Clinical decision support tool for diagnosis of COVID-19 in hospitals.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2021
2021
Historique:
received:
15
11
2020
accepted:
15
02
2021
entrez:
11
3
2021
pubmed:
12
3
2021
medline:
26
3
2021
Statut:
epublish
Résumé
The coronavirus infectious disease 19 (COVID-19) pandemic has resulted in significant morbidities, severe acute respiratory failures and subsequently emergency departments' (EDs) overcrowding in a context of insufficient laboratory testing capacities. The development of decision support tools for real-time clinical diagnosis of COVID-19 is of prime importance to assist patients' triage and allocate resources for patients at risk. From March 2 to June 15, 2020, clinical patterns of COVID-19 suspected patients at admission to the EDs of Liège University Hospital, consisting in the recording of eleven symptoms (i.e. dyspnoea, chest pain, rhinorrhoea, sore throat, dry cough, wet cough, diarrhoea, headache, myalgia, fever and anosmia) plus age and gender, were investigated during the first COVID-19 pandemic wave. Indeed, 573 SARS-CoV-2 cases confirmed by qRT-PCR before mid-June 2020, and 1579 suspected cases that were subsequently determined to be qRT-PCR negative for the detection of SARS-CoV-2 were enrolled in this study. Using multivariate binary logistic regression, two most relevant symptoms of COVID-19 were identified in addition of the age of the patient, i.e. fever (odds ratio [OR] = 3.66; 95% CI: 2.97-4.50), dry cough (OR = 1.71; 95% CI: 1.39-2.12), and patients older than 56.5 y (OR = 2.07; 95% CI: 1.67-2.58). Two additional symptoms (chest pain and sore throat) appeared significantly less associated to the confirmed COVID-19 cases with the same OR = 0.73 (95% CI: 0.56-0.94). An overall pondered (by OR) score (OPS) was calculated using all significant predictors. A receiver operating characteristic (ROC) curve was generated and the area under the ROC curve was 0.71 (95% CI: 0.68-0.73) rendering the use of the OPS to discriminate COVID-19 confirmed and unconfirmed patients. The main predictors were confirmed using both sensitivity analysis and classification tree analysis. Interestingly, a significant negative correlation was observed between the OPS and the cycle threshold (Ct values) of the qRT-PCR. The proposed approach allows for the use of an interactive and adaptive clinical decision support tool. Using the clinical algorithm developed, a web-based user-interface was created to help nurses and clinicians from EDs with the triage of patients during the second COVID-19 wave.
Sections du résumé
BACKGROUND
The coronavirus infectious disease 19 (COVID-19) pandemic has resulted in significant morbidities, severe acute respiratory failures and subsequently emergency departments' (EDs) overcrowding in a context of insufficient laboratory testing capacities. The development of decision support tools for real-time clinical diagnosis of COVID-19 is of prime importance to assist patients' triage and allocate resources for patients at risk.
METHODS AND PRINCIPAL FINDINGS
From March 2 to June 15, 2020, clinical patterns of COVID-19 suspected patients at admission to the EDs of Liège University Hospital, consisting in the recording of eleven symptoms (i.e. dyspnoea, chest pain, rhinorrhoea, sore throat, dry cough, wet cough, diarrhoea, headache, myalgia, fever and anosmia) plus age and gender, were investigated during the first COVID-19 pandemic wave. Indeed, 573 SARS-CoV-2 cases confirmed by qRT-PCR before mid-June 2020, and 1579 suspected cases that were subsequently determined to be qRT-PCR negative for the detection of SARS-CoV-2 were enrolled in this study. Using multivariate binary logistic regression, two most relevant symptoms of COVID-19 were identified in addition of the age of the patient, i.e. fever (odds ratio [OR] = 3.66; 95% CI: 2.97-4.50), dry cough (OR = 1.71; 95% CI: 1.39-2.12), and patients older than 56.5 y (OR = 2.07; 95% CI: 1.67-2.58). Two additional symptoms (chest pain and sore throat) appeared significantly less associated to the confirmed COVID-19 cases with the same OR = 0.73 (95% CI: 0.56-0.94). An overall pondered (by OR) score (OPS) was calculated using all significant predictors. A receiver operating characteristic (ROC) curve was generated and the area under the ROC curve was 0.71 (95% CI: 0.68-0.73) rendering the use of the OPS to discriminate COVID-19 confirmed and unconfirmed patients. The main predictors were confirmed using both sensitivity analysis and classification tree analysis. Interestingly, a significant negative correlation was observed between the OPS and the cycle threshold (Ct values) of the qRT-PCR.
CONCLUSION AND MAIN SIGNIFICANCE
The proposed approach allows for the use of an interactive and adaptive clinical decision support tool. Using the clinical algorithm developed, a web-based user-interface was created to help nurses and clinicians from EDs with the triage of patients during the second COVID-19 wave.
Identifiants
pubmed: 33705435
doi: 10.1371/journal.pone.0247773
pii: PONE-D-20-35915
pmc: PMC7951867
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0247773Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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