Using A Web-Based Nutrition Algorithm In Hemodialysis (Hd) Patients - Alison Steiber; Janeen Leon; Rosa Hand; Denis Fouque; Kamyar Kalantar-Zadeh; Lilian Cuppari (The Korean Society of Nephrology, 2012)
Nutrition care is complex and encompasses evaluation and correction of protein-energy wasting plus many nutrition abnormalities such as hyperphosphatemia, abdominal obesity, and risk factors of cardiovascular disease. The purpose of this study was to test a nutritionally comprehensive algorithm for feasibility and functionality in a diverse group of HD patients. This was a prospective, observational study designed to test a nutrition algorithm for 1) clinical feasibility; 2) logical progression; 3) ability to collect data; and 4) effectiveness in improving outcomes. Patients included in this study were enrolled by renal dietitians (RD) working in HD units based in five different countries. To select study subjects, RD were asked to screen and consent patients in their facilities until 4 patients were identified as at nutrition risk per the algorithm's screening tool. All data were collected via the algorithm including screening, assessment, nutrition related diagnosis, etiology of the nutrition diagnosis, nutrition related barriers, nutrition focused interventions, and outcome parameters. Statistics were performed using SPSS vs 20.0 and significance set at p<0.05. One hundred patients, enrolled by 29 RD, were included in this analysis. The screening parameters that triggered an "at risk flag" for more than 50% of the patients were: PTH, serum cholesterol and unintentional weight loss. Of the patients with an albumin of <3.8 mg/dl (37% of sample), 73% were given a nutritional diagnosis of insufficient protein intake. Overall, patients with insufficient intake had significantly lower serum albumin concentrations at baseline than those who did not have this (3.7±0.4 vs. 4.0±0.4, p<0.05). Patients with a diagnosis of "high phosphorus" had decreases in serum PTH (349.5±184.5 to 201.7±113.6, p=0.06) and phosphorus (from 6.5±1.0-5.3±1.9 mg/dl, p=0.04) at the three month data collection. This study is the first of its kind to show that a web-based, HD specific, nutrition algorithm is feasible and effective.