ArticleThe journal of allergy and clinical immunology. In practice2021
Predictive Nomogram for Severe COVID-19 and Identification of Mortality-Related Immune Features.
Article in The journal of allergy and clinical immunology. In practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.
- Prognostic models in COVID-19 infection that predict severity: a systematic review.European journal of epidemiology · 2023Pooled it
- Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis.Clinical reviews in allergy & immunology · 2023Pooled it
- An early novel prognostic model for predicting 80-day survival of patients with COVID-19.Frontiers in cellular and infection microbiology · 2022Trial
- Neutrophil-to-lymphocyte ratio as a correlative factor of severe SARS-CoV-2 infection in neonates: associations with lymphocyte subsets alterations.BMC infectious diseases · 2026Article
- Clinical and CT image features for survival prediction in severe pneumonia during the SARS-CoV-2 Omicron wave.Frontiers in medicine · 2025Article
- Article
- Dynamic Changes in Lymphocyte Populations and Their Relationship with Disease Severity and Outcome in COVID-19.International journal of molecular sciences · 2024Article
- Development and validation of a prognostic model for assessing long COVID risk following Omicron wave-a large population-based cohort study.Virology journal · 2024Article
- Risk factor analysis and nomogram prediction model construction for NEC complicated by intestinal perforation.BMC pediatrics · 2024Article
- Validation of the RIM Score-COVID in the Spanish SEMI-COVID-19 Registry.Internal and emergency medicine · 2023Article
- Development and Validation of a Predictive Nomogram with Age and Laboratory Findings for Severe COVID-19 in Hunan Province, China.Therapeutics and clinical risk management · 2022Article
- A Nomogram Model for Individualized Prediction of the Risk of Respiratory Tract Infection within Six Months after Diagnosis in Patients with Primary Immune Thrombocytopenia.Computational and mathematical methods in medicine · 2022Article
- Clinical value of plasma and peripheral blood mononuclear cells Epstein-Barr Virus DNA dynamics on prognosis of allogeneic stem cell transplantation.Frontiers in cellular and infection microbiology · 2022Article
- Features of HLA class I expression and its clinical relevance in SARS-CoV-2: What do we know so far?Reviews in medical virology · 2021Review
- Mortality-related immune features and COVID-19.The journal of allergy and clinical immunology. In practice · 2021Article
- Reply to "Mortality-related immune features and COVID-19".The journal of allergy and clinical immunology. In practice · 2021Article
- Establishment of a Clinical Nomogram Model to Predict the Progression of COVID-19 to Severe Disease.Therapeutics and clinical risk management · 2021Article
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPatients with severe 2019 novel coronavirus disease (COVID-19) have a high mortality rate. The early identification of severe COVID-19 is of critical concern. In addition, the correlation between the immunological features and clinical outcomes in severe cases needs to be explored.
objectiveTo build a nomogram for identifying patients with severe COVID-19 and explore the immunological features correlating with fatal outcomes.
methodsWe retrospectively enrolled 85 and 41 patients with COVID-19 in primary and validation cohorts, respectively. A predictive nomogram based on risk factors for severe COVID-19 was constructed using the primary cohort and evaluated internally and externally. In addition, in the validation cohort, immunological features in patients with severe COVID-19 were analyzed and correlated with disease outcomes.
resultsThe risk prediction nomogram incorporating age, C-reactive protein, and D-dimer for early identification of patients with severe COVID-19 showed favorable discrimination in both the primary (area under the curve [AUC] 0.807) and validation cohorts (AUC 0.902) and was well calibrated. Patients who died from COVID-19 showed lower abundance of peripheral CD45RO
conclusionThe novel nomogram aided the early identification of severe COVID-19 cases. In addition, the abundance of CD45RO
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.