Clinical adaptation of a pharmacokinetic model of Propofol plasma concentrations in children
Bibliographic record
Abstract
BACKGROUND: A previously published pharmacokinetic simulation suggested a simple manual infusion regimen to achieve propofol plasma concentrations of 3 microg.ml(-1). This study investigated if a simple variation in propofol infusion rates is able to achieve distinct propofol plasma concentrations and whether these are close to the propofol plasma concentrations predicted by the Kataria model. METHODS: With Research Ethics Board approval and written parental consent, a total of 17 healthy children requiring general anaesthesia were enrolled. Following inhalational induction of anaesthesia, a propofol bolus of 5 mg.kg(-1) was given and anaesthesia maintained using an adaptation of the McFarlan continuous propofol infusion regimen to achieve three distinct depths of propofol anaesthesia. Weight and propofol infusion data were used to calculate simulated propofol concentrations using the Kataria dataset and the TIVA simulation program. The performance of the infusion regimen was assessed by calculating the median performance error, median absolute performance error, wobble, and divergence. RESULTS: Measured propofol concentrations were (mean +/- sd) 7.15 +/- 1.4, 4.3 +/- 0.85, and 2.85 +/- 0.53 microg.ml(-1) against simulation values of 6.6, 4.1, and 2.8 microg.ml(-1), respectively, at 30, 50, and 70 min using the Kataria dataset. These differences were not significant. Formal assessment of the infusion regimen's performance was acceptable. CONCLUSION: The manual propofol infusion regimen achieved three distinct depths of propofol anaesthesia. The manual infusion regimen produced higher plasma propofol concentrations than predicted during the early part of the infusion period but was more accurate for later time points.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 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 teacher head, 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".