The SARS-CoV-2 pandemic has overwhelmed the treatment capacity of the health care systems during the highest viral diffusion rate. Patients reaching the emergency department had to be either hospitalized (inpatients) or discharged (outpatients). Still, the decision was taken based on the individual assessment of the actual clinical condition, without specific biomarkers to predict future improvement or deterioration, and discharged patients often returned to the hospital for aggravation of their condition. Here, we have developed a new combined approach of omics to identify factors that could distinguish coronavirus disease 19 (COVID-19) inpatients from outpatients.

A 'Multiomic' Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019

Levi, Riccardo;Garlanda, Cecilia;Voza, Antonio;Azzolini, Elena;Cecconi, Maurizio;Aghemo, Alessio
Membro del Collaboration Group
;
Brescia, Paola
Membro del Collaboration Group
;
Capucetti, Arianna
Membro del Collaboration Group
;
Carloni, Sara
Membro del Collaboration Group
;
Carnevale, Silvia
Membro del Collaboration Group
;
Lleo, Ana
Membro del Collaboration Group
;
Di Donato, Rachele
Membro del Collaboration Group
;
Digifico, Elisabeth
Membro del Collaboration Group
;
Ferrari, Valentina
Membro del Collaboration Group
;
Giugliano, Silvia
Membro del Collaboration Group
;
Lo Cascio, Antonino
Membro del Collaboration Group
;
Mozzarelli, Alessandro
Membro del Collaboration Group
;
My, Ilaria
Membro del Collaboration Group
;
Selmi, Carlo
Membro del Collaboration Group
;
Voza, Antonio
Membro del Collaboration Group
;
Mantovani, Alberto;Politi, Letterio S;Rescigno, Maria
2022-01-01

Abstract

The SARS-CoV-2 pandemic has overwhelmed the treatment capacity of the health care systems during the highest viral diffusion rate. Patients reaching the emergency department had to be either hospitalized (inpatients) or discharged (outpatients). Still, the decision was taken based on the individual assessment of the actual clinical condition, without specific biomarkers to predict future improvement or deterioration, and discharged patients often returned to the hospital for aggravation of their condition. Here, we have developed a new combined approach of omics to identify factors that could distinguish coronavirus disease 19 (COVID-19) inpatients from outpatients.
2022
AUC, area under the curve
CHI3L1
CHI3L1, chitinase 3-like-1
CI, confidence interval
COVID-19
COVID-19, coronavirus disease 19
DT, decision tree
ELISA, enzyme-linked immunosorbent assay
ESI, electrospray ionization
FDR, false discovery rate
IgG, immunoglobulin G
LR, logistic regression
Metabolome
Microbiota
PCA, principal component analysis
PTX3, pentraxin 3
RFE, recursive feature elimination
SVM, support vector machine
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11699/73232
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 11
  • ???jsp.display-item.citation.isi??? ND
social impact