Clinical features, diagnostics, and outcomes of patients presenting with acute respiratory illness: A retrospective cohort study of patients with and without COVID-19

  1. Sachin J. Shah
  2. Peter N. Barish
  3. Priya A. Prasad
  4. Amy Kistler
  5. Norma Neff
  6. Jack Kamm
  7. Lucy M. Li
  8. Charles Y. Chiu
  9. Jennifer M. Babik
  10. Margaret C. Fang
  11. Yumiko Abe-Jones
  12. Narges Alipanah
  13. Francisco N. Alvarez
  14. Olga Borisovna Botvinnik
  15. Gloria Castaneda
  16. Rand M. Dadasovich
  17. Jennifer Davis
  18. Xianding Deng
  19. Joseph L. DeRisi
  20. Angela M. Detweiler
  21. Scot Federman
  22. John Haliburton
  23. Samantha Hao
  24. Andrew D. Kerkhoff
  25. G. Renuka Kumar
  26. Katherine B. Malcolm
  27. Sabrina A. Mann
  28. Sandra Martinez
  29. Rupa Marya
  30. Eran Mick
  31. Lusajo Mwakibete
  32. Nader Najafi
  33. Michael J. Peluso
  34. Maira Phelps
  35. Angela Oliveira Pisco
  36. Kalani Ratnasiri
  37. Luis A. Rubio
  38. Anna Sellas
  39. Kyla D. Sherwood
  40. Jonathan Sheu
  41. Natasha Spottiswoode
  42. Michelle Tan
  43. Guixia Yu
  44. Kirsten Neudoerffer Kangelaris
  45. Charles Langelier

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Abstract

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  1. Version published to 10.1016/j.eclinm.2020.100518
  2. ScreenIT

    SciScore for 10.1101/2020.05.02.20082461: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The Human Research Protection Program Institutional Review Board at the University of California, San Francisco, approved this study (IRB# 16-20956).
    RandomizationRespiratory virus detection by metagenomic sequencing: To further screen for the presence of other respiratory viral pathogens, metagenomic next generation sequencing (mNGS) of RNA was performed on available residual RNA extracted for COVID-19 clinical PCR testing on 107 randomly selected patients.
    BlindingTwo physicians blinded to patients’ COVID-19 status, independently reviewed the documented clinical presentation of all patients and included only those who presented with acute respiratory symptoms (e.g., cough, dyspnea) or influenza-like illness symptoms (e.g., fever, myalgias).
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Negative control (water and HeLa cell RNA) samples enabled estimating the number of background reads to each virus, which were normalized by input mass determined based on the ratio of sample reads to spike-in positive control ERCC RNA standards.
    HeLa
    suggested: CLS Cat# 300194/p772_HeLa, RRID:CVCL_0030)
    Software and Algorithms
    SentencesResources
    The Human Research Protection Program Institutional Review Board at the University of California, San Francisco, approved this study (IRB# 16-20956).
    Human Research Protection Program
    suggested: None

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are several limitations inherent to the study design and data available that should be considered when interpreting the results of this study. As a retrospective study based in a single academic medical center and focusing on patients presenting for emergency care, it may not generalize to other institutions with different patient populations or patients with milder forms of disease. Variation in clinician assessment and documentation may lead to misclassification of some variables. Although all patients in the COVID-19 negative group presented with respiratory complaints and/or influenza-like illness, only 56% of patients were given a final diagnosis of respiratory infection, which may affect the generalizability of our outcomes data. Finally, this study was undertaken at the end of the influenza season and during a period of social distancing, both of which likely impacted the prevalence of circulating viruses and the rate of co-infections. In summary, while many clinical features of COVID-19 overlap with those of other acute respiratory illnesses, several unique characteristics were identified. Patients with COVID-19 had a longer duration of symptoms, particularly fatigue, fever, and myalgias, were more likely to be admitted to the hospital and for a longer duration, were unlikely to have co-existent viral infections, and were more likely to develop ARDS. Though this health system has not experienced a surge in COVID-19 cases, these key clinical characteristics may, ...

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.05.02.20082461v1 on medRxiv