Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test.

BackgroundAcute febrile illness is a frequent cause of hospitalization in the tropics and often presents with respiratory symptoms, even when caused by nonrespiratory pathogens. Previously, host-based gene expression signatures accurately identified acute respiratory infections as being bacterial or viral in a U.S. cohort. We determined signature performance in a Sri Lankan cohort with acute febrile respiratory illness (AFRI).MethodsWe enrolled patients with AFRI in Sri Lanka from July 2012 to May 2013 and collected nasopharygeal swabs, acute/ convalescent sera, and blood in PAXgene RNA tubes. Bacterial (Orientia tsutsugamushi, Leptospira spp.) and viral (influenza A/B, dengue) infections were confirmed using polymerase chain reaction, virus isolation, enzyme immunoassay, and/or microscopic agglutination testing. We extracted total RNA and performed host RNA sequencing (Illumina). We aligned reads to hg38 reference genome using Bowtie2, quantified at isoform level using Express version 1.5.1, and normalized using trimmed-mean normalization. The original model estimated three classes and separate signatures predicted bacterial infections, viral infections, and non-infectious illnesses. Regularized regression was used to predict bacterial and viral infections based on prior signatures. Accuracy was estimated using leave-one-out cross-validation.ResultsAmong 43 patients with viral infections (14 dengue, 29 influenza) and 16 patients with bacterial infections (six Leptospira spp., 10 O. tsutsumagushi), median age was 37 years (IQR 23–51) and 49% were male. Of five respiratory symptoms (cough, sore throat, rhinitis/ congestion, shortness of breath, and pain with breathing), median (IQR) number of symptoms was 2 (1–2) for influenza, 2 (1–2) for dengue, 2 (2–3) for Leptospira spp., and 1.5 (1–2) for O. tsutsumagushi. We observed high predictive accuracy in discriminating bacterial and viral infections: AUROC 0.91 for the bacterial and AUROC 0.81 for the viral model. At enrollment, 65% of viral and 50% of bacterial AFRI patients received antibiotics.ConclusionHost gene expression classifiers performed well in a Sri Lankan population with AFRI, even with nonrespiratory pathogens that may not be readily identified. Host-based diagnostics may play a critical role in improving diagnostic ability and antibiotic use globally.Disclosures E. L. Tsalik, Host Response, Inc.: Founder, Equity. G. S. Ginsburg, Host Response Inc.: Board Member, Founder, Scientific Advisor and Shareholder, Stock (currently worth <$100). C. W. Woods, Host Response, Inc.: Founder, Equity.

BackgroundDifficulty distinguishing bacterial and viral infections contributes to excess antibiotic use. A host response strategy overcomes many limitations of pathogen-based tests, but depends on a functional immune system. This approach may therefore be limited in immunocompromised (IC) hosts. Here, we evaluated a host response test in IC subjects, which has not been extensively studied in this manner.MethodsAn 81-gene signature was measured using qRT-PCR in previously enrolled IC subjects (chemotherapy, solid organ transplant, immunomodulatory agents, AIDS) with confirmed bacterial infection, viral infection, or non-infectious illness (NI). A regularized logistic regression model estimated the likelihood of bacterial, viral, and noninfectious classes. Clinical adjudication was the reference standard.ResultsA host gene expression model trained in a cohort of 136 immunocompetent subjects (43 bacterial, 41 viral, and 52 NI) had an overall accuracy of 84.6% for the diagnosis of bacterial vs. non-bacterial infection and 80.8% for viral vs. non-viral infection. The model was validated in an independent cohort of 134 IC subjects (64 bacterial, 28 viral, 42 NI). The overall accuracy was 73.9% for bacterial infection (p=0.03 vs. training cohort) and 75.4% for viral infection (p=0.27). Test utility could be improved by reporting probability ranges. For example, results divided into probability quartiles would allow the highest quartile to be used to rule in infection and the lowest to rule out infection. For IC subjects in the lowest quartile, the test had 90.1% and 96.4% sensitivity for bacterial and viral infection, respectively. For the highest quartile, the test had 91.4% and 84.0% specificity for bacterial and viral infection, respectively. The type or number of immunocompromising conditions did not impact performance.Illness Etiology ProbabilitiesConclusionA host gene expression test discriminated bacterial, viral, and non-infectious etiologies at a lower overall accuracy in IC patients compared to immunocompetent patients, though this difference was only significant for bacterial vs non-bacterial disease. With modified interpretive criteria, a host response strategy may offer clinically useful and complementary diagnostic information for IC patients.DisclosuresThomas W. Burke, PhD, Predigen, Inc (Consultant) Geoffrey S. Ginsburg, MD PhD, Predigen, Inc (Shareholder, Other Financial or Material Support) Christopher W. Woods, MD, MPH, FIDSA, Predigen, Inc (Shareholder, Other Financial or Material Support) Ephraim L. Tsalik, MD, MHS, PhD, FIDSA, Predigen, Inc (Scientific Research Study Investigator, Shareholder, Other Financial or Material Support)

