Background: Determination of resting energy expenditure (REE) is an important step for the nutritional and medical care of patients with chronic kidney disease (CKD). Methods such as indirect calorimetry or traditional predictive equations are costly or inaccurate to estimate REE of CKD patients. We aimed to develop and validate predictive equations to estimate the REE of non-dialysis dependent-CKD patients.
Methods: A database comprising REE measured by indirect calorimetry (mREE) of 170 non-dialysis dependent-CKD patients was used to develop (n = 119) and validate (n = 51) a new REE-predictive equation. Fat free mass (FFM) was assessed by anthropometry and by bioelectrical impedance (BIA).
Results: The multiple regression analysis generated three equations: (1) REE (kcal/day) = 854 + 7.4*Weight + 179*Sex - 3.3*Age + 2.1 *eGFR + 26 (if DM) (R2 = 0.424); (2) REE (kcal/day) = 678.3 + 14.07*FFM.ant + 54.8*Sex - 2*Age + 2.5*eGFR + 140.7* (if DM) (R2 = 0.449); (3) REE (kcal/day) = 668 + 17.1*FFM.BIA - 2.7*Age - 92.7*Sex + 1.3*eGFR - 152.3 (if DM) (R2 = 0.45). The estimated REE (eREE) was not different from the mREE (P = 0.181), a high ICC was found and the mean difference between mREE and eREE was not different from zero for the three equations in the validation group. eREE accuracy between 90 and 110% was observed in 55.3%, 62.5% and 61% of the patients for Eqs. (1), (2) and (3), respectively.
Conclusion: The equations showed acceptable accuracy for REE prediction making them a valuable tool to support practitioners to provide more reliable energy recommendations for this group of patients.
Keywords: Chronic kidney disease; Energy expenditure; Energy metabolism; Nutrition; Predictive equation.
© 2021. Italian Society of Nephrology.