Multisite validation of a host response signature for predicting likelihood of bacterial and viral infections in patients with suspected influenza

M Shojaei, UI Chen, U Midic, S Thair… - European Journal of …, 2023 - Wiley Online Library
M Shojaei, UI Chen, U Midic, S Thair, S Teoh, A McLean, TE Sweeney, M Thompson
European Journal of Clinical Investigation, 2023Wiley Online Library
Background Indiscriminate use of antimicrobials and antimicrobial resistance is a public
health threat. 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 …
Background
Indiscriminate use of antimicrobials and antimicrobial resistance is a public health threat. 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.
Results
Amongst 602 adult patients (74.9% ED, 16.9% ICU, 8.1% outpatients), 7.6% showed in‐hospital mortality and 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 nonbacterial illness was 0.81 and 0.87 when distinguishing viral from nonviral 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 noninfectious illness in patients with suspected influenza. Clinical utility of IMX‐BVN will be validated following integration into a point of care system.
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