A two-transcript biomarker of host classifier genes for discrimination of bacterial from viral infection in acute febrile illness: a multicentre discovery and validation study

Fewer early bacterial and viral infections following non-myeloablative vs. myeloablative conditioning for allotransplantation

BackgroundMeasuring host gene expression is a promising diagnostic strategy to discriminate bacterial and viral infections. Multiple signatures of varying size, complexity, and target populations have been described. However, there is little information to indicate how the performance of various published signatures compare to one another.MethodsThis systematic comparison of host gene expression signatures evaluated the performance of 28 signatures, validating them in 4589 subjects from 51 publicly available datasets. Thirteen COVID-specific datasets with 1416 subjects were included in a separate analysis. Individual signature performance was evaluated using the area under the receiving operating characteristic curve (AUC) value. Overall signature performance was evaluated using median AUCs and accuracies.ResultsSignature performance varied widely, with median AUCs ranging from 0.55 to 0.96 for bacterial classification and 0.69–0.97 for viral classification. Signature size varied (1–398 genes), with smaller signatures generally performing more poorly (P < 0.04). Viral infection was easier to diagnose than bacterial infection (84% vs. 79% overall accuracy, respectively; P < .001). Host gene expression classifiers performed more poorly in some pediatric populations (3 months–1 year and 2–11 years) compared to the adult population for both bacterial infection (73% and 70% vs. 82%, respectively; P < .001) and viral infection (80% and 79% vs. 88%, respectively; P < .001). We did not observe classification differences based on illness severity as defined by ICU admission for bacterial or viral infections. The median AUC across all signatures for COVID-19 classification was 0.80 compared to 0.83 for viral classification in the same datasets.ConclusionsIn this systematic comparison of 28 host gene expression signatures, we observed differences based on a signature’s size and characteristics of the validation population, including age and infection type. However, populations used for signature discovery did not impact performance, underscoring the redundancy among many of these signatures. Furthermore, differential performance in specific populations may only be observable through this type of large-scale validation.

Respiratory tract infections require early diagnosis and adequate treatment. With the antibiotic overuse and increment in antibiotic resistance there is an increased need to accurately distinguish between bacterial and viral infections. We investigated the diagnostic performance of calprotectin in respiratory tract infections and compared it with the performance of heparin binding protein (HBP) and procalcitonin (PCT). Biomarkers were analyzed in patients with viral respiratory infections and patients with bacterial pneumonia, mycoplasma pneumonia and streptococcal tonsillitis (n = 135). Results were compared with values obtained from 144 healthy controls. All biomarkers were elevated in bacterial and viral infections compared to healthy controls. Calprotectin was significantly increased in patients with bacterial infections; bacterial pneumonia, mycoplasma pneumonia and streptococcal tonsillitis compared with viral infections. PCT was significantly elevated in patients with bacterial pneumonia compared to viral infections but not in streptococcal tonsillitis or mycoplasma caused infections. HBP was not able to distinguish between bacterial and viral causes of infections. The overall clinical performance of calprotectin in the distinction between bacterial and viral respiratory infections, including mycoplasma was greater than performance of PCT and HBP. Rapid determination of calprotectin may improve the management of respiratory tract infections and allow more precise diagnosis and selective use of antibiotics.

