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A physio-chemical mathematical model of the effects of blood analysis delay on acid-base, metabolite and electrolyte status: evaluation in blood from critical care patients

  • Bahareh Nevirian , Steen Kåre Fagerberg , Mette Krogh Pedersen , Søren Risom Kristensen , Kjeld Asbjørn Jensen Damgaard , Stephen Edward Rees EMAIL logo and Lars Pilegaard Thomsen
Published/Copyright: December 31, 2024
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Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 63 Issue 6

Abstract

Objectives

Measurements of acid-base status are performed quickly after blood sampling avoiding errors. This necessitates rapid sample transport which can be problematic. This study measures blood sampled in critically ill patients over 180 min and proposes a mathematical physio-chemical model to simulate changes.

Methods

Eleven blood samples were taken from 30 critically ill patients and measured at baseline (2 samples) and 36, 54, 72, 90, 108, 126, 144, 162, and 180 min. A mathematical model was proposed including red blood cell metabolism, carbon dioxide diffusion, electrolyte distribution and water transport. This model was used to simulate values of plasma pH, pCO2, pO2, SO2, glucose, lactate, Na+ and Cl− during analysis delay. Simulated and measured values were compared using Bland-Altman and correlation analysis, and goodness of model fits evaluated with chi-squared.

Results

The mathematical model provided a good fit to data in 29 of 30 patients with no significant differences (p>0.1) between simulated and measured plasma values. Differences were (bias±SD): pH 0.000 ± 0.012, pCO2 0.00 ± 0.24 kPa, lactate −0.10 ± 0.23 mmol/L, glucose 0.00 ± 0.34 mmol/L, Cl− −0.2 ± 1.21 mmol/L, Na+ 0.0 ± 1.0 mmol/L, pO2 0.0 ± 0.44 kPa, SO2 −0.6 ± 5.5 %, with these values close to manufacturers’ measurement errors. All linear correlations had R2>0.86. Simulations of pH, PCO2, glucose and lactate could be performed from baseline values without patient specific parameters.

Conclusions

This paper illustrates that analysis delay can be accurately simulated with a mathematical model of physio-chemistry. While further evaluation is necessary, this may indicate a role for this model in clinical practice to simulate analysis delay.

Keywords: acid-base; mathematical modelling; analysis delay
Corresponding author: Stephen Edward Rees, Respiratory and Critical Care (Rcare) Group, Aalborg University, Aalborg, Denmark, E-mail:

  1. Research ethics: The local Institutional Review Board deemed the study exempt from review.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: Aalborg University, the institution of BN, LPT and SER, has applied for a patent based on this work. BN, SKF, SER and LPT are co-authors of the patent but all rights to the commercial exploitation of the patent lie with their academic institutions.

  6. Research funding: BN’s current PhD is funded by Roche Medical who played no part in the design of this study or the evaluation of the data.

  7. Data availability: All data is in the Supplementary Material.

References

1. Zavorsky, GS, Van Wijk, XMR. The stability of blood gases and CO-oximetry under slushed ice and room temperature conditions. Clin Chem Lab Med 2023;61:1750–9. https://doi.org/10.1515/cclm-2022-1085.Search in Google Scholar PubMed

2. Zavorsky, GS, Gasparyan, S, Stollenwerk, NS, Brooks, RA. Stability of whole blood lactate specimens at room temperature versus slushed ice conditions. Respir Care 2021;66:494–500. https://doi.org/10.4187/respcare.08023.Search in Google Scholar PubMed

3. Zavorsky, GS, Van Wijk, XMR, Gasparyan, S, Stollenwerk, NS, Brooks, RA. Stability of whole blood electrolyte specimens at room temperature vs. slushed ice conditions. J Appl Lab Med 2022;7:541–54. https://doi.org/10.1093/jalm/jfab089.Search in Google Scholar PubMed

4. Dent, RG, Boniface, DR, Fyffe, J, Yousef, Z. The effects of time delay and temperature on capillary blood gas measurements. Respir Med 1999;93:794–7. https://doi.org/10.1016/s0954-6111(99)90264-0.Search in Google Scholar PubMed

5. Knowles, TP, Mullin, RA, Hunter, JA, Douce, FH. Effects of syringe material, sample storage time, and temperature on blood gases and oxygen saturation in arterialized human blood samples. Respir Care 2006;51:732–6.Search in Google Scholar

