Observation on the Clinical Efficacy of Traditional Chinese Medicine Non-Drug Therapy in the Treatment of Insomnia: A Systematic Review and Meta-Analysis Based on Computer Artificial Intelligence System

Effects of Five-Element Music Stimulation in Perioperative Period on Sleep Status and Psychological Regulation in Patients Undergoing Orthopedic Surgery

OBJECTIVE

This study aimed to explore the effect of five-element music therapy on sleep status during perioperative period and psychological regulation in patients undergoing orthopedic surgery.

METHODS

The medical records of patients who underwent orthopedic surgery from March 2021 to December 2023 in the Gansu Provincial Hospital of Traditional Chinese Medicine were retrospectively analyzed. Patients were divided into two groups in accordance with the nursing time period. The control group (88 patients) received routine nursing, and the observation group (78 patients) received five-element music management in the perioperative period based on routine nursing. The management time was from admission to one week after surgery, with 30 min/times, TID. The sleep, physical signs, pain condition, and anxiety status of the two groups were compared on admission, before surgery, and one week after surgery.

RESULTS

On admission, no significant difference in the scores of the Pittsburgh Sleep Quality Index (PSQI), the pain rating index (PRI), and the Self-Rating Anxiety Scale (SAS) was found between the two groups (P > 0.05). Before and one week after surgery, the PSQI, PRI, and SAS scores of the observation group were significantly lower than those of the control group (P < 0.001). No significant difference was found in systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) between the two groups on admission and one week after surgery (P > 0.05). Before surgery, the observation group had significantly lower indices of SBP, DBP, and HR than the control group (P < 0.05).

CONCLUSION

Five-element music stimulation in the perioperative period can improve the pain and anxiety of patients undergoing orthopedic surgery and enhance their sleep status.

Exploring the mechanism of agarwood moxa smoke in treating sleep disorders based on GC-MS and network pharmacology

Background

Agarwood moxibustion is a folk therapy developed by individuals of the Li nationality in China. There is evidence that agarwood moxa smoke (AMS) generated during agarwood moxibustion therapy can treat sleep disorders via traditional Chinese medicines' multiple target and pathway characteristics. However, the specific components and mechanisms involved have yet to be explored.

Objective

GC-MS (Gas Chromatography-Mass Spectrometry) and network pharmacology were used to investigate AMS's molecular basis and mechanism in treating sleep deprivation.

Method

GC-MS was used to determine the chemical composition of AMS; component target information was collected from TCMSP (Traditional Chinese Medicine Systems Pharmacology), PubChem (Public Chemical Database), GeneCards (Human Gene Database), and DisGeNet (Database of Genes and Diseases) were used to identify disease targets, and JVenn (Joint Venn) was used to identify the common targets of AMS and sleep disorders. STRING was used to construct a protein interaction network, Cytoscape 3.9.1 was used to build a multilevel network diagram of the "core components-efficacy targets-action pathways," the targets were imported into Metascape and DAVID for GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses and Autodock was used for molecular docking. This research used a network pharmacology methodology to investigate the therapeutic potential of Agarwood Moxa Smoke (AMS) in treating sleep problems. Examining the target genes and chemical constituents of AMS offers insights into the molecular processes and targets of the disease.

Result

Nine active ingredients comprising anti-inflammatory substances and antioxidants, such as caryophyllene and p-cymene, found seven sleep-regulating signaling pathways and eight targets linked to sleep disorders. GC-MS was used to identify the 94 active ingredients in AMS, and the active ingredients had strong binding with the key targets. Key findings included active components with known medicinal properties, such as p-cymene, eucalyptol, and caryophyllene. An investigation of network pharmacology revealed seven signaling pathways for sleep regulation and eight targets linked to sleep disorders, shedding light on AMS's effectiveness in enhancing sleep quality.

Conclusion

AMS may alleviate sleep disorders by modulating cellular and synaptic signaling, controlling hormone and neurotransmitter pathways, etc. Understanding AMS's material basis and mechanism of action provides a foundation for future research on treating sleep disorders with AMS. According to the study, Agarwood Moxa Smoke (AMS) may improve sleep quality by modifying cellular and synaptic signaling pathways for those who suffer from sleep problems. This might lead to the development of innovative therapies with fewer side effects.

Traditional Chinese medicine for insomnia: Recommendation mapping of the global clinical guidelines

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional Chinese Medicine (TCM) represents a rich repository of empirically-developed traditional medicines. The findings call for more rigorous study into the efficacy, safety, and mechanisms of action of TCM remedies to strengthen the evidence base.

AIM OF THE STUDY

To systematically review the quality of insomnia clinical practice guidelines that involve TCM recommendations and to summarize the certainty of evidence supporting the recommendations, strength, and consistency of recommendations, providing valuable research references for the development of future insomnia guidelines.

MATERIALS AND METHODS

We systematically searched PubMed, Web of Science, Embase, CNKI, Wanfang, Chinese Biomedical Literature Database, Chinese Medical Association, Chinese Sleep Research Society, Medsci, Medlive, British National Institute of Health and Clinical Excellence (NICE), and the International Guidelines Collaboration Network (GIN) for clinical practice guidelines on insomnia from inception to March 5, 2023. Four evaluators conducted independent assessments of the quality of the guidelines by employing the AGREE II tool. Subsequently, the guideline recommendations were consolidated and presented as evidence maps.

