Association between the macrocirculation and the mitochondrial oxygenation in critically ill patients with sepsis

Association between the macrocirculation and the mitochondrial oxygenation in critically ill patients with sepsis

Brouwer, Fleur (TU Delft Mechanical, Maritime and Materials Engineering)

Arbous, Sesmu (mentor)
Schouten, A.C. (mentor)
Harlaar, J. (graduation committee)
French, P.J. (graduation committee)
Dodou, D. (graduation committee)

Delft University of Technology
Leiden University Medical Center
Erasmus Universiteit Rotterdam

Technical Medicine

2020-06-25

IntroductionThe Cellular Oxygen METabolism (COMET) monitor measures mitochondrial oxygentension (mitoPO2) in vivo at the bedside with delayed fluorescence ofmitochondrial protoporphyrin (PpIX). Blocking microcirculatory oxygen supply bypressing the measurement probe on the skin allows the measurement of mitochondrialoxygen consumption (mitoVO2). Combining the static mitochondrial parameter(i.e. mitoPO2) and the dynamic mitochondrial parameter (i.e. mitoVO2) canprovide useful information about different aspects of the mitochondrialfunction in sepsis. However, it is not yet known how these mitochondrialparameters relate to the traditional systemic hemodynamic parameters, such aslactate and central venous oxygen saturation (ScvO2). The first aim of thisstudy is to develop an analysis method to derive a measure for oxygenconsumption. The second aim of this study is to investigate the associationbetween the macrocirculation and the mitochondrial oxygenation, in particularmitoPO2 and mitoVO2, and to investigate the association between these twomitochondrial parameters in critically ill patients with sepsis.  Methods We performed a prospectiveobservational study in critically ill patients with suspicion of sepsis whowere admitted to the Intensive Care Unit of the Leiden Medical UniversityCenter. A patch containing 5-aminolevulinic (ALA) was placed on the anteriorchest wall of the patient to induce PpIX in the mitochondria. MitoPO2 wasmeasured by the oxygen-dependent fluorescence of mitochondrial PpIX. MitoVO2was determined by a dynamic mitoPO2 measurement (taking up a series of mitoPO2samples) while blocking the microcirculatory oxygen supply by applying pressurewith the measurement probe of the COMET monitor. MitoPO2 samples and bloodsamples were collected at the same predefined time points. A sigmoid functionwas used to fit the raw mitoPO2 signal of the dynamic mitoPO2 measurements. Amixed linear model was used to study the association between themacrocirculation and the mitochondrial oxygenation and the association betweenthe mitochondrial oxygenation and oxygen consumption. For this second model, wedivided the mitoPO2 levels into a low, medium and high mitoPO2 group. Results Atotal of 202 mitoPO2 measurements were performed in 41 critically ill patientswith sepsis. However, due to poor signal quality or insufficient fitperformance, 29 (14%) dynamic mitoPO2 measurements of different patients wereexcluded for further analysis. The results of this study showed that highermitoPO2 levels were significantly associated with lower lactate levels (β = -0.002744, p = 0.023). Moreover,mitoPO2 levels of the low mitoPO2 group were significantly associated withhigher mitoVO2 rates (β= 0.103822, p < 0.001). Interestingly, mitoVO2 could not be induced in 31(15%) dynamic mitoPO2 measurements.   ConclusionThese results show that mitoPO2 levels are associated with lactate levels incritically ill patients with sepsis. Mitochondria with low oxygen levels are instress and will switch to anaerobic metabolism leading to lactate production.Moreover, these mitochondria have no reserves and will directly suffer from theacute cessation of the oxygen supply because these mitochondria consume thepresent oxygen faster compared to the mitochondria with higher mitoPO2 levels.

sepsis
mitochondria
mitochondrial oxygen tension
mitochondrial oxygen consumption
COMET

http://resolver.tudelft.nl/uuid:411dea15-927a-4ad6-a705-942d578245c1

2022-08-01

https://doi.org/10.4121/uuid:b45c0507-b4ac-4da9-9880-9543f65804c1

Related dataset 4TU.ResearchData https://doi.org/10.4121/uuid:b45c0507-b4ac-4da9-9880-9543f65804c1

Student theses

master thesis

© 2020 Fleur Brouwer