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Recommendations Summary

CKD: Nutrition Screening and Assessment: Usual-Care Statements (2020)

Click here to see the explanation of recommendation ratings (Strong, Fair, Weak, Consensus, Insufficient Evidence) and labels (Imperative or Conditional). To see more detail on the evidence from which the following recommendations were drawn, use the hyperlinks in the Supporting Evidence Section below.


  • Recommendation(s)

    CKD: Routine Nutrition Screening

    In adults with CKD 3-5D or posttransplantation, it is reasonable to consider routine nutrition screening at least biannually with the intent of identifying those at risk of protein-energy wasting (OPINION).

    Rating: Consensus
    Conditional

    CKD: Nutrition Screening Tools

    In adults with CKD 3-5D or posttransplantation, there is limited evidence to suggest the use of one tool over others for identifying those at risk of protein-energy wasting (2D).

    Rating: Weak
    Conditional

    CKD: Routine Nutrition Assessment

    In adults with CKD 3-5D or posttransplantation, it is reasonable that a registered dietitian nutritionist (RDN) or an international equivalent conduct a comprehensive nutrition assessment (including but not limited to appetite, history of dietary intake, biochemical data, anthropometric measurements, and nutrition-focused physical findings) at least within the first 90 days of starting dialysis, annually, or when indicated by nutrition screening or provider referral (OPINION).

    Rating: Consensus
    Conditional

    • Risks/Harms of Implementing This Recommendation

      There are no obvious risks or harms associated with these recommendations. 

    • Conditions of Application

      Nutrition assessment methods should be conducted by individuals trained to perform the respective method. Medical Nutrition Therapy requires individualization of nutrition care based on patient’s CKD stage, comorbidities, diet and lifestyle as well as patient preferences. Routine nutrition screening of adults diagnosed with CKD stages 1-5D should occur to allow for the identification and further assessment and treatment of nutritional concerns.

    • Potential Costs Associated with Application

      There are no obvious costs associated with these recommendations. 

    • Recommendation Narrative

      Optimal frequency of nutrition screening and assessment are not described in the literature, and, therefore, recommendations were based from expert opinion. 

      There are several nutrition screening mechanisms in clinical practice, but few are specific to CKD, and there are limited data on their validity and reliability.  Most of the existing tools focus on identification of malnutrition risk; only one currently screens for protein energy wasting (PEW). Regardless of the mechanism used, the nutritional assessment conducted subsequent to the screening should be comprehensive and include the routine monitoring of nutrition care outcomes. 

      COMPOSITE NUTRITIONAL INDICES:  SCREENING TOOLS

      Geriatric Nutrition Risk Index (GNRI)
      Three studies reported on the use of GNRI to assess nutritional status, including two validity/reliability studies (Beberashvili et al 2013, Yamada et al 2013) and one prediction study in MHD patients (de Roij van Zuijdewijn et al 2015). In one study, GNRI had the greatest area under curve  (using MIS as a reference) of the nutrition screening tools (Yamada et al 2013). GNRI showed a significantly negative correlation with the MIS (r=-0.67, P 0.0001), and the most accurate GNRI cutoff to identify a malnourished patient according to the MIS was 91.2. The GNRI’s sensitivity, specificity, and accuracy of a score of 91.2 in predicting malnutrition according to the MIS were 73%, 82%, and 79% respectively. Another study reported that GNRI had high inter-observer agreement score (k=0.98) and high intra-observer reproducibility (k=0.82) (Beberashvili et al 2013).

      In another study, GNRI was a significant predictor for mortality at 2.97 years (p<0.001) but had lower predictive value for all-cause mortality compared to MIS and albumin levels (de Roij van Zuijdewijn et al 2015).

      Malnutrition Universal Screening Tool/Malnutrition Screening Tool (MUST/MST)
      Two validity/reliability study reported on the use of MUST and MST tools to assess nutritional status in MHD patients (Yamada et al 2013, Lawson et al 2012). A study by Lawson et al, reported on the validity and reliability of both MUST and MST tool in MHD patients. The sensitivity of both the MUST and MST tool was low (53.8% for MUST; 48.7% for MST), indicating that they are not particularly sensitive at identifying individuals with malnutrition in this group, compared to SGA. Both tools have a high specificity (MUST=78.3%; MST=85.5%), so they are good at excluding individuals who are not malnourished. Reliability assessed by kappa was 0.58 for MUST (95% CI, 0.20 to 0.80) and 0.33 for MST (95% CI, 20.03 to 0.54). Both tools had an NPV or 60% and PPV for MUST was 73.7% and for MST was 78.7%.  Though these tools are not sensitive enough to identify all malnourished renal in-patients, they are still fairly reliable and related to other nutrition status markers. In Yamada, et al., the authors compared results from various malnutrition assessment tools to the reference standard of MIS. MUST and MST scores were both significantly associated with MIS (p<0.0001 for each). The ROC curves of the MUST and MST compared to MIS were the smallest of the tools measured, and sensitivity, specificity and accuracy to detect hypoalbuminemia were among the lowest of all tools considered, indicating these may not be the best tools to discriminate nutritional risk in patients on MHD.

