Abstract
Objective
Debate still exists as to whether the Stewart (modern) or traditional model of acid–base chemistry is best in assessing the acid–base status of critically ill patients. Recent studies have compared various parameters from the modern and traditional approaches, assessing the clinical usefulness of parameters such as base excess, anion gap, corrected anion gap, strong ion difference and strong ion gap. To compare the clinical usefulness of these parameters, and hence the different approaches, requires a clear understanding of their meaning; a task only possible through understanding the mathematical basis of the approaches. The objective of this paper is to provide this understanding, limiting the mathematics to a necessary minimum.
Method
The first part of this paper compares the mathematics of these approaches, with the second part illustrating the clinical usefulness of the approaches using a patient example.
Results
This analysis illustrates the almost interchangeable nature of the equations and that the same clinical conclusions can be drawn regardless of the approach adopted.
Conclusions
Although different in their concepts, the traditional and modern approaches based on mathematical models can be seen as complementary giving, in principle, the same information about the acid–base status of plasma.
Similar content being viewed by others
Abbreviations
- A− :
-
Weak base form of non-bicarbonate buffers, amount of hydrogen binding sites in mmol l−1
- AG:
-
Anion gap, in mmol l−1
- AGcorr :
-
Corrected AG, in mmol l−1
- Atot :
-
Non-bicarbonate buffer concentratition, both in their acid and base form. Non-bicarbonate buffers are treated as a single monovalent weak acid in accordance with the Stewart’s model. Because of monovalency, units of meq l−1 and mmol l−1 can be treated interchangingly in most cases. We use mmol l−1
- A −pHn :
-
Charge of plasma buffer base at pH = 7.4; directly proportional to Atot. It depends linearly on the concentration of albumins, globulins and phosphates
- β:
-
Buffer Capacity, amount of univalent strong base needed to increase pH by 1, in mmoll−1. Only plasma buffer capacity is discussed in this article, i.e. β = βpl here
- BB:
-
Buffer base, in mmol l−1
- BE:
-
Base excess in mmol l−1, amount of univalent strong base added to plasma (blood) of pH = 7.4
- ΔA −I :
-
Change in charge of non-bicarbonate buffer base due to buffering, at normal albumin (plasma protein and phosphate) concentration
- ΔA −II :
-
Change in charge of non-bicarbonate buffer base due to buffering, at any albumin (plasma protein and phosphate) concentration
- ΔA −pHn :
-
Change in charge of non-bicarbonate buffer base due to change in albumin (plasma protein and phosphate) concentration at normal pH = 7.4
- HA:
-
Weak acid form of non-bicarbonate buffers, in mmol l−1
- KA :
-
Lumped dissociation constant of non-bicarbonate buffers, in mmol l−1
- pCO2 :
-
Partial pressure of carbon dioxide in arterial blood, in kPa (mmHg)
- SID:
-
Strong ion difference, in mmol l−1
- SIDA :
-
Apparent SID, sum of strong cations minus sum of strong anions, in mmol l−1
- SIDE :
-
Effective SID, sum of bicarbonate and non-bicarbonate buffer bases, in mmol l−1
- SIG:
-
Strong ion gap, SIDA minus SIDE, in mmol l−1
- X− :
-
Unmeasured anions, generally equal to SIG, in mmol l−1
References
Siggaard-Andersen O. The acid–base status of the blood. Copenhagen: Munksgaard; 1974:25–51.
Siggaard-Andersen O. The Van Slyke equation. Scand J Clin Lab Invest. 1977;37(S146):15–20.
Siggaard-Andersen O, Wimberly PD, Fogh-Andersen N, Gøthgen I. Measured and derived quantities with modern pH and blood gas equipment: calculation algorithms with 54 equations. Scand J Clin Lab Invest. 1988;48(S189):7–15.
Schwartz WB, Relman AS. A critique of the parameters used in the evaluation of acid-base disorders “whole-blood buffer base” and “standard bicarbonate” compared with blood pH and plasma bicarbonate concentration. N Engl J Med. 1963;268:1382–1388.
Stewart PA. Modern quantitative acid-base chemistry. Can J Physiol Pharmacol. 1983;61:1444–1461.
Figge J, Mydosh T, Fencl V. Serum proteins and acid-base equilibria: a follow-up. J Lab Clin Med. 1992;120:713–719.
Constable PD. A simplified strong ion model for acid-base equilibria: application to horse plasma. J Appl Physiol. 1997;83:297–311.
Watson PD. Modeling the effects of proteins on pH in plasma. J Appl Physiol. 1999;86(4):1421–1427.
Wooten EW. Analytic calculation of physiological acid-base parameters in plasma. J Appl Physiol. 1999;86(1):326–334.
Wooten EW. Calculation of physiological acid-base parameters in multicompartment systems with application to human blood. J Appl Physiol. 2003;95:2333–2344.
Rees SE, Andreassen S. Mathematical models of oxygen and carbon dioxide storage and transport: the acid-base chemistry of blood. Crit Rev Biomed Eng. 2005;33(3):209–264.
ABL800 Flex Specifications, Radiometer Medical A/S 2004. http://www.radiometer.com/abl800-specifications.
Constable PD. Hyperchloremic acidosis: the classic example of strong ion acidosis. Anesth Analg. 2003;96:919–922.
