Diagnostic System for Monitoring Patients on Ventilators for Secondary Infection

Abstract

Intubated patients are at high risk of developing secondary infections, which increases their risk of a poor outcome. Especially in COVID patients, clinicians need to closely monitor the presence of pathogenic agents responsible for these infections. The current standard of care involves culture-based detection methods, which may take days and may miss diagnoses due to their limited identification capabilities. As such, clinicians will often start suspected patients on a dose of broad-spectrum antibiotics, which are ineffective against viruses and fungi and promotes antibiotic resistance. A novel diagnostic technology is metagenomic, next-generation sequencing (mNGS) where it can identify a wide variety of organisms responsible for the secondary infections from the extratracheal exudate. We designed a web interface using R Shiny to successfully filter, label, and display the large amount of information outputted by mNGS. With clinician feedback from surveys, the website was made to mimic existing culture reports to facilitate clinician adoption and ensure ease of use. A secondary website was also created to context and information about the web application and to allow app users to provide feedback in the future. Our overall goal is that our system will serve as a proof-of-concept that mNGS may be one day popularized for secondary infection diagnostics.