A Monitor-Decoupled Pharmacodynamic Model of Propofol in Children Using State Entropy as Clinical Endpoint
Bibliographic record
Abstract
This paper presents a new monitor-decoupled model of propofol pharmacodynamics (PD) using the state entropy (SE) as the clinical endpoint of interest. In our model, the dynamics of the entropy monitor are separated from the PD response of the patient by explicitly accounting for the model of the entropy monitor in the PD identification process. The monitor model was then excluded from the identified PD model for the patient. The PD model, thus, obtained is distinct from its traditional counterpart in that it reflects the PD response of a patient with the dynamic effects of the monitor included as a specific entity. System identification trials using SE data of 31 pediatric subjects show that the PD models derived from the proposed approach are an improvement on the traditional approach. For the Paedfusor pharmacokinetic (PK) model, population-averaged effect site equilibration rate constant k(e0) was 5.4 and 3.0 for the proposed and traditional PD models ( p < 0.001), respectively. For the Kataria PK model, population-averaged k(e0) was 2.3 and 1.4 (p < 0.01). This significant difference suggests that the effects of the monitor must be considered when searching for the intrinsic PD of a patient that is free from the bias induced by the monitor characteristics.
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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".