Impact of butorphanol versus sufentanil on postoperative cognition and inflammation in elderly: a pilot study
Bibliographic record
Abstract
Background This randomized controlled trial aimed to compare the effects of butorphanol and sufentanil on early post-operative cognitive dysfunction (POCD) and systemic inflammation in older surgical patients. Methods Patients (aged 65 years or above) undergoing surgeries with general anesthesia were randomized to either the butorphanol group (40 μg/kg during anesthesia induction) or the sufentanil group (0.4 μg/kg). Cognitive function changes during the perioperative period were assessed using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) scale up to 3 days after surgery. POCD was defined as a Z-score or composite Z-score greater than 1.96 for both MMSE and MoCA scores. Circulating inflammatory factors, including tumor necrosis factor-alpha (TNF-α), interleukin 1 beta (IL-1β), and interleukin 10 (IL-10), were measured using enzyme-linked immunosorbent assay. Results The study included 114 patients (median age: 71 years, 57.7% male). Compared to sufentanil, butorphanol significantly reduced the incidence of POCD on the first (11.5% versus 32.7%, p = 0.017) and third day (3.8% versus 15.4%, p = 0.046) after surgery. Additionally, patients receiving butorphanol had significantly lower circulating levels of TNF-α and IL-1β at the time of discharge from the post-anesthesia care unit and on the first and third day after surgery (p < 0.05 for all comparisons). Furthermore, circulating IL-10 levels were significantly higher in patients receiving butorphanol (p < 0.05 for all comparisons). Conclusion Administration of butorphanol during anesthesia induction, as opposed to sufentanil, was associated with a significant reduction in the early incidence of POCD in older surgical patients, possibly attributed to its impact on systemic inflammation. Clinical trial registration: The present study was registered in the China Clinical Trial Center (ChiCTR2300070805, 24/04/2023).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".