PATIENTS AND METHODS: CGA data was collected from 249 Asian patients aged 70 years or older. Nutritional risk was assessed based on the Nutrition Screening Initiative (NSI) checklist. Univariate and multivariate logistic regression analyses were applied to assess the association between patient clinical factors together with domains within the CGA and moderate to high nutritional risk. Goodness of fit was assessed using Hosmer-Lemeshow test. Discrimination ability was assessed based on the area under the receiver operating characteristics curve (AUC). Internal validation was performed using simulated datasets via bootstrapping.

RESULTS: Among the 249 patients, 184 (74%) had moderate to high nutritional risk. Multivariate logistic regression analysis identified stage 3-4 disease (Odds Ratio [OR] 2.54; 95% CI, 1.14-5.69), ECOG performance status of 2-4 (OR 3.04; 95% CI, 1.57-5.88), presence of depression (OR 5.99; 95% CI, 1.99-18.02) and haemoglobin levels <12 g/dL (OR 3.00; 95% CI 1.54-5.84) as significant independent factors associated with moderate to high nutritional risk. The model achieved good calibration (Hosmer-Lemeshow test's p = 0.17) and discrimination (AUC = 0.80). It retained good calibration and discrimination (bias-corrected AUC = 0.79) under internal validation.

METHODS: A cross-sectional study was conducted among 134 geriatric patients with a mean age of 68.9 ± 8.4 who stayed at acute care wards in Hospital Tuanku Ampuan Rahimah, Klang from July 2017 to August 2017. The SGA, MNA, and GNRI were administered through face-to-face interviews with all the participants who gave their consent. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the GNRI and MNA were analyzed against the SGA. Receiver-operating characteristic (ROC) curve analysis was used to obtain the area under the curve (AUC) and suitable optimal cutoff values for both the GNRI and MNA.

RESULTS: According to the SGA, MNA, and GNRI, 26.9%, 42.5%, and 44.0% of the participants were malnourished, respectively. The sensitivity, specificity, PPV, and NPV for the GNRI were 0.622, 0.977, 0.982, and 0.558, respectively, while those for the MNA were 0.611, 0.909, 0.932, and 0.533, respectively. The AUC of the GNRI was comparable to that of the MNA (0.831 and 0.898, respectively). Moreover, the optimal malnutrition cutoff value for the GNRI was 94.95.

METHODS: This is a prospective observational study involving patients from the orthopaedic oncology unit who were undergoing surgery. They were assessed with Patient Generated Subjective Global Assessment (PG-SGA), Malnutrition Screening Tool (MST) and 3-minute Nutritional Screening (3MinNS) questionnaires. Anthropometric data such as body mass index, mid upper arm circumference (MUAC) and blood parameters such as serum albumin, total lymphocyte count and haemoglobin were also investigated. Patients were then followed up for 3 months. Post-operative complications were divided into infectious and non-infectious groups. Length of stay and unplanned readmission were also documented.

RESULTS: Prevalence of malnutrition ranged from 13.3% to 45.8% under different nutritional assessment methods. Patients who were determined as malnourished were significantly associated with both infectious and non-infectious post-operative complications ( p < 0.001). PG-SGA and 3MinNS values were also significant in univariate and multivariate analysis, respectively. Low serum albumin (<35 g/L) was associated with post-operative infectious complications, especially surgical site infection ( p < 0.001), prolonged hospital stay ( p = 0.009) and unplanned readmission ( p = 0.017). 3MinNS and Charlson Comorbidity Index were predictive of non-infectious complications, whereas serum albumin and the presence of metastasis were predictive of infectious complications.