Malnutrition Screening Tools Are Not Sensitive Enough to Identify Older Hospital Patients with Malnutrition

Nutrients. 2023 Dec 17;15(24):5126. doi: 10.3390/nu15245126.

Abstract

This study evaluates the concurrent validity of five malnutrition screening tools to identify older hospitalized patients against the Global Leadership Initiative on Malnutrition (GLIM) diagnostic criteria as limited evidence is available. The screening tools Short Nutritional Assessment Questionnaire (SNAQ), Malnutrition Universal Screening Tool (MUST), Malnutrition Screening Tool (MST), Mini Nutritional Assessment-Short Form (MNA-SF), and the Patient-Generated Subjective Global Assessment-Short Form (PG-SGA-SF) with cut-offs for both malnutrition (conservative) and moderate malnutrition or risk of malnutrition (liberal) were used. The concurrent validity was determined by the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the level of agreement by Cohen's kappa. In total, 356 patients were included in the analyses (median age 70 y (IQR 63-77); 54% male). The prevalence of malnutrition according to the GLIM criteria without prior screening was 42%. The conservative cut-offs showed a low-to-moderate sensitivity (32-68%) and moderate-to-high specificity (61-98%). The PPV and NPV ranged from 59 to 94% and 67-86%, respectively. The Cohen's kappa showed poor agreement (k = 0.21-0.59). The liberal cut-offs displayed a moderate-to-high sensitivity (66-89%) and a low-to-high specificity (46-95%). The agreement was fair to good (k = 0.33-0.75). The currently used screening tools vary in their capacity to identify hospitalized older patients with malnutrition. The screening process in the GLIM framework requires further consideration.

Keywords: GLIM; diagnosis; older adults; screening; undernutrition.

MeSH terms

  • Aged
  • Female
  • Hospitals
  • Humans
  • Male
  • Malnutrition* / diagnosis
  • Malnutrition* / epidemiology
  • Mass Screening
  • Nutrition Assessment
  • Nutritional Status
  • Predictive Value of Tests

Grants and funding

This research received no external funding.