Nutritional risk assessment using Malnutrition Universal Screening Tool (MUST) in COVID-19 patients: An observational study in a tertiary care hospital in Eastern India

  1. Sudeshna Maitra Nag
  2. Subhrojyoti Bhowmick
  3. Sayantani Bhowmick
  4. Uttiya Deb
  5. Debarati Kundu
  6. Krishnangshu Ray
  7. Sujit Kar Purkayastha

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Abstract

Aims

To diagnose malnutrition, the nutritional status of each infected patient should be evaluated before starting general treatment. The role of Malnutrition Universal Screening Tool (MUST) in evaluating nutritional status of COVID-19 patients is still unknown. The aim of this study was to evaluate the use of MUST in assessment of nutritional status of COVID-19 patients.

Methods

We retrospectively analyzed the data of hospitalized COVID-19 patients above 18 years of age from July 25 th to September 25 th , 2020. All COVID-19 patients with a length of hospital stay greater than 24 hours underwent malnutrition screening and nutritional assessment based upon MUST. Demographic data, laboratory parameters and MUST score were retrieved from case files.

Results

Out of 106 COVID-19 patients included in the study, 68 (64%) were male and 38 (36%) were female. Number of deaths due to COVID-19 was 17 (16.03%). A total of 22 (20.75%) patients had MUST score of 2 and above. Analysis between MUST score and age group showed statistically significant result (p=0.012). MUST score according to clinical outcome at the end of hospitalization was also statistically significant (p<0.001).

Conclusion

Our results highlight a possible role of MUST as screening tool for malnutrition in COVID-19 patients.

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  1. ScreenIT

    SciScore for 10.1101/2021.07.21.21260904: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: The institutional ethics committee approved the proposal of this study.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analysis was done using IBM SPSS 21.0 software and Microsoft Office Excel 2007.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    Microsoft Office Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The limitations of this study are small sample size and retrospective observational study design. Randomized controlled studies with larger sample sizes are required to determine whether MUST can effectively assess nutritional risk in COVID-19 patients.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.07.21.21260904v1 on medRxiv