6. Schmidt, C, Müller-Plathe, O. Stability of pO2, pCO2 and pH in heparinized whole blood samples: influence of storage temperature with regard to leukocyte count and syringe material. Eur J Clin Chem Clin Biochem 1992;30:767–73. https://doi.org/10.1515/cclm.1992.30.11.767.Search in Google Scholar PubMed

7. Beaulieu, M, Lapointe, Y, Vinet, B. Stability of PO2, PCO2, and pH in fresh blood samples stored in a plastic syringe with low heparin in relation to various blood-gas and hematological parameters. Clin Biochem 1999;32:101–7. https://doi.org/10.1016/s0009-9120(98)00098-8.Search in Google Scholar PubMed

8. Liss, HP, Piyne, CP. Stability of blood gases in ice and at room temperature. Chest 1993;103:1120–2. https://doi.org/10.1378/chest.103.4.1120.Search in Google Scholar PubMed

9. Srisan, P, Udomsri, T, Jetanachai, P, Lochindarat, S, Kanjanapattanakul, W. Effects of temperature and time delay on arterial blood gas and electrolyte measurements. J Med Assoc Thai 2011;94:S9–14.Search in Google Scholar

10. Woolley, A, Hickling, K. Errors in measuring blood gases in the intensive care unit: effect of delay in estimation. J Crit Care 2003;18:31–7. https://doi.org/10.1053/jcrc.2003.yjcrc7.Search in Google Scholar

11. Higgins, V, Nichols, M, Gao, H, Maravilla, N, Liang, E, Su, J, et al.. Defining blood gas analysis stability limits across five sample types. Clin Biochem 2023;115:107–11. https://doi.org/10.1016/j.clinbiochem.2022.09.006.Search in Google Scholar PubMed

12. Røys, EÅ, Husøy, AM, Brun, A, Aakre, KM. Impact of different sampling and storage procedures on stability of acid/base parameters in venous blood samples. Clin Chem Lab Med 2021;59:E370–3. https://doi.org/10.1515/cclm-2021-0202.Search in Google Scholar PubMed

13. Biswas, CK, Ramos, JM, Agroyannis, B, Kerr, DNS. Blood gas analysis: effect of air bubbles in syringe and delay in estimation. Br Med J 1982;284:923–7. https://doi.org/10.1136/bmj.284.6320.923.Search in Google Scholar PubMed PubMed Central

14. Chandel, NS. Glycolysis. Cold Spring Harbor Perspect Biol 2021;13. https://doi.org/10.1101/cshperspect.a040535.Search in Google Scholar PubMed PubMed Central

15. Müller-Plathe, O, Heyduck, S. Stability of blood gases, electrolytes and haemoglobin in heparinized whole blood samples: influence of the type of syringe. Clin Chem Lab Med 2009;30:349–56. https://doi.org/10.1515/cclm.1992.30.6.349.Search in Google Scholar PubMed

16. Scott, PV, Horton, JN, Mapleson, WW. Leakage of oxygen from blood and water samples stored in plastic and glass syringes. BMJ 1971;3:512–6. https://doi.org/10.1136/bmj.3.5773.512.Search in Google Scholar PubMed PubMed Central

17. Rosenberg, E, Price, N. Diffusion of CO2 and O2 through the walls of plastic syringes. Can J Physiol Pharmacol 1973;51:608–11. https://doi.org/10.1139/y73-091.Search in Google Scholar PubMed

18. Evers, W, Racz, GB, Levy, AA. A comparative study of plastic (polypropylene) and glass syringes in blood-gas analysis. Anesth Analg 1972;51:92–7. https://doi.org/10.1213/00000539-197201000-00025.Search in Google Scholar

19. Pretto, JJ, Rochford, PD. Effects of sample storage time, temperature and syringe type on blood gas tensions in samples with high oxygen partial pressures. Thorax 1994;49:610–2. https://doi.org/10.1136/thx.49.6.610.Search in Google Scholar PubMed PubMed Central

20. Wiwanitkit, V. Glass syringes are better than plastic for preserving arterial blood gas for oxygen partial pressure determination: an explanation based on nanomaterial composition. Int J Nanomed 2006;1:223–4. https://doi.org/10.2147/nano.2006.1.2.223.Search in Google Scholar PubMed PubMed Central

21. Rezende, ML, Haskins, SC, Hopper, K. The effects of ice-water storage on blood gas and acid-base measurements. J Vet Emerg Crit Care 2007;17:67–71. https://doi.org/10.1111/j.1476-4431.2006.00201.x.Search in Google Scholar

