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.

A host signature based on TRAIL, IP-10, and CRP for reducing antibiotic overuse in children by differentiating bacterial from viral infections: a prospective, multicentre cohort study

OBJECTIVES

Identifying infection aetiology is essential for appropriate antibiotic use. Previous studies have shown that a host-protein signature consisting of TNF-related apoptosis-induced ligand (TRAIL), interferon-γ-induced protein-10 (IP-10), and C-reactive protein (CRP) can accurately differentiate bacterial from viral infections.

METHODS

This prospective, multicentre cohort study, entitled AutoPilot-Dx, aimed to validate signature performance and to estimate its potential impact on antibiotic use across a broad paediatric population (>90 days to 18 years) with respiratory tract infections, or fever without source, at emergency departments and wards in Italy and Germany. Infection aetiology was adjudicated by experts based on clinical and laboratory investigations, including multiplex PCR and follow-up data.

RESULTS

In total, 1140 patients were recruited (February 2017-December 2018), of which 1008 met the eligibility criteria (mean age 3.5 years, 41.9% female). Viral and bacterial infections were adjudicated for 628 (85.8%) and 104 (14.2%) children, respectively; 276 patients were assigned an indeterminate reference standard outcome. For the 732 children with reference standard aetiology, the signature discriminated bacterial from viral infections with a sensitivity of 93.7% (95%CI 88.7-98.7), a specificity of 94.2% (92.2-96.1), positive predictive value of 73.0% (65.0-81.0), and negative predictive value of 98.9% (98.0-99.8); in 9.8% the test results were equivocal. The signature performed consistently across different patient subgroups and detected bacterial immune responses in viral PCR-positive patients.

CONCLUSIONS

The findings validate the high diagnostic performance of the TRAIL/IP-10/CRP signature in a broad paediatric cohort, and support its potential to reduce antibiotic overuse in children with viral infections.

Expert panel diagnosis demonstrated high reproducibility as reference standard in infectious diseases

OBJECTIVE

If a gold standard is lacking in a diagnostic test accuracy study, expert diagnosis is frequently used as reference standard. However, interobserver and intraobserver agreements are imperfect. The aim of this study was to quantify the reproducibility of a panel diagnosis for pediatric infectious diseases.

STUDY DESIGN AND SETTING

Pediatricians from six countries adjudicated a diagnosis (i.e., bacterial infection, viral infection, or indeterminate) for febrile children. Diagnosis was reached when the majority of panel members came to the same diagnosis, leaving others inconclusive. We evaluated intraobserver and intrapanel agreement with 6 weeks and 3 years' time intervals. We calculated the proportion of inconclusive diagnosis for a three-, five-, and seven-expert panel.

RESULTS

For both time intervals (i.e., 6 weeks and 3 years), intrapanel agreement was higher (kappa 0.88, 95%CI: 0.81-0.94 and 0.80, 95%CI: NA) compared to intraobserver agreement (kappa 0.77, 95%CI: 0.71-0.83 and 0.65, 95%CI: 0.52-0.78). After expanding the three-expert panel to five or seven experts, the proportion of inconclusive diagnoses (11%) remained the same.

CONCLUSION

A panel consisting of three experts provides more reproducible diagnoses than an individual expert in children with lower respiratory tract infection or fever without source. Increasing the size of a panel beyond three experts has no major advantage for diagnosis reproducibility.

1962. TRAIL Level and ImmunoXpert™ Score Complement Molecular Viral Detection in the Classification of Febrile Children: An Interim Analysis From the AutoPilotDx-Study

Background

Differentiating between viral and bacterial etiology is essential in order to enable the adequate use of antibiotics. Previous studies showed that TNF-related apoptosis induced ligand (TRAIL) can serve as a useful biomarker for distinguishing between bacterial and viral infections when combined with IP-10 and CRP (ImmunoXpert™). Here we evaluate the potential of a new proteomic fingerprints in children with suspected viral and bacterial infections that had a confirmed viral detection.