Background:Infections are a typical complication of chronic lymphocytic leukemia (CLL). Guidelines for prevention of infections in patients with CLL receiving ibrutinib is lacking, possibly due to a paucity of data in the literature.Aims:To analyze factors associated with severe bacterial, viral and fungal infections in CLL patients receiving ibrutinib.Methods:Data on bacterial, viral and fungal infections in CLL patients, who received ibrutinib during 3,6‐year period from May 2015 to December 2018 in a single centre are presented. Infections were graded according to CTCAE criteria, version IV. Cumulative incidences of infections were estimated according to Kaplan‐Meier and comparison between groups was performed using Hazard Ratios and CIs obtained from Cox regression models.Results:The study included 240 CLL patients. The median age was 65 years (range 32–91 years), 154 (64%) were male, 117 (48%) had stage C, 65 (27%) had ECOG status ≥ 2. Two hundred four patients (85%) received ibrutinib as monotherapy, 36 (15%) along with monoclonal antibodies to CD20. The median follow‐up was 14.8 months (range 1 ‐ 44 months). Most patients (224, 93%) received ibrutinib for relapse with a median number of previous treatment lines of 3 (range 1–12). Neutropenia (defined as &lt;1000 cells/mkl) prior to ibrutinib was found in 20 patients (8%). Steroid hormones were given to 20 patients. A total of 525 infectious episodes were recorded in 183 patients. Of these, 381 (72.5%) episodes were bacterial/mixed infections, 115 (22%) viral and 29 (5.5%) fungal infections. Among bacterial infections 121 (32%) were scored as grade III, 43 (11%) as grade IV and 7 (1,8%) infections were fatal. The overall cumulative incidence of grade III‐V bacterial infections during 12 months was 37% (95% CI 31–43%), viral infections ‐ 28% (95% CI 22–34), and fungal infections 8% (95% CI 4–12). There was a significantly (p &lt; .05) higher cumulative incidence of grade III‐V bacterial infections in patients with ≥3 lines of prior therapy (HR: 2.0; 95% CI 1.36–2.97), Binet stage C (HR: 1.4; 95% CI 0.95–2.08), ECOG ≥ 2 (HR: 2.4; 95% CI 1.6–3.6), baseline neutropenia (HR: 1.25; 95% CI 0.73–2.13), as well as in males (HR: 1.8; 95% CI 1.16–2.8, p = 0.004). In a multivariate analysis male gender (RR 1.89, 95% CI 0.5–3, p = 0.006), ECOG ≥ 2 (RR = 1.97, 95% CI 0.5–3) and initial neutropenia (RR = 1.76, 95% CI 0.99–3.1) were significant and independent risk factors. Cumulative incidence of any fungal infections was associated with simultaneous use of corticosteroids (HR: 6; 95% CI 5.85–14,7) and baseline neutropenia (HR: 2.36; 95% CI 0.95–5.85). The only parameter significantly associated with viral infections was ≥3 lines of prior therapy (HR: 1.74; 95% CI 1.06–2.86). As 160 (87%) patients experienced &gt;1 episode of infections, we compared rates of infections expressed as number per 100 patient‐months. Grade III‐V bacterial infections were significantly associated with ≥3 lines of previous therapy (3,6 vs 2,3), ECOG ≥ 2 (5,72 vs 2,27), male gender (3,2 vs 2,03) and stage C (3,8 vs 2,24). Fungal infections were more frequently observed in patients with a history of &gt;3 lines of treatment (0,87 vs 0,31), initial neutropenia (1,75 vs 0,47), simultaneous use of steroids (1,96 vs 0,39).Summary/Conclusion:Patients with ECOG status &gt;2 and initial neutropenia are at highest risk of severe bacterial infections and may benefit from antibacterial prophylaxis. Antifungal prophylaxis can be considered in patients who receive corticosteroid hormones simultaneously with ibrutinib

