• FluTrackers.com Inc. does not provide medical advice. Information on this web site is collected from various internet resources, and the FluTrackers board of directors makes no warranty to the safety, efficacy, correctness or completeness of the information posted on this site by any author or poster. The information collated here is for instructional and/or discussion purposes only and is NOT intended to diagnose or treat any disease, illness, or other medical condition. Every individual reader or poster should seek advice from their personal physician/healthcare practitioner before considering or using any interventions that are discussed on this website. By continuing to access this website you agree to consult your personal physican before using any interventions posted on this website, and you agree to hold harmless FluTrackers.com Inc., the board of directors, the members, and all authors and posters for any effects from use of any medication, supplement, vitamin or other substance, device, intervention, etc. mentioned in posts on this website, or other internet venues referenced in posts on this website.
  • We are not asking for any donations. Do not donate to any entity who says they are raising funds for us.

J Clin Med . Prediction of SARS-CoV-2-Related Lung Inflammation Spreading by V:ERITAS (Vanvitelli Early Recognition of Inflamed Thoracic Areas Sprea

tetano

Editor, Senior Moderator
J Clin Med


. 2022 Apr 26;11(9):2434.
doi: 10.3390/jcm11092434.
Prediction of SARS-CoV-2-Related Lung Inflammation Spreading by V:ERITAS (Vanvitelli Early Recognition of Inflamed Thoracic Areas Spreading)


Ciro Romano[SUP] 1 [/SUP], Domenico Cozzolino[SUP] 1 [/SUP], Giovanna Cuomo[SUP] 2 [/SUP], Marianna Abitabile[SUP] 1 [/SUP], Caterina Carusone[SUP] 1 [/SUP], Francesca Cinone[SUP] 1 [/SUP], Francesco Nappo[SUP] 1 [/SUP], Riccardo Nevola[SUP] 1 [/SUP], Ausilia Sellitto[SUP] 1 [/SUP], Annamaria Auricchio[SUP] 3 [/SUP], Francesca Cardella[SUP] 3 [/SUP], Giovanni Del Sorbo[SUP] 3 [/SUP], Eva Lieto[SUP] 3 [/SUP], Gennaro Galizia[SUP] 3 [/SUP], Luigi Elio Adinolfi[SUP] 1 [/SUP], Aldo Marrone[SUP] 1 [/SUP], Luca Rinaldi[SUP] 1 [/SUP]



Affiliations
Free article

Abstract

Background Coronavirus disease 2019 (COVID-19) can be complicated by interstitial pneumonia, possibly leading to severe acute respiratory failure and death. Because of variable evolution ranging from asymptomatic cases to the need for invasive ventilation, COVID-19 outcomes cannot be precisely predicted on admission. The aim of this study was to provide a simple tool able to predict the outcome of COVID-19 pneumonia on admission to a low-intensity ward in order to better plan management strategies for these patients. Methods The clinical records of 123 eligible patients were reviewed. The following variables were analyzed on admission: chest computed tomography severity score (CTSS), PaO[SUB]2[/SUB]/FiO[SUB]2[/SUB] ratio, lactate dehydrogenase (LDH), neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio, C-reactive protein (CRP), fibrinogen, D-dimer, aspartate aminotransferase (AST), alanine aminotransferase, alkaline phosphatase, and albumin. The main outcome was the intensity of respiratory support (RS). To simplify the statistical analysis, patients were split into two main groups: those requiring no or low/moderate oxygen support (group 1); and those needing subintensive/intensive RS up to mechanical ventilation (group 2). Results The RS intensity was significantly associated with higher CTSS and NLR scores; lower PaO[SUB]2[/SUB]/FiO[SUB]2[/SUB] ratios; and higher serum levels of LDH, CRP, D-dimer, and AST. After multivariate logistic regression and ROC curve analysis, CTSS and LDH were shown to be the best predictors of respiratory function worsening. Conclusions Two easy-to-obtain parameters (CTSS and LDH) were able to reliably predict a worse evolution of COVID-19 pneumonia with values of >7 and >328 U/L, respectively.

Keywords: COVID-19; CPAP; HFNC; OTI; pneumonia; risk prediction.
 
Back
Top Bottom