Perioperative estimations of oxygen consumption from LiDCO™plus-derived cardiac output and Ca-cvO2 difference: Relationship with measurements by indirect calorimetry in elderly patients undergoing major abdominal surgery.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2024
Historique:
received: 16 07 2022
accepted: 10 06 2024
medline: 26 7 2024
pubmed: 26 7 2024
entrez: 25 7 2024
Statut: epublish

Résumé

Feasible estimations of perioperative changes in oxygen consumption (VO2) could enable larger studies of its role in postoperative outcomes. Current methods, either by reverse Fick calculations using pulmonary artery catheterisation or metabolic by breathing gas analysis, are often deemed too invasive or technically requiring. In addition, reverse Fick calculations report generally lower values of oxygen consumption. We investigated the relationship between perioperative estimations of VO2 (EVO2), from LiDCO™plus-derived (LiDCO Ltd, Cambridge, UK) cardiac output and arterial-central venous oxygen content difference (Ca-cvO2), with indirect calorimetry (GVO2) by QuarkRMR (COSMED srl. Italy), using data collected 2017-2018 during a prospective observational study on perioperative oxygen transport in 20 patients >65 years during epidural and general anaesthesia for open pancreatic or liver resection surgery. Eighty-five simultaneous intra- and postoperative measurements at different perioperative stages were analysed for prediction, parallelity and by traditional agreement assessment. Unadjusted bias between GVO2 and EVO2 indexed for body surface area was 26 (95% CI 20 to 32) with limits of agreement (1.96SD) of -32 to 85 ml min-1m-2. Correlation adjusted for the bias was moderate, intraclass coefficient(A,1) 0.51(95% CI 0.34 to 0.65) [F (84,84) = 3.07, P<0.001]. There was an overall association between GVO2 and EVO2, in a random coefficient model [GVO2 = 73(95% CI 62 to 83) + 0.45(95% CI 0.29 to 0.61) EVO2 ml min-1m-2, P<0.0001]. GVO2 and EVO2 changed in parallel intra- and postoperatively when normalised to their respective overall means. Based on this data, estimations from LiDCO™plus-derived cardiac output and Ca-cvO2 are not reliable as a surrogate for perioperative VO2. Results were in line with previous studies comparing Fick-based and metabolic measurements but limited by variability of data and possible underpowering. The parallelity at different perioperative stages and the prediction model can provide useful guidance and methodological tools for future studies on similar methods in larger samples.

Sections du résumé

BACKGROUND BACKGROUND
Feasible estimations of perioperative changes in oxygen consumption (VO2) could enable larger studies of its role in postoperative outcomes. Current methods, either by reverse Fick calculations using pulmonary artery catheterisation or metabolic by breathing gas analysis, are often deemed too invasive or technically requiring. In addition, reverse Fick calculations report generally lower values of oxygen consumption.
METHODS METHODS
We investigated the relationship between perioperative estimations of VO2 (EVO2), from LiDCO™plus-derived (LiDCO Ltd, Cambridge, UK) cardiac output and arterial-central venous oxygen content difference (Ca-cvO2), with indirect calorimetry (GVO2) by QuarkRMR (COSMED srl. Italy), using data collected 2017-2018 during a prospective observational study on perioperative oxygen transport in 20 patients >65 years during epidural and general anaesthesia for open pancreatic or liver resection surgery. Eighty-five simultaneous intra- and postoperative measurements at different perioperative stages were analysed for prediction, parallelity and by traditional agreement assessment.
RESULTS RESULTS
Unadjusted bias between GVO2 and EVO2 indexed for body surface area was 26 (95% CI 20 to 32) with limits of agreement (1.96SD) of -32 to 85 ml min-1m-2. Correlation adjusted for the bias was moderate, intraclass coefficient(A,1) 0.51(95% CI 0.34 to 0.65) [F (84,84) = 3.07, P<0.001]. There was an overall association between GVO2 and EVO2, in a random coefficient model [GVO2 = 73(95% CI 62 to 83) + 0.45(95% CI 0.29 to 0.61) EVO2 ml min-1m-2, P<0.0001]. GVO2 and EVO2 changed in parallel intra- and postoperatively when normalised to their respective overall means.
CONCLUSION CONCLUSIONS
Based on this data, estimations from LiDCO™plus-derived cardiac output and Ca-cvO2 are not reliable as a surrogate for perioperative VO2. Results were in line with previous studies comparing Fick-based and metabolic measurements but limited by variability of data and possible underpowering. The parallelity at different perioperative stages and the prediction model can provide useful guidance and methodological tools for future studies on similar methods in larger samples.

Identifiants

pubmed: 39052563
doi: 10.1371/journal.pone.0272239
pii: PONE-D-22-19510
doi:

Substances chimiques

Oxygen S88TT14065

Types de publication

Journal Article Observational Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0272239

Informations de copyright

Copyright: © 2024 Jakobsson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Julia Jakobsson (J)

Division of Anaesthesia and Intensive Care, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm, Sweden.
Department of Perioperative Medicine and Intensive Care, Karolinska University Hospital Huddinge, Stockholm, Sweden.

Carl Norén (C)

Department of Anaesthesia and Intensive Care, Nyköping County Hospital, Nyköping, Sweden.

Eva Hagel (E)

Department of Learning, Information, Management and Ethics (LIME), Medical Statistics Unit, Karolinska Institutet, Stockholm, Sweden.

Magnus Backheden (M)

Department of Learning, Information, Management and Ethics (LIME), Medical Statistics Unit, Karolinska Institutet, Stockholm, Sweden.

Sigridur Kalman (S)

Division of Anaesthesia and Intensive Care, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm, Sweden.
Department of Perioperative Medicine and Intensive Care, Karolinska University Hospital Huddinge, Stockholm, Sweden.

Erzsébet Bartha (E)

Division of Anaesthesia and Intensive Care, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm, Sweden.
Department of Perioperative Medicine and Intensive Care, Karolinska University Hospital Huddinge, Stockholm, Sweden.

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