BackgroundAcute respiratory infections (ARI) are the commonest reason for antibiotic use, but much of this is unnecessary as a high proportion is caused by viruses. Distinguishing bacterial from viral ARIs is challenging, and detecting viral pathogens does not rule out concurrent bacterial infection, leading to inappropriate antibiotic use and driving antimicrobial resistance. Novel tests assessing the host immune response have the potential to differentiate bacterial and viral ARIs and direct antibiotic use. In this study, we evaluated the accuracy of the TriVerity Acute Infection and Sepsis Test (Inflammatix, Sunnyvale, CA, US), a transcriptomic-based host response point-of-care test which measures 29 mRNAs to determine the likelihood of bacterial and viral infection, in adults with acute respiratory illness.MethodsAdults hospitalised with ARI were enrolled as part of the FluPOC study. The aetiology for each patient (bacterial and viral), was clinically adjudicated by 3 clinicians independently using a pre-specified guidance document. RNA paxgene blood samples were tested using the TriVerity test on the Myrna platform (Inflammatix, Sunnyvale CA, US). The test assigns one of five probability bands (very low, low, moderate, high, very high) for both bacterial and viral infection. Measures of diagnostic accuracy were calculated between the TriVerity results and adjudicated infection status.Results169 patients were tested, and TriVerity testing gave an initial valid result in 168 (99%). The median (IQR) time to result was 32.49 (32.41, 32.53) minutes. Median age was 60 (45, 74) years and baseline characteristics are shown in table 1. 61 (36%) were adjudicated as bacterial, 54 (32%) as viral, 26 (15%) as viral/bacterial co-infection and 29 (17%) as non-infected. Measures of diagnostic accuracy for bacterial and viral infection compared to adjudication are shown in table 2 and 3 respectively.ConclusionThe TriVerity test demonstrated good levels of accuracy in distinguishing bacterial from viral ARIs compared with clinical adjudication and was reliable with a short turnaround time. TriVerity could support early informed antibiotic decisions and reduce unnecessary antibiotics use. Prospective impact trials with clinical outcome measures are needed.DisclosuresTristan William Clark, BM MRCP DTM&H MD, Biomerieux/Biofire diagnositcs: Advisor/Consultant|Biomerieux/Biofire diagnositcs: Grant/Research Support|Biomerieux/Biofire diagnositcs: Honoraria|Cepheid: Advisor/Consultant|GSK: Advisor/Consultant|Inflammatix: Grant/Research Support|Roche: Advisor/Consultant|Sanofi: Advisor/Consultant|Sanofi: Grant/Research Support|Sequirus: Advisor/Consultant|Sherlock Biosciences: Grant/Research Support|Shionogi: Advisor/Consultant|Synairgen: Advisor/Consultant|Synairgen: Grant/Research Support|Synairgen: Honoraria|Synairgen: Stocks/Bonds (Public Company)

The aim was to assess the performance of a blood assay combining measurements of MxA (myxovirus resistance protein A) and CRP (C-reactive protein) to differentiate viral from bacterial respiratory infections. In a prospective study, MxA and CRP were measured in the blood by the AFIAS panel in adults admitted with respiratory infection. Patients were split into discovery and validation cohorts. Final diagnosis was adjudicated by a panel of experts. Microbiology-confirmed cases comprised the discovery cohort, and infections adjudicated as highly probable viral or bacterial comprised the validation cohort. A total of 537 patients were analyzed: 136 patients were adjudicated with definitive viral infections and 131 patients with definitive bacterial infections. Using logistic regression analysis, an equation was developed to calculate the probability for bacterial infection using the absolute value of MxA and CRP. Calculated probability≥0.5 and/or MxA to CRP ratio less than 2 applied as the diagnostic rule for bacterial infections. This rule provided 91.6% sensitivity and 90.4% negative predictive value for the diagnosis of bacterial infections. This diagnostic sensitivity was confirmed in the validation cohort. A MxA/CRP ratio less than 0.15 was associated with unfavorable outcome. The calculation of the probability for bacterial infection using MxA and CRP may efficiently discriminate between viral and bacterial respiratory infections.