22. Bryant, MTT. Gases stored in disposable syringes: a study of changes in their concentrations. Proc Roy Soc Med 1976;69:795. https://doi.org/10.1177/003591577606901102.Search in Google Scholar PubMed PubMed Central

23. Mahoney, JJ, Harvey, JA, Wong, RJ, Van Kessel, AL. Changes in oxygen measurements when whole blood is stored in iced plastic or glass syringes. Clin Chem 1991;37:1244–8. https://doi.org/10.1093/clinchem/37.7.1244.Search in Google Scholar

24. Smeenk, FWJM, Janssen, JDJ, Arends, BJ, Harff, GA, Van Den Bosch, JA, Schönberger, JPAM, et al.. Effects of four different methods of sampling arterial blood and storage time on gas tensions and shunt calculation in the 100% oxygen test. Eur Respir J 1997;10:910–3. https://doi.org/10.1183/09031936.97.10040910.Search in Google Scholar

25. Chillar, RK, Belman, MJ, Farbstein, M. Explanation for apparent hypoxemia associated with extreme leukocytosis: leukocytic oxygen consumption. Blood 1980;55:922–4. https://doi.org/10.1182/blood.v55.6.922.922.Search in Google Scholar

26. Baierlein, JL, Foster, JM. Studies on the energy metabolism of human leukocytes. II. Mechanism of the Pasteur Effect in human leukocytes. Blood 1968;32:412–22. https://doi.org/10.1182/blood.v32.3.412.412.Search in Google Scholar

27. Holtkamp, HC, Verhoef, NJ, Leijnse, B. The difference between the glucose concentrations in plasma and whole blood. Clin Chim Acta 1975;59:41–9. https://doi.org/10.1016/0009-8981(75)90216-8.Search in Google Scholar PubMed

28. 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;33:209–64. https://doi.org/10.1615/critrevbiomedeng.v33.i3.10.Search in Google Scholar PubMed

29. Funder, J, Wieth, JO. Chloride and hydrogen ion distribution between human red cells and plasma. Acta Physiol Scand 1966;68:234–45. https://doi.org/10.1111/j.1748-1716.1966.tb03423.x.Search in Google Scholar

30. Prange, HD, Shoemaker, JL, Westen, EA, Horstkotte, DG, Pinshow, B. Physiological consequences of oxygen-dependent chloride binding to hemoglobin. J Appl Physiol 2001;91:33–8. https://doi.org/10.1152/jappl.2001.91.1.33.Search in Google Scholar PubMed

31. Raftos, JE, Bulliman, BT, Kuchel, PW. Evaluation of an electrochemical model of erythrocyte pH buffering using 31P nuclear magnetic resonance data. J Gen Physiol 1990;95:1183–204. https://doi.org/10.1085/jgp.95.6.1183.Search in Google Scholar PubMed PubMed Central

32. Wahl, P, Yue, Z, Zinner, C, Bloch, W, Mester, J. A mathematical model for lactate transport to red blood cells. J Physiol Sci 2011;61:93–102. https://doi.org/10.1007/s12576-010-0125-8.Search in Google Scholar PubMed PubMed Central

33. Buono, MJ, Yeager, JE. Intraerythrocyte and plasma lactate concentrations during exercise in humans.Eur J Appl Physiol Occup Physiol 1986;55. https://doi.org/10.1007/bf02343807.Search in Google Scholar PubMed

34. Smith, EW, Skelton, MS, Kremer, DE, Pascoe, DD, Gladden, LB. Lactate distribution in the blood during steady-state exercise. Med Sci Sports Exerc 1998;30:1424–9. https://doi.org/10.1249/00005768-199809000-00012.Search in Google Scholar

35. Vincent, JL, Dubois, MJ, Navickis, RJ, Wilkes, MM. Hypoalbuminemia in acute illness: is there a rationale for intervention? A meta-analysis of cohort studies and controlled trials. Ann Surg 2003;237:319–34. https://doi.org/10.1097/01.sla.0000055547.93484.87.Search in Google Scholar

36. Radiometer Medical A/S. Blood gas, oximetry and electrolyte systems, reference manual. Copenhagen: Radiometer Medical A/S; 2017.Search in Google Scholar

