Qatar Prediction Rule Using ED Indicators of COVID-19 at Triage

Abstract

Introduction: The presence of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) and its associated disease, COVID-19 has had an enormous impact on the operations of the emergency department (ED), particularly the triage area. The aim of the study was to derive and validate a prediction rule that would be applicable to Qatar’s adult ED population to predict COVID-19-positive patients. Methods: This is a retrospective study including adult patients. The data were obtained from the electronic medical records (EMR) of the Hamad Medical Corporation (HMC) for three EDs. Data from the Hamad General Hospital ED were used to derive and internally validate a prediction rule (Q-PREDICT). The Al Wakra Hospital ED and Al Khor Hospital ED data formed an external validation set consisting of the same time frame. The variables in the model included the weekly ED COVID-19-positivity rate and the following patient characteristics: region (nationality), age, acuity, cough, fever, tachypnea, hypoxemia, and hypotension. All statistical analyses were executed with Stata 16.1 (Stata Corp). The study team obtained appropriate institutional approval. Results: The study included 45,663 adult patients who were tested for COVID-19. Out of these, 47% (n = 21461) were COVID-19 positive. The derivation-set model had very good discrimination (c = 0.855, 95% Confidence intervals (CI) 0.847–0.861). Cross-validation of the model demonstrated that the validation-set model (c = 0.857, 95% CI 0.849–0.863) retained high discrimination. A high Q-PREDICT score ( ≥ 13) is associated with a nearly 6-fold increase in the likelihood of being COVID-19 positive (likelihood ratio 5.9, 95% CI 5.6–6.2), with a sensitivity of 84.7% (95% CI, 84.0%–85.4%). A low Q-PREDICT ( ≤ 6) is associated with a nearly 20-fold increase in the likelihood of being COVID-19 negative (likelihood ratio 19.3, 95% CI 16.7–22.1), with a specificity of 98.7% (95% CI 98.5%–98.9%). Conclusion: The Q-PREDICT is a simple scoring system based on information readily collected from patients at the front desk of the ED and helps to predict COVID-19 status at triage. The scoring system performed well in the internal and external validation on datasets obtained from the state of Qatar.

Real-world diagnostic value of a nationwide standardized COVID-19 triage chart in Turkey

“…24 A Qatar-based study presented a scoring system based on a logistic regression model using predictors identified by random forest, which includes emergency department indicators (demographic data, chief complaint and vital signs) for COVID-19 positivity; the model had a 5.9 positive likelihood ratio and a 19.3 negative likelihood ratio at different cutoff points. 25 In contrast to these studies, a similar scoring system from southern Tunisia, which included contact history, fever, cough and/or dyspnea, sore throat, nausea/vomiting/diarrhea, renal/respiratory, or cardiac failure, had insufficient AUC to discriminate COVID-19 cases. 26 Our results demonstrate that the "Possible COVID-19 Case Questioning Guide for Outpatients" triage chart had high sensitivity and specificity value as a whole, with a considerable AUC for discriminating possible COVID-19 cases, similar to the currently published literature.…”