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Eur J Clin Invest . Multi-site validation of a host response signature for predicting likelihood of bacterial and viral infections in patients with suspected influenza

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  • Eur J Clin Invest . Multi-site validation of a host response signature for predicting likelihood of bacterial and viral infections in patients with suspected influenza


    Eur J Clin Invest


    . 2023 Jan 24;e13957.
    doi: 10.1111/eci.13957. Online ahead of print.
    Multi-site validation of a host response signature for predicting likelihood of bacterial and viral infections in patients with suspected influenza


    Maryam Shojaei 1 2 3 , Uan-I Chen 4 , Uros Midic 4 , Simone Thair 4 , Sally Teoh 2 , Anthony McLean 2 , Timothy E Sweeney 4 , Matthew Thompson 4 , Oliver Liesenfeld 4 , Purvesh Khatri # 4 , Benjamin Tang # 2 3



    Affiliations

    Abstract

    Background: Indiscriminate use of antimicrobials and antimicrobial resistance are public health threats. IMX-BVN-1, a 29-host mRNA classifier provides two separate scores that predict likelihoods of bacterial and viral infections in patients with suspected acute infections. We validated the performance of IMX-BVN-1 in adults attending acute health care settings with suspected influenza.
    Method: We amplified 29 host response genes in RNA extracted from blood by NanoString nCounter. IMX-BVN-1 calculated two scores to predict probabilities of bacterial and viral infections. Results were compared against the infection status (no infection; highly probable/possible infection; confirmed infection) determined by clinical adjudication.
    Result: Among 602 adult patients (74.9% ED, 16.9% ICU, 8.1% outpatients) 7.6% showed in-hospital mortality, 15.5% immunosuppression. Median IMX-BVN-1 bacterial and viral scores were higher in patients with confirmed bacterial (0.27) and viral (0.62) infections than in those without bacterial (0.08) or viral (0.21) infection, respectively. The AUROC distinguishing bacterial from non-bacterial illness was 0.81 and 0.87 when distinguishing viral from non-viral illness. The bacterial top quartile's positive likelihood ratio (LR) was 4.38 with a rule-in specificity of 88%; the bacterial bottom quartile's negative LR was 0.13 with a rule-out sensitivity of 96%. Similarly, the viral top quartile showed an infinite LR with rule-in specificity of 100%; the viral bottom quartile had a LR of 0.22 and a rule-out sensitivity of 85%.
    Conclusion: IMX-BVN-1 showed high accuracy for differentiating bacterial and viral infections from non-infectious illness in patients with suspected influenza. Clinical utility of IMX-BVN will be validated following integration into a point of care system.

    Keywords: Host response; bacterial; classifier; gene expression signatures; influenza; point of care; predict; viral.

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