      Mini-Nutrition Assessment (MNA)
      Four studies reported on the use of MNA to assess nutritional status in MHD patients, three were validity/reliability studies (Yamada et al 2013, Afsar et al 2006, Santin et al 2016) and one was a correlational study (Erdogan et al 2013). Afsar et al. reported on the reliability of MNA tool compared to SGA 3-point scale. The reliability coef?cients (alpha) for MNA was 0.93 (good degree of reproducibility). MNA might underestimate the nutritional status of patients on MHD who are not in an in?ammatory state. Hence, MNA may not be as reliable as SGA in detecting PEM in the MHD population. Erdogan et al. compared MNA to Bio-electrical Impedance Analysis (BIA), reported a significant correlation between MNA score and single frequency-BIA (r=0.2, p=0.045), muscle mass (r=0.382; p<0.001) and visceral fat ratio (r=0.270; p=0.007). Authors concluded BIA is not as sensitive as MNA to detect early effects of secondary causes for malnutrition.  Santin et al 2015, compared SGA (7-point), MIS, MNA-Short Form (MNA-SF) to handgrip strength (HGS), albumin, c-reactive protein (CRP), and skinfolds. SGA and MNA-SF had fair agreement (kappa=0.24; p<0.001). The worst agreement was found between MIS and MNA-SF (kappa=0.14, none to slight; p<0.004). Again, both SGA and MIS had good concurrent and predictive validity for CKD population, whereas MNA-SF validity results were more comparable to non-CKD elderly individuals. Yamada et al, compared MNA to other nutritional tools and reported that MNA had lower area under curve (0.73) than GNRI and Nutritional Risk Score but higher than MUST and MST.

      Nutrition Impact Symptoms (NIS)
      One validity study reported on the use of NIS score for identifying those at risk of malnutrition in patients on HD and concluded that NIS score is a useful nutrition screening tool for identifying who are at risk of malnutrition (Campbell et al 2013). NIS score >2 had the strongest predictive value for mortality and for predicting poor nutritional outcomes, behind the rating of malnourished by SGA. Concurrent validity indicated similar agreement between each of the malnutrition risk tools (patient-generated subjective global assessment (PG-SGA), an abbreviated PG-SGA and NIS). Serum albumin was negatively correlated with NIS (Spearman Rho= -0.161; p=0.018).

      Nutrition Screening Tool (NST)
      One validity study reported on the use of NST to assess nutritional status in PD patients. In this study, NST had a sensitivity of 0.84 (range: 0.74 to 0.94; p<0.05) and speci?city of 0.9 (range: 0.82 to 0.99; p<0.05) which is clinically acceptable (Bennett et al 2006).

      Renal Nutrition Screening Tool (R-NST)
      In another study by Xia et al in PD patients, the R-NST was compared to SGA-7 point scale (Xia et al 2016). Authors determined that the R-NST tool when compared to SGA- 7 point scale is valid to detect risk of malnutrition (sensitivity=97.3% (95% CI 90.7-99.7), specificity=74.4% (95% CI 57.9-87.0), PPV=88.0% (95% CI 79.0-94.1), NPV=93.6% (95% CI 78.6-99.2). These results indicate that R-NST is a good tool for identifying renal in-patients at risk of undernutrition.

      Protein Energy Wasting (PEW) score
      Two predictive studies reported on the use of PEW score to assess nutritional status. Leining and colleagues identified that SGA and albumin were significant predictors of mortality, but BMI, mid-arm muscle circumference (MAMC) and PEW score did not predict mortality at 24 months in PD patients (Leinig et al 2011). However, Moreau-Gaudry et al, a study conducted in patients on MHD recorded that PEW predicts survival. Each unit decrease in score was related with a 5-7% reduction in survival (p<0.01) (Moreau-Gaudry et al 2014). This score can be helpful in identifying subgroups of patients with a high mortality rate and recommend nutrition support.

    • Recommendation Strength Rationale

      The evidence supporting the recommendation on nutrition screening tools is based on Grade III/ Grade D evidence. The recommendations regarding frequency of nutrition screening and assessment are based on Consensus/expert opinion. 

    • Minority Opinions

      Consensus reached.