Methods

In the prospective multinational multicenter study “AutoPilot-Dx” (NCT03052088) we aim to validate the diagnostic accuracy of the ImmunoXpert™ test. Infection etiology was assigned by majority adjudication of three experts based on comprehensive clinical and laboratory investigation. Viruses were detected using multiplex-PCR applied to nasopharyngeal swabs (Allplex™, Seegene). We performed an interim analysis of the first 134 febrile children recruited that had both PCR viral detection and etiology determination. TRAIL, IP-10, CRP and ImmunoXpert™ values were measured via a Tecan EVO75 ELISA platform.

Results

Bacterial diagnoses were assigned by the experts to 29%, 29% and 25% of patients with adenovirus (ADV), rhinovirus (RV), and respiratory syncytial virus (RSV) detection, respectively. Children with a viral infection including ADV, RSV, and RV had significantly lower ImmunoXpert™ scores as compared with children with a bacterial infection. Notably, TRAIL levels were markedly increased in viral infections as compared with bacterial infection, irrespective of the detected virus.

Conclusion

Classification of viral infections correlated significantly with elevated TRAIL levels and low ImmunoXpert™ scores. The differential expression of TRAIL in response to viral vs. bacterial infections can complement molecular viral detection, appears useful in the diagnostic workup for febrile children and may reduce antibiotic misuse.

Disclosures

L. Etshtein, MeMed Diagnostics: Employee, Salary. N. Mastboim, MeMed Diagnostics: Employee, Salary. A. Cohen, MeMed Diagnostics: Employee, Salary. E. Simon, MeMed: Employee, Salary. O. Boico, MeMed Diagnostics: Employee, Salary. L. Shani, MeMed Diagnostics: Employee, Salary. T. Gottlieb, MeMed Diagnostics: Employee, Salary. R. Navon, MeMed Diagnostics: Employee, Salary. K. Oved, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary. E. Eden, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary.

873. Using the Host Immune Response to Identify Viral-Bacterial Coinfection in Children With Respiratory Syncytial Virus Infection

Background

A major challenge in the effective management of children with RSV infection is the clinical difficulty of distinguishing a simple viral from viral–bacterial coinfections. As a result, despite the low rates of viral–bacterial coinfection, RSV patients are often prescribed antibiotics with recent reports demonstrating more than 60% antibiotic overuse rates (Van Houten et al. 2018). Here, we examined whether a host-immune signature combining the viral-induced proteins TRAIL and IP-10 with the bacterial-induced protein CRP (ImmunoXpert; Oved et al. 2015) can distinguish simple viral from viral–bacterial coinfection in RSV patients.

Methods

We studied 402 febrile children enrolled as part of “Curiosity,” a prospective study designed to develop and validate the host-immune signature. Infection etiology—viral or viral-bacterial coinfection—was determined by a panel of experts following a review of patients’ clinical, laboratory, radiological, microbiological, and follow-up data. RSV strains were detected using a respiratory multiplex PCR applied to nasal swabs (Seeplex-RV15).

Results

Out of the 402 children with suspected acute infection 29 had a positive RSV detection (Figure 1); of them, 27 had a unanimous expert panel etiology determination: 24 viral and 3 viral–bacterial coinfections. Out of the 24 patients unanimously assigned viral by the expert panel, 13 were given antibiotics, indicating a 54% antibiotic overuse rate. The host-immune signature correctly identified all 3 viral-bacterial coinfection cases, as well as 22 out of the 24 (92%) simple viral patients. This finding supports that the signature has the potential to reduce antibiotic overuse by 6.5-fold (from an overuse of 13/24 = 54% to 2/24 = 8%, P < 0.001).

Conclusion

Our results demonstrate high antibiotic overuse rates for RSV patients, consistent with previous reports. The host-immune signature correctly distinguished simple viral from viral–bacterial coinfection and therefore may have the potential to aid physicians in the correct management of children with RSV infection. Implementation studies are required to evaluate its utility in safely decreasing unnecessary antibiotic use for RSV patients.

