The effect of a target controlled infusion of propofol on predictability of recovery from anesthesia in children
Bibliographic record
Abstract
BACKGROUND: Emergence following termination of a general anesthetic depends on the effect site concentration (C(e)) of the drug declining to an awakening value (C(e)-awake). C(e)-awake has been described in adults, but is unknown in children. OBJECTIVES: To determine C(e)-awake in children following a target-controlled infusion (TCI) of propofol and to assess a C(e)-driven TCI system's ability to predict times to emergence from anesthesia. METHODS: Subjects undergoing elective surgery, aged 3 months to <10 years were recruited into three age-stratified groups. A target C(e) of 3-4 microg x ml(-1) was selected for induction and subsequently titrated to patient response and surgical stimulus. Preoperative acetaminophen, a remifentanil infusion and regional anesthesia were permitted for supplemental analgesia. State Entropy (SE) was monitored from induction to emergence. Emergence was defined as the time of first purposeful spontaneous movement (PSM). Time zero was defined as the end of propofol infusion. Based on a pilot study, a C(e)-awake of 1.9 microg x ml(-1) was chosen as the wake-up threshold used by the software to predict emergence times. RESULTS: Data was collected for 90 of 104 recruited patients. PSM occurred at a mean (sd) C(e) of 2.0 (0.5) microg x ml(-1) and an SE of 79 (11). There were no differences between age groups. A wide variation in emergence time was observed, with a mean (sd) of 16.9 (7) min, and a trend to more rapid emergence in older subjects. CONCLUSION: A predicted C(e)-awake of 2.0 microg x ml(-1) in children aged 3 months to <10 years was identified with the selected model. For expert users of propofol in children, during shorter surgical procedures, TCI predicted emergence times do not offer significant clinical advantages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".