Propofol and Fentanyl Pharmacokinetics and Pharmacodynamics in Extracorporeal Membrane Oxygenation
Bibliographic record
Abstract
Abstract Rationale Despite the potential risks associated with sedation, there is a paucity of pharmacokinetic/pharmacodynamic (PK/PD) data for propofol and fentanyl in patients supported with venovenous extracorporeal membrane oxygenation (V-V ECMO). Objective Describe propofol and fentanyl PK/PD profiles in patients receiving V-V ECMO. Methods Prospective, single-center, open-label PK/PD study at the Toronto General Hospital intensive care unit between July 2022 and January 2023. Using high-performance liquid chromatography/tandem mass spectrometry, propofol and fentanyl total concentrations were measured during V-V ECMO. Sequential PK/PD modeling, using sex as a covariate, was conducted with processed electroencephalography (patient state index [PSI]) for sedation and expiratory occlusion pressure and airway occlusion pressure during the first 0.1 second for respiratory effort. Results Eleven patients underwent 106 evaluations over a median follow-up of 146 (interquartile ranges, 116–146) hours. Patients’ average age was 43 (standard deviation, 13) years, and 55% were female. Propofol and fentanyl PKs were best described by a two-compartment model. Propofol PSI PD were described using an effect compartment, with a coefficient of determination of 0.78. There was a significant increase in propofol (P = 0.01) and fentanyl (P = 0.03) clearance within 10 minutes of ECMO initiation, plateauing after 8 hours of ECMO support. Despite this, patient oversedation (PSI <40) occurred in 74% of the observations. Female patients exhibited a higher sedative central volume of distribution and lower propofol clearance. Conclusions ECMO initiation resulted in a time-limited increased sedative clearance. PSI accurately described sedative PD, but variable respiratory effort was observed irrespective of sedative plasma concentrations. Sex-based differences were found in sedative PK/PD parameters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".