Patient-Generated Subjective Global Assessment Short Form better predicts length of stay than Short Nutritional Assessment Questionnaire

Priya Dewansingh*, Margreet Euwes, Wim P Krijnen, Jaap H Strijbos, Cees P van der Schans, Harriët Jager-Wittenaar

*Corresponding author for this work

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OBJECTIVE: Malnutrition screening instruments used in hospitals mainly include criteria to identify characteristics of malnutrition. However, to tackle malnutrition in an early stage, identifying risk factors for malnutrition in addition to characteristics may be valuable. The aim of this study was to determine the predictive validity of the Patient-Generated Subjective Global Assessment (PG-SGA SF), which addresses malnutrition characteristics and risk factors, and the Short Nutritional Assessment Questionnaire (SNAQ), which addresses mainly malnutrition characteristics, for length of stay (LOS) in a mixed hospital population.

METHODS: Patients (N = 443) were screened with the PG-SGA SF and SNAQ in the first 72 h after admission to the lung, cardiology, or surgery ward. The McNemar-Bowker test was used to investigate the symmetry between the SNAQ and PG-SGA SF categorization for low, medium, and high risk. The predictive value of the PG-SGA SF and SNAQ was assessed by γ-regression before and after adjusting for several confounders.

RESULTS: Of the 443 patients included, 23% and 58% were categorized as being at medium/high risk for malnutrition according to the SNAQ and PG-SGA SF, respectively. The regression analysis indicated that LOS of high-risk patients according to PG-SGA SF was 36% longer than that of low-risk patients (P = 0.001). LOS in patients at high risk according to the SNAQ did not significantly differ from that of SNAQ low-risk patients.

CONCLUSIONS: The PG-SGA SF, as a proactive malnutrition screening instrument, predicts LOS in various hospital wards, whereas the SNAQ, as a reactive instrument, does not. Therefore, we recommend the PG-SGA SF for proactive screening for malnutrition risk.

Original languageEnglish
Article number111366
Number of pages8
Publication statusPublished - Nov-2021

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