Anesthetic Management Using Multiple Closed-loop Systems and Delayed Neurocognitive Recovery
Bibliographic record
Abstract
BACKGROUND: Cognitive changes after anesthesia and surgery represent a significant public health concern. We tested the hypothesis that, in patients 60 yr or older scheduled for noncardiac surgery, automated management of anesthetic depth, cardiac blood flow, and protective lung ventilation using three independent controllers would outperform manual control of these variables. Additionally, as a result of the improved management, patients in the automated group would experience less postoperative neurocognitive impairment compared to patients having standard, manually adjusted anesthesia. METHODS: In this single-center, patient-and-evaluator-blinded, two-arm, parallel, randomized controlled, superiority study, 90 patients having noncardiac surgery under general anesthesia were randomly assigned to one of two groups. In the control group, anesthesia management was performed manually while in the closed-loop group, the titration of anesthesia, analgesia, fluids, and ventilation was performed by three independent controllers. The primary outcome was a change in a cognition score (the 30-item Montreal Cognitive Assessment) from preoperative values to those measures 1 week postsurgery. Secondary outcomes included a battery of neurocognitive tests completed at both 1 week and 3 months postsurgery as well as 30-day postsurgical outcomes. RESULTS: Forty-three controls and 44 closed-loop patients were assessed for the primary outcome. There was a difference in the cognition score compared to baseline in the control group versus the closed-loop group 1 week postsurgery (-1 [-2 to 0] vs. 0 [-1 to 1]; difference 1 [95% CI, 0 to 3], P = 0.033). Patients in the closed-loop group spent less time during surgery with a Bispectral Index less than 40, had less end-tidal hypocapnia, and had a lower fluid balance compared to the control group. CONCLUSIONS: Automated anesthetic management using the combination of three controllers outperforms manual control and may have an impact on delayed neurocognitive recovery. However, given the study design, it is not possible to determine the relative contribution of each controller on the cognition score.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".