Design and Evaluation of a Closed-Loop Anesthesia System With Robust Control and Safety System
Bibliographic record
Abstract
BACKGROUND: Closed-loop control of anesthesia involves continual adjustment of drug infusion rates according to measured clinical effect. The NeuroSENSE monitor provides an electroencephalographic measure of depth of hypnosis (wavelet-based anesthetic value for central nervous system monitoring [WAVCNS]). It has previously been used as feedback for closed-loop control of propofol, in a system designed using robust control engineering principles, which implements features specifically designed to ensure patient safety. Closed-loop control of a second drug, remifentanil, may be added to improve WAVCNS stability in the presence of variable surgical stimulation. The objective of this study was to design and evaluate the feasibility of a closed-loop system for robust control of propofol and remifentanil infusions using WAVCNS feedback, with an infusion safety system based on the known pharmacological characteristics of these 2 drugs. METHODS: With Health Canada authorization, research ethics board approval, and informed consent, American Society of Anesthesiologists I-III adults, requiring general anesthesia for elective surgery, were enrolled in a 2-phase study. In both phases, infusion of propofol was controlled in closed loop during induction and maintenance of anesthesia, using WAVCNS feedback, but bounded by upper- and lower-estimated effect-site concentration limits. In phase I, remifentanil was administered using an adjustable target-controlled infusion and a controller was designed based on the collected data. In phase II, remifentanil was automatically titrated to counteract rapid increases in WAVCNS. RESULTS: Data were analyzed for 127 patients, of median (range) age 64 (22-86) years, undergoing surgical procedures lasting 105 (9-348) minutes, with 52 participating in phase I and 75 in phase II. The overall control performance indicator, global score, was a median (interquartile range) 18.3 (14.2-27.7) in phase I and 14.6 (11.6-20.7) in phase II (median difference, -3.25; 95% confidence interval, -6.35 to -0.52). The WAVCNS was within ±10 of the setpoint for 84.3% (76.6-90.6) of the maintenance of anesthesia in phase I and 88.2% (83.1-93.4) in phase II (median difference, 3.7; 95% confidence interval, 0.1-6.9). The lower propofol safety bound was activated during 30 of 52 (58%) cases in phase I and 51 of 75 (68%) cases in phase II. CONCLUSIONS: Adding closed-loop control of remifentanil improved overall controller performance. This controller design offers a robust method to optimize the control of 2 drugs using a single sensor. The infusion safety system is an important component of a robust automated anesthesia system, but further research is required to determine the optimal constraints for these safe conditions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".