Moreover this poor nutritional status is associated with poorer outcomes[3]. .... Journal of human nutrition and dietetics : the official journal of the British Dietetic ...
Paediatric Chronic Kidney Disease – Identifying those at Risk from Malnutrition. M. Harmer*2,3,4, C.E. Anderson1, 3, 4, R.D. Gilbert2,3, 4, S Wootton,3, 4 1Nutrition and Dietetics, 2Child Health, 3 The Southampton Biomedical Research Centre (Nutrition), 4University Hospital Southampton NHS Foundation Trust and the University of Southampton. United Kingdom
BACKGROUND
Chronic Kidney Disease (CKD) is associated with poor nutritional status [1, 2]. Moreover this poor nutritional status is associated with poorer outcomes [3]. Identifying children who are at increased risk from malnutrition is difficult due to the heterogeneity of CKD populations, with varying aetiologies and timing of onset of disease, amongst others factors. In an attempt to easily identify those at risk of nutritional inadequacy, a number of screening tools have been developed for the paediatric population. Such tools are promoted to be routinely used in clinical practice, but have not been evaluated in children with CKD. METHODS and SUBJECTS
60 children aged 3 to 18 years with all-cause, all-treatment CKD were screened using four nutrition screening tools: Screening Tool for the Assessment of Malnutrition in Paediatrics (STAMP) [4]; Screening Tool for Risk On Nutritional Status and Growth (STRONGkids) [5]; Simple Paediatric Nutrition Risk Score (PNRS) [6]; and Paediatric Yorkhill Malnutrition Score (PYMS) [7] . For comparison, the degree of malnutrition was additionally assessed by anthropometry alone using World Health Organization International Classification of Diseases (ICD-10) criteria. RESULTS
A total of 60 children (40 males) with CKD were recruited with a mean age of 10.7 years. 46 children were conservatively managed, 10 had previously received renal transplant grafts, 3 were receiving 3-times-a-week haemodialysis and 1 child was receiving continuous ambulatory peritoneal dialysis. Mean values (with standard deviations) of height SDS, weight SDS and BMI SDS for the cohort were -1.19 (±1.53),-0.42 (±1.76), and 0.46 (±1.36), respectively. Inter-tool comparison demonstrated poor concordance between ICD-10 anthropometric definitions of malnutrition risk and all screening tools, and poor inter-tool agreement; with no 2 tools showing a Cohen’s kappa value of greater than 0.2.
DISCUSSION
•These data show that there is no concordance between malnutrition risk screening tool scores. Unfortunately, there is no gold standard for identifying those at risk from malnutrition, and therefore assessment of specific tools, such as those assessed in this study, can only be done through inter-tool comparison. •Although discrepancy is to be expected from tool, to be used as a clinically useful screening tool, they must be able to identify those at risk, and not miss individuals that require assessment / intervention. •False negative results in screening, means that we are missing an opportunity to optimise preventative care that could ultimately improve clinical outcome and health care costs to both the service and patients. •There is also potential to overestimate risk. STRONGkids and PRNS have pathology score components. As all of the study cohort have CKD, all were allocated an initial score, resulting in no children being identified as “low risk”; the tool has the potential not to stratify a population, and not be useful in allocating resources for those most in need. With limited specialist paediatric dietitian capacity, there is need for such stratification of risk. •Limitations of the screening tools contribute to the discordance with each other. For example: the PRNS tool does not have anthropometry included in the scoring matrix and the PYMS tool only includes BMI, and so although perhaps having poor linear growth, if appropriate weight-for-height, individuals are not identified as at increased nutritional risk. •The lack of concordance may mean that none of these tools contains the correct metrics for appropriate identification as none of the evaluated tools were specifically developed to stratify risk for the CKD population. •The