Nutrition
-
Malnutrition in stroke is associated with poor clinical outcomes. Bioelectrical impedance analysis-derived phase angle (PhA) is widely used for assessing nutritional status as an index of muscle quality. This study aimed to evaluate the associations between whole body and limb PhAs and nutritional risk in stroke patients. PhA predictors were also identified. ⋯ In stroke patients, low PhA values were associated with high nutritional risk. PhA at the beginning of rehabilitation may serve as a reliable parameter to be considered in the evaluation of nutritional status.
-
It is important to cover energy targets among patients with head and neck cancer (HNC) to minimize weight and skeletal muscles loss. This study aimed to assess the agreement between indirect calorimetry (IC) and predictive equations for determining resting energy expenditures (REE) in HNC patients receiving home enteral nutrition (HEN). ⋯ The predictive equations examined in this study cannot replace IC for determining REE in HNC patients at the individual level. When equations are used, special attention should be given to planning HEN to account for possible discrepancies between pREE and mREE.
-
The COntrolling NUTritional Status (CONUT) score and the Global Nutrition Risk Index (GNRI) are screening tools for assessing the risk of malnutrition based on widely available biochemical parameters. The primary objective of this study was to investigate the predictive value of CONUT and GNRI score on 36 months mortality and hospitalization risk in hospitalized older patients. ⋯ The CONUT score seems a valid tool to predict long-term mortality and hospitalization risk. Conversely, the GNRI is associated with long-term mortality, but not with hospital readmissions.
-
Although the effects of an unhealthy diet on the risks of diabetes and its renal complications are well understood, the effects of hygiene status have not been fully elucidated. ⋯ Gut microbial dysbiosis, owing to the combined effects of inappropriate diet and excessive hygiene, accompanied by lower intestinal SCFA production, may contribute to the development and/or progression of diabetes and diabetic kidney disease through the induction of inflammation and fibrosis.
-
Malnutrition, particularly wasting, continues to be a significant public health issue among children under five years in Egypt. Despite global advancements in child health, the prevalence of wasting remains a critical concern. This study employs machine learning techniques to identify and analyze the determinants of wasting in this population. ⋯ Machine learning techniques, particularly XGBoost, show significant potential for improving the classification of nutritional status and addressing wasting among children in Egypt. However, the limitations in simpler models highlight the need for further research to refine predictive tools and develop targeted interventions. Addressing the identified determinants of wasting can contribute to more effective public health strategies.