Fluid overload has a very high predictive value for all-cause mortality and seems to be one of the major killers in the HD population. Patients might strongly benefit from active management of fluid overload.
Protein-energy malnutrition reduces the quality of life, lengthens the time in hospital and dramatically increases mortality. Currently there is no simple and objective method available for assessing nutritional status and identifying malnutrition. The aim of this work is to develop a novel assistance system that supports the physician in the assessment of the nutritional status. Therefore, three subject groups were investigated: the first group consisted of 688 healthy subjects. Two additional groups consisted of 707 patients: 94 patients with primary diseases that are known to cause malnutrition, and 613 patients from a hospital admission screening. In all subjects bioimpedance spectroscopy measurements were performed, and the body composition was calculated. Additionally, in all patients the nutritional status was assessed by the subjective global assessment score. These data are used for the development and validation of the assistance system. The basic idea of the system is that nutritional status is reflected by body composition. Hence, features of the nutritional status, based on the body composition, are determined and compared with reference ranges, derived from healthy subjects' data. The differences are evaluated by a fuzzy logic system or a decision tree in order to identify malnourished patients. The novel assistance system allows the identification of malnourished patients, and it can be applied for screening and monitoring of the nutritional status of hospital patients.
Bioimpedance measurements with the Body Composition Monitor (BCM) have been shown to improve fluid management in haemodialysis. However, there is a lack of a sufficiently robust evidence-base for use of the BCM outside of standard protocols. This study aims to characterise BCM measurement variation to allow users to make measurements and interpret the results with confidence in a range of clinical scenarios. BCM measurements were made in 48 healthy controls and in 48 stable haemodialysis patients before and immediately after dialysis. The effect of utilising alternative measurement paths was assessed using mixed effects models and the effect of measuring post-dialysis was assessed by comparing changes in BCM-measured overhydration (OH) with weight changes over dialysis. The data from healthy controls suggest that there is no difference in BCM-measured OH between all the whole-body paths other than the foot-to-foot measurement. Dialysis patients showed similar results other than having higher BCM-measured OH when measured across the site of a vascular access. There was good agreement between BCM-measured OH and change in weight, suggesting post-dialysis measurements can be utilised. These results suggest BCM protocols can be flexible regarding measurement paths and timing of measurement to ensure as many patients as possible can benefit from the technology.
This article aims to provide an overview of the different nutritional markers and the available methodologies for the physical assessment of nutrition status in hemodialysis patients, with special emphasis on early detection of protein energy wasting (PEW). Nutrition status assessment is made on the basis of anamnesis, physical examination, evaluation of nutrient intake, and on a selection of various screening/diagnostic methodologies. These methodologies can be subjective, e.g. the Subjective Global Assessment score (SGA), or objective in nature (e.g. bioimpedance analysis). In addition, certain biochemical tests may be employed (e.g. albumin, pre-albumin). The various subjective-based and objective methodologies provide different insights for the assessment of PEW, particularly regarding their propensity to differentiate between the important body composition compartments-fluid overload, fat mass and muscle mass. This review of currently available methods showed that no single approach and no single marker is able to detect alterations in nutrition status in a timely fashion and to follow such changes over time. The most clinically relevant approach presently appears to be the combination of the SGA method with the bioimpedance spectroscopy technique with physiological model and, additionally, laboratory tests for the detection of micro-nutrient deficiency.
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