KDOQI guidelines offer an initial framework to offer nutritional assessment, but is only a guide determined on degree of pathology (CKD stage). Those with a given CKD classification are heterogeneous in many characteristics; including known nutritional risk factors, such as anthropometric data and ability to take normal food. It is, therefore, unlikely that this approach alone is appropriate. •Tools, such as PYMS, that only ascribed value to low anthropometry values will fail to recognise those with increased adiposity. Malnutrition and stunting as defined by anthropometry is often only those under-weight or –height. Not only does an excess of intake of energy not ensure adequate supply of other nutrients [8], it is becoming increasingly recognised that over-nourishment reflects alternative malnutrition status. This is perhaps especially so for those with CKD who are known to be at risk of disease progression and increase in complications with obesity [9], which is becoming increasingly prevalent in end stage CKD populations across the UK and Europe [10]. CONCLUSION
Currently used screening tools are not adequate for stratifying nutritional risk in the paediatric CKD population, and standardised nutritional assessment is needed in order to identify those at risk, although inadequate resources for this are in place. Attention must be given to a identifying those at risk from nutritional inadequacy in children with CKD; including adiposity, with weight SDS, height SDS, and BMI SDS routinely collected as a good starting point. REFERENCES 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
Fouque D, Kalantar-Zadeh K, Kopple J, Cano N, Chauveau P, Cuppari L, Franch H, Guarnieri G, Ikizler TA, Kaysen G, Lindholm B, Massy Z, Mitch W, Pineda E, Stenvinkel P, Trevino-Becerra A, Wanner C (2008) A proposed nomenclature and diagnostic criteria for protein-energy wasting in acute and chronic kidney disease. Kidney international 73:391-398. Pupim LB, Cuppari L, Ikizler TA (2006) Nutrition and metabolism in kidney disease. Seminars in nephrology 26:134-157. Wong CS, Gipson DS, Gillen DL, Emerson S, Koepsell T, Sherrard DJ, Watkins SL, Stehman-Breen C (2000) Anthropometric measures and risk of death in children with end-stage renal disease. American journal of kidney diseases : the official journal of the National Kidney Foundation 36:811-819. McCarthy H, Dixon M, Crabtree I, Eaton-Evans MJ, McNulty H (2012) The development and evaluation of the Screening Tool for the Assessment of Malnutrition in Paediatrics (STAMP(c)) for use by healthcare staff. Journal of human nutrition and dietetics : the official journal of the British Dietetic Association 25:311-318. Hulst JM, Zwart H, Hop WC, Joosten KF (2010) Dutch national survey to test the STRONGkids nutritional risk screening tool in hospitalized children. Clinical nutrition (Edinburgh, Scotland) 29:106-111. Sermet-Gaudelus I, Poisson-Salomon AS, Colomb V, Brusset MC, Mosser F, Berrier F, Ricour C (2000) Simple pediatric nutritional risk score to identify children at risk of malnutrition. The American journal of clinical nutrition 72:64-70. Gerasimidis K, Keane O, Macleod I, Flynn DM, Wright CM (2010) A four-stage evaluation of the Paediatric Yorkhill Malnutrition Score in a tertiary paediatric hospital and a district general hospital. The British journal of nutrition 104:751-756. Gillis L, Gillis A (2005) Nutrient inadequacy in obese and non-obese youth. Canadian journal of dietetic practice and research : a publication of Dietitians of Canada = Revue canadienne de la pratique et de la recherche en dietetique : une publication des Dietetistes du Canada 66:237-242. Hsu CY, McCulloch CE, Iribarren C, Darbinian J, Go AS (2006) Body mass index and risk for end-stage renal disease. Annals of internal medicine 144:21-28. Bonthuis M, van Stralen KJ, Verrina E, Groothoff JW, Alonso Melgar A, Edefonti A, Fischbach M, Mendes P, Molchanova EA, Paripovic D, Peco-Antic A, Printza N, Rees L, Rubik J, Stefanidis CJ, Sinha MD, Zagozdzon I, Jager KJ, Schaefer F (2013) Underweight, overweight and obesity in paediatric dialysis and renal transplant patients. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 28 Suppl 4:iv195-iv204.
