Ulinastatin May Significantly Improve Postoperative Cognitive Function of Elderly Patients Undergoing Spinal Surgery by Reducing the Translocation of Lipopolysaccharide and Systemic Inflammation
Bibliographic record
Abstract
Purpose: To investigate the effects of ulinastatin on inflammatory response and early postoperative cognitive function in elderly patients undergoing spinal surgery. Methods: This clinical trial was approved by the Xuanwu Hospital Ethical Committee (Registration number: ChiCTR-IPR-16008931). Sixty elderly patients undergoing elective spinal surgery with ASA status of I–II were randomized into ulinastatin and control groups; total intravenous anesthesia was performed. The elderly patients in ulinastatin group underwent intravenous infusion of ulinastatin 10,000 units/kg following anesthesia induction and before surgical incision, and 5000 units/kg on postoperative days 1 and 2. Cognitive function was determined with Montreal Cognitive Assessment test preoperatively and on postoperative day 7 by a neurologist. Serum lipopolysaccharide (LPS), interleukin-6 (IL-6), C-reactive protein (CRP), and matrix metalloprotease-9 (MMP-9) concentration levels were measured at baseline, the end of surgery, and on postoperative days 1 and 3. Results: All elderly patients completed the study. Ulinastatin infusion significantly reduced the incidence of postoperative cognitive dysfunction in elderly patients undergoing spine surgery (ulinastatin group 16% vs. control group 43%, P< 0.05). The elderly patients in ulinastatin group exhibited lower serum LPS, IL-6, CRP, and MMP-9 concentrations, as well as a shortened peak value duration, compared with those in the control group following surgery (P< 0.05). Conclusion: Systemic inflammation and translocation of LPS were inhibited by the infusion of ulinastatin in elderly patients undergoing spinal surgery. The anti-inflammation intervention with ulinastatin can significantly improve the elderly patients’ postoperative cognitive function. Keywords: Ulinastatin, elderly patients, spine surgery, lipopolysaccharide, systemic inflammation, POCD
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".