Propofol in Exhaled Air and Plasma During Paedfusor Target‐Controlled Infusion in Children

ABSTRACT Background Target‐controlled infusion (TCI) algorithms for propofol are widely employed, but inter‐individual variability in achieved plasma concentrations highlights the likely potential value of real‐time monitoring. This prospective observational study evaluated the Exhaled Drug Monitor (Edmon) for online estimation of exhaled propofol concentrations ( C A ) as a proxy for plasma propofol concentrations ( C P ) in children. We also explored the relationships between Paedfusor‐estimated concentrations ( C E–P ) and C P , and between C P and Bispectral Index (BIS). Methods Children undergoing propofol‐based anaesthesia with the Paedfusor TCI model had continuous recordings of C A (parts per billion [ppb]) and C E–P , with BIS values available in a subset of patients, as electrode placement was sometimes incompatible with the surgical field. Four arterial blood samples were obtained to determine C P . Linear mixed‐model analyses were employed to assess the relationships between variables. Results Twenty‐six children aged 3–10 years were included. During maintenance of anaesthesia at a TCI target concentration of 3.0 μg mL −1 , C A lagged behind C P by 4 min. At this delay, the slope (gain) for estimation of C P from C A was 0.36 μg mL −1 ppb −1 (95% confidence interval [CI] 0.08 to 0.64, p = 0.015) and the intercept (offset) 1.16 μg mL −1 (95% CI −0.52 to 2.84, p = 0.16), RSquare 0.63. The pooled median absolute performance error based on samples obtained at 20 and 30 min after induction was 8.8% for the Edmon and 13.5% for the Paedfusor. C P was 19%, 16% and 1% higher than Paedfusor predictions at 20 min, 30 min and end of surgery, respectively. In an exploratory analysis, BIS values decreased by 4.8 for each 1 μg mL −1 increase in C P . Conclusion This exploratory study demonstrates that online monitoring of exhaled propofol during surgery is feasible in children. The Edmon provided estimates of C P comparable with those of the Paedfusor algorithm during maintenance of anaesthesia, but its use is limited by a complex setup and a 4‐min time lag relative to plasma concentrations. Editorial Comment In this study, propofol infusion in children using a target‐controlled infusion was performed, and propofol concentration in exhaled air was sampled intermittently and measured. This assessment demonstrated practical feasibility aspects of this sampling and measurement along with challenges for clinical application. Trial Registration: ClinicalTrials.gov (NCT04150432): URL: https://clinicaltrials.gov/study/NCT04150432?term=NCT04150432&rank=1

Authors

Institutions

Publication Details

Journal
Acta Anaesthesiologica Scandinavica
Published
2026-11-02
DOI
https://doi.org/10.1111/aas.70368
Primary Topic
Anesthesia and Sedative Agents
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Propofol in Exhaled Air and Plasma During Paedfusor Target‐Controlled Infusion in Children

Torsten Eken, Johan C. Raeder, Martin Rygh Braathen, Terje Dybvik et al.
Acta Anaesthesiologica Scandinavica
Anesthesia and Sedative Agents
article

Propofol in Exhaled Air and Plasma During Paedfusor Target‐Controlled Infusion in Children

Torsten Eken, Johan C. Raeder, Martin Rygh Braathen, Terje Dybvik, Ivan Rimstad
article en

Abstract

ABSTRACT Background Target‐controlled infusion (TCI) algorithms for propofol are widely employed, but inter‐individual variability in achieved plasma concentrations highlights the likely potential value of real‐time monitoring. This prospective observational study evaluated the Exhaled Drug Monitor (Edmon) for online estimation of exhaled propofol concentrations ( C A ) as a proxy for plasma propofol concentrations ( C P ) in children. We also explored the relationships between Paedfusor‐estimated concentrations ( C E–P ) and C P , and between C P and Bispectral Index (BIS). Methods Children undergoing propofol‐based anaesthesia with the Paedfusor TCI model had continuous recordings of C A (parts per billion [ppb]) and C E–P , with BIS values available in a subset of patients, as electrode placement was sometimes incompatible with the surgical field. Four arterial blood samples were obtained to determine C P . Linear mixed‐model analyses were employed to assess the relationships between variables. Results Twenty‐six children aged 3–10 years were included. During maintenance of anaesthesia at a TCI target concentration of 3.0 μg mL −1 , C A lagged behind C P by 4 min. At this delay, the slope (gain) for estimation of C P from C A was 0.36 μg mL −1 ppb −1 (95% confidence interval [CI] 0.08 to 0.64, p = 0.015) and the intercept (offset) 1.16 μg mL −1 (95% CI −0.52 to 2.84, p = 0.16), RSquare 0.63. The pooled median absolute performance error based on samples obtained at 20 and 30 min after induction was 8.8% for the Edmon and 13.5% for the Paedfusor. C P was 19%, 16% and 1% higher than Paedfusor predictions at 20 min, 30 min and end of surgery, respectively. In an exploratory analysis, BIS values decreased by 4.8 for each 1 μg mL −1 increase in C P . Conclusion This exploratory study demonstrates that online monitoring of exhaled propofol during surgery is feasible in children. The Edmon provided estimates of C P comparable with those of the Paedfusor algorithm during maintenance of anaesthesia, but its use is limited by a complex setup and a 4‐min time lag relative to plasma concentrations. Editorial Comment In this study, propofol infusion in children using a target‐controlled infusion was performed, and propofol concentration in exhaled air was sampled intermittently and measured. This assessment demonstrated practical feasibility aspects of this sampling and measurement along with challenges for clinical application. Trial Registration: ClinicalTrials.gov (NCT04150432): URL: https://clinicaltrials.gov/study/NCT04150432?term=NCT04150432&rank=1

Acta Anaesthesiologica ScandinavicaVol. 71(1)
Oslo University Hospital (NO), University of Oslo (NO)
B. Braun Medical, Oslo universitetssykehus HF
Good health and well-being
Openalex Percentile: Top 9%
Anesthesia and Sedative Agents
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon