tetano
Editor, Senior Moderator
J Med Virol
. 2020 Jun 8.
doi: 10.1002/jmv.26143. Online ahead of print.
A Novel Risk Score to Predict Diagnosis With Coronavirus Disease 2019 (COVID-19) in Suspected Patients: A Retrospective, Multi-Center, Observational Study
Dong Huang[SUP] 1 [/SUP], Ting Wang[SUP] 1 [/SUP], Zhu Chen[SUP] 2 [/SUP], Huan Yang[SUP] 1 [/SUP], Rong Yao[SUP] 3 4 [/SUP], Zongan Liang[SUP] 1 [/SUP]
Affiliations
Abstract
Background: The aim of the study was to explore a novel risk score to predict diagnosis with COVID-19 among all suspected patients at admission.
Methods: This was a retrospective, multi-center, observational study. The clinical data of all suspected patients were analyzed. Independent risk factors were identified via multivariate logistic regression analysis.
Results: Finally, 336 confirmed COVID-19 patients and 139 control patients were included. We found nine independent risk factors for diagnosis with COVID-19 at admission to hospital: epidemiological exposure histories (OR:13.32, 95%CI 6.39-27.75), weakness/fatigue (OR:4.51, 95%CI 1.70-11.96), heart rate <100 beat/min (OR:3.80, 95%CI 2.00-7.22), bilateral pneumonia (OR:3.60, 95%CI 1.83-7.10), neutrophil count ≤6.3?10[SUP]9[/SUP] /L (OR: 6.77, 95%CI 2.52-18.19), eosinophil count ≤0.02?10[SUP]9[/SUP] /L (OR:3.14, 95%CI 1.58-6.22), glucose ≥6 mmol/L (OR:2.43, 95%CI 1.04-5.66), D-dimer ≥0.5 mg/L (OR:3.49, 95%CI 1.22-9.96), and C-reactive protein <5 mg/L (OR:3.83, 95%CI 1.86-7.92). As for the performance of this risk score, a cut-off value of 20 (specificity: 0.866, sensitivity: 0.813) was identified to predict COVID-19 according to ROC curve and the area under the curve (AUC) was 0.921 (95%CI: 0.896-0.945, p<0.01).
Conclusions: We designed a novel risk score which might have a promising predictive capacity for diagnosis with COVID-19 among suspected patients. This article is protected by copyright. All rights reserved.
Keywords: COVID-19; clinical characteristics; predicting risk score; suspected cases.
. 2020 Jun 8.
doi: 10.1002/jmv.26143. Online ahead of print.
A Novel Risk Score to Predict Diagnosis With Coronavirus Disease 2019 (COVID-19) in Suspected Patients: A Retrospective, Multi-Center, Observational Study
Dong Huang[SUP] 1 [/SUP], Ting Wang[SUP] 1 [/SUP], Zhu Chen[SUP] 2 [/SUP], Huan Yang[SUP] 1 [/SUP], Rong Yao[SUP] 3 4 [/SUP], Zongan Liang[SUP] 1 [/SUP]
Affiliations
- PMID: 32510164
- DOI: 10.1002/jmv.26143
Abstract
Background: The aim of the study was to explore a novel risk score to predict diagnosis with COVID-19 among all suspected patients at admission.
Methods: This was a retrospective, multi-center, observational study. The clinical data of all suspected patients were analyzed. Independent risk factors were identified via multivariate logistic regression analysis.
Results: Finally, 336 confirmed COVID-19 patients and 139 control patients were included. We found nine independent risk factors for diagnosis with COVID-19 at admission to hospital: epidemiological exposure histories (OR:13.32, 95%CI 6.39-27.75), weakness/fatigue (OR:4.51, 95%CI 1.70-11.96), heart rate <100 beat/min (OR:3.80, 95%CI 2.00-7.22), bilateral pneumonia (OR:3.60, 95%CI 1.83-7.10), neutrophil count ≤6.3?10[SUP]9[/SUP] /L (OR: 6.77, 95%CI 2.52-18.19), eosinophil count ≤0.02?10[SUP]9[/SUP] /L (OR:3.14, 95%CI 1.58-6.22), glucose ≥6 mmol/L (OR:2.43, 95%CI 1.04-5.66), D-dimer ≥0.5 mg/L (OR:3.49, 95%CI 1.22-9.96), and C-reactive protein <5 mg/L (OR:3.83, 95%CI 1.86-7.92). As for the performance of this risk score, a cut-off value of 20 (specificity: 0.866, sensitivity: 0.813) was identified to predict COVID-19 according to ROC curve and the area under the curve (AUC) was 0.921 (95%CI: 0.896-0.945, p<0.01).
Conclusions: We designed a novel risk score which might have a promising predictive capacity for diagnosis with COVID-19 among suspected patients. This article is protected by copyright. All rights reserved.
Keywords: COVID-19; clinical characteristics; predicting risk score; suspected cases.