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Updated: Aug 6, 2026

Measurement of Tissue Oxygenation Using Near-Infrared Spectroscopy in Patients Undergoing Hemodialysis
Published on: October 2, 2020
Longitudinal Changes in Acid-Base Parameters From Dialysis Initiation to Death in Maintenance Hemodialysis Patients
Christoph Schwarz1, Gregor Lindner2,3, Markus Pirklbauer4
1Department of Internal Medicine, Pyhrn-Eisenwurzen Klinikum Steyr, Steyr, Austria.
Introduction:
Blood gas analysis is routinely performed in hemodialysis patients to monitor acid-base status and serum potassium. Despite frequent testing, longitudinal analyses of acid-base parameters over patients' lifetime are lacking.
Methods:
We conducted a retrospective analysis of 45 chronic hemodialysis patients at a secondary dialysis center in Austria, including 7946 blood gas analyses. Acid-base disturbances and respiratory compensation to metabolic acidosis were evaluated. Longitudinal changes were assessed at three time points: START (4 weeks after dialysis initiation), MID (mid-survival), and EOL (last 4 weeks of dialysis). Four measurements per patient were included at each time point. Venous blood gas values were adjusted to arterial equivalents to improve comparability. Linear mixed-effects models were used for analysis.
Findings:
Venous blood gas analysis systematically misclassified respiratory status; standard formulas for compensation (e.g., Winter's formula) were not applicable. Over the course of dialysis treatment, acid-base and electrolyte homeostasis changed significantly. Temporal patterns were largely comparable between expected and unexpected death, with the exception of lactate, which increased significantly in patients with unexpected death.
Discussion:
This study provides a comprehensive longitudinal evaluation of acid-base parameters from dialysis initiation to death. Observed temporal patterns, particularly in patients with unexpected death, suggest distinct terminal metabolic trajectories. These findings warrant further investigation in larger cohorts, potentially supported by artificial intelligence-based analyses.
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