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Observational Study
. 2024 Aug 5;24(1):273.
doi: 10.1186/s12871-024-02662-y.

Evaluating tissue hypoxia and the response to fluid administration in septic shock patients: a metabolic cluster analysis

Affiliations
Observational Study

Evaluating tissue hypoxia and the response to fluid administration in septic shock patients: a metabolic cluster analysis

Cristina Espinal et al. BMC Anesthesiol. .

Abstract

Background: The selection of adequate indicators of tissue hypoxia for guiding the resuscitation process of septic patients is a highly relevant issue. Current guidelines advocate for the use of lactate as sole metabolic marker, which may be markedly limited, and the integration of different variables seems more adequate. In this study, we explored the metabolic profile and its implications in the response to the administration of a fluid challenge in early septic shock patients.

Methods: Observational study including septic shock patients within 24 h of ICU admission, monitored with a cardiac output estimation system, with ongoing resuscitation. Hemodynamic and metabolic variables were measured before and after a fluid challenge (FC). A two-step cluster analysis was used to define the baseline metabolic profile, including lactate, central venous oxygen saturation (ScvO2), central venous-to-arterial carbon dioxide difference (PcvaCO2), and PcvaCO2 corrected by the difference in arterial-to-venous oxygen content (PcvaCO2/CavO2).

Results: Seventy-seven fluid challenges were analyzed. Cluster analysis revealed two distinct metabolic profiles at baseline. Cluster A exhibited lower ScvO2, higher PcvaCO2, and lower PcvaCO2/CavO2. Increases in cardiac output (CO) were associated with increases in VO2 exclusively in cluster A. Baseline isolated metabolic variables did not correlate with VO2 response, and changes in ScvO2 and PcvaCO2 were associated to VO2 increase only in cluster A.

Conclusions: In a population of early septic shock patients, two distinct metabolic profiles were identified, suggesting tissue hypoxia or dysoxia. Integrating metabolic variables enhances the ability to detect those patients whose VO2 might increase as results of fluid administration.

Keywords: Circulatory shock; Fluid responsiveness; Hemodynamic monitoring; Lactate; Venous oxygen saturation; Venous-to-arterial carbon dioxide difference.

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Conflict of interest statement

Competing interests. The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Metabolic clusters model. The best model was obtained combining ScvO2, PcvaCO2 and PcvaCO2/CavO2, where ScvO2 and PcvaCO2 showed higher weight. The figure shows the distribution of the three metabolic parameters at baseline in all the measurements (central panel), in cluster A (left panel) and in cluster B (right panel). The distribution was significantly different between the two final clusters: * p < 0.001 as compared to cluster A
Fig. 2
Fig. 2
Changes in CO and VO2 as results of the fluid expansion. Relationship between change in cardiac output (CO), and global oxygen consumption (VO2), expressed as % change from baseline (2A). When separately analyzing the metabolic clusters, the correlation was only significant for cluster A patients (2B)
Fig. 3
Fig. 3
Changes in metabolic parameters according to baseline cluster and VO2 response. Absolute change in ScvO2 (3A), PcvaCO2 (3B), and PcvaCO2/CavO2 (3C), according to the increase of VO2 after the fluid challenge. The final value was obtained as (post-intervention - baseline) value. * p < 0.05 for comparisons within the same cluster
Fig. 4
Fig. 4
Changes in CO and O2ER as results of the fluid expansion. Change in O2ER was computed from (O2ER after the FC) - (O2ER at baseline). A negative value indicates a decrease in O2ER as results of the FC

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