Abstract
BackgroundMost 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).MethodsA 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.ResultsThe 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.ConclusionsHerein, 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.
Highlights
The novel beta coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in December 2019 in Wuhan, China and is the cause of the coronavirus disease 2019 (COVID-19) [1], that was acknowledged by the World Health Organization as a pandemic in March 2020 [2], and has challenged and overwhelmed all the healthcare systems around the world [3].Currently, the American continent is the epicenter of this pandemic, contributing with 51% of all new cases and 45% of all new deaths as reported in the first week of 2021 [4]
We recruited a cohort of 121 patients with COVID-19 confirmed by a positive polymerase chain reaction (PCR) for SARS-CoV-2 in nasopharyngeal swab who consecutively attended to the emergency department of the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, a reference hospital for patients with COVID-19 in Mexico from March to August, 2020
Prior to the initiation of medical treatment, a blood sample was drawn for the assessment of the following laboratory tests: complete blood count, glucose, blood urea nitrogen (BUN), creatinine, liver function tests, ultra-sensitive C-reactive protein (CRP), lactate dehydrogenase (LDH), creatine phosphokinase (CPK), troponin-I, thromboplastin time (TP), activated partial thromboplastin time, D-dimer, fibrinogen, and arterial blood gases
Summary
The novel beta coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in December 2019 in Wuhan, China and is the cause of the coronavirus disease 2019 (COVID-19) [1], that was acknowledged by the World Health Organization as a pandemic in March 2020 [2], and has challenged and overwhelmed all the healthcare systems around the world [3].Currently, the American continent is the epicenter of this pandemic, contributing with 51% of all new cases and 45% of all new deaths as reported in the first week of 2021 [4]. Current evidence suggests that besides the clinical risk factors related to COVID-19 severity, there are diverse immunological [7, 8], metabolic [9] and muscle [10] abnormalities that play a key role in disease severity. Diverse prognostic models for COVID-19 severity have been proposed, most of them only include limited immunological variables, with clinical, radiographic and laboratory features, without the incorporation of a comprehensive assessment of the wide COVID-19 spectrum of abnormalities. The aim of the present study was to create and validate a compound explanatory model including diverse clinical, immunological, metabolomic, and muscle atrophy variables to classify COVID-19 patients according to their disease severity and to predict adverse outcomes. The aim of this study was to unveil novel biological features to explain COVID-19 severity and prognosis (death and disease progression)
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