ArticleAmerican journal of kidney diseases : the official journal of the National Kidney Foundation2019
Predictors of Net Acid Excretion in the Chronic Renal Insufficiency Cohort (CRIC) Study.
Article in American journal of kidney diseases : the official journal of the National Kidney Foundation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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5 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Pooled it
- Adverse event profiles of fenofibrate and gemfibrozil: a retrospective comparative study and literature synthesis.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- The case for a ketogenic diet in the management of kidney disease.BMJ open diabetes research & care · 2024Review
- A Therapeutic Approach in the Management of Chronic Kidney Disease: Plant-Based Dietary Models and Associated Parameters.Current nutrition reports · 2024Review
- Review
Corrections and comments
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Authors and funding
18 authors at 10 institutions in 1 country.
Funding
Abstract
RATIONALE &
objectiveHigher urine net acid excretion (NAE) is associated with slower chronic kidney disease progression, particularly in patients with diabetes mellitus. To better understand potential mechanisms and assess modifiable components, we explored independent predictors of NAE in the CRIC (Chronic Renal Insufficiency Cohort) Study. STUDY
designCross-sectional. SETTING &
participantsA randomly selected subcohort of adults with chronic kidney disease enrolled in the CRIC Study with NAE measurements. PREDICTORS: A comprehensive set of variables across prespecified domains including demographics, comorbid conditions, medications, laboratory values, diet, physical activity, and body composition. OUTCOME: 24-hour urine NAE. ANALYTICAL APPROACH: NAE was defined as the sum of urine ammonium and calculated titratable acidity in a subset of CRIC participants. 22 individuals were excluded for urine pH < 4 (n = 1) or ≥7.4 (n = 19) or extreme outliers of NAE values (n = 2). From an analytic sample of 978, we identified the association of individual variables with NAE in the selected domains using linear regression. We estimated the percent variance explained by each domain using the adjusted R
resultsMean NAE was 33.2 ± 17.4 (SD) mEq/d. Multiple variables were associated with NAE in models adjusted for age, sex, estimated glomerular filtration rate (eGFR), race/ethnicity, and body surface area, including insulin resistance, dietary potential renal acid load, and a variety of metabolically active medications (eg, metformin, allopurinol, and nonstatin lipid agents). Body size, as indicated by body surface area, body mass index, or fat-free mass; race/ethnicity; and eGFR also were independently associated with NAE. By domains, more variance was explained by demographics, body composition, and laboratory values, which included eGFR and serum bicarbonate level. LIMITATIONS: Cross-sectional; use of stored biological samples.
conclusionsNAE relates to several clinical domains including body composition, kidney function, and diet, but also to metabolic factors such as insulin resistance and the use of metabolically active medications.
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