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Published in: BMC Infectious Diseases 1/2022

01-12-2022 | Triage | Research

A new screening tool for SARS-CoV-2 infection based on self-reported patient clinical characteristics: the COV19-ID score

Authors: Pablo Diaz Badial, Hugo Bothorel, Omar Kherad, Philippe Dussoix, Faustine Tallonneau Bory, Majd Ramlawi

Published in: BMC Infectious Diseases | Issue 1/2022

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Abstract

Background

While several studies aimed to identify risk factors for severe COVID-19 cases to better anticipate intensive care unit admissions, very few have been conducted on self-reported patient symptoms and characteristics, predictive of RT-PCR test positivity. We therefore aimed to identify those predictive factors and construct a predictive score for the screening of patients at admission.

Methods

This was a monocentric retrospective analysis of clinical data from 9081 patients tested for SARS-CoV-2 infection from August 1 to November 30 2020. A multivariable logistic regression using least absolute shrinkage and selection operator (LASSO) was performed on a training dataset (60% of the data) to determine associations between self-reported patient characteristics and COVID-19 diagnosis. Regression coefficients were used to construct the Coronavirus 2019 Identification score (COV19-ID) and the optimal threshold calculated on the validation dataset (20%). Its predictive performance was finally evaluated on a test dataset (20%).

Results

A total of 2084 (22.9%) patients were tested positive to SARS-CoV-2 infection. Using the LASSO model, COVID-19 was independently associated with loss of smell (Odds Ratio, 6.4), fever (OR, 2.7), history of contact with an infected person (OR, 1.7), loss of taste (OR, 1.5), muscle stiffness (OR, 1.5), cough (OR, 1.5), back pain (OR, 1.4), loss of appetite (OR, 1.3), as well as male sex (OR, 1.05). Conversely, COVID-19 was less likely associated with smoking (OR, 0.5), sore throat (OR, 0.9) and ear pain (OR, 0.9). All aforementioned variables were included in the COV19-ID score, which demonstrated on the test dataset an area under the receiver-operating characteristic curve of 82.9% (95% CI 80.6%–84.9%), and an accuracy of 74.2% (95% CI 74.1%–74.3%) with a high sensitivity (80.4%, 95% CI [80.3%–80.6%]) and specificity (72.2%, 95% CI [72.2%–72.4%]).

Conclusions

The COV19-ID score could be useful in early triage of patients needing RT-PCR testing thus alleviating the burden on laboratories, emergency rooms, and wards.
Appendix
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Metadata
Title
A new screening tool for SARS-CoV-2 infection based on self-reported patient clinical characteristics: the COV19-ID score
Authors
Pablo Diaz Badial
Hugo Bothorel
Omar Kherad
Philippe Dussoix
Faustine Tallonneau Bory
Majd Ramlawi
Publication date
01-12-2022
Publisher
BioMed Central
Published in
BMC Infectious Diseases / Issue 1/2022
Electronic ISSN: 1471-2334
DOI
https://doi.org/10.1186/s12879-022-07164-1

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