department participants with suspected infection. We also recorded clinician diagnosis and clinician-recommended treatment. These 4 diagnostic strategies were compared with clinical adjudication as the reference. To estimate the clinical impact of host gene expression, we calculated the change in overall Net Benefit (∆NB; the difference in Net Benefit comparing 1 diagnostic strategy with a reference) across a range of prevalence estimates while factoring in the clinical significance of false-positive and -negative errors.

Results

Gene expression correctly classified bacterial, viral, or noninfectious illness in 74.1% of subjects, similar to the other strategies. Clinical diagnosis and clinician-recommended treatment revealed a bias toward overdiagnosis of bacterial infection resulting in high sensitivity (92.6% and 94.5%, respectively) but poor specificity (67.2% and 58.8%, respectively), resulting in a 33.3% rate of inappropriate antibacterial use. Gene expression offered a more balanced sensitivity (79.0%) and specificity (80.7%), which corresponded to a statistically significant improvement in average weighted accuracy (79.9% vs 71.5% for procalcitonin and 76.3% for clinician-recommended treatment; P<.0001 for both). Consequently, host gene expression had greater Net Benefit in diagnosing bacterial infection than clinician-recommended treatment (∆NB=6.4%) and procalcitonin (∆NB=17.4%).

Conclusions

Host gene expression-based tests to distinguish bacterial and viral infection can facilitate appropriate treatment, improving patient outcomes and mitigating the antibacterial resistance crisis.

Seeking diagnostic and prognostic biomarkers for childhood bacterial pneumonia in sub-Saharan Africa: study protocol for an observational study

INTRODUCTION

Clinically diagnosed pneumonia in children is a leading cause of paediatric hospitalisation and mortality. The aetiology is usually bacterial or viral, but malaria can cause a syndrome indistinguishable from clinical pneumonia. There is no method with high sensitivity to detect a bacterial infection in these patients and, as result, antibiotics are frequently overprescribed. Conversely, unrecognised concomitant bacterial infection in patients with malarial infections occur with omission of antibiotic therapy from patients with bacterial infections. Previously, we identified two combinations of blood proteins with 96% sensitivity and 86% specificity for detecting bacterial disease. The current project aimed to validate and improve these combinations by evaluating additional biomarkers in paediatric patients with clinical pneumonia. Our goal was to describe combinations of a limited number of proteins with high sensitivity and specificity for bacterial infection to be incorporated in future point-of-care tests. Furthermore, we seek to explore signatures to prognosticate clinical pneumonia.

METHODS AND ANALYSIS

Patients (n=900) aged 2-59 months presenting with clinical pneumonia at two Gambian hospitals will be enrolled and classified according to criteria for definitive bacterial aetiology (based on microbiological tests and chest radiographs). We will measure proteins at admission using Luminex-based immunoassays in 90 children with definitive and 160 with probable bacterial aetiology, and 160 children classified according to the prognosis of their disease. Previously identified diagnostic signatures will be assessed through accuracy measures. Moreover, we will seek new diagnostic and prognostic signatures through machine learning methods, including support vector machine, penalised regression and classification trees.

ETHICS AND DISSEMINATION

Ethics approval has been obtained from the Gambia Government/Medical Research Council Unit The Gambia Joint Ethics Committee (protocol 1616) and the institutional review board of Boston University Medical Centre (STUDY00000958). Study results will be disseminated to the staff of the study hospitals, in scientific seminars and meetings, and in publications.

TRIAL REGISTRATION NUMBER

H-38462.

Challenge of diagnosing acute infections in poor resource settings in Africa

Frequent disease outbreaks and acute infections occur in rural and low-income urban areas of Africa, with many health systems unprepared to diagnose and control diseases that are recurrent, endemic or have extended their geographic zone. In this review, we focus on acute infections that can be characterized by sudden onset, rapid progression, severe symptoms and poor prognosis. Consequently, these infections require early diagnosis and intervention. While effective vaccines have been developed against some of these diseases, lack of compliance and accessibility, and the need for repeated or multiple vaccinations mean large populations can remain vulnerable to infection. It follows that there is a need for enhancement of national surveillance and diagnostic capacity to avert morbidity and mortality from acute infections. We discuss the limitations of traditional diagnostic methods and explore the relative merits and applicability of protein-, carbohydrate- and nucleic acid-based rapid diagnostic tests that have been trialled for some infectious diseases. We also discuss the utility and limitations of antibody-based serological diagnostics and explore how systems biology approaches can better inform diagnosis. Lastly, given the complexity and high cost associated with after-service support of emerging technologies, we propose that, for resource-limited settings in Africa, multiplex point-of-care diagnostic tools be tailor-made to detect both recurrent acute infections and endemic infections.

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.

Biosensors for detecting viral and bacterial infections using host biomarkers: a review

A schematic diagram showing multiple modes of biosensing platforms for the diagnosis of bacterial or viral infections.

