ArticleBMC infectious diseases2021
An easy-to-use nomogram for predicting in-hospital mortality risk in COVID-19: a retrospective cohort study in a university hospital.
Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.
- Prognostic models in COVID-19 infection that predict severity: a systematic review.European journal of epidemiology · 2023Pooled it
- Risk factor analysis and development of a nomogram prediction model for Plasma Cell Mastitis.PloS one · 2025Article
- Risk Factor Analysis and Nomogram for Early Progression of COVID-19 Pneumonia in Older Adult Patients in the Omicron Era.Clinical interventions in aging · 2024Article
- Associated Biochemical and Hematological Markers in COVID-19 Severity Prediction.Advances in medicine · 2023Article
- Construction of a nomogram for predicting COVID-19 in-hospital mortality: A machine learning analysis.Informatics in medicine unlocked · 2023Article
- Outcomes of SARS-CoV-2 infection in Ph-neg chronic myeloproliferative neoplasms: results from the EPICOVIDEHA registry.Therapeutic advances in hematology · 2023Article
- Development and validation of a predicted nomogram for mortality of COVID-19: a multicenter retrospective cohort study of 4,711 cases in multiethnic.Frontiers in medicine · 2023Article
- Development and validation of prognostic scoring system for COVID-19 severity in South India.Irish journal of medical science · 2022Article
- Predicting In-Hospital Mortality in Severe COVID-19: A Systematic Review and External Validation of Clinical Prediction Rules.Biomedicines · 2022Article
- Heterogeneity and Risk of Bias in Studies Examining Risk Factors for Severe Illness and Death in COVID-19: A Systematic Review and Meta-Analysis.Pathogens (Basel, Switzerland) · 2022Review
- Clinical outcomes of geriatric patients with COVID-19: review of one-year data.Aging clinical and experimental research · 2022Article
- A nomogram prediction of outcome in patients with COVID-19 based on individual characteristics incorporating immune response-related indicators.Journal of medical virology · 2022Article
- Development and validation of nomogram to predict severe illness requiring intensive care follow up in hospitalized COVID-19 cases.BMC infectious diseases · 2021Article
- Prediction of COVID-19-related Mortality and 30-Day and 60-Day Survival Probabilities Using a Nomogram.Journal of Korean medical science · 2021Article
- Risk stratification scores for hospitalization duration and disease progression in moderate and severe patients with COVID-19.BMC pulmonary medicine · 2021Observational
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOne-fifth of COVID-19 patients are seriously and critically ill cases and have a worse prognosis than non-severe cases. Although there is no specific treatment available for COVID-19, early recognition and supportive treatment may reduce the mortality. The aim of this study is to develop a functional nomogram that can be used by clinicians to estimate the risk of in-hospital mortality in patients hospitalized and treated for COVID-19 disease, and to compare the accuracy of model predictions with previous nomograms.
methodsThis retrospective study enrolled 709 patients who were over 18 years old and received inpatient treatment for COVID-19 disease. Multivariable Logistic Regression analysis was performed to assess the possible predictors of a fatal outcome. A nomogram was developed with the possible predictors and total point were calculated.
resultsOf the 709 patients treated for COVID-19, 75 (11%) died and 634 survived. The elder age, certain comorbidities (cancer, heart failure, chronic renal failure), dyspnea, lower levels of oxygen saturation and hematocrit, higher levels of C-reactive protein, aspartate aminotransferase and ferritin were independent risk factors for mortality. The prediction ability of total points was excellent (Area Under Curve = 0.922).
conclusionsThe nomogram developed in this study can be used by clinicians as a practical and effective tool in mortality risk estimation. So that with early diagnosis and intervention mortality in COVID-19 patients may be reduced.
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