Prognostic accuracy of emergency department triage tools for children with suspected COVID-19: The PRIEST observational cohort study

Abstract

Objectives

Emergency department clinicians can use triage tools to predict adverse outcome and support management decisions for children presenting with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in children presenting to the emergency department (ED) with suspected COVID-19 infection.

Methods

We undertook a mixed prospective and retrospective observational cohort study in 44 EDs across the United Kingdom (UK). We collected data from children attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment using the WHO algorithm, swine flu hospital pathway for children (SFHPC), Paediatric Observation Priority Score (POPS) and Children’s Observation and Severity Tool (COAST). We recorded 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome.

Results

We collected data from 1530 children, including 26 (1.7%) with an adverse outcome. C-statistics were 0.80 (95% confidence interval 0.73-0.87) for the WHO algorithm, 0.80 (0.71-0.90) for POPS, 0.76 (0.67-0.85) for COAST, and 0.71 (0.59-0.82) for SFHPC. Using pre-specified thresholds, the WHO algorithm had the highest sensitivity (0.85) and lowest specificity (0.75), but POPS and COAST could optimise sensitivity (0.96 and 0.92 respectively) at the expense of specificity (0.25 and 0.38 respectively) by using a threshold of any score above zero instead of the pre-specified threshold.

Conclusion

Existing triage tools have good but not excellent prediction for adverse outcome in children with suspected COVID-19. POPS and COAST could achieve an appropriate balance of sensitivity and specificity for supporting decisions to discharge home by considering any score above zero to be positive.

Registration

ISRCTN registry, ISRCTN28342533 , http://www.isrctn.com/ISRCTN28342533

SciScore for 10.1101/2020.09.01.20185793: (What is this?)

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

Table 1: Rigor

Institutional Review Board Statement	Consent: We did not seek consent to collect data but information about the study was provided in the ED and patients or parents could withdraw their data at their request.
Randomization	not detected.
Blinding	not detected.
Power Analysis	not detected.
Sex as a biological variable	not 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:

Strengths and limitations: We collected data across multiple varied sites throughout the first wave of the pandemic in the UK. This analysis is therefore based on a large and representative sample of children with suspected COVID-19. However, the low rate of adverse outcome (1.7%) meant that our study lacked statistical power to detect associations between predictors and adverse outcome. We were unable to address our original aim of deriving a new triage tool and lacked sufficient adverse outcomes to undertake multivariable analysis. The associations reported in Table 1 are based on univariate analysis and should be considered with caution. The differences between point estimates for c-statistics and sensitivity are relatively imprecise. Another limitation is that we relied on a mixture of prospective and retrospective methods to record predictor variables, which resulted in missing data for some variables and inability to determine whether some predictors were not present or not recorded. This may have resulted in some predictor variables being under-recorded, leading to under-estimation of the performance of the triage tools. It should be noted that we evaluated modified versions of POPS, COAST and the SFHPC that dropped a predictor variable from each tool. Inclusion of these dropped variables could have improved prediction, and improved sensitivity at the expense of specificity. Finally, we may have missed adverse outcomes if patients attended a different hospital after in...

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

Identifier	Status	Title
ISRCTN28342533	NA	NA

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.
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No protocol registration statement was detected.

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