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection are often non-specific, and there is no definitive test for the accurate diagnosis of infection. The 'omics' approaches to identifying biomarkers from the host-response to bacterial infection are promising. In this study, lipidomic analysis was carried out with plasma samples obtained from febrile children with confirmed bacterial infection (n = 20) and confirmed viral infection (n = 20). We show for the first time that bacterial and viral infection produces distinct profile in the host lipidome. Some species of glycerophosphoinositol, sphingomyelin, lysophosphatidylcholine and cholesterol sulfate were higher in the confirmed virus infected group, while some species of fatty acids, glycerophosphocholine, glycerophosphoserine, lactosylceramide and bilirubin were lower in the confirmed virus infected group when compared with confirmed bacterial infected group. A combination of three lipids achieved an area under the receiver operating characteristic (ROC) curve of 0.911 (95% CI 0.81 to 0.98). This pilot study demonstrates the potential of metabolic biomarkers to assist clinicians in distinguishing bacterial from viral infection in febrile children, to facilitate effective clinical management and to the limit inappropriate use of antibiotics.

Automating a new host-protein assay for differentiating bacterial from viral infection to reduce operator hands-on time

Distinguishing bacterial from viral infections is often challenging, leading to antibiotic misuse, and detrimental ramifications for the patient, the healthcare system and society. A novel ELISA-based assay that integrates the circulating levels of three host-response proteins (TRAIL, IP-10 and CRP) was developed to assist in differentiation between bacterial and viral etiologies. We developed a new protocol for measuring the host-based assay biomarkers using an automated ELISA workstation. The automated protocol was validated and was able to reduce technician hands-on time by 76%, while maintaining high analytical performance. Following automation, the assay has been incorporated into the routine workflow at a pediatric department, and is performed daily on admitted and emergency department patients. The automation protocol reduces the overall burden on the hospital laboratory performing the assay. This benefit has potential to promote adoption of the host-based assay, facilitating timely triage of febrile patients and prudent use of antibiotics.

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.

The host response as a tool for infectious disease diagnosis and management

INTRODUCTION

A century of advances in infectious disease diagnosis and treatment changed the face of medicine. However, challenges continue to develop including multi-drug resistance, globalization that increases pandemic risks, and high mortality from severe infections. These challenges can be mitigated through improved diagnostics, and over the past decade, there has been a particular focus on the host response. Since this article was originally published in 2015, there have been significant developments in the field of host response diagnostics, warranting this updated review. Areas Covered: This review begins by discussing developments in single biomarkers and pauci-analyte biomarker panels. It then delves into 'omics, an area where there has been truly exciting progress. Specifically, progress has been made in sepsis diagnosis and prognosis; differentiating viral, bacterial, and fungal pathogen classes; pre-symptomatic diagnosis; and understanding disease-specific diagnostic challenges in tuberculosis, Lyme disease, and Ebola. Expert Commentary: As 'omics have become faster, more precise, and less expensive, the door has been opened for academic, industry, and government efforts to develop host-based infectious disease classifiers. While there are still obstacles to overcome, the chasm separating these scientific advances from the patient's bedside is shrinking.

Differential Diagnosis of the Etiologies of Bacterial and Viral Infections Using Infrared Microscopy of Peripheral Human Blood Samples and Multivariate Analysis

Human viral and bacterial infections are responsible for a variety of diseases that are still the main causes of death and economic burden for society across the globe. Despite the different responses of the immune system to these infections, some of them have similar symptoms, such as fever, sneezing, inflammation, vomiting, diarrhea, and fatigue. Thus, physicians usually encounter difficulties in distinguishing between viral and bacterial infections on the basis of these symptoms. Rapid identification of the etiology of infection is highly important for effective treatment and can save lives in some cases. The current methods used for the identification of the nature of the infection are mainly based on growing the infective agent in culture, which is a time-consuming (over 24 h) and usually expensive process. The main objective of this study was to evaluate the potential of the mid-infrared spectroscopic method for rapid and reliable identification of bacterial and viral infections based on simple peripheral blood samples. For this purpose, white blood cells (WBCs) and plasma were isolated from the peripheral blood samples of patients with confirmed viral or bacterial infections. The obtained spectra were analyzed by multivariate analysis: principle component analysis (PCA) followed by linear discriminant analysis (LDA), to identify the infectious agent type as bacterial or viral in a time span of about 1 h after the collection of the blood sample. Our preliminary results showed that it is possible to determine the infectious agent with high success rates of 82% for sensitivity and 80% for specificity, based on the WBC data.

A host-protein signature is superior to other biomarkers for differentiating between bacterial and viral disease in patients with respiratory infection and fever without source: a prospective observational study