RESULTS

Thirteen clinical practice guidelines addressing insomnia, encompassing 211 recommendations (consisting of 127 evidence-based and 84 expert consensus recommendations), were deemed eligible for inclusion in our analysis. The evaluation results revealed an overall suboptimal quality, with the "scope and purpose" domain achieving the highest score (58.1%), while the "applicability" domain garnered the lowest score (13.0%). Specifically, it was observed that 74.8% (n = 95) of the evidence-based recommendations were supported by evidence of either very low or low certainty, in contrast to the expert consensus recommendations, which accounted for 61.9% (n = 52). We subsequently synthesized 44 recommendations into four evidence maps, focusing on proprietary Chinese medicines, Chinese medicine prescriptions, acupuncture, and massage, respectively. Notably, Chinese herbal remedies and acupuncture exhibited robust support, substantiated by high-certainty evidence, exemplified by interventions such as Xuefu Zhuyu decoction, spleen decoction, body acupuncture, and ear acupuncture, resulting in solid recommendations. Conversely, proprietary Chinese medicines needed more high-certainty evidence, predominantly yielding weak recommendations. As for other therapies, the level of certainty was predominantly categorized as low or very low. Recommendations about magnetic therapy, bathing, and fumigation relied primarily on expert consensus, needing more substantive clinical research evidence, consequently forming weak recommendations. Hot ironing and acupoint injection recommendations were weakly endorsed, primarily based on observational studies. Furthermore, interventions like qigong, gua sha, and moxibustion displayed a relatively limited number of clinical studies, necessitating further exploration to ascertain their efficacy.

CONCLUSIONS

Our analysis revealed a need for substantial improvement in the quality of all the included guidelines related to insomnia. Notably, recommendations for Traditional Chinese Medicine (TCM) treatments predominantly rely on low-certainty evidence. This study represents a pioneering effort in the utilization of recommendation mapping to both present and identify existing gaps in the evidence landscape within TCM therapies, thus setting the stage for future research initiatives. The evidence supporting TCM therapy recommendations must be fortified to achieve a more substantial level of recommendation and higher certainty. Consequently, there exists a critical and pressing demand for high-quality clinical investigations dedicated to TCM, with a specific focus on ascertaining its long-term efficacy, safety, and potential side effects in the context of insomnia treatment. These endeavors are poised to establish a robust scientific foundation to inform the development of TCM therapy recommendations within the insomnia guidelines.

Opportunities and challenges of traditional Chinese medicine doctors in the era of artificial intelligence

With the exponential advancement of artificial intelligence (AI) technology, the realm of medicine is experiencing a paradigm shift, engendering a multitude of prospects and trials for healthcare practitioners, encompassing those devoted to the practice of traditional Chinese medicine (TCM). This study explores the evolving landscape for TCM practitioners in the AI era, emphasizing that while AI can be helpful, it cannot replace the role of TCM practitioners. It is paramount to underscore the intrinsic worth of human expertise, accentuating that artificial intelligence (AI) is merely an instrument. On the one hand, AI-enabled tools like intelligent symptom checkers, diagnostic assistance systems, and personalized treatment plans can augment TCM practitioners' expertise and capacity, improving diagnosis accuracy and treatment efficacy. AI-empowered collaborations between Western medicine and TCM can strengthen holistic care. On the other hand, AI may disrupt conventional TCM workflow and doctor-patient relationships. Maintaining the humanistic spirit of TCM while embracing AI requires upholding professional ethics and establishing appropriate regulations. To leverage AI while retaining the essence of TCM, practitioners need to hone holistic analytical skills and see AI as complementary. By highlighting promising applications and potential risks of AI in TCM, this study provides strategic insights for stakeholders to promote the integrated development of AI and TCM for better patient outcomes. With proper implementation, AI can become a valuable assistant for TCM practitioners to elevate healthcare quality.

Clinical efficacy and safety of Guipi decoction combined with escitalopram oxalate tablets in patients with depression

BACKGROUND

Depression is a widespread mental health condition that requires effective treatment. In the treatment of depression, traditional Chinese medicine (TCM) offers obvious advantages, fewer adverse reactions, and a lower recurrence rate.

AIM

To evaluate the clinical benefits of Guipi decoction combined with escitalopram oxalate tablets for individuals with depression.

METHODS

In total, 80 patients diagnosed as having depression were enrolled in the study and divided into either an experimental group or a control group. All of the patients were orally administered escitalopram oxalate tablets. Additionally, the experimental group received Jiajian Guipi decoction and reduced Governor vessel fumigation over 4 wk. TCM syndrome scores, Hamilton depression rating scale (HAM-D) scores, self-rating depression scale (SDS) scores, and Pittsburgh sleep quality index scores were measured for the two groups and compared before and after the treatment. The two groups were monitored for any adverse reactions.

RESULTS

After 4 wk of treatment, both groups exhibited a significant reduction in TCM syndrome scores compared with their pre-treatment scores (P < 0.05). However, the experimental group exhibited significantly lower TCM syndrome scores than the control group (P < 0.05). Similarly, the post-treatment SDS and HAM-D-24 scores were significantly lower in both groups than the pre-treatment scores (P < 0.05), with the experimental group exhibiting lower scores than the control group (P < 0.05). The total treatment efficiency was significantly better in the experimental group (97.14%) than in the control group (77.78%) (P < 0.05). Furthermore, after 4 wk of treatment, the Pittsburgh sleep quality index scores for both groups were significantly lower than those before the treatment (P < 0.05), with the experimental group exhibiting lower scores than the control group (P < 0.05). The incidence of adverse reactions was significantly lower in the experimental group than in the control group (P < 0.05).

CONCLUSION

The combination of Guipi decoction and escitalopram oxalate tablets was found to be an effective and safe treatment for depression. This combination could reduce TCM syndrome scores, improve depressive symptoms, and enhance sleep quality.