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Abstract
Background: Protein‑energy wasting (PEW) is a multifactorial complication in children with chronic kidney disease (CKD), leading to growth failure, poor quality of life, and increased mortality. However, routine nutritional assessment often lacks predictive tools and integrated management strategies.
Objective: To develop a predictive model for nutritional deterioration in children with CKD stages 3‑5D and to evaluate the efficacy of a targeted, multi‑component nutritional intervention protocol at the Children's National Medical Center.
Methods: A prospective cohort study (January 2022 – December 2025) enrolled 154 children with CKD (7‑17 years, stages 3‑5D). Comprehensive assessment included anthropometry, bioelectrical impedance analysis (BIA), dietary records, and serum biomarkers. A multivariate logistic regression model was developed to predict weight‑for‑height decline (≥0.5 SD over 12 months). High-risk patients (n=72) were allocated to either the intervention or standard care group based on consent and logistical feasibility.” to a 12‑month intensive Nutritional Optimization Protocol (NOP) or standard care.
Results: “The baseline prevalence of PEW was 38.3%.”
The final predictive model included dialysis vintage >12 months (OR=4.21), low phase angle (PhA<5°) (OR=3.84), energy intake <80% (OR=3.52), low leptin (OR=2.93), and frequent hospitalizations (OR=2.71); AUC‑ROC=0.89. After 12 months, the NOP group showed significant improvements vs. controls: weight‑for‑height Z‑score (+0.42 vs. −0.11, p<0.001), mid‑upper arm circumference (+1.8 vs. +0.3 cm, p<0.001), serum albumin (+0.35 vs. +0.05 g/dL, p=0.003), and a 32% reduction in hospitalization days. Phase angle <4.5° predicted low prealbumin with 85% sensitivity and 78% specificity.
Conclusion: A validated predictive model using clinical, dietary, and BIA parameters enables early identification of children at risk for PEW. A multi‑modal, individualized nutritional intervention significantly improves nutritional status and reduces hospitalizations, supporting its integration into routine care at the Children's National Medical Center
Keywords:
pediatric chronic kidney disease, protein energy wasting, nutritional assessment, predictive model.
References
GBD Chronic Kidney Disease Collaboration. Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2020;395(10225):709-733.DOI: 10.1016/S0140-6736(20)30045-3
Rees L, Shaw V. Nutrition in children with chronic kidney disease. Pediatr Nephrol. 2021;36(10):3079-3091. DOI: 10.1007/s00467-021-04922-y
Mak RH, Cheung WW, Hazzard P. Protein-energy wasting in children with chronic kidney disease. J Ren Nutr. 2019;29(4):276-280. DOI: 10.1053/j.jrn.2018.09.006
Kopple JD. Pathophysiology of protein-energy wasting in chronic renal failure. J Nutr. 1999;129(1 Suppl):247S-251S. DOI: 10.1093/jn/129.1.247S
Ikizler TA. Protein and energy intake in advanced chronic kidney disease: how much is too much? Semin Dial. 2018;31(5):473-478. DOI: 10.1111/sdi.12706
Mitch WE, Goldberg AL. Mechanisms of muscle wasting. The role of the ubiquitin-proteasome pathway. N Engl J Med. 1996;335(25):1897-1905. DOI: 10.1056/NEJM199612193352507
Ikizler TA, Hakim RM. Nutrition in end-stage renal disease. Kidney Int. 1996;50(2):343-357. DOI: 10.1038/ki.1996.348
Fouque D, Kalantar-Zadeh K, Kopple J, et al. A proposed nomenclature and diagnostic criteria for protein-energy wasting in acute and chronic kidney disease. Kidney Int. 2008;73(4):391-398. DOI: 10.1038/sj.ki.5002585
Rees L, Mak RH. Nutrition and growth in children with chronic kidney disease. Nat Rev Nephrol. 2011;7(11):615-623.DOI: 10.1038/nrneph.2011.137
Foster BJ, Leonard MB. Measuring nutritional status in children with chronic kidney disease. Am J Clin Nutr. 2004;80(4):801-814. DOI: 10.1093/ajcn/80.4.801
Windt F, Vogt L, Feldt-Rasmussen B, et al. Bioelectrical impedance analysis in children with chronic kidney disease. Pediatr Nephrol. 2018;33(8):1329-1338. DOI: 10.1007/s00467-017-3858-2
Nightingale S, Taal MW, Tattersall J, et al. Assessment of nutritional status in children with chronic kidney disease using bioelectrical impedance analysis. Pediatr Nephrol. 2022;37(2):385-394. DOI: 10.1007/s00467-021-05176-4
Wesseling-Perry K, Salusky IB. Chronic kidney disease: mineral and bone disorder in children. Semin Nephrol. 2013;33(2):169-179. DOI: 10.1016/j.semnephrol.2012.12.011
Abraham AG, Mak RH, Mitsnefes M, et al. Protein energy wasting in children with chronic kidney disease. Pediatr Nephrol. 2014;29(7):1231-1238. DOI: 10.1007/s00467-013-2723-2
Müller D, Zimmering M, Chan CT, McFarlane PA, Klarenbach S. Nutritional management in children with chronic kidney disease: a systematic review and meta-analysis. Kidney Int Rep. 2021;6(10):2558-2571. DOI: 10.1016/j.ekir.2021.07.021Chronic Kidney Disease
Kayumov A, Khasanov A, Mirkhaitov U. Clinical and epidemiological characteristics of chronic kidney disease in children in the Republic of Uzbekistan. Central Asian J Med. 2020;3(2):112-118.
Wühl E, Schaefer F. Assessment of body composition in children with chronic kidney disease. Pediatr Nephrol. 2021;36(1):67-77. DOI: 10.1007/s00467-020-04628-5
Norman K, Stobäus N, Pirlich M, Bosy-Westphal A. Bioelectrical phase angle and impedance vector analysis – clinical relevance and applicability of impedance parameters. Clin Nutr. 2012;31(6):854-861. DOI: 10.1016/j.clnu.2012.05.008
Carrero JJ, Stenvinkel P, Cuppari L, et al. Etiology of the protein-energy wasting syndrome in chronic kidney disease: a consensus statement from the International Society of Renal Nutrition and Metabolism (ISRNM). J Ren Nutr. 2013;23(2):77-90. DOI: 10.1053/j.jrn.2013.01.00