Bacterial and viral infections often present with similar symptoms. Etiologic misdiagnosis can alter the trajectory of patient care, including antibiotic overuse. A host-protein signature comprising tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), interferon gamma-induced protein-10 (IP-10), and C-reactive protein (CRP) was validated recently for differentiating bacterial from viral disease. However, a focused head-to-head comparison of its diagnostic performance against other biomarker candidates for this indication was lacking in patients with respiratory infection and fever without source. We compared the signature to other biomarkers and prediction rules using specimens collected prospectively at two secondary medical centers from children and adults. Inclusion criteria included fever > 37.5 °C, symptom duration ≤ 12 days, and presentation with respiratory infection or fever without source. Comparator method was based on expert panel adjudication. Signature and biomarker cutoffs and prediction rules were predefined. Of 493 potentially eligible patients, 314 were assigned unanimous expert panel diagnosis and also had sufficient specimen volume. The resulting cohort comprised 175 (56%) viral and 139 (44%) bacterial infections. Signature sensitivity 93.5% (95% CI 89.1–97.9%), specificity 94.3% (95% CI 90.7–98.0%), or both were significantly higher (all p values < 0.01) than for CRP, procalcitonin, interleukin-6, human neutrophil lipocalin, white blood cell count, absolute neutrophil count, and prediction rules. Signature identified as viral 50/57 viral patients prescribed antibiotics, suggesting potential to reduce antibiotic overuse by 88%. The host-protein signature demonstrated superior diagnostic performance in differentiating viral from bacterial respiratory infections and fever without source. Future utility studies are warranted to validate potential to reduce antibiotic overuse.

A novel host-protein assay outperforms routine parameters for distinguishing between bacterial and viral lower respiratory tract infections

Bacterial and viral lower respiratory tract infections (LRTIs) are often clinically indistinguishable, leading to antibiotic overuse. We compared the diagnostic accuracy of a new assay that combines 3 host-biomarkers (TRAIL, IP-10, CRP) with parameters in routine use to distinguish bacterial from viral LRTIs. Study cohort included 184 potentially eligible pediatric and adult patients. Reference standard diagnosis was based on adjudication by an expert panel following comprehensive clinical and laboratory investigation (including respiratory PCRs). Experts were blinded to assay results and assay performers were blinded to reference standard outcomes. Evaluated cohort included 88 bacterial and 36 viral patients (23 did not fulfill inclusion criteria; 37 had indeterminate reference standard outcome). Assay distinguished bacterial from viral LRTI patients with sensitivity of 0.93±0.06 and specificity of 0.91±0.09, outperforming routine parameters, including WBC, CRP and chest x-ray signs. These findings support the assay's potential to help clinicians avoid missing bacterial LRTIs or overusing antibiotics.

Validation of a Novel Assay to Distinguish Bacterial and Viral Infections

BACKGROUND

Reliably distinguishing bacterial from viral infections is often challenging, leading to antibiotic misuse. A novel assay that integrates measurements of blood-borne host-proteins (tumor necrosis factor-related apoptosis-inducing ligand, interferon γ-induced protein-10, and C-reactive protein [CRP]) was developed to assist in differentiation between bacterial and viral disease.

METHODS

We performed double-blind, multicenter assay evaluation using serum remnants collected at 5 pediatric emergency departments and 2 wards from children ≥3 months to ≤18 years without (n = 68) and with (n = 529) suspicion of acute infection. Infectious cohort inclusion criteria were fever ≥38°C and symptom duration ≤7 days. The reference standard diagnosis was based on predetermined criteria plus adjudication by experts blinded to assay results. Assay performers were blinded to the reference standard. Assay cutoffs were predefined.

RESULTS

Of 529 potentially eligible patients with suspected acute infection, 100 did not fulfill infectious inclusion criteria and 68 had insufficient serum. The resulting cohort included 361 patients, with 239 viral, 68 bacterial, and 54 indeterminate reference standard diagnoses. The assay distinguished between bacterial and viral patients with 93.8% sensitivity (95% confidence interval: 87.8%-99.8%) and 89.8% specificity (85.6%-94.0%); 11.7% had an equivocal assay outcome. The assay outperformed CRP (cutoff 40 mg/L; sensitivity 88.2% [80.4%-96.1%], specificity 73.2% [67.6%-78.9%]) and procalcitonin testing (cutoff 0.5 ng/mL; sensitivity 63.1% [51.0%-75.1%], specificity 82.3% [77.1%-87.5%]).

CONCLUSIONS

Double-blinded evaluation confirmed high assay performance in febrile children. Assay was significantly more accurate than CRP, procalcitonin, and routine laboratory parameters. Additional studies are warranted to support its potential to improve antimicrobial treatment decisions.

New Biomarkers and Diagnostic Tools for the Management of Fever in Low- and Middle-Income Countries: An Overview of the Challenges

A lack of simple, inexpensive, and rapid diagnostic tests for febrile illnesses other than malaria leads to overtreatment with antibiotics for those who test negative for malaria, and contributes to the global rise in antimicrobial resistance. New tests for the detection of host biomarkers provide promising tools to differentiate bacterial from non-bacterial infections in febrile patients. However, most available biomarker tests are not currently used in resource-limited settings, and very few evaluations have been performed in low- and middle-income country populations with non-severe febrile illness. As a result, our knowledge of the performance of these tests in settings with high prevalence of infectious and poverty-related diseases such as malaria, HIV, malnutrition and intestinal parasites is poor. This paper describes challenges faced during the process of getting to an approved test, including difficulties in selecting the most appropriate fever biomarkers; suitable study designs and sites for test evaluations; lack of available reference tests to evaluate the performance of new tests; and lack of clear regulatory pathways to introduce such tests. As many new biomarker assays are in development, understanding these challenges will better enable those working in this area to address them during product development.