ArticleFrontiers in public health2020
Prediction of COVID-19 Patients at High Risk of Progression to Severe Disease.
Article in Frontiers in public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Performance fairness of neural network models in early risk assessment of inpatients with varying severity: a retrospective study.BMC medical informatics and decision making · 2026Article
- Article
- C-reactive protein: structure, function, regulation, and role in clinical diseases.Frontiers in immunology · 2024Review
- Validation of a risk prediction model for COVID-19: the PERIL prospective cohort study.Future virology · 2023Article
- The effect of ACE2 receptor, IFN-γ, and TNF-α polymorphisms on the severity and prognosis of the disease in SARS-CoV-2 infection.Journal of investigative medicine : the official publication of the American Federation for Clinical Research · 2023Article
- Severe/critical COVID-19 early warning system based on machine learning algorithms using novel imaging scores.World journal of clinical cases · 2023Article
- Article
- Impact of upper and lower respiratory symptoms on COVID-19 outcomes: a multicenter retrospective cohort study.Respiratory research · 2022Article
- Speech as a Biomarker for COVID-19 Detection Using Machine Learning.Computational intelligence and neuroscience · 2022Article
- Development and validation of nomogram to predict severe illness requiring intensive care follow up in hospitalized COVID-19 cases.BMC infectious diseases · 2021Article
- Applications of laboratory findings in the prevention, diagnosis, treatment, and monitoring of COVID-19.Signal transduction and targeted therapy · 2021Review
- The Quest for System-Theoretical Medicine in the COVID-19 Era.Frontiers in medicine · 2021Article
- The association between serum levels of micronutrients and the severity of disease in patients with COVID-19.Nutrition (Burbank, Los Angeles County, Calif.)Article
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17 authors.
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No grant is acknowledged in the PubMed record.
Abstract
In order to develop a novel scoring model for the prediction of coronavirus disease-19 (COVID-19) patients at high risk of severe disease, we retrospectively studied 419 patients from five hospitals in Shanghai, Hubei, and Jiangsu Provinces from January 22 to March 30, 2020. Multivariate Cox regression and orthogonal projections to latent structures discriminant analysis (OPLS-DA) were both used to identify high-risk factors for disease severity in COVID-19 patients. The prediction model was developed based on four high-risk factors. Multivariate analysis showed that comorbidity [hazard ratio (HR) 3.17, 95% confidence interval (CI) 1.96-5.11], albumin (ALB) level (HR 3.67, 95% CI 1.91-7.02), C-reactive protein (CRP) level (HR 3.16, 95% CI 1.68-5.96), and age ≥60 years (HR 2.31, 95% CI 1.43-3.73) were independent risk factors for disease severity in COVID-19 patients. OPLS-DA identified that the top five influencing parameters for COVID-19 severity were CRP, ALB, age ≥60 years, comorbidity, and lactate dehydrogenase (LDH) level. When incorporating the above four factors, the nomogram had a good concordance index of 0.86 (95% CI 0.83-0.89) and had an optimal agreement between the predictive nomogram and the actual observation with a slope of 0.95 (
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