ArticleJournal of translational internal medicine2021
Development and Validation of a Nomogram for Predicting the Disease Progression of Nonsevere Coronavirus Disease 2019.
Article in Journal of translational internal medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prognostic models in COVID-19 infection that predict severity: a systematic review.European journal of epidemiology · 2023Pooled it
- EV-Call 120: A new-generation emergency medical service system in China.Journal of translational internal medicine · 2024Article
- HB-EGF Plasmatic Level Contributes to the Development of Early Risk Prediction Nomogram for Severe COVID-19 Cases.Biomedicines · 2024Article
- Characteristics of the Severe Acute Respiratory Syndrome Coronavirus 2 Omicron BA.2 Subvariant in Jilin, China from March to May 2022.Journal of translational internal medicine · 2022Article
- NUTRIC Score Is Not Superior to mNUTRIC Score in Prediction of Mortality of COVID-19 Patients.International journal of clinical practice · 2022Article
- Ultrasound Assessment of the Rectus Femoris in Patients with Chronic Obstructive Pulmonary Disease Predicts Sarcopenia.International journal of chronic obstructive pulmonary disease · 2022Observational
- Resistin as a Systemic Inflammation-Related Biomarker for Sarcopenia in Patients With Chronic Obstructive Pulmonary Disease.Frontiers in nutrition · 2022Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesThe majority of coronavirus disease 2019 (COVID-19) cases are nonsevere, but severe cases have high mortality and need early detection and treatment. We aimed to develop a nomogram to predict the disease progression of nonsevere COVID-19 based on simple data that can be easily obtained even in primary medical institutions.
methodsIn this retrospective, multicenter cohort study, we extracted data from initial simple medical evaluations of 495 COVID-19 patients randomized (2:1) into a development cohort and a validation cohort. The progression of nonsevere COVID-19 was recorded as the primary outcome. We built a nomogram with the development cohort and tested its performance in the validation cohort.
resultsThe nomogram was developed with the nine factors included in the final model. The area under the curve (AUC) of the nomogram scoring system for predicting the progression of nonsevere COVID-19 into severe COVID-19 was 0.875 and 0.821 in the development cohort and validation cohort, respectively. The nomogram achieved a good concordance index for predicting the progression of nonsevere COVID-19 cases in the development and validation cohorts (concordance index of 0.875 in the development cohort and 0.821 in the validation cohort) and had well-fitted calibration curves showing good agreement between the estimates and the actual endpoint events.
conclusionsThe proposed nomogram built with a simplified index might help to predict the progression of nonsevere COVID-19; thus, COVID-19 with a high risk of disease progression could be identified in time, allowing an appropriate therapeutic choice according to the potential disease severity.
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