Nutrición Hospitalaria (Aug 2006)
Proceso INFORNUT®: validación de la fase de filtro -FILNUT- y comparación con otros métodos de detección precoz de desnutrición hospitalaria INFORNUT process: validation of the filter phase -FILNUT- and comparison with other methods for the detection of early hospital hyponutrition
Abstract
Introducción: El problema de la desnutrición hospitalaria afecta según las series entre un 30-50% de los pacientes ingresados. Esta alta prevalencia justifica la necesidad de su detección precoz al ingreso. Existen múltiples herramientas clásicas de cribaje que muestran limitaciones importantes en su aplicación sistemática en la práctica clínica habitual. Objetivos: Ver la relación entre desnutrición, detectada por nuestro método de cribaje, y mortalidad, estancia o reingresos. Asimismo analizar la relación entre desnutrición y prescripción de soporte nutricional. Comparar distintos métodos de cribaje nutricional al ingreso sobre una muestra aleatoria de pacientes hospitalizados. Validación del método INFORNUT para cribaje nutricional. Material y Métodos: En una fase previa al diseño del estudio se realizo un análisis retrospectivo con datos del año 2003 con el fin de conocer la situación de la desnutrición en el Hospital Virgen de la Victoria de Málaga, recogiendo datos del CMBD (Conjunto Mínimo Básico de Datos), analíticas de riesgo nutricional (filtro FILNUT) y prescripción de soporte nutricional. En la fase experimental se realizo un estudio de cohorte transversal con una muestra aleatoria de 255 pacientes en Mayo del 2004. Se realiza estudio antropométrico, Valoración Subjetiva Global (VSG), Mini-Nutritional Assessment (MNA) y Nutrtional Risk Screening (NRS), método de Gassull, CONUT® e INFORNUT. Las condiciones de filtro aplicadas por INFORNUT son: albúmina Introduction: According to several series, hospital hyponutrition involves 30-50% of hospitalized patients.The high prevalence justifies the need for early detection from admission. There several classical screening tools that show important limitations in their systematic application in daily clinical practice. Objectives: To analyze the relationship between hyponutrition, detected by our screening method, and mortality, hospital stay, or re-admissions. To analyze, as well, the relationship between hyponutrition and prescription of nutritional support. To compare different nutritional screening methods at admission on a random sample of hospitalized patients.Validation of the INFORNUT method for nutritional screening. Material and methods: In a previous phase from the study design, a retrospective analysis with data from the year 2003 was carried out in order to know the situation of hyponutrition in Virgen de la Victoria Hospital, at Malaga, gathering data from the MBDS (Minimal Basic Data Set), laboratory analysis of nutritional risk (FILNUT filter), and prescription of nutritional support. In the experimental phase, a cross-sectional cohort study was done with a random sample of 255 patients, on May of 2004. Anthropometrical study, Subjective Global Assessment (SGA), Mini-Nutritional Assessment (MNA), Nutritional Risk Screening (NRS), Gassull"s method,CONUT® and INFORNUT® were done. The settings of the INFORNUT filter were: albumin< 3.5 g/dL, and/or total proteins < 5 g/dL, and/or prealbumin < 18 mg/dL, with or without total lymphocyte count < 1.600 cells/mm3 and/or total cholesterol < 180 mg/dL. In order to compare the different methods, a gold standard is created based on the recommendations of the SENPE on anthropometrical and laboratory data. The statistical association analysis was done by the chi-squared test (a: 0.05) and agreement by the k index. Results: In the study performed in the previous phase, it is observed that the prevalence of hospital hyponutrition is 53.9%. One thousand six hundred and forty four patients received nutritional support, of which 66,9% suffered from hyponutrition. We also observed that hyponutrition is one of the factors favoring the increase in mortality (hyponourished patients 15.19% vs. non-hyponourished 2.58%), hospital stay (hyponourished patients 20.95 days vs. non-hyponourished 8.75 days), and re-admissions (hyponourished patients 14.30% vs. non-hyponourished 6%). The results from the experimental study are as follows: the prevalence of hyponutrition obtained by the gold standard was 61%, INFORNUT 60%. Agreement levels between INFORNUT, CONUT, and GASSULL are good or very good between them (k: 0.67 INFORNUT with CONUT, and k: 0.94 INFORNUT and GASSULL) and wit the gold standard (k: 0.83; k: 0.64 CONUT; k: 0.89 GASSULL). However, structured tests (SGA, MNA, NRS) show low agreement indexes with the gold standard and laboratory or mixed tests (Gassull), although they show a low to intermediate level of agreement when compared one to each other (k: 0.489 NRS with SGA). INFORNUT shows sensitivity of 92.3%, a positive predictive value of 94.1%, and specificity of 91.2%. After the filer phase, a preliminary report is sent, on which anthropometrical and intake data are added and a Nutritional Risk Report is done. Conclusions: Hyponutrition prevalence in our study (60%) is similar to that found by other authors. Hyponutrition is associated to increased mortality, hospital stay, and re-admission rate. There are no tools that have proven to be effective to show early hyponutrition at the hospital setting without important applicability limitations. FILNUT, as the first phase of the filter process of INFORNUT represents a valid tool: it has sensitivity and specificity for nutritional screening at admission. The main advantages of the process would be early detection of patients with risk for hyponutrition, having a teaching and sensitization function to health care staff implicating them in nutritional assessment of their patients, and doing a hyponutrition diagnosis and nutritional support need in the discharge report that would be registered by the Clinical Documentation Department. Therefore, INFORNUT would be a universal screening method with a good cost-effectiveness ratio.
