Multimodal Brain Monitoring-Guided Anesthesia Management Improves Functional Connectivity, Enhances Recovery and Attenuates Postoperative Pain in Elderly Surgical Patients
Bibliographic record
Abstract
Purpose: Perioperative neurocognitive disorder (PND) is common in elderly surgical patients and severely affects postoperative recovery. However, effective prevention is still lacking. Potential perioperative cerebral stressors (including inappropriate sedative/analgesic depth and imbalanced cerebral oxygen supply/demand) may be important contributing factors. We developed an anesthesia management protocol based on multimodal brain monitoring to achieve standardized, individualized, and real-time regulation of sedative/analgesic depth and cerebral oxygen saturation and investigated whether it could reduce the incidence of PND and its underlying mechanisms. Patients and Methods: Patients (aged ≥ 65 years) were randomized into Groups C (n=88) and E (n=93). Patients in Group E received multimodal brain monitoring-guided anesthesia management, and those in Group C received BIS-guided anesthesia management. The Montreal Cognitive Assessment (MoCA) was performed both before and seven days after surgery. The postoperative pain scores were recorded. Resting-state functional MRI data were analyzed to examine functional connectivity (FC). Results: Group E demonstrated a numerically lower incidence of PND (15.50% vs 21.59% in Group C), but this difference was not statistically significant. Patients in Group E had increased FC within the right pulvinar, right sub-gyral region, and right inferior parietal lobule ( P < 0.05). Significantly lower pain scores were observed in Group E at rest (1h: P =0.04; 24h: P =0.04) and during movement (1h: P =0.03). Conclusion: These results suggest that multimodal brain monitoring-guided anesthesia management may protect neurocognition by enhancing FC within cognition-associated brain regions and attenuating postoperative acute pain. And multimodal brain monitoring-guided anesthesia management may confer a clinically relevant reduction in PND incidence compared to BIS-guided management in elderly surgical patients. Keywords: multimodal brain monitoring, elderly patients, perioperative neurocognitive disorders, functional connectivity, postoperative acute pain
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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 | 0.001 |
| 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".