Objective To compare and analyze serum levels of procalcitonin (PCT) of children with viral and bacterial infection and probe into the importance of determining the level of serum PCT in the diagnosis of bacterial infection in order to provide evidences of the clinical use of antibiotics. Methods A total of 85 cases of children with an average age of 8.9 years (10 months -12 years) were enrolled in this study, 53 cases were with viral infection and 32 cases with bacterial infection. We determined serum levels of PCT by semi-quantitative solid phase immunoassay, and the serum levels of PCT were divided into four grades as &lt;0.5 μg / L, ≥ 0.5μg / L, ≥ 2.0μg / L and ≥ 10μg / L for x2 test and Ridit analysis. Results The serum level of PCT of the group with bacterial infection were significantly higher than that of the group with viral infection (P &lt; 0.001). The sensitivity of diagnosis of bacterial infection in children with determination of serum levels of PCT was 87.50% while the specificity was 92.13%, and positive predictive value was 73.68% while negative predictive value was 91.49%, and positive likelihood ratio was 4.65 while negative likelihood ratio was 0.15, and the diagnostic accuracy was 83.53%. Conclusions Serum PCT is a bacterial sensitive marker of bacterial infection in children, and the determination of the level of serum PCT is helpful for the diagnosis of bacterial infection, which can also be a basis for the use of antibiotics.

Viral and bacterial antigen and antibody assays were prospectively applied to study the microbial actiology of community-acquired pneumonia in 195 hospitalised children during a surveillance period of 12 months. A viral infection alone was indicated in 37 (19%), a bacterial infection alone in 30 (15%) and a mixed viral-bacterial infection in 32 (16%) patients. Thus, 46% of the 69 patients with viral infection and 52% of the 62 patients with bacterial infection had a mixed viral and bacterial aetiology. Respiratory syncytial virus (RSV) was identified in 52 patients andStreptococcus pneumoniae in 41 patients. The next common agents in order were non-classifiedHaemophilus influenzae (17 cases), adenoviruses (10 cases) andChlamydia species (8 cases). The diagnosis of an RSV infection was based on detecting viral antigen in nasopharyngeal secretions in 79% of the cases. Pneumococcal infections were in most cases identified by antibody assays; in 39% they were indicated by demonstrating pneumococcal antigen in acute phase serum. An alveolar infiltrate was present in 53 (27%) and an interstitial infiltrate in 108 (55%) of the 195 patients. The remaining 34 patients had probable pneumonia. C-reactive protein (CRP), erythrocyte sedimentation rate and total white blood cell count were elevated in 25%, 40% and 36% of the patients, respectively, CRP was more often elevated in patients with bacterial infection alone than in those with viral or mixed viral-bacterial infections. No other correlation was seen between the radiological or laboratory findings and serologically identified viral, bacterial or mixed viralbacterial infections. By using a comprehensive serological panel, the causative agent could be found in over 50% of patients with pneumonia. We conclude that RSV and pneumococcus are the two most common organisms causing pneumonia in children. Our results suggest that mixed viral-bacterial aetiology is common in lower respiratory tract infections affecting children.

Differentiating infectious from non-infectious respiratory syndromes is critical in emergency settings. This study aimed to assess whether nCD64 and mCD169 exhibit specific distributions in patients with respiratory infections (viral, bacterial, or co-infections) and to evaluate their diagnostic accuracy compared to non-infectious conditions. A prospective cohort study enrolled 443 consecutive emergency department patients with respiratory syndromes, categorized into four groups: no infection group (NOIG), bacterial infection group (BIG), viral infection group (VIG), and co-infection group (COING). Multinomial logistic regression was used to evaluate nCD64 and mCD169's association with diagnostic groups and estimate their predictive accuracy. 290 patients were included in VIG, 53 in BIG, 46 in COING, and 54 in NOIG. nCD64 was associated with bacterial infections and co-infections (p = 2.73 × 10- 16 and p = 8.83 × 10- 11, respectively), but not viral infections. mCD169 was associated with viral infections and co-infections (p = < 2 × 10- 16 and p = 2.45 × 10- 13, respectively), but not bacterial infections. The sensitivity and specificity of nCD64 for detecting bacterial infections were 0.75 and 0.84 (AUC = 0.83), respectively, while for mCD169 they were 0.87 and 0.91 (AUC = 0.92), respectively, for diagnosing viral infections. A diagnostic algorithm incorporating fever, nasopharyngeal swabs for the main respiratory virus, C-reactive protein, procalcitonin, and mCD169 reached an accuracy of 0.79 (95% CI 0.72-0.85) in distinguishing among the different groups. nCD64 and MCD169 seem valuable for distinguishing between bacterial and viral respiratory infections. Integrating these biomarkers into diagnostic algorithms could enhance diagnostic accuracy aiding patient management in emergency settings.

