Psychological and neurological predictors of acupuncture effect in patients with chronic pain: a randomized controlled neuroimaging trial.

ABSTRACT: Chronic pain has been one of the leading causes of disability. Acupuncture is globally used in chronic pain management. However, the efficacy of acupuncture treatment varies across patients. Identifying individual factors and developing approaches that predict medical benefits may promise important scientific and clinical applications. Here, we investigated the psychological and neurological factors collected before treatment that would determine acupuncture efficacy in knee osteoarthritis. In this neuroimaging-based randomized controlled trial, 52 patients completed a baseline assessment, 4-week acupuncture or sham-acupuncture treatment, and an assessment after treatment. The patients, magnetic resonance imaging operators, and outcome evaluators were blinded to treatment group assignment. First, we found that patients receiving acupuncture treatment showed larger pain intensity improvements compared with patients in the sham-acupuncture arm. Second, positive expectation, extraversion, and emotional attention were correlated with the magnitude of clinical improvements in the acupuncture group. Third, the identified neurological metrics encompassed striatal volumes, posterior cingulate cortex (PCC) cortical thickness, PCC/precuneus fractional amplitude of low-frequency fluctuation (fALFF), striatal fALFF, and graph-based small-worldness of the default mode network and striatum. Specifically, functional metrics predisposing patients to acupuncture improvement changed as a consequence of acupuncture treatment, whereas structural metrics remained stable. Furthermore, support vector machine models applied to the questionnaire and brain features could jointly predict acupuncture improvement with an accuracy of 81.48%. Besides, the correlations and models were not significant in the sham-acupuncture group. These results demonstrate the specific psychological, brain functional, and structural predictors of acupuncture improvement and may offer opportunities to aid clinical practices.

Overall Reporting Descriptions of Acupuncture for Chronic Pain in Randomized Controlled Trials in English Journals.

BACKGROUND: Whether the clinical effect of acupuncture in chronic pain is effective has always been a hot topic of research, which has a great relationship with the overall reporting descriptions of acupuncture, especially the sham acupuncture intervention. To confirm the effectiveness of acupuncture, more clinical studies are often required. Therefore, it is necessary to report high-quality and complete descriptions of acupuncture in clinical trials. This study aims to assess the overall reporting quality of acupuncture for chronic pain in randomized controlled trials (RCTs). METHODS: Three databases from inception to March 2020 were searched, to assess the quality of acupuncture reports included the RCTs based on the pain-specific supplement to Consolidated Standards for Reporting Trials (CONSORT) and Standards for Reporting Interventions in Controlled Trials of Acupuncture (STRICTA) guidelines. The quality of sham acupuncture descriptions was evaluated based on the Template for Intervention Description and Replication (TIDieR)-placebo checklist. Descriptive statistics and analysis of the results were carried out according to the percentage of each item. RESULTS: A total of 74 RCTs were included which met the inclusion criteria. Based on the pain-specific CONSORT, the reporting rates of "Statistical methods", "Participant flow", and "Blinding" were "52.70%", "70.27%", and "77.03%", respectively. The weakest reported items in STRICTA were related to the depth of insertion (Item 2c, 54.05%) and the setting and context of treatment (Item 4b, 0.00%). Based on the TIDieR-placebo checklist, the reporting rates of "Item 12", "Item 11", "Item 13", "Item 3", and "Item 4" were "8.11%", "10.81%", "29.73%", " 44.59% ", and "47.30%", respectively. CONCLUSION: At present, the overall report quality of acupuncture treatment for chronic pain in English journals is acceptable, but the report rate in some aspects is still low. In the future, researchers should report RCTs of acupuncture following cleaner checklists and guidelines.

[Current studies on biomarkers of acupuncture analgesia using magnetic resonance imaging combining with machine learning].

Acupuncture is effective for the management and treatment of pain related diseases. At present, the patients'subjective evaluations were often used to measure the effect of acupuncture analgesia in clinical research, but it lacks objectivity and accuracy. In recent years, some studies had tried to analyze the magnetic resonance images of patients' brains using magne-tic resonance imaging and machine learning methods before and after acupuncture intervention, so as to identify specific neural markers. These markers not only helped explain the brain mechanism of acupuncture analgesia, but also provided objective indicators for the analgesic effect of acupuncture. This article analyzes the significance and feasibility of pain biomarkers research based on magnetic resonance imaging and machine learning technology, summarizes its research status in acupuncture analgesia, and makes suggestions in the future study.