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1.
Int J Mol Sci ; 21(22)2020 Nov 16.
Article in English | MEDLINE | ID: covidwho-927563

ABSTRACT

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread to nearly every continent, registering over 1,250,000 deaths worldwide. The effects of SARS-CoV-2 on host targets remains largely limited, hampering our understanding of Coronavirus Disease 2019 (COVID-19) pathogenesis and the development of therapeutic strategies. The present study used a comprehensive untargeted metabolomic and lipidomic approach to capture the host response to SARS-CoV-2 infection. We found that several circulating lipids acted as potential biomarkers, such as phosphatidylcholine 14:0_22:6 (area under the curve (AUC) = 0.96), phosphatidylcholine 16:1_22:6 (AUC = 0.97), and phosphatidylethanolamine 18:1_20:4 (AUC = 0.94). Furthermore, triglycerides and free fatty acids, especially arachidonic acid (AUC = 0.99) and oleic acid (AUC = 0.98), were well correlated to the severity of the disease. An untargeted analysis of non-critical COVID-19 patients identified a strong alteration of lipids and a perturbation of phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, aminoacyl-tRNA degradation, arachidonic acid metabolism, and the tricarboxylic acid (TCA) cycle. The severity of the disease was characterized by the activation of gluconeogenesis and the metabolism of porphyrins, which play a crucial role in the progress of the infection. In addition, our study provided further evidence for considering phospholipase A2 (PLA2) activity as a potential key factor in the pathogenesis of COVID-19 and a possible therapeutic target. To date, the present study provides the largest untargeted metabolomics and lipidomics analysis of plasma from COVID-19 patients and control groups, identifying new mechanisms associated with the host response to COVID-19, potential plasma biomarkers, and therapeutic targets.


Subject(s)
Coronavirus Infections/metabolism , Metabolome , Pneumonia, Viral/metabolism , Aged , Aged, 80 and over , Amino Acids/blood , Arachidonic Acid/blood , Biomarkers/blood , COVID-19 , Citric Acid Cycle , Coronavirus Infections/blood , Coronavirus Infections/pathology , Female , Gluconeogenesis , Humans , Male , Middle Aged , Oleic Acid/blood , Pandemics , Phosphatidylcholines/blood , Phosphatidylethanolamines/blood , Phospholipases A2/blood , Pneumonia, Viral/blood , Pneumonia, Viral/pathology , Triglycerides/blood
2.
Minerva Med ; 112(1): 118-123, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-890935

ABSTRACT

BACKGROUND: The Novara-COVID score was developed to help the emergency physician to decide which Coronavirus disease (COVID) patient required hospitalization at Emergency Department (ED) presentation and to which intensity of care. We aimed at evaluating its prognostic role. METHODS: We retrospectively collected data of COVID patients admitted to our ED between March 16 and April 22, 2020. The Novara-COVID score was systematically applied to all COVID patients since its introduction in clinical practice and adopted to decide patients' destination. The ability of the Novara-COVID score to predict in-hospital clinical stability and in-hospital mortality were evaluated through multivariable logistic regression and cox regression hazard models, respectively. RESULTS: Among the 480 COVID patients admitted to the ED, 338 were hospitalized: the Novara-COVID score was 0-1 in 49.7%, 2 in 24.6%, 3 in 15.4% and 4-5 in 10.3% of patients. Novara-COVID score values of 3 and 4-5 were associated with lower clinical stability with adjusted odds ratios of 0.28 (0.13-0.59) and 0.03 (0.01-0.12), respectively. When in-hospital mortality was evaluated, a significant difference emerged between scores of 0-1 and 2 vs. 3 and 4-5. In particular, the death adjusted hazard ratio for Novara-COVID scores of 3 and 4-5 were 2.6 (1.4-4.8) and 8.4 (4.7-15.2), respectively. CONCLUSIONS: The Novara-COVID score reliably predicts in-hospital clinical instability and mortality of COVID patients at ED presentation. This tool allows the emergency physician to detect patients at higher risk of clinical deterioration, suggesting a more aggressive therapeutic management from the beginning.


Subject(s)
COVID-19/mortality , Emergency Service, Hospital/statistics & numerical data , Hospital Mortality , Hospitalization/statistics & numerical data , SARS-CoV-2 , Severity of Illness Index , Adult , Age Factors , Aged , Aged, 80 and over , COVID-19/classification , COVID-19/physiopathology , Clinical Deterioration , Comorbidity , Female , Humans , Intensive Care Units , Logistic Models , Male , Middle Aged , Oxygen Consumption , Patient Readmission/statistics & numerical data , Proportional Hazards Models , Reproducibility of Results , Respiratory Rate , Retrospective Studies , Sex Factors , Triage/methods
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