Original Research
Comparing Tests Assessing Protein-Energy Wasting: Relation With Quality of Life

https://doi.org/10.1053/j.jrn.2015.09.003Get rights and content

Objective

Protein-energy wasting (PEW), a state of decreased bodily protein and energy fuels, is highly prevalent among hemodialysis patients. The best method to determine PEW, however, remains debated. As an independent, negative association between PEW and quality of life (QOL) has been demonstrated, establishing which nutrition-related test correlates best with QOL may help to identify how PEW should preferably be assessed.

Design and Methods

Data were used from CONTRAST, a cohort of end-stage kidney disease patients. At baseline, Subjective Global Assessment (SGA), Malnutrition Inflammation Score (MIS), Geriatric Nutritional Risk Index, composite score on protein-energy nutritional status, normalized protein nitrogen appearance, body mass index, serum albumin, and serum creatinine were determined. QOL was assessed by the Kidney Disease Quality of Life Short Form 1.3. The present study reports on 2 general and 11 kidney disease–specific QOL scores. Spearman's rho (ρ) was calculated to determine correlations between nutrition-related tests and QOL domains. Twelve months after randomization, a sensitivity analysis was performed to test the robustness of the results.

Results

Of 714 patients, 489 representative subjects were available for analysis. All tests correlated with the Physical Component Score, except body mass index. Only SGA and MIS correlated significantly with the Mental Component Score. SGA correlated significantly with 10 of 11 kidney disease–specific QOL domains. The MIS not only correlated significantly with all (11) kidney disease–specific QOL domains but also with higher correlation coefficients.

Conclusion

Of the 8 investigated nutrition-related tests, only MIS correlates with all QOL domains (13 of 13) with the strongest associations.

Introduction

Many end-stage kidney disease patients need lifelong dialysis treatment. Despite continuous developments in dialysis techniques and improving knowledge concerning the uremic syndrome over the last decades,1 not only remains the life expectancy of these patients severely impaired but also is their quality of life (QOL) usually severely negatively affected in comparison to the general population.2, 3 Among others, QOL is influenced by appetite,4 quality of sleep,5 and nutritional status, i.e. protein-energy wasting (PEW).6, 7

The International Society of Renal Nutrition and Metabolism (ISRNM) introduced the term PEW in 2008 to determine the state of decreased bodily protein and energy fuels in chronic kidney disease patients. PEW appears to be highly prevalent among hemodialysis (HD) patients.8, 9 The following diagnostic criteria were proposed for this syndrome: (1) low blood chemistry (albumin, prealbumin, or cholesterol), (2) low or decreasing body mass, (3) low or decreasing muscle mass, and (4) low dietary intake.10 In the absence of a gold standard, however, the debate on how this syndrome should be assessed is ongoing.11, 12 Although randomized interventional trials are awaited, observational studies and experts suggest that patients suffering from PEW may benefit from supplementation of proteins and energy.13, 14, 15 In addition, a recent randomized trial showed that in patients with a low serum albumin concentration, help with patient-specific barriers such as cooking or improvement of nutritional knowledge resulted in increased serum albumin levels.16 Hence, it appears important to find a reliable way to identify PEW in these patients accurately and easily.

The quest for a gold standard has resulted in many clinical scoring lists, tools, and parameters to diagnose malnutrition or PEW. The most widely investigated clinical nutrition-related scoring lists are the 3-point scaled SGA17, 18 as well as its modified successors, such as the 7-point scaled SGA (SGA-7)19 and the Malnutrition Inflammation Score (MIS).20 Other clinical nutrition-related scoring lists that have been proposed to assess PEW include the Geriatric Nutritional Risk Index (GNRI)21 and the composite score on protein-energy nutritional status (cPENS).22 Furthermore, a number of more or less individual parameters have been associated with PEW, such as serum albumin,23 body mass index (BMI),24 and the normalized protein nitrogen appearance (nPNA) rate.25, 26

In short, presently, it is unknown how PEW can be determined best. With respect to mortality, we recently showed that serum albumin and MIS as markers for PEW predict mortality equally well.27 Besides an impaired life expectancy, a consequence of PEW is a decrease in QOL, as has been stated by the ISRNM in 2008.10 As such, it appears justified to assume that a preferred nutrition-related test should correlate with QOL. To contribute a piece of the puzzle in finding the preferred test to assess PEW, various nutrition-related tests are compared in their relation with various domains of QOL in the present study.

Section snippets

Methods

Various cross-sectional analyses were performed using data from the CONvective TRAnsport STudy (CONTRAST, NCT00205556). Details concerning the design and methods of this study are described elsewhere.28, 29 In brief, CONTRAST was a randomized controlled trial primarily evaluating the effect of postdilution online hemodiafiltration compared with low-flux HD on all-cause mortality and cardiovascular events. Seven hundred fourteen patients were enrolled between 2004 and 2010 in 29 dialysis centers

Demographical, Clinical, and Laboratory Characteristics

Baseline patient characteristics of the entire cohort (n = 714) and the investigated cohort (n = 489) are summarized in Table 1. No marked differences between these groups were observed, suggesting this cohort is a representative sample of the CONTRAST cohort. Patients excluded from the present analysis mostly had a missing nPNA value (n = 120) or lacked information on an MIS item (n = 125). In the investigated cohort, mean age was 63.3 ± 13.8 years. The majority was male (60.5%), and more than

Discussion

The present study investigated correlations between 8 well-established nutrition-related tests and QOL. We clearly demonstrated that of these nutrition-related tests, MIS correlates best with QOL. The other 7 tests had either no or an inferior relation with QOL. We know of no previous study comparing various nutrition-related tests using the correlations of these tests with QOL. From this study, 2 important conclusions can be drawn. First, MIS correlates best with QOL. This adds evidence toward

Practical Application

The present study shows that of the 8 investigated nutrition-related tests, MIS clearly correlates best with QOL. Not only did this score correlate with all (13 of 13) domains of QOL, it also has the highest correlation coefficients. This finding may help to identify the preferred test to assess PEW.

Acknowledgments

The authors are grateful to all staff and patients who participated in this project. Furthermore, they would like to thank Isabelle Chapdelaine for her support in the determination of nutrition-related scores.

CONTRAST (NCT00205556) was supported by a grant from the Dutch Kidney Foundation (Nierstichting Nederland, grant C02.2019) and unrestricted grants from Fresenius Medical Care NL, Gambro Lundia AB (Sweden), the Dr. E.E. Twiss Fund, Roche, the Netherlands, the International Society of

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    Financial Disclosure: The authors declare that they have no relevant financial interests.

    Support: See Acknowledgments on page 116.

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