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. 2024 Apr 24;12(1):41.
doi: 10.1186/s40635-024-00626-7.

Carboxyhemoglobin predicts oxygenator performance and imminent oxygenator change in extracorporeal membrane oxygenation

Rolf Erlebach #  1 , Alix Buhlmann #  1 , Rea Andermatt  1 , Benjamin Seeliger  2 , Klaus Stahl  3 , Christian Bode  4 , Reto Schuepbach  1 , Pedro David Wendel-Garcia #  1 , Sascha David #  5 ; BonHanZA (Bonn-Hannover-Zurich-ARDS) study group
Collaborators, Affiliations

Carboxyhemoglobin predicts oxygenator performance and imminent oxygenator change in extracorporeal membrane oxygenation

Rolf Erlebach et al. Intensive Care Med Exp. .

Abstract

Background: The continuous exposure of blood to a non-biological surface during extracorporeal membrane oxygenation (ECMO) may lead to progressive thrombus formation in the oxygenator, hemolysis and consequently impaired gas exchange. In most centers oxygenator performance is monitored only on a once daily basis. Carboxyhemoglobin (COHb) is generated upon red cell lysis and is routinely measured with any co-oximetry performed to surveille gas exchange and acid-base homeostasis every couple of hours. This retrospective cohort study aims to evaluate COHb in the arterial blood gas as a novel marker of oxygenator dysfunction and its predictive value for imminent oxygenator change.

Results: Out of the 484 screened patients on ECMO 89, cumulatively requiring 116 oxygenator changes within 1833 patient days, including 19,692 arterial COHb measurements were analyzed. Higher COHb levels were associated with lower post-oxygenator pO2 (estimate for log(COHb): - 2.176 [95% CI - 2.927, - 1.427], p < 0.0001) and with a shorter time to oxygenator change (estimate for log(COHb): - 67.895 [95% CI - 74.209, - 61.542] hours, p < 0.0001). COHb was predictive of oxygenator change within 6 h (estimate for log(COHb): 5.027 [95% CI 1.670, 15.126], p = 0.004).

Conclusion: COHb correlates with oxygenator performance and can be predictive of imminent oxygenator change. Therefore, longitudinal measurements of COHb in clinical routine might be a cheap and more granular candidate for ECMO surveillance that should be further analyzed in a controlled prospective trial design.

Keywords: Blood gas analysis; Co-oximetry; Coagulation; Hemolysis; Surveillance; Thrombosis.

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Conflict of interest statement

Sascha David and Pedro David Wendel-Garcia are editors of this journal, and recused themselves from all decisions about this paper.

Figures

Fig. 1
Fig. 1
Association of COHb with oxygenator performance (post-oxygenator pO2) based on an unadjusted hierarchical linear mixed-effects model of log(COHb) on PpostO2—COHb expressed as fraction of total Hb. COHb was logarithmically transformed for modeling purposes, and backtransformed for plotting purposes in order to improve interpretability
Fig. 2
Fig. 2
Association of time after oxygenator change and COHb based on an unadjusted hierarchical linear mixed-effects model of log(COHb)—COHb expressed as fraction of total Hb. COHb was logarithmically transformed for modeling purposes, and backtransformed for plotting purposes in order to improve interpretability
Fig. 3
Fig. 3
Association of COHb with time to oxygenator change based on an unadjusted hierarchical linear mixed-effects model of log(COHb)—COHb expressed as fraction of total Hb. COHb was logarithmically transformed for modeling purposes, and backtransformed for plotting purposes in order to improve interpretability
Fig. 4
Fig. 4
Probability of oxygenator change within 6 h based on COHb (expressed as fraction of total Hb), modeled by means of a hierarchical generalized linear mixed-effects model. Odds ratio for log(COHb): 5.027 [95% CI 1.670, 15.126], p = 0.004. COHb was logarithmically transformed for modeling purposes, and backtransformed for plotting purposes in order to improve interpretability
Fig. 5
Fig. 5
Cumulative probability of oxygenator change (within 6 h) based on time from COHb measurement and grouped by COHb levels (hierarchical multilevel mixed-effects time-varying Cox proportional hazards model)
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References

    1. Raasveld SJ, Volleman C, Combes A, Broman LM, Taccone FS, Peters E, et al. Knowledge gaps and research priorities in adult veno-arterial extracorporeal membrane oxygenation: a scoping review. Intensive Care Med Exp. 2022;10(1):50. doi: 10.1186/s40635-022-00478-z. - DOI - PMC - PubMed
    1. Extracorporeal Life Support Organization (ELSO). General Guidelines for all ECLS Cases—Version 1.4. 2017. https://www.elso.org/portals/0/elso%20guidelines%20general%20all%20ecls%.... Accessed 10 May 2023.
    1. Combes A, Hajage D, Capellier G, Demoule A, Lavoué S, Guervilly C, et al. Extracorporeal membrane oxygenation for severe acute respiratory distress syndrome. N Engl J Med. 2018;378(21):1965–1975. doi: 10.1056/NEJMoa1800385. - DOI - PubMed
    1. Vasques F, Sanderson B, Correa G, Collins P, Camarda V, Giosa L, et al. Prevalence and indications for oxygenator circuit replacement in patients receiving venovenous extracorporeal membrane oxygenation. ASAIO J. 2023 doi: 10.1097/MAT.0000000000001977. - DOI - PubMed
    1. Lubnow M, Philipp A, Foltan M, Enger TB, Lunz D, Bein T, et al. Technical complications during veno-venous extracorporeal membrane oxygenation and their relevance predicting a system-exchange – retrospective analysis of 265 cases. PLoS ONE. 2014;9(12):e112316. doi: 10.1371/journal.pone.0112316. - DOI - PMC - PubMed

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