Predictors of Net Acid Excretion in the Chronic Renal Insufficiency Cohort (CRIC) Study

CRIC Study Investigators

Research output: Contribution to journalArticle

Abstract

Rationale & Objective: Higher 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 Design: Cross-sectional. Setting & Participants: A 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 2 from a domain-specific model. Results: Mean 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. Conclusions: NAE 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.

Original languageEnglish (US)
JournalAmerican Journal of Kidney Diseases
DOIs
StatePublished - Jan 1 2019

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Chronic Renal Insufficiency
Cohort Studies
Acids
Body Composition
Glomerular Filtration Rate
Urine
Body Surface Area
Insulin Resistance
Demography
Diet
Kidney
Allopurinol
Metformin
Body Size
Bicarbonates
Ammonium Compounds
Disease Progression
Linear Models
Diabetes Mellitus
Body Mass Index

Keywords

  • acid load
  • acidosis
  • chronic kidney disease (CKD)
  • CKD progression
  • diabetes mellitus
  • diet
  • metabolism
  • Net acid excretion (NAE)
  • nutrition
  • urine ammonium
  • urine pH

ASJC Scopus subject areas

  • Nephrology

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Predictors of Net Acid Excretion in the Chronic Renal Insufficiency Cohort (CRIC) Study. / CRIC Study Investigators.

In: American Journal of Kidney Diseases, 01.01.2019.

Research output: Contribution to journalArticle

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title = "Predictors of Net Acid Excretion in the Chronic Renal Insufficiency Cohort (CRIC) Study",
abstract = "Rationale & Objective: Higher 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 Design: Cross-sectional. Setting & Participants: A 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 2 from a domain-specific model. Results: Mean 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. Conclusions: NAE 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.",
keywords = "acid load, acidosis, chronic kidney disease (CKD), CKD progression, diabetes mellitus, diet, metabolism, Net acid excretion (NAE), nutrition, urine ammonium, urine pH",
author = "{CRIC Study Investigators} and Landon Brown and Alison Luciano and Jane Pendergast and Pascale Khairallah and Anderson, {Cheryl A.M.} and James Sondheimer and Hamm, {L. Lee} and Ricardo, {Ana C.} and Panduranga Rao and Mahboob Rahman and Miller, {Edgar R} and Daohang Sha and Dawei Xie and Feldman, {Harold I.} and John Asplin and Myles Wolf and Scialla, {Julia J.} and Lawrence Appel and Go, {Alan S.} and Jiang He and Kusek, {John W.} and Lash, {James P.} and Rao, {Panduranga S.} and Townsend, {Raymond R.}",
year = "2019",
month = "1",
day = "1",
doi = "10.1053/j.ajkd.2018.12.043",
language = "English (US)",
journal = "American Journal of Kidney Diseases",
issn = "0272-6386",
publisher = "W.B. Saunders Ltd",

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TY - JOUR

T1 - Predictors of Net Acid Excretion in the Chronic Renal Insufficiency Cohort (CRIC) Study

AU - CRIC Study Investigators

AU - Brown, Landon

AU - Luciano, Alison

AU - Pendergast, Jane

AU - Khairallah, Pascale

AU - Anderson, Cheryl A.M.

AU - Sondheimer, James

AU - Hamm, L. Lee

AU - Ricardo, Ana C.

AU - Rao, Panduranga

AU - Rahman, Mahboob

AU - Miller, Edgar R

AU - Sha, Daohang

AU - Xie, Dawei

AU - Feldman, Harold I.

AU - Asplin, John

AU - Wolf, Myles

AU - Scialla, Julia J.

AU - Appel, Lawrence

AU - Go, Alan S.

AU - He, Jiang

AU - Kusek, John W.

AU - Lash, James P.

AU - Rao, Panduranga S.

AU - Townsend, Raymond R.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Rationale & Objective: Higher 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 Design: Cross-sectional. Setting & Participants: A 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 2 from a domain-specific model. Results: Mean 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. Conclusions: NAE 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.

AB - Rationale & Objective: Higher 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 Design: Cross-sectional. Setting & Participants: A 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 2 from a domain-specific model. Results: Mean 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. Conclusions: NAE 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.

KW - acid load

KW - acidosis

KW - chronic kidney disease (CKD)

KW - CKD progression

KW - diabetes mellitus

KW - diet

KW - metabolism

KW - Net acid excretion (NAE)

KW - nutrition

KW - urine ammonium

KW - urine pH

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U2 - 10.1053/j.ajkd.2018.12.043

DO - 10.1053/j.ajkd.2018.12.043

M3 - Article

JO - American Journal of Kidney Diseases

JF - American Journal of Kidney Diseases

SN - 0272-6386

ER -