Benjamin H Parmenter1, Gary J Slater1, Lynda A Frassetto2. 1. Faculty of Health, Science and Engineering, University of the Sunshine Coast, Queensland, Australia. 2. School of Medicine, University of California San Francisco (UCSF), California, USA.
Abstract
AIM: The gold standard of measurement for net endogenous acid production (NEAP) is net acid excretion (NAE), a test that is not readily available, and consequently, estimative equations by Remer and Manz and Frassetto et al. are often used. These equations rely on nutrient databases and it is recommended that their validity be assessed using a country's database before their application in research in that country. We sought to delineate the accuracy and precision of these estimation equations using the Australian food database. METHODS: In a double blind, randomised, cross-over fashion, healthy participants (n = 13) residing in regional Australia were exposed to varying net acid loads while they collected weighted food diaries and 24-hour urine samples for measurement of NAE. RESULTS: In comparison to the Frassetto et al. equations (equation one bias = -57.1 mEq/day, equation two bias = -32.8 mEq/day), only the Remer and Manz equation was accurate (bias = -5.4 mEq/day); however, all equations were imprecise. CONCLUSIONS: Using the Australian database, the performance of these equations to predict NEAP appears equal to other databases; however, caveats apply in their application. For future research, the equation by Remer and Manz is preferential for group estimates. None of the equations are recommended for individual estimates.
RCT Entities:
AIM: The gold standard of measurement for net endogenous acid production (NEAP) is net acid excretion (NAE), a test that is not readily available, and consequently, estimative equations by Remer and Manz and Frassetto et al. are often used. These equations rely on nutrient databases and it is recommended that their validity be assessed using a country's database before their application in research in that country. We sought to delineate the accuracy and precision of these estimation equations using the Australian food database. METHODS: In a double blind, randomised, cross-over fashion, healthy participants (n = 13) residing in regional Australia were exposed to varying net acid loads while they collected weighted food diaries and 24-hour urine samples for measurement of NAE. RESULTS: In comparison to the Frassetto et al. equations (equation one bias = -57.1 mEq/day, equation two bias = -32.8 mEq/day), only the Remer and Manz equation was accurate (bias = -5.4 mEq/day); however, all equations were imprecise. CONCLUSIONS: Using the Australian database, the performance of these equations to predict NEAP appears equal to other databases; however, caveats apply in their application. For future research, the equation by Remer and Manz is preferential for group estimates. None of the equations are recommended for individual estimates.
Authors: Amelie Bernier-Jean; Germaine Wong; Valeria Saglimbene; Marinella Ruospo; Suetonia C Palmer; Patrizia Natale; Vanessa Garcia-Larsen; David W Johnson; Marcello Tonelli; Jörgen Hegbrant; Jonathan C Craig; Armando Teixeira-Pinto; Giovanni F M Strippoli Journal: Clin J Am Soc Nephrol Date: 2021-12-01 Impact factor: 8.237
Authors: Benjamin H Parmenter; Michael Dymock; Tanushree Banerjee; Anthony Sebastian; Gary J Slater; Lynda A Frassetto Journal: Kidney Int Rep Date: 2020-07-29
Authors: Amelie Bernier-Jean; Germaine Wong; Valeria Saglimbene; Marinella Ruospo; Suetonia C Palmer; Patrizia Natale; Vanessa Garcia-Larsen; David W Johnson; Marcello Tonelli; Jörgen Hegbrant; Jonathan C Craig; Armando Teixeira-Pinto; Giovanni F M Strippoli Journal: Kidney Int Rep Date: 2021-09-15