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Related Experiment Videos

Acid-base regulation: a comparison of quantitative methods

J M Kowalchuk1, B W Scheuermann

  • 1Faculty of Kinesiology, University of Western Ontario, London, Canada.

Canadian Journal of Physiology and Pharmacology
|July 1, 1994
PubMed
Summary

The Stewart and Fencl models accurately estimate plasma hydrogen ion ([H+]) and bicarbonate ([HCO3-]) concentrations during exercise. Both models showed strong correlation with measured values, with minimal differences, validating their use in acid-base balance assessment.

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Area of Science:

  • Physiology
  • Biochemistry
  • Mathematical Modeling

Background:

  • Plasma acid-base balance ([H+] and [HCO3-]) is influenced by PCO2, strong ion difference (SID), and weak acids.
  • Two models, Stewart and Fencl, quantitatively describe plasma acid-base behavior but differ in weak acid treatment.

Purpose of the Study:

  • To compare the accuracy of the Stewart and Fencl models in predicting measured [H+] and [HCO3-] in whole-blood samples.
  • To assess the predictive performance of these quantitative models during strenuous exercise.

Main Methods:

  • Whole-blood samples from eight subjects during exercise to exhaustion were analyzed.
  • Measurements included [H+], PCO2, total protein ([protein]TOT), albumin, total inorganic phosphate ([Pi]TOT), and SID.
  • These variables were input into the Stewart and Fencl models to estimate [H+] and [HCO3-].

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Main Results:

  • Both the Stewart and Fencl models provided good estimates of measured [H+] (r = 0.81 for both) and [HCO3-] (r = 0.93 for both).
  • Linear regression showed no significant differences (p > 0.05) between estimated and measured values compared to the line of identity.
  • Average differences were small: < 3 nmol/L for [H+] and < 2 mmol/L for [HCO3-].

Conclusions:

  • The Stewart and Fencl models are accurate in estimating plasma [H+] and [HCO3-] during exercise.
  • Both models demonstrate strong predictive capability for acid-base status in physiological conditions.
  • The findings support the utility of these quantitative models in clinical and research settings.