Your browser doesn't support javascript.
Individualized prediction nomograms for disease progression in mild COVID-19.
Huang, Jiaofeng; Cheng, Aiguo; Lin, Su; Zhu, Yueyong; Chen, Gongping.
  • Huang J; Department of Liver Research Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
  • Cheng A; Department of Critical Care, The Third People's Hospital of Yichang, China.
  • Lin S; Department of Liver Research Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
  • Zhu Y; Department of Liver Research Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
  • Chen G; Department of Respiratory, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
J Med Virol ; 92(10): 2074-2080, 2020 10.
Article in English | MEDLINE | ID: covidwho-175876
ABSTRACT
The coronavirus disease 2019 (COVID-19) has evolved into a pandemic rapidly. The majority of COVID-19 patients are with mild syndromes. This study aimed to develop models for predicting disease progression in mild cases. The risk factors for the requirement of oxygen support in mild COVID-19 were explored using multivariate logistic regression. Nomogram as visualization of the models was developed using R software. A total of 344 patients with mild COVID-19 were included in the final analysis, 45 of whom progressed and needed high-flow oxygen therapy or mechanical ventilation after admission. There were 188 (54.7%) males, and the average age of the cohort was 52.9 ± 16.8 years. When the laboratory data were not included in multivariate analysis, diabetes, coronary heart disease, T ≥ 38.5℃ and sputum were independent risk factors of progressive COVID-19 (Model 1). When the blood routine test was included the CHD, T ≥ 38.5℃ and neutrophil-to-lymphocyte ratio were found to be independent predictors (Model 2). The area under the receiver operator characteristic curve of model 2 was larger than model 1 (0.872 vs 0.849, P = .023). The negative predictive value of both models was greater than 96%, indicating they could serve as simple tools for ruling out the possibility of disease progression. In conclusion, two models comprised common symptoms (fever and sputum), underlying diseases (diabetes and coronary heart disease) and blood routine test are developed for predicting the future requirement of oxygen support in mild COVID-19 cases.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Observational study / Prognostic study Topics: Variants Limits: Female / Humans / Male / Middle aged Language: English Journal: J Med Virol Year: 2020 Document Type: Article Affiliation country: Jmv.25969

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Observational study / Prognostic study Topics: Variants Limits: Female / Humans / Male / Middle aged Language: English Journal: J Med Virol Year: 2020 Document Type: Article Affiliation country: Jmv.25969