RESUMO
The global health community has recognized the role of food and nutrition in health maintenance and disease prevention. Undernutrition is an important problem in clinical circles but it is still not highly considered by specialists. It is well known the consequences of undernutrition on the immunological systems. Furthermore, the main consequences are an increase of morbidity-mortality rates, postoperative complications, length of stay and number of hospital early readmissions. These are all reasons to lead to increase health-care financial costs. The total assistance quality could be improved by the arrangement of an automatic detection system of undernutrition. In our hospital, we use the screening tool "CONtrolling NUTritional status" (CONUT). To measure albumin, the laboratory could use bromocresol green (BCG) and bromocresol purple (BCP) method. The aim of this study is to evaluate the CONNUT tool to classify patients using two different albumin methods to measure. MATERIAL AND METHODS: The albumin and cholesterol performed in Advia 2400 analyzer using bromocresol green and purple methods to measure albumin. The total lymphocytes performed in Advia 2120. We calculate CONNUT index and classify the patients based on nutritional status. When we classified our patients based on nutritional status (CONNUT), 28% were misclassified, almost in moderate and severe groups. This is very important because this tool generates a multidisciplinary action to the patient. Therefore, in the Clinical Laboratory we have to know the methods we use, the validity of these methods in future tools/index and the management and outcome of the patients.