Disclosures

N. Mastboim, MeMed Diagnostics: Employee, Salary. K. Oved, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary. T. Gottlieb, MeMed Diagnostics: Employee, Salary. A. Cohen, MeMed Diagnostics: Employee, Salary. R. Navon, MeMed Diagnostics: Employee, Salary. M. Paz, MeMed Diagnostics: Employee, Salary. E. Bamberger, MeMed Diagnostics: Employee, Salary. T. Friedman, MeMed Diagnostics: Employee, Salary. L. Etshtein, MeMed Diagnostics: Employee, Salary. O. Boico, MeMed Diagnostics: Employee, Salary. I. Potasman, MeMed Diagnostics: Holding stock options, Stock options. E. Eden, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary. L. Shani, MeMed Diagnostics: Employee, Salary.

1948. A Host-Response Assay Distinguishes Between Simple Influenza Patients and Influenza Patients With Bacterial Coinfection

Background

Identifying bacterial coinfection in influenza patients can be difficult as the symptoms of simple influenza vs. mixed infections are often similar, leading to antibiotic overuse. A new host-response assay (ImmunoXpert™) that integrates the levels of three proteins (TRAIL, IP-10, and CRP) was shown to exhibit high performance in distinguishing between bacterial and viral disease in two double-blind validation studies. Here we sought to evaluate its ability to differentiate between simple influenza and influenza with bacterial coinfection.

Methods

The study population included 653 febrile pediatric and adult patients prospectively recruited in the “Curiosity” study. Patient etiology (simple viral vs. mixed infection) was determined by unanimous expert adjudication based on comprehensive clinical, laboratory and radiological assessment. Influenza strains (A or B) were detected using multiplex PCR applied to nasal swabs (Seeplex-RV15). We compared the expert panel diagnosis with the assay that gives three possible outcomes: viral, bacterial (including viral with bacterial coinfection) or equivocal. An equivocal outcome does not provide diagnostic information and is observed in ~10% of cases.

Results

Out of 653 patients, 51 had positive influenza detection and unanimous expert diagnosis: 44 simple viral infections and seven influenza with bacterial coinfections (Figure 1). Antibiotics were prescribed to all seven cases of influenza with bacterial coinfection and to 20/44 cases adjudicated as simple viral infections, indicating an overuse rate of 45%. The assay correctly classified 40 of the 44 simple viral cases (out of the remaining four, two were assigned viral with bacterial coinfection, and two received equivocal outcomes) as well as five of the seven viral with bacterial coinfection cases (the remaining two received equivocal outcomes) supporting the assay’s potential to reduce antibiotic overuse 5-fold (from 45% to 4/44 = 9%, P < 0.001).

Conclusion

The host–response assay can differentiate between simple influenza and influenza patients with bacterial coinfection, with potential to reduce antibiotic overuse. Utility studies are warranted to demonstrate that the assay can safely assist physicians in correct management of influenza patients.

Disclosures

M. Paz, MeMed Diagnostics: Employee, Salary. K. Oved, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary. T. Gottlieb, MeMed Diagnostics: Employee, Salary. A. Cohen, MeMed Diagnostics: Employee, Salary. R. Navon, MeMed Diagnostics: Employee, Salary. N. Mastboim, MeMed Diagnostics: Employee, Salary. E. Bamberger, MeMed Diagnostics: Employee, Salary. T. Friedman, MeMed Diagnostics: Employee, Salary. L. Etshtein, MeMed Diagnostics: Employee, Salary. O. Boico, MeMed Diagnostics: Employee, Salary. I. Potasman, MeMed Diagnostics: Holding stock options, Stock options. E. Eden, MeMed Diagnostics: Board Member, Employee and Shareholder, Salary. L. Shani, MeMed Diagnostics: Employee, Salary.