Prevalence of malnutrition in coronavirus disease 19: the NUTRICOV study

Br J Nutr. 2021 Nov 14;126(9):1296-1303. doi: 10.1017/S0007114520005127. Epub 2020 Dec 21.

Abstract

Recent European Society of Parenteral and Enteral Nutrition guidelines highlighted the interest of prevention, diagnosis and treatment of malnutrition in the management of coronavirus disease 19 (COVID-19) patients. The aim of our study was to evaluate the prevalence of malnutrition in patients hospitalised for COVID-19. In a prospective observational cohort study malnutrition was diagnosed according to the Global Leadership Initiative on Malnutrition (GLIM) two-step approach. Patients were divided into two groups according to the diagnosis of malnutrition. Covariate selection for the multivariate analysis was based on P <0·2 in univariate analysis, with a logistic regression model and a backward elimination procedure. A partitioning of the population was realised. Eighty patients were prospectively enrolled. Thirty patients (37·5 %) had criteria for malnutrition. The need for intensive care unit admission (n 46, 57·5 %) was similar in the two groups. Three patients who died (3·75 %) were malnourished. Multivariate analysis exhibited that low BMI (OR 0·83, 95 % CI 0·73, 0·96, P = 0·0083), dyslipidaemia (OR 29·45, 95 % CI 3·12, 277·73, P = 0·0031), oral intake reduction <50 % (OR 3·169, 95 % CI 1·04, 9·64, P = 0·0422) and glomerular filtration rate (Chronic Kidney Disease Epidemiology Collaboration; CKD-EPI) at admission (OR 0·979, 95 % CI 0·96, 0·998, P = 0·0297) were associated with the occurrence of malnutrition. We demonstrate the existence of a high prevalence of malnutrition in a general cohort of COVID-19 inpatients according to GLIM criteria. Nutritional support in COVID-19 care seems an essential element.

Keywords: COVID-19; European Society of Parenteral and Enteral Nutrition; Intensive care units; Malnutrition.

Publication types

  • Observational Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • COVID-19 / complications*
  • Female
  • Humans
  • Inpatients / statistics & numerical data*
  • Logistic Models
  • Male
  • Malnutrition / epidemiology*
  • Malnutrition / virology
  • Middle Aged
  • Nutrition Assessment
  • Prevalence
  • Prospective Studies
  • SARS-CoV-2*
  • Young Adult