METHODS: A cross-sectional study was conducted between January and December 2012. A total of 350 adult patients in a teaching hospital were screened for risk of malnutrition using 3-MinNS and Subjective Global Assessment (SGA). To assess interrater reliability, each patient was screened for risk of malnutrition using 3-MinNS by 2 different nurses on 2 different occasions within 24 hours after admission. To assess the validity of 3-MinNS, the level of risk of malnutrition identified by the nurses using 3-MinNS was compared with the risk of malnutrition as assessed by a dietitian using SGA within 48 hours after the patients' enrolment into the study. The sensitivity, specificity, and predictive values were calculated in detecting patients at risk of malnutrition. Interrater reliability was determined using κ statistics.
RESULTS: Using SGA, the estimated prevalence of moderate to severe malnutrition was 36.3% (127/350). There was 94% proportional agreement between 2 nurses using 3-MinNS, and interrater reliability was substantial (κ = 0.79, P < .001). The analysis showed that 3-MinNS had moderate sensitivity (61.4%-68.5%) but high specificity (95.1%).
CONCLUSIONS: The 3-MinNS is a reliable and valid screening tool for use by healthcare professionals for identifying newly admitted medical and surgical patients who are at risk of malnutrition.
METHODS: This cross-sectional study collected sociodemographic and clinical characteristics, stoma output, and dietary intake upon discharge, hospitalization, and readmission within 30 d of discharge.
RESULTS: A total of 29 participants were recruited, with 72.4% having moderate malnutrition risk. Patients who received partially hydrolyzed guar gum (PHGG) fiber reported lower stoma output with firmer output consistency than patients who received standard care (SC) (P < 0.05 and P < 0.01). Patients who received PHGG achieved higher energy, protein, and soluble fiber intake than did the SC group (P < 0.01) upon discharge. There was a significant inverse association between soluble fiber (PHGG fiber + dietary soluble fiber) intake and ileostomy output (r, -0.494; P = 0.006).
CONCLUSIONS: Partially hydrolyzed guar gum fiber acts as an agent to hold water, reduce the speed of gastrointestinal tract transit, increase effluent viscosity, and potentially decrease water losses. Supplementation with PHGG fiber appeared to minimize ileostomy output and improve clinical outcomes among postoperative ileostomy patients. This needs to be evaluated further with a randomized controlled trial to confirm this preliminary finding.
METHODS: This study used available under-five nutritional secondary data from the Demographic and Health Surveys performed in sub-Saharan African countries. The research used bagging, boosting, and voting algorithms, such as random forest, decision tree, eXtreme Gradient Boosting, and k-nearest neighbors machine learning methods, to generate the MVBHE model.
RESULTS: We evaluated the model performances in contrast to each other using different measures, including accuracy, precision, recall, and the F1 score. The results of the experiment showed that the MVBHE model (96%) was better at predicting malnutrition than the random forest (81%), decision tree (60%), eXtreme Gradient Boosting (79%), and k-nearest neighbors (74%).
CONCLUSIONS: The random forest algorithm demonstrated the highest prediction accuracy (81%) compared with the decision tree, eXtreme Gradient Boosting, and k-nearest neighbors algorithms. The accuracy was then enhanced to 96% using the MVBHE model. The MVBHE model is recommended by the present study as the best way to predict malnutrition in under-five children.