Transcutaneous carbon dioxide measurement is not a reliable alternative to arterial blood gas sampling in the acute medical setting

Individualized estimation of arterial carbon dioxide partial pressure using machine learning in children receiving mechanical ventilation

BACKGROUND

Measuring arterial partial pressure of carbon dioxide (PaCO2) is crucial for proper mechanical ventilation, but the current sampling method is invasive. End-tidal carbon dioxide (EtCO2) has been used as a surrogate, which can be measured non-invasively, but its limited accuracy is due to ventilation-perfusion mismatch. This study aimed to develop a non-invasive PaCO2 estimation model using machine learning.

METHODS

This retrospective observational study included pediatric patients (< 18 years) admitted to the pediatric intensive care unit of a tertiary children's hospital and received mechanical ventilation between January 2021 and June 2022. Clinical information, including mechanical ventilation parameters and laboratory test results, was used for machine learning. Linear regression, multilayer perceptron, and extreme gradient boosting were implemented. The dataset was divided into 7:3 ratios for training and testing. Model performance was assessed using the R2 value.

RESULTS

We analyzed total 2,427 measurements from 32 patients. The median (interquartile range) age was 16 (12-19.5) months, and 74.1% were female. The PaCO2 and EtCO2 were 63 (50-83) mmHg and 43 (35-54) mmHg, respectively. A significant discrepancy of 19 (12-31) mmHg existed between EtCO2 and the measured PaCO2. The R2 coefficient of determination for the developed models was 0.799 for the linear regression model, 0.851 for the multilayer perceptron model, and 0.877 for the extreme gradient boosting model. The correlations with PaCO2 were higher in all three models compared to EtCO2.

CONCLUSIONS

We developed machine learning models to non-invasively estimate PaCO2 in pediatric patients receiving mechanical ventilation, demonstrating acceptable performance. Further research is needed to improve reliability and external validation.

Influence of Face Masks on Physiological and Subjective Response during 130 Min of Simulated Light and Medium Physical Manual Work-An Explorative Study

BACKGROUND

Undesirable side effects from wearing face masks during the ongoing COVID-19 pandemic continue to be discussed and pose a challenge to occupational health and safety when recommending safe application. Only few studies examined the effects of continuously wearing a face mask for more than one hour. Therefore, the influence of wearing a medical mask (MedMask) and a filtering facepiece class II respirator (FFP2) on the physiological and subjective outcomes in the course of 130 min of manual work was exploratively investigated. Physical work load and cardiorespiratory fitness levels were additionally considered as moderating factors.

METHODS

Twenty-four healthy subjects (12 females) from three different cardiorespiratory fitness levels each performed 130 min of simulated manual work with light and medium physical workload using either no mask, a MedMask or FFP2. Heart rate, transcutaneous oxygen and carbon dioxide partial pressure (PtcO2, PtcCO2) as well as perceived physical exertion and respiratory effort were assessed continuously at discrete time intervals. Wearing comfort of the masks were additionally rated after the working period.

RESULTS

There was no difference in time-dependent changes of physiological outcomes when using either a MedMask or a FFP2 compared to not wearing a mask. A stronger increase over time in perceived respiratory effort occurred when the face masks were worn, being more prominent for FFP2. Physical workload level and cardiorespiratory fitness level were no moderating factors and higher wearing comfort was rated for the MedMask.

CONCLUSION

Our results suggest that using face masks during light and medium physical manual work does not induce detrimental side effects. Prolonged wearing episodes appeared to increase respiratory effort, but without affecting human physiology in a clinically relevant way.

Transcutaneous carbon dioxide monitoring as a predictive tool for all-cause 6-month mortality after acute pulmonary embolism

BACKGROUND

Pulmonary embolism (PE) frequently remains undiagnosed. The partial pressure of carbon dioxide (Pa_CO2)_, a surrogate of dead-space ventilation, is useful in the evaluation of the degree of pulmonary artery occlusion. At present, there is no knowledge about the prognostic role of Pa_CΟ2 variations during the first hours of an acute PE. Transcutaneous measurement of CO₂ (Ptc_CO2) is a simple, non-invasive method that correlates well with Pa_CO2 levels, evaluated in this study for the first time in patients with PE.

PURPOSE

To assess the correlation between Ptc_CO2 and Pa_CO2 levels in the acute phase of PE and the role of Ptc_CO2 in predicting 6-months mortality.

METHODS

This was a pilot study including 53 patients with acute PE who hospitalized in Respiratory Medicine Department at University Hospital of Larissa in central Greece during 15 months. Ptc_CO2 was constantly monitored for four hours after PE diagnosis with the TCM40 monitoring system (SmartCal). Simultaneous arterial blood gas measurements were performed. Each patient was prospectively recorded for six months via standard telephone calls.

RESULTS

Pa_CO2 and Ptc_CO2 values were well-correlated in the acute phase of PE. Decreased Ptc_CO2 levels in the first monitoring hour were associated with a higher risk of mortality. In the PE subgroup who died, the lower Ptc_CO2 level in the first hour of PE was a predictor of shorter survival time independently of gender, age, comorbidities, and smoking status.

CONCLUSION

Ptc_CO2 measurement, especially in the first hour after PE, seemed to be a valid tool in predicting all-cause 6-month mortality.