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. 2024 Jan;13(1):105-119.
doi: 10.1007/s40121-023-00901-2. Epub 2023 Dec 19.

Developing a Tool for Differentiation Between Bacterial and Viral Respiratory Infections Using Myxovirus Resistance Protein A and C-Reactive Protein

Affiliations

Developing a Tool for Differentiation Between Bacterial and Viral Respiratory Infections Using Myxovirus Resistance Protein A and C-Reactive Protein

Konstantina Iliopoulou et al. Infect Dis Ther. 2024 Jan.

Abstract

Introduction: 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.

Methods: 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.

Results: 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.

Conclusion: The calculation of the probability for bacterial infection using MxA and CRP may efficiently discriminate between viral and bacterial respiratory infections.

Keywords: Bacterial infection; CRP; Diagnosis; MxA; Viral infection.

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Conflict of interest statement

Garyphalia. Poulakou has received honoraria and/or consulting fees by Astra-Zeneca, Gilead, GSK, Menarini, MSD, Norma, Pfizer and SOBI and research grants by the University of Minnesota/University College London, the Hellenic Institute for the Study of Sepsis, Bausch, Roche, Xenothera, FabNTech and Pfizer. Ilias C. Papanikolaou has received honoraria or served as PI for studies from Boehringer-Ingelheim, GlaxoSmithKline and AstraZeneca. Haralampos. Milionis reports receiving honoraria, consulting fees and non-financial support from healthcare companies, including Amgen, Angelini, Bayer, Mylan, MSD, Pfizer, and Servier. George N Dalekos is an advisor or lecturer for Pfizer, Roche, Sanofi and Sobi, and received research grants from Gilead and has served as PI in studies for Gilead, Novo Nordisk, Genkyotex, Regulus Therapeutics Inc, Tiziana Life Sciences, Bayer, Astellas, Pfizer, Amyndas Pharmaceuticals, CymaBay Therapeutics Inc., Sobi and Intercept Pharmaceuticals. Evangelos. J. Giamarellos-Bourboulis has received honoraria from Abbott Products Operations, bioMérieux, Brahms GmbH, GSK, InflaRx GmbH, Sobi and Xbiotech Inc; independent educational grants from Abbott Products Operations, bioMérieux Inc, InflaRx GmbH, Johnson & Johnson, MSD, Sobi and Xbiotech Inc.; and funding from the Horizon2020 Marie Skłodowska-Curie International Training Network “the European Sepsis Academy” (granted to the National and Kapodistrian University of Athens), the Horizon 2020 European Grants ImmunoSep and RISCinCOVID and the Horizon Health grant EPIC-CROWN-2 (granted to the Hellenic Institute for the Study of Sepsis). Konstantina Iliopoulou, Panagiotis Koufargyris, Sarantia Doulou, Elisavet Tasouli, Sokratis Katopodis, Stavroula-Porphyria Chachali, Georgios Schinas, Charalambos Karachalios, Myrto Astriti, Parakevi Katsaounou, George Chrysos, Theodors Seferlis, Effrosyni Dimopoulou, Myrto Kollia, Styliani Gerakari, Vasiliki Tzavara, and Theano Kontopoulou have no competing interests.

Figures

Fig. 1
Fig. 1
Study design and flow chart; n number of patients
Fig. 2
Fig. 2
Diagnostic performance of MxA and CRP based on pre-defined cut-offs for bacterial and viral infections. A Diagnostic performance of the MxA in definitive viral infection group; definitive viral infection (n = 136), definitive viral/bacterial co-infection (n = 20), definitive viral/high probability bacterial co-infection (n = 71). B Diagnostic performance of the CRP in definitive bacterial infection group; definitive bacterial infection (n = 131), definitive viral/bacterial co-infection (n = 20). The confidence intervals (95% CIs) of each percentage are provided in parentheses. CRP C-reactive protein, MxA myxovirus resistance protein A, n number of patients, NPV negative predictive value, PPV positive predictive value
Fig. 3
Fig. 3
MxA, CRP, and MxA/CRP ratio for the differential diagnosis between definitive bacterial and viral infection at the discovery cohort. A Blood concentrations of MxA and CRP of comparators without infection (n = 40), of patients with definitive viral infection (n = 136), and of patients with definitive bacterial infection (n = 131). Circles denote extreme values and asterisks denote outliers #p < 0.001 versus no infection; ##p < 0.0001 versus definitive viral infection. B Diagnostic performance of the combination of MxA and of CRP using the rule which combines the probability for bacterial infection (P) and the MxA/CRP ratio. Analysis involved the total of 267 patients with either definitive viral infection or definitive bacterial infection. The confidence intervals of each percentage are provided in parentheses. CRP C-reactive protein, n number of patients, MxA myxovirus resistance protein A, NPV negative predictive value, PPV positive predictive value, Se sensitivity, Sp specificity
Fig. 4
Fig. 4
MxA and CRP for the differential diagnosis between high probability bacterial infection and high probability viral infection in the validation cohort. Blood concentrations of MxA and CRP of patients with high probability for viral infection (n = 11) and of patients with high probability for bacterial infection (n = 128) are provided. Circles denote extreme values and asterisks denote outliers #p < 0.05 versus high probability for bacterial infection; ##p < 0.0001 versus high probability for viral infection. CRP C-reactive protein, n number of patients, MxA myxovirus resistance protein A
Fig. 5
Fig. 5
MxA and CRP for the diagnosis of viral/bacterial co-infection. Blood concentrations of MxA and CRP of patients with definitive viral infection and high-probability for bacterial infection (n = 71) and of patients with definitive viral/bacterial co-infection (n = 20). #p: 0.351 versus high probability for bacterial infection; ##p: 0.413 versus high probability for viral infection. CRP C-reactive protein, n number of patients, MxA myxovirus resistance protein A
Fig. 6
Fig. 6
MxA/CRP ratio for the prognosis of unfavorable outcome. A Comparison of MxA between 28-day survivors and 28-day non-survivors; the p value of comparison is provided. B Comparison of CRP between 28-day survivors and 28-day non-survivors; the p value of comparison is provided. C ROC curves of MxA and MxA/CRP ratio for the prognosis of unfavorable outcome. D Prognostic performance of the MxA/CRP ratio less than 0.15 for death after 28 days; the OR and 95% confidence intervals for death with MxA/CRP less than 0.15 are provided. Analysis involves the total of 537 studied patients. AUC area under the curve, CI confidence interval, CRP C-reactive protein, MxA myxovirus resistance protein A, n number of patients, NPV negative predictive value, OR odds ratio, PPV positive predictive value, ROC receiver operating characteristics

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