Effects of different depths of sedation on serum adiponectin concentrations in elderly patients undergoing general anesthesia
Bibliographic record
Abstract
Objective To evaluate the effects of different depths of sedation on serum adiponectin (ADP) concentrations in elderly patients undergoing general anesthesia. Methods A total of 120 elderly patients of both sexes, aged 65-83 yr, weighing 45-75 kg, of American Society of Anesthesiologists physical status Ⅱ or Ⅲ, undergoing elective noncardiac surgery under general anesthesia, were divided into Ⅰ and Ⅱ groups (n=60 each) using a random number table.Propofol was given by closed-loop target-controlled infusion, and bispectral index value was maintained at 40-50 in group Ⅰ and at 50-60 in group Ⅱ.The cognitive function was assessed by the Montreal Cognitive Assessment at 1 day before operation ant 1 and 7 days after operation.Blood samples were collected from the internal jugular vein immediately before surgery, at 2 h after the beginning of surgery and at 1 and 7 days after surgery for determination of serum ADP and S-100β protein concentrations. Results Compared with group Ⅰ, Montreal Cognitive Assessment scores were significantly increased at 1 and 7 days after surgery, the serum concentrations of ADP were increased and S-100β protein concentrations in serum were decreased at 1 and 7 days after surgery, and the intraoperative requirement for ephedrine and atropine and incidence of postoperative cognitive dysfunction were decreased during surgery in group Ⅱ (P<0.05). Conclusion Maintaining BIS value at 50-60 can reduce the development of postoperative cognitive dysfunction, which is related to the increased concentration of serum ADP in elderly patients undergoing general anesthesia. Key words: Electroencephalography; Aged; Cognition disorders; Adiponectin
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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 | 0.000 | 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 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".