Utility of a Clinical Scoring System for Point of Care Triaging in COVID-19 Pneumonia

  1. Andrew J Gangemi
  2. Rohit Gupta
  3. Gustavo Fernandez-Romero
  4. Huaqing Zhao
  5. Maulin Patel
  6. Junad Chowdhury
  7. Massa Zantah
  8. Matthew Zheng
  9. Osheen Abramian
  10. Stephen Codella
  11. Linda Vien
  12. Eduardo Dominguez-Castillo
  13. Timothy Buckey
  14. Charles Earley
  15. Jourdan Frankovich
  16. Mali Jurkowski
  17. Zachary Jurkowski
  18. Jenny O’Brien
  19. Nanzhou Guo
  20. Paige Stanley
  21. Brenton Halsey
  22. Jasleen Kahlon
  23. Navjot Kaur
  24. Roman Prosniak
  25. Maruti Kumaran
  26. Chandra Dass
  27. David Fleece
  28. Michael R Jacobs
  29. Gerard J. Criner

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Abstract

Background

Surges in COVID-19 disease cases can rapidly overwhelm healthcare resources; triaging to appropriate levels of care can assist in resource planning. At the beginning of the pandemic, we developed a simple triage tool, the Temple COVID-19 Pneumonia Triage Tool (TemCOV) based on a combination of clinical and radiographic features that are readily available on presentation to categorize and predict illness severity.

Methods

We prospectively examined 579 sequential cases admitted to Temple University Hospital who were assigned severity categories on admission. Our primary outcome was to compare the performance of TemCOV in predicting patients who have the highest likely of admission to the ICU at 24 and at 72 hours to other standard triage tools: the National Early Warning System (NEWS), the Modified Early Warning System (MEWS) and the CURB65 score. Additional endpoints included need for invasive mechanical ventilation (IMV) within 72 hours, total hospital admission charges, and mortality.

Results

26% of patients fell within our highest risk Category 4 and were more likely to require ICU admission at 24 hours (OR 11.51) and 72 hours (OR 8.6). Additionally they had the highest likelihood of needing IMV (OR 29.47) and in-hospital mortality (OR 2.37)., TemCOV performed similar to MEWS in predicting ICU admission at 24 hours (receive operator characteristic (ROC) curve area under the curve (AUC) 0.77 vs. 0.74, p=0.21) but better than NEWS2 and CURB65 (ROC AUC 0.77 vs. 0.69 and 0.77 vs. 0.64, respectively, p<0.01). While all severity scores had a weak correlation to hospital charges, the TemCOV performed the best among all severity scores measured (r=0.18); median hospital charges for Category 4 patients was $170,468 ($96,972-$487,556).

Conclusion

TemCOV is a simple triage score that can be used upon hospitalization in patients with COVID-19 that predicts the need for hospital resources such as ICU bed capacity, invasive mechanical ventilation and personnel staffing.

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    SciScore for 10.1101/2021.02.26.21252256: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Waiver of informed consent was granted (Temple University IRB Protocol #27051).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analyses were performed with the use of Stata 14.0 (StataCorp LP, College Station, TX).
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    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:
    Limitations of our study include the validation of scores in a single health care system. We also recognize that our score does not take into account baseline comorbidities which can play a major role in the clinical outcomes and has been advocated by joint task forces.1 Some of our patients on high flow nasal cannula therapy were managed on the general medical floor, which may be atypical for some institutions, but the incidence of this was low overall (6%).

    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.

    About SciScore

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  2. Version published to 10.1101/2021.02.26.21252256v1 on medRxiv