A novel risk score to predict diagnosis with coronavirus disease 2019 (COVID-19) in suspected patients : A retrospective, multicenter, and observational study
© 2020 Wiley Periodicals LLC..
The aim of the study was to explore a novel risk score to predict diagnosis with COVID-19 among all suspected patients at admission. This was a retrospective, multicenter, and observational study. The clinical data of all suspected patients were analyzed. Independent risk factors were identified via multivariate logistic regression analysis. 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 less than 100 beat/minutes (OR:3.80, 95%CI, 2.00-7.22), bilateral pneumonia (OR:3.60, 95%CI, 1.83-7.10), neutrophil count less than equal to 6.3 × 109 /L (OR: 6.77, 95%CI, 2.52-18.19), eosinophil count less than equal to 0.02 × 109 /L (OR:3.14, 95%CI, 1.58-6.22), glucose more than equal to 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 less than 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 reciever operator characteristic curve and the area under the curve was 0.921 (95%CI: 0.896-0.945; P < .01). We designed a novel risk score which might have a promising predictive capacity for diagnosis with COVID-19 among suspected patients.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:92 |
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| Enthalten in: |
Journal of medical virology - 92(2020), 11 vom: 01. Nov., Seite 2709-2717 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Huang, Dong [VerfasserIn] |
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| Links: |
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| Themen: |
COVID-19 |
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| Anmerkungen: |
Date Completed 24.12.2020 Date Revised 16.07.2022 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1002/jmv.26143 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM310896525 |
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| 245 | 1 | 2 | |a A novel risk score to predict diagnosis with coronavirus disease 2019 (COVID-19) in suspected patients |b A retrospective, multicenter, and observational study |
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| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2020 Wiley Periodicals LLC. | ||
| 520 | |a The aim of the study was to explore a novel risk score to predict diagnosis with COVID-19 among all suspected patients at admission. This was a retrospective, multicenter, and observational study. The clinical data of all suspected patients were analyzed. Independent risk factors were identified via multivariate logistic regression analysis. 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 less than 100 beat/minutes (OR:3.80, 95%CI, 2.00-7.22), bilateral pneumonia (OR:3.60, 95%CI, 1.83-7.10), neutrophil count less than equal to 6.3 × 109 /L (OR: 6.77, 95%CI, 2.52-18.19), eosinophil count less than equal to 0.02 × 109 /L (OR:3.14, 95%CI, 1.58-6.22), glucose more than equal to 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 less than 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 reciever operator characteristic curve and the area under the curve was 0.921 (95%CI: 0.896-0.945; P < .01). We designed a novel risk score which might have a promising predictive capacity for diagnosis with COVID-19 among suspected patients | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Multicenter Study | |
| 650 | 4 | |a Observational Study | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a clinical characteristics | |
| 650 | 4 | |a predicting risk score | |
| 650 | 4 | |a suspected cases | |
| 700 | 1 | |a Wang, Ting |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Zhu |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Huan |e verfasserin |4 aut | |
| 700 | 1 | |a Yao, Rong |e verfasserin |4 aut | |
| 700 | 1 | |a Liang, Zongan |e verfasserin |4 aut | |
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