Nutritional status assessed by scored patient-generated subjective global assessment associated with length of hospital stay in adult patients receiving an appendectomy

Biomed J. 2014 Mar-Apr;37(2):71-7. doi: 10.4103/2319-4170.113183.


Background: Malnutrition has been associated with poor health outcomes in hospitalized patients. This study assessed the validity of the scored patient-generated subjective global assessment (PG-SGA) in adult patients who had undergone an open appendectomy, and examined the association of this assessment tool with length of hospital stay.

Methods: Nutritional status was determined by using the scored PG-SGA in adult patients (n = 86) who had undergone an open appendectomy within 24 hours of admission. Variables were compared between well-nourished and malnourished participants. Regression analysis was used to identify potential predictors for length of hospital stay. Receiver operator characteristic (ROC) analysis was used to examine the validity of the PG-SGA score to predict the nutritional status.

Results: On admission, 17% of the study subjects were malnourished and associated with a significantly older age (53.0 vs. 39.5), greater PG-SGA score (8 vs. 2), higher comorbidity (67% vs. 27%), and longer length of hospital stay (6.9 d vs. 4.1 d). The PG-SGA score and comorbidity were the determined risk factors for length of hospital stay after performing multiple regression analysis. Furthermore, the PG-SGA score had a significantly positive correlation with length of hospital stay (Spearman's rho = 0.378, p < 0.001). The area under the ROC curve indicating the PG-SGA score, compared with nutritional status, is 0.9751.

Conclusions: The scored PG-SGA in adults receiving an appendectomy is significantly associated with length of hospital stay, and is an effective tool for assessing the nutritional status of patients with cancer and chronic illness, as well as of patients with acute surgical abdomen.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Appendectomy* / adverse effects
  • Female
  • Hospitalization / statistics & numerical data*
  • Humans
  • Length of Stay*
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Nutrition Assessment*
  • Nutritional Status*
  • Surveys and Questionnaires