End-tidal to arterial carbon dioxide gradient is associated with increased mortality in patients with traumatic brain injury: a retrospective observational study

Abstract

Early definitive airway protection and normoventilation are key principles in the treatment of severe traumatic brain injury. These are currently guided by end tidal CO₂ as a proxy for PaCO₂. We assessed whether the difference between end tidal CO₂ and PaCO₂ at hospital admission is associated with in-hospital mortality. We conducted a retrospective observational cohort study of consecutive patients with traumatic brain injury who were intubated and transported by Helicopter Emergency Medical Services to a Level 1 trauma center between January 2014 and December 2019. We assessed the association between the CO₂ gap-defined as the difference between end tidal CO₂ and PaCO₂-and in-hospital mortality using multivariate logistic regression models. 105 patients were included in this study. The mean ± SD CO₂ gap at admission was 1.64 ± 1.09 kPa and significantly greater in non-survivors than survivors (2.26 ± 1.30 kPa vs. 1.42 ± 0.92 kPa, p < .001). The correlation between EtCO₂ and PaCO₂ at admission was low (Pearson's r = .287). The mean CO₂ gap after 24 h was only 0.64 ± 0.82 kPa, and no longer significantly different between non-survivors and survivors. The multivariate logistic regression model showed that the CO₂ gap was independently associated with increased mortality in this cohort and associated with a 2.7-fold increased mortality for every 1 kPa increase in the CO₂ gap (OR 2.692, 95% CI 1.293 to 5.646, p = .009). This study demonstrates that the difference between EtCO₂ and PaCO₂ is significantly associated with in-hospital mortality in patients with traumatic brain injury. EtCO₂ was significantly lower than PaCO₂, making it an unreliable proxy for PaCO₂ when aiming for normocapnic ventilation. The CO2 gap can lead to iatrogenic hypoventilation when normocapnic ventilation is aimed and might thereby increase in-hospital mortality.

Figure 1

Correlation of PaCO2 and EtCO2. Pearson's correlation coefficient overall r = 0.287, for survivors r = 0.438, for non-survivors r = 0.150. PaCO2 and EtCO2 in kPa. Figure was created using RStudio (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/ and the package ggplot2 by Wickham H (2016).

Figure 2

Bland–Altman plots and point plots comparing PaCO2 and EtCO2. Top row: Bland–Altman plots for all available pairs of PaCO2 and EtCO2 at different time points. Bottom row: corresponding point plots for the same data. The red and blue lines illustrate the mean CO2 gap for deceased and surviving patients, respectively. The mean CO2 gap lines are trimmed, illustrating the EtCO2 range for both groups, respectively. Difference between PaCO2 and EtCO2 was highly significant for the initial pairs (p < 0.001) but not for the pairs after 24 h (see Table 2). Figures were created using RStudio (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/ and the package ggplot2 by Wickham H (2016).

Figure 3

Bar diagram showing survival for CO2 gap groups. Bar diagram showing outcome by groups of CO2 gap measured initially. Figure was created using RStudio (2020). RStudio: integrated development for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/ and the package ggplot2 by Wickham H (2016).

Figure 4

Scaled regression coefficient of the multivariate logistic regression. Illustration of the multivariate logistic regression model summarized on Table 3. Regression coefficients are exponentiated and scaled. The horizontal lines around the dots indicates the 95% confidence interval of the odds ratio. CO2 gap = PaO2—EtCO2. Figure was created using RStudio (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/. and the package ggplot2 by Wickham H (2016).