The diagnostic value of nasal microbiota and clinical parameters in a multi-parametric prediction model to differentiate bacterial versus viral infections in lower respiratory tract infections.

BACKGROUND: The ability to accurately distinguish bacterial from viral infection would help clinicians better target antimicrobial therapy during suspected lower respiratory tract infections (LRTI). Although technological developments make it feasible to rapidly generate patient-specific microbiota profiles, evidence is required to show the clinical value of using microbiota data for infection diagnosis. In this study, we investigated whether adding nasal cavity microbiota profiles to readily available clinical information could improve machine learning classifiers to distinguish bacterial from viral infection in patients with LRTI. RESULTS: Various multi-parametric Random Forests classifiers were evaluated on the clinical and microbiota data of 293 LRTI patients for their prediction accuracies to differentiate bacterial from viral infection. The most predictive variable was C-reactive protein (CRP). We observed a marginal prediction improvement when 7 most prevalent nasal microbiota genera were added to the CRP model. In contrast, adding three clinical variables, absolute neutrophil count, consolidation on X-ray, and age group to the CRP model significantly improved the prediction. The best model correctly predicted 85% of the 'bacterial' patients and 82% of the 'viral' patients using 13 clinical and 3 nasal cavity microbiota genera (Staphylococcus, Moraxella, and Streptococcus). CONCLUSIONS: We developed high-accuracy multi-parametric machine learning classifiers to differentiate bacterial from viral infections in LRTI patients of various ages. We demonstrated the predictive value of four easy-to-collect clinical variables which facilitate personalized and accurate clinical decision-making. We observed that nasal cavity microbiota correlate with the clinical variables and thus may not add significant value to diagnostic algorithms that aim to differentiate bacterial from viral infections.

Differential Serum and Urine CRP, IP-10, and TRAIL Levels in Pediatric Urinary Tract Infection.

Background: It is estimated that clinical evaluation and urinalysis are unable to diagnose >10% of urinary tract infections (UTI) in young children. TNF-related apoptosis induced ligand (TRAIL), interferon gamma induced protein-10 (IP-10), and C-reactive protein (CRP) exhibit differential expression in the blood in response to bacterial vs. viral infection. We assessed if the urinary and serum levels of these host biomarkers discriminate UTI, nephronia, and response to antibiotic treatment. Methods: Hospitalized febrile children aged <18 years with suspected UTI based on abnormal urinalysis were recruited prospectively between 2016 and 2018; also, non-febrile controls were recruited. Following urine culture results and hospitalization course, participants were divided into three groups based on AAP criteria and expert adjudication: UTI, viral infection, and indeterminate. Results: Seventy-three children were enrolled, 61 with suspected UTI and 12 non-febrile controls. Of the 61 with suspected UTI, 40 were adjudicated as UTI, 10 viral infection, and 11 as indeterminate. Urinary CRP and IP-10 levels were significantly higher in the UTI group (p ≤ 0.05). Urinary CRP differentiated UTI from non-bacterial etiology in children under and over 3 months of age, with AUCs 0.98 (95% CI: 0.93-1.00) and 0.82 (0.68-0.95), respectively. Similarly, urinary IP-10 discriminated with AUCs of 0.80 (0.59-1.00) and 0.90 (0.80-1.00), respectively. Serum CRP and IP-10 levels were significantly higher in UTI cases with nephronia (p ≤ 0.03). UTI-induced changes in the levels of urinary and serum biomarkers resolved during recovery. Conclusions: CRP, IP-10, and TRAIL represent biomarkers with potential to aid the clinician in diagnosis and management of UTI.

Antibiotic misuse in respiratory tract infections in children and adults-a prospective, multicentre study (TAILORED Treatment).

Respiratory tract infections (RTI) are more commonly caused by viral pathogens in children than in adults. Surprisingly, little is known about antibiotic use in children as compared to adults with RTI. This prospective study aimed to determine antibiotic misuse in children and adults with RTI, using an expert panel reference standard, in order to prioritise the target age population for antibiotic stewardship interventions. We recruited children and adults who presented at the emergency department or were hospitalised with clinical presentation of RTI in The Netherlands and Israel. A panel of three experienced physicians adjudicated a reference standard diagnosis (i.e. bacterial or viral infection) for all the patients using all available clinical and laboratory information, including a 28-day follow-up assessment. The cohort included 284 children and 232 adults with RTI (median age, 1.3 years and 64.5 years, respectively). The proportion of viral infections was larger in children than in adults (209(74%) versus 89(38%), p < 0.001). In case of viral RTI, antibiotics were prescribed (i.e. overuse) less frequently in children than in adults (77/209 (37%) versus 74/89 (83%), p < 0.001). One (1%) child and three (2%) adults with bacterial infection were not treated with antibiotics (i.e. underuse); all were mild cases. This international, prospective study confirms major antibiotic overuse in patients with RTI. Viral infection is more common in children, but antibiotic overuse is more frequent in adults with viral RTI. Together, these findings support the need for effective interventions to decrease antibiotic overuse in RTI patients of all ages.

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.

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.

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.

Thioredoxin-mimetic peptides as catalysts of S-denitrosylation and anti-nitrosative stress agents.

S-nitrosylation, the coupling of a nitric oxide moiety to a reactive cysteine residue to form an S-nitrosothiol (SNO), is an important posttranslational mechanism for regulating protein activity. Growing evidence indicates that hyper-S-nitrosylation may contribute to cellular dysfunction associated with various human diseases. It is also increasingly appreciated that thioredoxin and thioredoxin reductase play significant roles in the cellular catabolism of SNO and protection from nitrosative stress. Here, we investigated the SNO reductase activity and protective effects of thioredoxin-mimetic peptides (TXMs), Ac-Cys-Pro-Cys-amide (CB3) and Ac-Cys-Gly-Pro-Cys-amide (CB4), both under cell-free conditions and in nitrosatively stressed cultured cells. In vitro biochemical analyses revealed that the TXM peptides reduced small-molecule SNO compounds, such as S-nitrosoglutathione (GSNO), and acted as general and efficient protein-denitrosylating agents. In particular, CB3 was found to be a highly potent SNO-metabolizing agent. Notably, CB3 mimicked the activity of thioredoxin by coupling with thioredoxin reductase to enhance GSNO reduction. Moreover, in a cell-free lysate system, both CB3 and CB4 synergized with an NADPH-dependent activity to denitrosylate proteins. Further investigation revealed that the TXM peptides protect the peroxiredoxin-thioredoxin system from SNO-dependent inhibition. Indeed, SNO-inhibited Prx1 was efficiently denitrosylated and reactivated by CB3 or CB4. In addition, CB3 protected thioredoxin reductase from SNO-mediated inactivation both in vitro and in intact cells. Finally, CB3 and CB4 partially rescued human neuroblastoma SH-SY5Y cells and rat insulinoma INS-1 832/13 cells from GSNO-induced growth inhibition. Collectively, the present findings indicate the efficient denitrosylation activity and protective effects of TXM peptides and suggest their potential therapeutic value in treating pathological conditions related to nitrosative stress.