Effects of preemptive acupuncture on cognitive function of older patients after hip replacement: a randomized controlled trial
Bibliographic record
Abstract
Background Postoperative cognitive impairment is a common complication in older patients after major orthopedic surgery; however, the underlying mechanism is not completely understood. Objective This study aimed to evaluate the effects of preemptive acupuncture on cognitive dysfunction after hip replacement and explore its potential mechanisms. Methods Finally, 54 participants were randomized into sham acupuncture (n = 27) or acupuncture (n = 27) groups, who received acupuncture at the Sishencong (EX-HN1) and Baihui (DU20) acupoints, while participants in the sham acup group received sham acup at the target acupoints. Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) scores, the incidence of postoperative cognitive dysfunction (POCD), and other adverse events were assessed. The levels of microRNA (miR)-124 and miR-146a and inflammatory cytokines in the peripheral blood were detected. Correlations among miR-124, miR-146a, and inflammatory cytokines were analyzed. Results Compared with the sham acup group, the MMSE and MoCA scores in the acup group on the first and seventh day after surgery were higher, and the incidence of POCD on the first day was lower. Acupuncture upregulated levels of miR-124 and -146a and decreased the levels of TNF-α, IL-6, and IL-1β to protect cognitive function. Correlation analysis indicated that upregulated miR-124 and miR-146 were associated with lower levels of inflammatory cytokines. Conclusion Acupuncture protects postoperative cognitive function in older patients undergoing hip replacement, potentially reducing the incidence of POCD by upregulating miR-124 and miR-146a to inhibit neuroinflammation. Clinical trial registration www.chictr.org.cn , identifier ChiCTR2200062027.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".