Cargando…

Nutritional Risk Assessment Scores Effectively Predict Mortality in Critically Ill Patients with Severe COVID-19

Background: Malnutrition predicts a worse outcome for critically ill patients. However, quick, easy-to-use nutritional risk assessment tools have not been adequately validated. Aims and Methods: The study aimed to evaluate the role of four biological nutritional risk assessment instruments (the Prog...

Descripción completa

Detalles Bibliográficos
Autores principales: Bodolea, Constantin, Nemes, Andrada, Avram, Lucretia, Craciun, Rares, Coman, Mihaela, Ene-Cocis, Mihaela, Ciobanu, Cristina, Crisan, Dana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9144143/
https://www.ncbi.nlm.nih.gov/pubmed/35631246
http://dx.doi.org/10.3390/nu14102105
_version_ 1784715976938356736
author Bodolea, Constantin
Nemes, Andrada
Avram, Lucretia
Craciun, Rares
Coman, Mihaela
Ene-Cocis, Mihaela
Ciobanu, Cristina
Crisan, Dana
author_facet Bodolea, Constantin
Nemes, Andrada
Avram, Lucretia
Craciun, Rares
Coman, Mihaela
Ene-Cocis, Mihaela
Ciobanu, Cristina
Crisan, Dana
author_sort Bodolea, Constantin
collection PubMed
description Background: Malnutrition predicts a worse outcome for critically ill patients. However, quick, easy-to-use nutritional risk assessment tools have not been adequately validated. Aims and Methods: The study aimed to evaluate the role of four biological nutritional risk assessment instruments (the Prognostic Nutritional Index—PNI, the Controlling Nutritional Status Score—CONUT, the Nutrition Risk in Critically Ill—NUTRIC, and the modified NUTRIC—mNUTRIC), along with CT-derived fat tissue and muscle mass measurements in predicting in-hospital mortality in a consecutive series of 90 patients hospitalized in the intensive care unit for COVID-19-associated ARDS. Results: In-hospital mortality was 46.7% (n = 42/90). Non-survivors had a significantly higher nutritional risk, as expressed by all four scores. All scores were independent predictors of mortality on the multivariate regression models. PNI had the best discriminative capabilities for mortality, with an area under the curve (AUC) of 0.77 for a cut-off value of 28.05. All scores had an AUC above 0.72. The volume of fat tissue and muscle mass were not associated with increased mortality risk. Conclusions: PNI, CONUT, NUTRIC, and mNUTRIC are valuable nutritional risk assessment tools that can accurately predict mortality in critically ill patients with COVID-19-associated ARDS.
format Online
Article
Text
id pubmed-9144143
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-91441432022-05-29 Nutritional Risk Assessment Scores Effectively Predict Mortality in Critically Ill Patients with Severe COVID-19 Bodolea, Constantin Nemes, Andrada Avram, Lucretia Craciun, Rares Coman, Mihaela Ene-Cocis, Mihaela Ciobanu, Cristina Crisan, Dana Nutrients Article Background: Malnutrition predicts a worse outcome for critically ill patients. However, quick, easy-to-use nutritional risk assessment tools have not been adequately validated. Aims and Methods: The study aimed to evaluate the role of four biological nutritional risk assessment instruments (the Prognostic Nutritional Index—PNI, the Controlling Nutritional Status Score—CONUT, the Nutrition Risk in Critically Ill—NUTRIC, and the modified NUTRIC—mNUTRIC), along with CT-derived fat tissue and muscle mass measurements in predicting in-hospital mortality in a consecutive series of 90 patients hospitalized in the intensive care unit for COVID-19-associated ARDS. Results: In-hospital mortality was 46.7% (n = 42/90). Non-survivors had a significantly higher nutritional risk, as expressed by all four scores. All scores were independent predictors of mortality on the multivariate regression models. PNI had the best discriminative capabilities for mortality, with an area under the curve (AUC) of 0.77 for a cut-off value of 28.05. All scores had an AUC above 0.72. The volume of fat tissue and muscle mass were not associated with increased mortality risk. Conclusions: PNI, CONUT, NUTRIC, and mNUTRIC are valuable nutritional risk assessment tools that can accurately predict mortality in critically ill patients with COVID-19-associated ARDS. MDPI 2022-05-18 /pmc/articles/PMC9144143/ /pubmed/35631246 http://dx.doi.org/10.3390/nu14102105 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bodolea, Constantin
Nemes, Andrada
Avram, Lucretia
Craciun, Rares
Coman, Mihaela
Ene-Cocis, Mihaela
Ciobanu, Cristina
Crisan, Dana
Nutritional Risk Assessment Scores Effectively Predict Mortality in Critically Ill Patients with Severe COVID-19
title Nutritional Risk Assessment Scores Effectively Predict Mortality in Critically Ill Patients with Severe COVID-19
title_full Nutritional Risk Assessment Scores Effectively Predict Mortality in Critically Ill Patients with Severe COVID-19
title_fullStr Nutritional Risk Assessment Scores Effectively Predict Mortality in Critically Ill Patients with Severe COVID-19
title_full_unstemmed Nutritional Risk Assessment Scores Effectively Predict Mortality in Critically Ill Patients with Severe COVID-19
title_short Nutritional Risk Assessment Scores Effectively Predict Mortality in Critically Ill Patients with Severe COVID-19
title_sort nutritional risk assessment scores effectively predict mortality in critically ill patients with severe covid-19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9144143/
https://www.ncbi.nlm.nih.gov/pubmed/35631246
http://dx.doi.org/10.3390/nu14102105
work_keys_str_mv AT bodoleaconstantin nutritionalriskassessmentscoreseffectivelypredictmortalityincriticallyillpatientswithseverecovid19
AT nemesandrada nutritionalriskassessmentscoreseffectivelypredictmortalityincriticallyillpatientswithseverecovid19
AT avramlucretia nutritionalriskassessmentscoreseffectivelypredictmortalityincriticallyillpatientswithseverecovid19
AT craciunrares nutritionalriskassessmentscoreseffectivelypredictmortalityincriticallyillpatientswithseverecovid19
AT comanmihaela nutritionalriskassessmentscoreseffectivelypredictmortalityincriticallyillpatientswithseverecovid19
AT enecocismihaela nutritionalriskassessmentscoreseffectivelypredictmortalityincriticallyillpatientswithseverecovid19
AT ciobanucristina nutritionalriskassessmentscoreseffectivelypredictmortalityincriticallyillpatientswithseverecovid19
AT crisandana nutritionalriskassessmentscoreseffectivelypredictmortalityincriticallyillpatientswithseverecovid19