C-Reactive Protein Level May Predict the Risk of COVID-19 Aggravation
BackgroundClinical findings indicated that a fraction of coronavirus disease 2019 (COVID-19) patients diagnosed as mild early may progress to severe cases. However, it is difficult to distinguish these patients in the early stage. The present study aimed to describe the clinical characteristics of t...
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| Vydáno v: | Open forum infectious diseases Ročník 7; číslo 5; s. ofaa153 |
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01.05.2020
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| Abstract | BackgroundClinical findings indicated that a fraction of coronavirus disease 2019 (COVID-19) patients diagnosed as mild early may progress to severe cases. However, it is difficult to distinguish these patients in the early stage. The present study aimed to describe the clinical characteristics of these patients, analyze related factors, and explore predictive markers of the disease aggravation.MethodsClinical and laboratory data of nonsevere adult COVID-19 patients in Changsha, China, were collected and analyzed on admission. A logistic regression model was adopted to analyze the association between the disease aggravation and related factors. The receiver operating characteristic curve (ROC) was utilized to analyze the prognostic ability of C-reactive protein (CRP).ResultsAbout 7.7% (16/209) of nonsevere adult COVID-19 patients progressed to severe cases after admission. Compared with nonsevere patients, the aggravated patients had much higher levels of CRP (median [range], 43.8 [12.3–101.9] mg/L vs 12.1 [0.1–91.4] mg/L; P = .000). A regression analysis showed that CRP was significantly associated with aggravation of nonsevere COVID-19 patients, with an area under the curve of 0.844 (95% confidence interval, 0.761–0.926) and an optimal threshold value of 26.9 mg/L.ConclusionsCRP could be a valuable marker to anticipate the possibility of aggravation of nonsevere adult COVID-19 patients, with an optimal threshold value of 26.9 mg/L. |
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| AbstractList | BackgroundClinical findings indicated that a fraction of coronavirus disease 2019 (COVID-19) patients diagnosed as mild early may progress to severe cases. However, it is difficult to distinguish these patients in the early stage. The present study aimed to describe the clinical characteristics of these patients, analyze related factors, and explore predictive markers of the disease aggravation.MethodsClinical and laboratory data of nonsevere adult COVID-19 patients in Changsha, China, were collected and analyzed on admission. A logistic regression model was adopted to analyze the association between the disease aggravation and related factors. The receiver operating characteristic curve (ROC) was utilized to analyze the prognostic ability of C-reactive protein (CRP).ResultsAbout 7.7% (16/209) of nonsevere adult COVID-19 patients progressed to severe cases after admission. Compared with nonsevere patients, the aggravated patients had much higher levels of CRP (median [range], 43.8 [12.3–101.9] mg/L vs 12.1 [0.1–91.4] mg/L; P = .000). A regression analysis showed that CRP was significantly associated with aggravation of nonsevere COVID-19 patients, with an area under the curve of 0.844 (95% confidence interval, 0.761–0.926) and an optimal threshold value of 26.9 mg/L.ConclusionsCRP could be a valuable marker to anticipate the possibility of aggravation of nonsevere adult COVID-19 patients, with an optimal threshold value of 26.9 mg/L. Clinical findings indicated that a fraction of coronavirus disease 2019 (COVID-19) patients diagnosed as mild early may progress to severe cases. However, it is difficult to distinguish these patients in the early stage. The present study aimed to describe the clinical characteristics of these patients, analyze related factors, and explore predictive markers of the disease aggravation. Clinical and laboratory data of nonsevere adult COVID-19 patients in Changsha, China, were collected and analyzed on admission. A logistic regression model was adopted to analyze the association between the disease aggravation and related factors. The receiver operating characteristic curve (ROC) was utilized to analyze the prognostic ability of C-reactive protein (CRP). About 7.7% (16/209) of nonsevere adult COVID-19 patients progressed to severe cases after admission. Compared with nonsevere patients, the aggravated patients had much higher levels of CRP (median [range], 43.8 [12.3-101.9] mg/L vs 12.1 [0.1-91.4] mg/L; = .000). A regression analysis showed that CRP was significantly associated with aggravation of nonsevere COVID-19 patients, with an area under the curve of 0.844 (95% confidence interval, 0.761-0.926) and an optimal threshold value of 26.9 mg/L. CRP could be a valuable marker to anticipate the possibility of aggravation of nonsevere adult COVID-19 patients, with an optimal threshold value of 26.9 mg/L. Clinical findings indicated that a fraction of coronavirus disease 2019 (COVID-19) patients diagnosed as mild early may progress to severe cases. However, it is difficult to distinguish these patients in the early stage. The present study aimed to describe the clinical characteristics of these patients, analyze related factors, and explore predictive markers of the disease aggravation.BACKGROUNDClinical findings indicated that a fraction of coronavirus disease 2019 (COVID-19) patients diagnosed as mild early may progress to severe cases. However, it is difficult to distinguish these patients in the early stage. The present study aimed to describe the clinical characteristics of these patients, analyze related factors, and explore predictive markers of the disease aggravation.Clinical and laboratory data of nonsevere adult COVID-19 patients in Changsha, China, were collected and analyzed on admission. A logistic regression model was adopted to analyze the association between the disease aggravation and related factors. The receiver operating characteristic curve (ROC) was utilized to analyze the prognostic ability of C-reactive protein (CRP).METHODSClinical and laboratory data of nonsevere adult COVID-19 patients in Changsha, China, were collected and analyzed on admission. A logistic regression model was adopted to analyze the association between the disease aggravation and related factors. The receiver operating characteristic curve (ROC) was utilized to analyze the prognostic ability of C-reactive protein (CRP).About 7.7% (16/209) of nonsevere adult COVID-19 patients progressed to severe cases after admission. Compared with nonsevere patients, the aggravated patients had much higher levels of CRP (median [range], 43.8 [12.3-101.9] mg/L vs 12.1 [0.1-91.4] mg/L; P = .000). A regression analysis showed that CRP was significantly associated with aggravation of nonsevere COVID-19 patients, with an area under the curve of 0.844 (95% confidence interval, 0.761-0.926) and an optimal threshold value of 26.9 mg/L.RESULTSAbout 7.7% (16/209) of nonsevere adult COVID-19 patients progressed to severe cases after admission. Compared with nonsevere patients, the aggravated patients had much higher levels of CRP (median [range], 43.8 [12.3-101.9] mg/L vs 12.1 [0.1-91.4] mg/L; P = .000). A regression analysis showed that CRP was significantly associated with aggravation of nonsevere COVID-19 patients, with an area under the curve of 0.844 (95% confidence interval, 0.761-0.926) and an optimal threshold value of 26.9 mg/L.CRP could be a valuable marker to anticipate the possibility of aggravation of nonsevere adult COVID-19 patients, with an optimal threshold value of 26.9 mg/L.CONCLUSIONSCRP could be a valuable marker to anticipate the possibility of aggravation of nonsevere adult COVID-19 patients, with an optimal threshold value of 26.9 mg/L. |
| Author | Li, Yiming Wu, Chao Li, Tiao Wu, Chenfang Wang, Guyi Wu, Guobao Yu, Bo Lv, Jianlei Zhong, Yanjun Zhang, Quan Wu, Fang Zhang, Siye |
| AuthorAffiliation | 1 Critical Care Medicine, The Second Xiangya Hospital, Central South University , Changsha, China 5 Department of Respiratory Medicine, The Second Xiangya Hospital, Central-South University , Changsha, Hunan, China 2 Critical Care Medicine, The First Hospital of Changsha , Changsha, China 4 Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University , Wuhan, Hubei, China 3 Department of Oncology, The Second Xiangya Hospital, Central South University , Changsha, Hunan, China 7 Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education , Changsha, Hunan, China 8 National Clinical Research Center for Metabolic Diseases , Changsha, Hunan, China 6 Department of Metabolism & Endocrinology, The Second Xiangya Hospital, Central South University , Changsha, Hunan, China |
| AuthorAffiliation_xml | – name: 6 Department of Metabolism & Endocrinology, The Second Xiangya Hospital, Central South University , Changsha, Hunan, China – name: 2 Critical Care Medicine, The First Hospital of Changsha , Changsha, China – name: 5 Department of Respiratory Medicine, The Second Xiangya Hospital, Central-South University , Changsha, Hunan, China – name: 7 Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education , Changsha, Hunan, China – name: 8 National Clinical Research Center for Metabolic Diseases , Changsha, Hunan, China – name: 3 Department of Oncology, The Second Xiangya Hospital, Central South University , Changsha, Hunan, China – name: 4 Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University , Wuhan, Hubei, China – name: 1 Critical Care Medicine, The Second Xiangya Hospital, Central South University , Changsha, China |
| Author_xml | – sequence: 1 givenname: Guyi surname: Wang fullname: Wang, Guyi organization: Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, China – sequence: 2 givenname: Chenfang surname: Wu fullname: Wu, Chenfang organization: Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, China – sequence: 3 givenname: Quan surname: Zhang fullname: Zhang, Quan organization: Critical Care Medicine, The First Hospital of Changsha, Changsha, China – sequence: 4 givenname: Fang surname: Wu fullname: Wu, Fang organization: Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China – sequence: 5 givenname: Bo surname: Yu fullname: Yu, Bo organization: Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, China – sequence: 6 givenname: Jianlei surname: Lv fullname: Lv, Jianlei organization: Critical Care Medicine, The First Hospital of Changsha, Changsha, China – sequence: 7 givenname: Yiming surname: Li fullname: Li, Yiming organization: Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China – sequence: 8 givenname: Tiao surname: Li fullname: Li, Tiao organization: Department of Respiratory Medicine, The Second Xiangya Hospital, Central-South University, Changsha, Hunan, China – sequence: 9 givenname: Siye surname: Zhang fullname: Zhang, Siye organization: Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, China – sequence: 10 givenname: Chao surname: Wu fullname: Wu, Chao organization: Department of Metabolism & Endocrinology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China – sequence: 11 givenname: Guobao surname: Wu fullname: Wu, Guobao organization: Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, China – sequence: 12 givenname: Yanjun surname: Zhong fullname: Zhong, Yanjun email: zhongyanjun@csu.edu.cn organization: Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32455147$$D View this record in MEDLINE/PubMed |
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| Snippet | BackgroundClinical findings indicated that a fraction of coronavirus disease 2019 (COVID-19) patients diagnosed as mild early may progress to severe cases.... Clinical findings indicated that a fraction of coronavirus disease 2019 (COVID-19) patients diagnosed as mild early may progress to severe cases. However, it... |
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| SubjectTerms | C-reactive protein Coronaviruses COVID-19 Major |
| Title | C-Reactive Protein Level May Predict the Risk of COVID-19 Aggravation |
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