37. Mishra, P, Singh, U, Pandey, CM, Mishra, P, Pandey, G. Application of student’s t-test, analysis of variance, and covariance. Ann Card Anaesth 2019;22:407–11. https://doi.org/10.4103/aca.aca_94_19.Search in Google Scholar PubMed PubMed Central

38. Li, H, Johnson, T. Wilcoxon’s signed-rank statistic: what null hypothesis and why it matters. Pharmaceut Stat 2014;13:281–5. https://doi.org/10.1002/pst.1628.Search in Google Scholar PubMed

39. Bland, JM, Altman, DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307–10.10.1016/S0140-6736(86)90837-8Search in Google Scholar

40. Pandis, N. The chi-square test. Am J Orthod Dentofacial Orthop 2016;150:898–9. https://doi.org/10.1016/j.ajodo.2016.08.009.Search in Google Scholar PubMed

41. Ring, T, Kellum, JA. Modeling acid-base by minimizing charge-balance. ACS Omega 2019;4:6521–9. https://doi.org/10.1021/acsomega.9b00270.Search in Google Scholar PubMed PubMed Central

42. Wolf, MB. Whole body acid-base and fluid-electrolyte balance: a mathematical model. Am J Physiol Ren Physiol 2013;305:F1118–31. https://doi.org/10.1152/ajprenal.00195.2013.Search in Google Scholar PubMed

43. Pedersen, SF, Okada, Y, Nilius, B. Biophysics and physiology of the volume-regulated anion channel (VRAC)/volume-sensitive outwardly rectifying anion channel (VSOR). Pflügers Archiv 2016;468:371–83. https://doi.org/10.1007/s00424-015-1781-6.Search in Google Scholar PubMed

44. Giosa, L, Zadek, F, Busana, M, De Simone, G, Brusatori, S, Krbec, M, et al.. Quantifying pH-induced changes in plasma strong ion difference during experimental acidosis: clinical implications for base excess interpretation. J Appl Physiol 2024;136:966–76. https://doi.org/10.1152/japplphysiol.00917.2023.Search in Google Scholar PubMed PubMed Central

45. Burnett, RW, Covington, AK, Fogh-Andersen, N, Külpmann, WR, Maas, AH, Müller-Plathe, O, et al.. International Federation of Clinical Chemistry (IFCC). Scientific Division. Committee on pH, Blood Gases and Electrolytes. Approved IFCC recommendations on whole blood sampling, transport and storage for simultaneous determination of pH, blood gases and electrolytes. Eur J Clin Chem Clin Biochem 1995;33:247–53.Search in Google Scholar

46. Higgins, C. Useful tips to avoid preanalytical errors in blood gas testing: pH, pCO₂ and pO₂. Acute Care Test 2016.Search in Google Scholar

47. Rees, SE, Klaestrup, 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;108:483–94. https://doi.org/10.1007/s00421-009-1244-x.Search in Google Scholar PubMed

Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/cclm-2024-1350).

Received: 2024-11-18
Accepted: 2024-12-13
Published Online: 2024-12-31
Published in Print: 2025-05-26

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/cclm-2024-1350
Keywords for this article
acid-base; mathematical modelling; analysis delay

Articles in the same Issue

  1. Frontmatter
  2. Editorials
  3. The Friedewald formula strikes back
  4. Liquid biopsy in oncology: navigating technical hurdles and future transition for precision medicine
  5. The neglected issue of pyridoxal- 5′ phosphate
  6. Reviews
  7. Health literacy: a new challenge for laboratory medicine
  8. Clinical applications of circulating tumor cell detection: challenges and strategies
  9. Opinion Papers
  10. Pleural effusion as a sample matrix for laboratory analyses in cancer management: a perspective
  11. Interest of hair tests to discriminate a tail end of a doping regimen from a possible unpredictable source of a prohibited substance in case of challenging an anti-doping rule violation
  12. Perspectives
  13. Sigma Metrics misconceptions and limitations
  14. EN ISO 15189 revision: EFLM Committee Accreditation and ISO/CEN standards (C: A/ISO) analysis and general remarks on the changes
  15. General Clinical Chemistry and Laboratory Medicine
  16. Evaluation of current indirect methods for measuring LDL-cholesterol
  17. Verification of automated review, release and reporting of results with assessment of the risk of harm for patients: the procedure algorithm proposal for clinical laboratories
  18. Progranulin measurement with a new automated method: a step forward in the diagnostic approach to neurodegenerative disorders
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  24. Evaluation of pre-analytical factors impacting urine test strip and chemistry results
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