CCEDRRN COVID-19 Infection Score (CCIS): development and validation in a Canadian cohort of a clinical risk score to predict SARS-CoV-2 infection in patients presenting to the emergency department with suspected COVID-19

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Abstract

To develop and validate a clinical risk score that can accurately quantify the probability of SARS-CoV-2 infection in patients presenting to an emergency department without the need for laboratory testing.

Design

Cohort study of participants in the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) registry. Regression models were fitted to predict a positive SARS-CoV-2 test result using clinical and demographic predictors, as well as an indicator of local SARS-CoV-2 incidence.

Setting

32 emergency departments in eight Canadian provinces.

Participants

27 665 consecutively enrolled patients who were tested for SARS-CoV-2 in participating emergency departments between 1 March and 30 October 2020.

Main outcome measures

Positive SARS-CoV-2 nucleic acid test result within 14 days of an index emergency department encounter for suspected COVID-19 disease.

Results

We derived a 10-item CCEDRRN COVID-19 Infection Score using data from 21 743 patients. This score included variables from history and physical examination and an indicator of local disease incidence. The score had a c-statistic of 0.838 with excellent calibration. We externally validated the rule in 5295 patients. The score maintained excellent discrimination and calibration and had superior performance compared with another previously published risk score. Score cut-offs were identified that can rule-in or rule-out SARS-CoV-2 infection without the need for nucleic acid testing with 97.4% sensitivity (95% CI 96.4 to 98.3) and 95.9% specificity (95% CI 95.5 to 96.0).

Conclusions

The CCEDRRN COVID-19 Infection Score uses clinical characteristics and publicly available indicators of disease incidence to quantify a patient’s probability of SARS-CoV-2 infection. The score can identify patients at sufficiently high risk of SARS-CoV-2 infection to warrant isolation and empirical therapy prior to test confirmation while also identifying patients at sufficiently low risk of infection that they may not need testing.

Trial registration number

NCT04702945 .

Article activity feed

  1. SciScore for 10.1101/2021.07.15.21260590: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Trained research assistants entered anonymized participant data into a REDCap database (Version 10.9.4; Vanderbilt University, Nashville, Tennessee, USA).
    REDCap
    suggested: (REDCap, RRID:SCR_003445)

    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:
    These tools were developed in studies with substantial methodological limitations and incorporate variables not immediately available at the time of a patient’s hospital arrival, so are not useful to guide early isolation, testing and treatment decisions.2 None of these risk prediction tools considered the prevalence of disease in the population. Prevalence can substantially change the approach to testing and cohorting, and this will become increasingly important as prevalence rates drop and selective rather than liberal testing may be more appropriate. United States-based investigators recently reported the development of the CORC score using only clinical variables. The CORC score contains several similar variables to the CCIS. However, the CORC score was derived in a non-consecutive sample of patients which had a much higher incidence of disease than our study cohort and may be vulnerable to selection bias. The CORC score also included race and ethnicity as predictor variables. This inclusion of race and ethnicity variables limits the generalizability of the CORC score beyond the urban American population in which it was developed, as it does not reflect the international diversity of ethnic backgrounds. Moreover, it is unlikely race or ethnicity represents a biologic risk. The association between race and ethnicity and SARS-CoV-2 infection in the CORC score likely reflects other sociodemographic and geographic predictors of the risk of COVID-19 infection in the American p...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04702945RecruitingCanadian COVID-19 Emergency Department Registry


    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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