A Direct Dynamic Dose-Response Model of Propofol for Individualized Anesthesia Care
Bibliographic record
Abstract
In an effort to open up new opportunities in individualized anesthesia care, this paper presents a dynamic dose-response model of propofol that relates propofol dose (i.e., infusion rate) directly to a clinical effect. The proposed model consists of a first-order equilibration dynamics plus a nonlinear Hill equation model, each representing the transient distribution of propofol dose from the plasma to the effect site and the steady-state dose-effect relationship. Compared to traditional pharmacokinetic-pharmacodynamic (PKPD) models, the proposed model has structural parsimony and comparable predictive capability, making it more attractive than its PKPD counterpart for identifying an individualized dose-response model in real-time. The efficacy of the direct dynamic dose-response model over a traditional PKPD model was assessed using a mixed effects modeling analysis of the electroencephalogram (EEG)-based state entropty (SE) response to intravenous propofol administration in 34 pediatric subjects. An improvement in the mean-squared error and r(2) value of individual prediction, as well as the Akaike's information criterion (AIC) was seen with the direct dynamic dose-response model.
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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".