Evidence map›Paper›PMID 34422577›Full record

ArticleQatar medical journal2021

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

Sameer A Pathan, Caroline E Thomas, Zain A Bhutta, Isma Qureshi, Sarah A Thomas, Jibin Moinudheen, Stephen H Thomas

Abstract read
In one paragraph

Article in Qatar medical journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Sameer A Pathan
Caroline E ThomasSouthbank International School, Westminster, London, UK.
Zain A BhuttaHamad Medical Corporation, Doha, Qatar E-mail: IQureshi@hamad.qa.
Isma QureshiHamad Medical Corporation, Doha, Qatar E-mail: IQureshi@hamad.qa.
Sarah A ThomasBachelor Candidate in Medical Biosciences, Faculty of Medicine, Imperial College London, UK.
Jibin MoinudheenHamad Medical Corporation, Doha, Qatar E-mail: IQureshi@hamad.qa.
Stephen H ThomasHamad Medical Corporation, Doha, Qatar E-mail: IQureshi@hamad.qa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe 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.

methodsThis 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.

resultsThe 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%).

conclusionThe 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.

Indexed as

COVID-19COVID positiveemergency departmentpredictQatartriage

Identifiers

PMID34422577
PMCPMC8359675

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