Department Experimental Medicine, Medical Physiopathology, Food Science and Endocrinology Section, Food Science and Human Nutrition Research Unit, Sapienza University of Rome, 00185 Roma, Italy.
Department of Medicine and Surgery, Unit of Metabolic Diseases & Clinical Dietetics, "Alma Mater Studiorum" University of Bologna, Italy.
Clin Nutr. 2014 Dec;33(6):1087-94. doi: 10.1016/j.clnu.2013.12.001. Epub 2013 Dec 14.
BACKGROUND & AIMS: Malnutrition (over and under-nutrition) is highly prevalent in patients admitted to hospital and it is a well-known risk factor for increased morbidity and mortality. Nutritional problems are often misdiagnosed, and especially the coexistence of over and undernutrition is not usually recognized. We aimed to develop and validate a screening tool for the easy detection and reporting of both undernutrition and overnutrition, specifically identifying the clinical conditions where the two types of malnutrition coexist.
The study consisted of three phases: 1) selection of an appropriate study population (estimation sample) and of the hospital admission parameters to identify overnutrition and undernutrition; 2) combination of selected variables to create a screening tool to assess the nutritional risk in case of undernutrition, overnutrition, or the copresence of both the conditions, to be used by non-specialist health care professionals; 3) validation of the screening tool in a different patient sample (validation sample).
Two groups of variables (12 for undernutrition, 7 for overnutrition) were identified in separate logistic models for their correlation with the outcome variables. Both models showed high efficacy, sensitivity and specificity (overnutrition, 97.7%, 99.6%, 66.6%, respectively; undernutrition, 84.4%, 83.6%, 84.8%). The logistic models were used to construct a two-faced test (named JaNuS - Just A Nutritional Screening) fitting into a two-dimension Cartesian coordinate graphic system. In the validation sample the JaNuS test confirmed its predictive value. Internal consistency and test-retest analysis provide evidence for the reliability of the test.
The study provides a screening tool for the assessment of the nutritional risk, based on parameters easy-to-use by health care personnel lacking nutritional competence and characterized by excellent predictive validity. The test might be confidently applied in the clinical setting to determine the importance of malnutrition (including the copresence of over and undernutrition) as a risk factor for morbidity and mortality.
营养不良（营养不足和营养过剩）在住院患者中非常普遍，是发病率和死亡率增加的已知危险因素。营养问题经常被误诊，特别是营养不足和营养过剩同时存在的情况通常没有被识别。我们旨在开发和验证一种简便的筛查工具，用于检测和报告营养不足和营养过剩，并特别确定两种类型的营养不良同时存在的临床情况。
该研究包括三个阶段：1）选择合适的研究人群（估计样本）和住院参数，以确定营养过剩和营养不足；2）结合选定的变量，创建一种筛查工具，以评估非专业医疗保健人员在营养不足、营养过剩或两种情况并存时的营养风险；3）在不同的患者样本（验证样本）中验证筛查工具。
在单独的逻辑回归模型中，确定了两组变量（营养不足 12 个，营养过剩 7 个）与结局变量相关。两个模型都显示出高效、高灵敏度和高特异性（营养过剩分别为 97.7%、99.6%、66.6%；营养不足分别为 84.4%、83.6%、84.8%）。逻辑回归模型用于构建两面测试（命名为 JaNuS-Just A Nutritional Screening），适合于二维笛卡尔坐标图形系统。在验证样本中，JaNuS 测试证实了其预测价值。内部一致性和测试-重测分析为测试的可靠性提供了证据。
本研究提供了一种基于易于医疗保健人员使用且具有优异预测有效性的参数的营养风险评估筛查工具。该测试可在临床环境中自信地应用，以确定营养不良（包括营养过剩和营养不足同时存在）作为发病率和死亡率风险因素的重要性。
