Malnutrition screening tools for patients recovering from Covid-19
- What malnutrition screening tools are best for use with patients recovering from Covid-19 in acute and community settings?
- Has any data been published to show that these are effective in screening accurately for malnutrition?
- Is there any potential for under-over diagnosis been reported with existing screening tools?
Clinical guidelines endorse use of validated tools for screening patients with or recovering from COVID-19. These guidelines also endorse the GLIM two-step approach where screening is first conducted to identify those at high risk of malnutrition and further assessment is conducted for those identified at risk of malnutrition. Guidelines and literature on malnutrition screening tools are often focused on acutely ill COVID-19 patients. MUST is commonly recommended for use in the community setting but guidelines suggest that various validated tools can be used.
The effectiveness of malnutrition screening tools considers a range of factors: how sensitive and specific the tools are as well as how well they perform compared to other validated measures and how well they predict patient outcomes. Within COVID-19 patients, the literature is limited. Many of the tools were found to have high sensitivity including the NRS-2002, MNA-SF, and MUST. This suggests that the tools are unlikely to miss those at risk of malnutrition. MUST may be slightly less sensitive but may be more specific – that is, it would be less likely to incorrectly identify someone as being at risk of malnutrition. However, the COVID-19 and broader literature on the utility of the nutrition screening tools is considered low quality and studies provide mixed estimates of their effectiveness.
Nutritional biomarkers have also been suggested to provide valid estimates of malnutrition. An additional consideration is the extent to which screening tools can be used remotely in the community setting. Practices for remote screening have been developed and recommended but the effectiveness of these approaches requires further evaluation.
The content of this document is correct as of 31/05/2021.