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Early predictors of severe COVID-19 among hospitalized patients.
Zhao, Qiongrui; Yuan, Youhua; Zhang, Jiangfeng; Li, Jieren; Li, Wei; Guo, Kunshan; Wang, Yanchao; Chen, Juhua; Yan, Wenjuan; Wang, Baoya; Jing, Nan; Ma, Bing; Zhang, Qi.
  • Zhao Q; Centre of Clinical Research Service, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, China.
  • Yuan Y; Department of Clinical Microbiology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, China.
  • Zhang J; Department of Critical Care Medicine, Huaibin County People's Hospital, Huaibin, China.
  • Li J; Department of Critical Care Medicine, Huaibin County People's Hospital, Huaibin, China.
  • Li W; Department of Infectious Disease, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, China.
  • Guo K; Department of Clinical Microbiology, Xuchang Municipal Central Hospital, Xuchang, China.
  • Wang Y; Department of Clinical Microbiology, Hebi Infectious Disease Hospital, Hebi, China.
  • Chen J; Department of Clinical Microbiology, Xinyang Municipal First People's Hospital, Xinyang, China.
  • Yan W; Department of Clinical Microbiology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, China.
  • Wang B; Department of Clinical Microbiology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, China.
  • Jing N; Department of Clinical Microbiology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, China.
  • Ma B; Department of Clinical Microbiology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, China.
  • Zhang Q; Department of Clinical Microbiology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, China.
J Clin Lab Anal ; 36(2): e24177, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1589070
ABSTRACT

BACKGROUND:

Limited research has been conducted on early laboratory biomarkers to identify patients with severe coronavirus disease (COVID-19). This study fills this gap to ensure appropriate treatment delivery and optimal resource utilization.

METHODS:

In this retrospective, multicentre, cohort study, 52 and 64 participants with severe and mild cases of COVID-19, respectively, were enrolled during January-March 2020. Least absolute shrinkage and selection operator and binary forward stepwise logistic regression were used to construct a predictive risk score. A prediction model was then developed and verified using data from four hospitals.

RESULTS:

Of the 50 variables assessed, eight were independent predictors of COVID-19 and used to calculate risk scores for severe COVID-19 age (odds ratio (OR = 14.01, 95% confidence interval (CI) 2.1-22.7), number of comorbidities (OR = 7.8, 95% CI 1.4-15.5), abnormal bilateral chest computed tomography images (OR = 8.5, 95% CI 4.5-10), neutrophil count (OR = 10.1, 95% CI 1.88-21.1), lactate dehydrogenase (OR = 4.6, 95% CI 1.2-19.2), C-reactive protein OR = 16.7, 95% CI 2.9-18.9), haemoglobin (OR = 16.8, 95% CI 2.4-19.1) and D-dimer levels (OR = 5.2, 95% CI 1.2-23.1). The model was effective, with an area under the receiver-operating characteristic curve of 0.944 (95% CI 0.89-0.99, p < 0.001) in the derived cohort and 0.8152 (95% CI 0.803-0.97; p < 0.001) in the validation cohort.

CONCLUSION:

Predictors based on the characteristics of patients with COVID-19 at hospital admission may help predict the risk of subsequent critical illness.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Diagnostic study / Observational study / Prognostic study Limits: Adult / Aged / Female / Humans / Male / Middle aged / Young adult Language: English Journal: J Clin Lab Anal Journal subject: Laboratory Techniques and procedures Year: 2022 Document Type: Article Affiliation country: Jcla.24177

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Diagnostic study / Observational study / Prognostic study Limits: Adult / Aged / Female / Humans / Male / Middle aged / Young adult Language: English Journal: J Clin Lab Anal Journal subject: Laboratory Techniques and procedures Year: 2022 Document Type: Article Affiliation country: Jcla.24177