A New Index of Coordinated Posterior and Anterior Evoked EEG to Detect Recall Under Sedation – A Pilot Study
Bibliographic record
Abstract
EEG-based technologies may be limited in identifying recall under sedation (RUS). We developed a novel index, posteriorization/anteriorization (P/A) index, based on auditory evoked EEG signal and assessed whether it could differentiate between patients with or without RUS. Methods: EEG and BIS were sampled from 3 groups: 1. Patients undergoing sedation (n = 26); 2. Awake volunteers (n = 13, positive control for recall) 3. Patients undergoing general anesthesia (GA, n = 12, negative control for recall). In recovery, recall was assessed using the BRICE questionnaire. Of the 26 sedated patients, 12 experienced recall. Both The P/A index and BIS differentiated between patients with recall and no recall. However, BIS differentiation may have been sensitive to the main drug used for sedation (midazolam vs. propofol) and the P/A index did not show similar drug-based sensitivity. Furthermore, only BIS results were correlated with EMG. Conclusion: This pilot study provided support for the association between P/A index and recall after sedation. Further research is needed in integrating the index into clinical use: (1) it should be derived by an easy-to-use EEG system with a better signal-to-noise ratio; (2) its applicability to other drugs must be shown.
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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 | 0.001 | 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".