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Acid excretion is impaired in calcium oxalate stone formers

  • Pedro H. Imenez Silva*
  • , Nasser A. Dhayat
  • , Daniel G. Fuster
  • , Harald Seeger
  • , Alexander Ritter
  • , Thomas Ernandez
  • , Florian Buchkremer
  • , Beat Roth
  • , Olivier Bonny
  • , Isabel Rubio-Aliaga
  • , Carsten A. Wagner*
  • *Corresponding author for this work
  • B. Braun Medical Care AG
  • University Hospital Bern
  • University Hospital Zürich
  • Cantonal Hospital Baden
  • Cantonal Hospital St. Gallen
  • Kantonsspital Aarau
  • University of Lausanne
  • NCCR Kidney.CH
  • University of Fribourg
  • Hôpital Cantonal de Fribourg
  • University of Zurich

Research output: Contribution to journalComment/Letter to the editorAcademicpeer-review

1 Citation (Scopus)
67 Downloads (Pure)

Abstract

To the Editor,
Urine pH and supersaturation contribute to urine crystal formation (1). However, how the renal capacity to excrete acid influences the formation of common kidney stone types is not completely understood. Leveraging the extensive urine biochemistry profile available in the Swiss Kidney Stone Cohort (SKSC) (2), we tested whether urinary acid-base parameters, including pH, ammonium, titratable acids (TA), net acid excretion (NAE), and citrate were associated with the presence of calcium oxalate (CaOx) and calcium phosphate (CaP) stones. We assessed the kidney’s capacity of excreting acids by calculating an index that determines how much net acid is excreted in relation to urine pH, which was previously termed as net acid excretion capacity (NAEC) (3). NAEC is obtained from the residuals of the relation between net acid excretion and urine pH. A similar ammonium-topH index, the acid-base (AB) score, was recently validated in chronic kidney disease (4). We also included titratable acid and gastrointestinal alkali absorption in our analyses as similarly done in (5).
The SKSC is a prospective, multicentric, longitudinal cohort with patients with kidney stones (2). Participants with kidney stone disease (SF) were followed for 3 years to collect blood, urine samples, and clinical data. This analysis used baseline data collected 2 weeks after screening, with the last stone episode occurring 6–17 weeks prior to baseline (Supplementary Tables 1-3). Stone composition was determined via Fourier transform infrared spectroscopy. A control group (NSF), CT-confirmed to be free of kidney stones and calcifications, was also recruited. Exclusion criteria specific to this study are in Supplementary Figure 1. Biochemical parameters were measured as described in (2) with participants eating their usual diet, and data analysis was conducted using R/RStudio (6).
Original languageEnglish
Article numbergfaf038
Pages (from-to)1433-1435
Number of pages3
JournalNephrology Dialysis Transplantation
Volume40
Issue number7
Early online date20 Feb 2025
DOIs
Publication statusPublished - 1 Jul 2025

Bibliographical note

© The Author(s) 2025. Published by Oxford University Press on behalf of the ERA.

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