Author: Torres-Ruiz, Jiram; Pérez-Fragoso, Alfredo; Maravillas-Montero, José Luis; Llorente, Luis; MejÃa-DomÃnguez, Nancy R.; Páez-Franco, José Carlos; Romero-RamÃrez, Sandra; Sosa-Hernández, Victor Andrés; Cervantes-DÃaz, Rodrigo; Absalón-Aguilar, Abdiel; Nuñez-Aguirre, Miroslava; Juárez-Vega, Guillermo; Meza-Sánchez, David; Kleinberg-Bid, Ari; Hernández-Gilsoul, Thierry; Ponce-de-León, Alfredo; Gómez-MartÃn, Diana
Title: Redefining COVID-19 Severity and Prognosis: The Role of Clinical and Immunobiotypes Cord-id: 6m0juar0 Document date: 2021_9_8
ID: 6m0juar0
Snippet: BACKGROUND: Most of the explanatory and prognostic models of COVID-19 lack of a comprehensive assessment of the wide COVID-19 spectrum of abnormalities. The aim of this study was to unveil novel biological features to explain COVID-19 severity and prognosis (death and disease progression). METHODS: A predictive model for COVID-19 severity in 121 patients was constructed by ordinal logistic regression calculating odds ratio (OR) with 95% confidence intervals (95% CI) for a set of clinical, immuno
Document: BACKGROUND: Most of the explanatory and prognostic models of COVID-19 lack of a comprehensive assessment of the wide COVID-19 spectrum of abnormalities. The aim of this study was to unveil novel biological features to explain COVID-19 severity and prognosis (death and disease progression). METHODS: A predictive model for COVID-19 severity in 121 patients was constructed by ordinal logistic regression calculating odds ratio (OR) with 95% confidence intervals (95% CI) for a set of clinical, immunological, metabolomic, and other biological traits. The accuracy and calibration of the model was tested with the area under the curve (AUC), Somer’s D, and calibration plot. Hazard ratios with 95% CI for adverse outcomes were calculated with a Cox proportional-hazards model. RESULTS: The explanatory variables for COVID-19 severity were the body mass index (BMI), hemoglobin, albumin, 3-Hydroxyisovaleric acid, CD8+ effector memory T cells, Th1 cells, low-density granulocytes, monocyte chemoattractant protein-1, plasma TRIM63, and circulating neutrophil extracellular traps. The model showed an outstanding performance with an optimism-adjusted AUC of 0.999, and Somer’s D of 0.999. The predictive variables for adverse outcomes in COVID-19 were severe and critical disease diagnosis, BMI, lactate dehydrogenase, Troponin I, neutrophil/lymphocyte ratio, serum levels of IP-10, malic acid, 3, 4 di-hydroxybutanoic acid, citric acid, myoinositol, and cystine. CONCLUSIONS: Herein, we unveil novel immunological and metabolomic features associated with COVID-19 severity and prognosis. Our models encompass the interplay among innate and adaptive immunity, inflammation-induced muscle atrophy and hypoxia as the main drivers of COVID-19 severity.
Search related documents:
Co phrase search for related documents- absolute lymphocyte count and logistic regression model: 1, 2, 3, 4, 5, 6
- absolute number and academic practice: 1
- adequate number and logistic regression model: 1
- adipose tissue and liver function: 1, 2, 3
- liver function and logistic regression model: 1, 2, 3, 4, 5
- liver function test and logistic regression model: 1
Co phrase search for related documents, hyperlinks ordered by date