PDF(Pubmed)
Abstract：
UNASSIGNED: There are no standardized assessment criteria for selecting nutritional risk screening tools or indicators to assess reduced muscle mass (RMM) in the Global Leadership Initiative on Malnutrition (GLIM) criteria. We aimed to compare the consistency of different GLIM criteria with Subjective Global Assessment (SGA) and protein-energy wasting (PEW).
UNASSIGNED: In this study, nutritional risk screening 2002 first four questions (NRS-2002-4Q), Nutritional Risk Screening 2002 (NRS-2002), Malnutrition Universal Screening Tool (MUST), and Mini-Nutritional Assessment Short-Form (MNA-SF) tools were used as the first step of nutritional risk screening for the GLIM. The RMM is expressed using different metrics. The SGA and PEW were used to diagnose patients and classify them as malnourished and non-malnourished. Kappa (κ) tests were used to compare the concordance between the SGA, PEW, and GLIM of each combination of screening tools.
UNASSIGNED: A total of 157 patients were included. Patients with Chronic kidney disease (CKD) stage 1-3 accounted for a large proportion (79.0%). The prevalence rates of malnutrition diagnosed using the SGA and PEW were 18.5% and 19.7%, respectively. The prevalence of GLIM-diagnosed malnutrition ranges from 5.1% to 37.6%, depending on the different screening methods for nutritional risk and the different indicators denoting RMM. The SGA was moderately consistent with the PEW (κ = 0.423, p < 0.001). The consistency among the GLIM, SGA, and PEW was generally low. Using the NRS-2002-4Q to screen for nutritional risk, GLIM had the best agreement with SGA and PEW when skeletal muscle index (SMI), fat-free mass index (FFMI), and hand grip strength (HGS) indicated a reduction in muscle mass (SGA: κ = 0.464, 95% CI 0.28-0.65; PEW: κ = 0.306, 95% CI 0.12-0.49).
UNASSIGNED: The concordance between the GLIM criteria and the SGA and PEW depended on the screening tool used in the GLIM process. The inclusion of RMM in the GLIM framework is important. The addition of HGS could further improve the performance of the GLIM standard compared to the use of body composition measurements.
UNASSIGNED: In this study, nutritional risk screening 2002 first four questions (NRS-2002-4Q), Nutritional Risk Screening 2002 (NRS-2002), Malnutrition Universal Screening Tool (MUST), and Mini-Nutritional Assessment Short-Form (MNA-SF) tools were used as the first step of nutritional risk screening for the GLIM. The RMM is expressed using different metrics. The SGA and PEW were used to diagnose patients and classify them as malnourished and non-malnourished. Kappa (κ) tests were used to compare the concordance between the SGA, PEW, and GLIM of each combination of screening tools.
UNASSIGNED: A total of 157 patients were included. Patients with Chronic kidney disease (CKD) stage 1-3 accounted for a large proportion (79.0%). The prevalence rates of malnutrition diagnosed using the SGA and PEW were 18.5% and 19.7%, respectively. The prevalence of GLIM-diagnosed malnutrition ranges from 5.1% to 37.6%, depending on the different screening methods for nutritional risk and the different indicators denoting RMM. The SGA was moderately consistent with the PEW (κ = 0.423, p < 0.001). The consistency among the GLIM, SGA, and PEW was generally low. Using the NRS-2002-4Q to screen for nutritional risk, GLIM had the best agreement with SGA and PEW when skeletal muscle index (SMI), fat-free mass index (FFMI), and hand grip strength (HGS) indicated a reduction in muscle mass (SGA: κ = 0.464, 95% CI 0.28-0.65; PEW: κ = 0.306, 95% CI 0.12-0.49).
UNASSIGNED: The concordance between the GLIM criteria and the SGA and PEW depended on the screening tool used in the GLIM process. The inclusion of RMM in the GLIM framework is important. The addition of HGS could further improve the performance of the GLIM standard compared to the use of body composition measurements.
摘要：
■在全球营养不良领导倡议（GLIM）标准中，没有选择营养风险筛查工具或指标来评估肌肉质量减少（RMM）的标准化评估标准。我们旨在比较不同GLIM标准与主观整体评估（SGA）和蛋白质能量消耗（PEW）的一致性。
■在这项研究中，2002年营养风险筛查前四个问题(NRS-2002-4Q)，营养风险筛查2002（NRS-2002），营养不良通用筛查工具（必须），和迷你营养评估简表（MNA-SF）工具被用作GLIM营养风险筛查的第一步。使用不同的度量来表示RMM。SGA和PEW用于诊断患者，并将其分类为营养不良和非营养不良。Kappa(κ)测试用于比较SGA之间的一致性，PEW,和GLIM的每个组合的筛选工具。
■共纳入157例患者。慢性肾脏病(CKD)1-3期患者占较大比例(79.0%)。使用SGA和PEW诊断的营养不良患病率分别为18.5%和19.7%，分别。GLIM诊断的营养不良的患病率从5.1%到37.6%不等。根据不同的营养风险筛查方法和不同的指标表示RMM。SGA与PEW中度一致(κ=0.423,p<0.001)。GLIM之间的一致性，SGA,PEW普遍较低。使用NRS-2002-4Q筛查营养风险，当骨骼肌指数（SMI）时，GLIM与SGA和PEW的一致性最好，无脂质量指数（FFMI），和手握力（HGS）表明肌肉质量减少（SGA：κ=0.464，95％CI0.28-0.65；PEW：κ=0.306，95％CI0.12-0.49）。
■GLIM标准与SGA和PEW之间的一致性取决于GLIM过程中使用的筛选工具。在GLIM框架中包含RMM非常重要。与使用身体组成测量相比,添加HGS可以进一步改善GLIM标准的性能。
■在这项研究中，2002年营养风险筛查前四个问题(NRS-2002-4Q)，营养风险筛查2002（NRS-2002），营养不良通用筛查工具（必须），和迷你营养评估简表（MNA-SF）工具被用作GLIM营养风险筛查的第一步。使用不同的度量来表示RMM。SGA和PEW用于诊断患者，并将其分类为营养不良和非营养不良。Kappa(κ)测试用于比较SGA之间的一致性，PEW,和GLIM的每个组合的筛选工具。
■共纳入157例患者。慢性肾脏病(CKD)1-3期患者占较大比例(79.0%)。使用SGA和PEW诊断的营养不良患病率分别为18.5%和19.7%，分别。GLIM诊断的营养不良的患病率从5.1%到37.6%不等。根据不同的营养风险筛查方法和不同的指标表示RMM。SGA与PEW中度一致(κ=0.423,p<0.001)。GLIM之间的一致性，SGA,PEW普遍较低。使用NRS-2002-4Q筛查营养风险，当骨骼肌指数（SMI）时，GLIM与SGA和PEW的一致性最好，无脂质量指数（FFMI），和手握力（HGS）表明肌肉质量减少（SGA：κ=0.464，95％CI0.28-0.65；PEW：κ=0.306，95％CI0.12-0.49）。
■GLIM标准与SGA和PEW之间的一致性取决于GLIM过程中使用的筛选工具。在GLIM框架中包含RMM非常重要。与使用身体组成测量相比,添加HGS可以进一步改善GLIM标准的性能。