Balasubramanyan N, Havens PL, Hoffman GM. Unmeasured anions identified by the Fencl-Stewart method predict mortality better than base excess, anion gap, and lactate in the pediatric intensive care unit. Crit Care Med. 1999;28(7):1577–1581.
Kaplan LJ, Kellum JA. Comparison of acid-base models for prediction of hospital mortality after trauma. Shock. 2008;29:662–666.
Funk GC, Doberer D, Sterz F, Richling N, Kneidinger N, Lindner G, Schneeweiss B, Eisenburger P. The strong ion gap and outcome after cardiac arrest in patients treated with therapeutic hypothermia: a retrospective study. Intensive Care Med. 2009;35:232–239.
Honore PM, Joannes-Boyau O, Boer W. Strong ion gap and outcome after cardiac arrest: another nail in the coffin of traditional acid-base quantification. Intensive Care Med. 2009;35:189–191.
Kellum JA. Acid-base physiology in the post-Copernican era. Curr Opin Crit Care. 1999;5:429–435.
Kellum JA. Clinical review: reunification of acid-base physiology. Crit Care. 2005;9:500–507.
Constable PD. Total weak acid concentration and effective dissociation constrant of nonvolatile buffers in human plasma. J Appl Physiol. 2001;91:1364–1371.
Siggaard-Andersen O, Engel K. A new acid–base nomogram- an improved method for the calculation of the relevant blood acid–base data. Scand J Clin Lab Invest. 1960;12:177–186.
Siggaard-Andersen O. The pH–log PCO2 blood acid–base nomogram revised. Scand J Clin Lab Invest. 1962;14:598–604.
Figge J, Jabor A, Kazda A, Fencl V. Anion gap and hypoalbuminemia. Crit Care Med. 1998;26:1807–1810.
Staempfli HR, Constable PD. Experimental determination of net protein charge and Atot and Ka of nonvolatile buffers in human plasma. J Appl Physiol. 2003;95:620–630.
Fencl V, Jabor A, Kazda A, Figge J. Diagnosis of metabolic acid–base disturbances in critically ill patients. Am J Respir Crit Care Med. 2000;162:2246–2251.
Siggaard-Andersen O, Fogh-Andersen N. Base excess or buffer base (strong ion difference) as a measure of a non-respiratory acid-base disturbance. Acta Anaesthesiol Scand. 1995;39((S107)):123–128.
Emmet M, Narins RG. Clinical use of anion gap. Medicine (Baltimore). 1977;56:38–54.
Yahwak JA, Riker RR, Fraser GL, Subak-Sharpe S. Determination of a lorazepam dose threshold for using the osmol gap to monitor for propylene glycol toxicity. Pharmacotherapy. 2008;28:984–991.
Goldberg M, Green SB, Moss ML, Marbach CB, Garfinkel D. Computerised instruction and diagnosis of acid–base disorders. J Am Med Assoc. 1973;223:269–275.
Siggaard-Andersen O. An acid-base chart for arterial blood with normal and pathophysiological reference areas. Scand J Clin Lab Invest. 1974;27:239–245.
Kofranek J, Matousek S, Andrlik M. Border flux balance approach towards modelling acid-base chemistry and blood gases transport. In: Zupanic B, Karba R, Blazic S, editors. In: Proceedings of the 6th EUROSIM congress on modelling and simulation. Ljubljana: University of Ljubljana; 2007. pp. 1–9.
Singer RB, Hastings AB. An improved clinical method for the estimation of disturbances of the acid-base balance of human blood. Medicine. 1948;27:223–242.
Rees SE, Klæstrup E, Handy J, Andreassen S, Kristensen SR. Mathematical modelling of the acid-base chemistry and oxygenation of blood: a mass balance, mass action approach including plasma and red blood cells. Eur J Appl Physiol. 2010;108(3):483–494.
Siggaard-Andersen O, Rorth M, Strickland DAP. The buffer value of plasma, erythrocyte fluid and whole blood. In: Workshop on pH and Blood Gases. Washington DC: National Bureau of Standards; 1977:11–19.
Lloyd P. Strong ion calculator–a practical bedside application of modern quantitative acid-base physiology. Crit Care Resusc. 2004;6:285–294.
Moviat M, Terpstra AM, Ruitenbeek W, Kluijtmans LA, Pickkers P, van der Hoeven JG. Contribution of various metabolites to the “unmeasured” anions in critically ill patients with metabolic acidosis. Crit Care Med. 2008;36:752–758.
Figge J, Rossing TH, Fencl VJ. The role of serum proteins in acid–base equilibria. J Lab Clin Med. 1991;117:453–467.
Winter SD, Pearson JR, Gabow PA, Schultz AL, Lepoff RB. The fall of the serum anion gap. Arch Intern Med. 1990;150:311–313.
Van Leeuven AM. Net cation equivalency (base binding power) of the plasma proteins. Acta Med Scand. 1964;S422:1–212.
Author information
Authors and Affiliations
Corresponding author
Additional information
Matousek S, Handy J, Rees SE. Acid–base chemistry of plasma: consolidation of the traditional and modern approaches from a mathematical and clinical perspective.
Rights and permissions
About this article
Cite this article
Matousek, S., Handy, J. & Rees, S.E. Acid–base chemistry of plasma: consolidation of the traditional and modern approaches from a mathematical and clinical perspective. J Clin Monit Comput 25, 57–70 (2011). https://doi.org/10.1007/s10877-010-9250-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10877-010-9250-4