Using a 29-mRNA Host Response Classifier To Detect Bacterial Coinfections and Predict Outcomes in COVID-19 Patients Presenting to the Emergency Department

  1. Nikhil Ram-Mohan
  2. Angela J. Rogers
  3. Catherine A. Blish
  4. Kari C. Nadeau
  5. Elizabeth J. Zudock
  6. David Kim
  7. James V. Quinn
  8. Lixian Sun
  9. Oliver Liesenfeld
  10. The Stanford COVID-19 Biobank Study Group
  11. Samuel Yang
  12. The additional author members of the Stanford COVID-19 Biobank Study Group are as follows:
  13. Marjan M. Hashemi
  14. Kristel C. Tjandra
  15. Jennifer A. Newberry
  16. Andra L. Blomkalns
  17. Ruth O’Hara
  18. Euan Ashley
  19. Rosen Mann
  20. Anita Visweswaran
  21. Thanmayi Ranganath
  22. Jonasel Roque
  23. Monali Manohar
  24. Hena Naz Din
  25. Komal Kumar
  26. Kathryn Jee
  27. Brigit Noon
  28. Jill Anderson
  29. Bethany Fay
  30. Donald Schreiber
  31. Nancy Zhao
  32. Rosemary Vergara
  33. Julia McKechnie
  34. Aaron Wilk
  35. Lauren de la Parte
  36. Kathleen Whittle Dantzler
  37. Maureen Ty
  38. Nimish Kathale
  39. Arjun Rustagi
  40. Giovanny Martinez-Colon
  41. Geoff Ivison
  42. Ruoxi Pi
  43. Maddie Lee
  44. Rachel Brewer
  45. Taylor Hollis
  46. Andrea Baird
  47. Michele Ugur
  48. Drina Bogusch
  49. Georgie Nahass
  50. Kazim Haider
  51. Kim Quyen Thi Tran
  52. Laura Simpson
  53. Michal Tal
  54. Iris Chang
  55. Evan Do
  56. Andrea Fernandes
  57. Allie Lee
  58. Neera Ahuja
  59. Theo Snow
  60. James Krempski

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Abstract

We assay the utility of the single-test IMX-BVN-3/IMX-SEV-3 classifiers that require just 2.5 mL of patient blood in concurrently detecting viral and bacterial infections as well as predicting the severity and 30-day outcome from the infection. A point-of-care device, in development, will circumvent the need for blood culturing and drastically reduce the time needed to detect an infection.

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  1. Version published to 10.1128/spectrum.02305-22
  2. ScreenIT

    SciScore for 10.1101/2022.03.14.22272394: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Other limitations of our study include the fact that this study was conducted at a single center and used biobanked blood samples obtained from a limited cohort of 161 patients. As only PCR confirmed COVID-19 positive patients were enrolled we could not determine the IMX-BVN-3 classifier’s specificity. We were also unable to clinically adjudicate the entire patient cohort for bacterial infections and thus calculated sensitivity for a subset of patients only. Lastly, since bacterial co-or superinfections are defined based on when the patient presents to the ED1,2 and not when in the course of the infection the patient presents, we were unable to determine the timeline of the infection to distinguish between the two. Additionally, the host response-based classifier detects any bacterial infection and, hence, does not allow differentiating between co-or superinfections. In conclusion, once the IMX-BVN-3 and SEV-3 classifiers are introduced as a rapid point of care host RNA detection platform with a turnaround time of less than 30 min (currently in development), results at the point of care could guide decisions about starting or withholding antibiotics allowing escalation of therapy or antimicrobial stewardship but also the initiation of contact precaution measures and/or viral therapy and choosing the appropriate level of care for SARS-CoV-2 positive patients.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  3. Version published to 10.1101/2022.03.14.22272394v1 on medRxiv