The physiological determinants of near-infrared spectroscopy-derived regional cerebral oxygenation in critically ill adults

Michael D Wood, Jill A Jacobson, David M Maslove, John G Muscedere, J Gordon Boyd, Cerebral Oxygenation and Neurological Outcomes Following Critical Illness (CONFOCAL) Research Group, Michael D Wood, Jill A Jacobson, David M Maslove, John G Muscedere, J Gordon Boyd, Cerebral Oxygenation and Neurological Outcomes Following Critical Illness (CONFOCAL) Research Group

Abstract

Background: To maintain adequate oxygen delivery to tissue, resuscitation of critically ill patients is guided by assessing surrogate markers of perfusion. As there is no direct indicator of cerebral perfusion used in routine critical care, identifying an accurate strategy to monitor brain perfusion is paramount. Near-infrared spectroscopy (NIRS) is a non-invasive technique to quantify regional cerebral oxygenation (rSO2) that has been used for decades during cardiac surgery which has led to targeted algorithms to optimize rSO2 being developed. However, these targeted algorithms do not exist during critical care, as the physiological determinants of rSO2 during critical illness remain poorly understood.

Materials and methods: This prospective observational study was an exploratory analysis of a nested cohort of patients within the CONFOCAL study ( NCT02344043 ) who received high-fidelity vital sign monitoring. Adult patients (≥ 18 years) admitted < 24 h to a medical/surgical intensive care unit were eligible if they had shock and/or required mechanical ventilation. Patients underwent rSO2 monitoring with the FORESIGHT oximeter for 24 h, vital signs were concurrently recorded, and clinically ordered arterial blood gas samples and hemoglobin concentration were also documented. Simultaneous multiple linear regression was performed using all available predictors, followed by model selection using the corrected Akaike information criterion (AICc).

Results: Our simultaneous multivariate model included age, heart rate, arterial oxygen saturation, mean arterial pressure, pH, partial pressure of oxygen, partial pressure of carbon dioxide (PaCO2), and hemoglobin concentration. This model accounted for a significant proportion of variance in rSO2 (R2 = 0.58, p < 0.01) and was significantly associated with PaCO2 (p < 0.05) and hemoglobin concentration (p < 0.01). Our selected regression model using AICc accounted for a significant proportion of variance in rSO2 (R2 = 0.54, p < 0.01) and was significantly related to age (p < 0.05), PaCO2 (p < 0.01), hemoglobin (p < 0.01), and heart rate (p < 0.05).

Conclusions: Known and established physiological determinants of oxygen delivery accounted for a significant proportion of the rSO2 signal, which provides evidence that NIRS is a viable modality to assess cerebral oxygenation in critically ill adults. Further elucidation of the determinants of rSO2 has the potential to develop a NIRS-guided resuscitation algorithm during critical illness.

Trial registration: This trial is registered on clinicaltrials.gov (Identifier: NCT02344043 ), retrospectively registered January 8, 2015.

Keywords: Brain tissue oxygenation; Cerebral oximetry; Cerebral perfusion; Critical illness; Near-infrared spectroscopy.

Conflict of interest statement

Ethics approval and consent to participate

The Queen’s University and Affiliated Hospitals Health Sciences Research Ethics Board approved this study protocol, which included deferred consent for 24 h due to the non-invasive nature of the monitoring device. Informed consent was obtained from all subjects or their proxy before enrollment.

Consent for publication

Not applicable.

Competing interests

JGM is the scientific director of the Canadian Frailty Network. JGB receives a stipend from the Trillium Gift of Life Network to support his role as the Hospital Donation Support Physician. All other authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
CONSORT diagram demonstrating patient inclusion and exclusion during patient recruitment and subsequent data analysis
Fig. 2
Fig. 2
Scatter plots illustrating the various relationships between regional mean cerebral oxygenation (rSO2) recordings and mean levels of various predictors of oxygen delivery (i.e., age, hemoglobin, partial pressure of carbon dioxide, and heart rate). Black data points represent each individual patient with the blue line representing a linear model fit to the data and the gray-shaded region representing the 95% confidence interval

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