SARS-CoV-2 antibody assays are used for epidemiological studies and for the assessment of vaccine responses in highly vulnerable patients. So far, data on cross-reactivity of SARS-CoV-2 antibody assays is limited. Here, we compared four enzyme-linked immunosorbent assays (ELISAs; Vircell SARS-CoV-2 IgM/IgA and IgG, Euroimmun SARS-CoV-2 IgA and IgG) for detection of anti-SARS-CoV-2 antibodies in 207 patients with COVID-19, 178 patients with serological evidence of different bacterial infections, 107 patients with confirmed viral respiratory disease, and 80 controls from the pre-COVID-19 era. In COVID-19 patients, the assays showed highest sensitivity in week 3 (Vircell-IgM/A and Euroimmun-IgA: 78.9% each) and after week 7 (Vircell-IgG: 97.9%; Euroimmun-IgG: 92.1%). The antibody indices were higher in patients with fatal disease. In general, IgM/IgA assays had only limited or no benefit over IgG assays. In patients with non-SARS-CoV-2 respiratory infections, IgG assays were more specific than IgM/IgA assays, and bacterial infections were associated with more false-positive results than viral infections. The specificities in bacterial and viral infections were 68.0 and 81.3% (Vircell-IgM/IgA), 84.8 and 96.3% (Euroimmun-IgA), 97.8 and 86.0% (Vircell-IgG), and 97.8 and 99.1% (Euroimmun-IgG), respectively. Sera from patients positive for antibodies against Mycoplasma pneumoniae, Chlamydia psittaci, and Legionella pneumophila yielded particularly high rates of unspecific false-positive results in the IgM/IgA assays, which was revealed by applying a highly specific flow-cytometric assay using HEK 293 T cells expressing the SARS-CoV-2 spike protein. Positive results obtained with anti-SARS-CoV-2 IgM/IgA ELISAs require careful interpretation, especially if there is evidence for prior bacterial respiratory infections.

Empirical antibiotic use is prescribed in managing children with pneumonia worldwide. We assessed the usefulness of procalcitonin (PCT) and interferon-alpha (IFN-alpha) in differentiating viral from bacterial pneumonia. Among 159 hospitalized children, pneumonia was diagnosed based on clinical complaints plus pulmonary infiltrate. Aetiology was investigated for 9 viruses and 4 atypical and 3 typical bacteria. PCT and IFN-alpha were measured in the serum sample collected on admission. Eight patients had bacteraemic infections, 38 had non-bacteraemic typical infections, and 19 patients had atypical bacterial infections. Viral and unknown aetiology was established in 57 (36%) and 34 (21%) cases, respectively. Three patients with bacterial infection without collected blood culture were excluded. IFN-alpha (IU/ml) was detectable in 20 (13%) cases. The difference among median PCT values of the bacteraemic (4.22; 1.56-7.56), non-bacteraemic typical bacterial (1.47; 0.24-4.07), atypical bacterial (0.18; 0.06-1.03) and only viral (0.65; 0.11-2.22) subgroups was significant (p = 0.02). PCT was > or =2 ng/ml in 52 (33%) cases. The presence of IFN-alpha was associated with PCT <2 ng/ml (90% vs. 64%, p = 0.02). The negative predictive value (95% confidence interval) of PCT > or =2 ng/ml was 95% (89-100%), 89% (78-100%), 93% (85-100%) for differentiation of bacteraemic from viral, atypical bacterial and non-bacteraemic typical bacterial infection, respectively, and 58% (49-68%) for differentiation between bacterial and viral infection. PCT may be useful in identifying bacteraemia among children hospitalized with community-acquired pneumonia. IFN-alpha was uncommonly detected.

Differentiation Bacterial from Viral Infection-Advantage of Procalcitonin