Efficacy of preoperative transcutaneous electrical acupoint stimulation in reducing postoperative delirium in older adults undergoing orthopedic surgery: a randomized controlled trial
Bibliographic record
Abstract
Background Postoperative delirium (POD) is a common complication. Pain and sleep disturbances may contribute to the development of postoperative delirium, while transcutaneous electrical acupoint stimulation (TEAS) can alleviate these symptoms. This study investigated the effect of preoperative TEAS on POD prevention in older patients undergoing orthopedic surgery. Methods A total of 608 patients were randomly assigned to either an intervention group (TEAS group) or a placebo group (control group). The TEAS group received stimulation at bilateral Hegu–Neiguan and Zusanli–Taichong acupoints for three consecutive days prior to surgery. POD was assessed twice daily using the Confusion Assessment Method from postoperative day 1 through day 5. Sleep disturbances were evaluated using the Athens Insomnia Scale (AIS), and pain was measured using the visual analog scale (VAS) on preoperative 3 days. Serum levels of interleukin-6 (IL-6), C-reactive protein (CRP), and S100β protein were quantified on postoperative days 1 and 3. In addition, cognitive function was evaluated on postoperative day 7 using the Montreal Cognitive Assessment (MoCA). Results The incidence of POD was significantly lower in the TEAS group compared to the control group (6.08% vs. 17.57%, p < 0.001). Patients in the TEAS group also exhibited significantly lower serum levels of IL-6, CRP, and S100β on both postoperative days 1 and 3 ( p < 0.05). Furthermore, significant improvements were observed in preoperative AIS scores and VAS scores for pain on days 1 and 2 prior to surgery in the TEAS group compared to the control group ( p < 0.05). Besides, the MoCA score in the TEAS group was significantly higher than in the control group on postoperative day 7 ( p < 0.05). Conclusion Preoperative application of TEAS was associated with a reduced incidence of POD in older adults undergoing orthopedic surgery. The intervention may also contribute to improvements in preoperative sleep quality and pain reduction, as well as attenuation of postoperative inflammatory responses. Clinical trial registration The trial was prospectively registered with the Chinese Clinical Trial Registry (Registration No. ChiCTR-INR-17012951; October 12, 2017).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| 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".