BACKGROUND: The use of inserted sham acupuncture as a placebo in randomized controlled trials (RCTs) is controversial, because it may produce specific effects that cause an underestimation of the effect of acupuncture treatment. OBJECTIVE: This systematic survey investigates the magnitude of insert-specific effects of sham acupuncture and whether they affect the estimation of acupuncture treatment effects. SEARCH STRATEGY: PubMed, Embase and Cochrane Central Register of Controlled Trials were searched to identify acupuncture RCTs from their inception until December 2022. INCLUSION CRITERIA: RCTs that evaluated the effects of acupuncture compared to sham acupuncture and no treatment. DATA EXTRACTION AND ANALYSIS: The total effect measured for an acupuncture treatment group in RCTs were divided into three components, including the natural history and/or regression to the mean effect (controlled for no-treatment group), the placebo effect, and the specific effect of acupuncture. The first two constituted the contextual effect of acupuncture, which is mimicked by a sham acupuncture treatment group. The proportion of acupuncture total effect size was considered to be 1. The proportion of natural history and/or regression to the mean effect (PNE) and proportional contextual effect (PCE) of included RCTs were pooled using meta-analyses with a random-effect model. The proportion of acupuncture placebo effect was the difference between PCE and PNE in RCTs with non-inserted sham acupuncture. The proportion of insert-specific effect of sham acupuncture (PIES) was obtained by subtracting the proportion of acupuncture placebo effect and PNE from PCE in RCTs with inserted sham acupuncture. The impact of PIES on the estimation of acupuncture's treatment effect was evaluated by quantifying the percentage of RCTs that the effect of outcome changed from no statistical difference to statistical difference after removing PIES in the included studies, and the impact of PIES was externally validated in other acupuncture RCTs with an inserted sham acupuncture group that were not used to calculate PIES. RESULTS: This analysis included 32 studies with 5492 patients. The overall PNE was 0.335 (95% confidence interval [CI], 0.255-0.415) and the PCE of acupuncture was 0.639 (95% CI, 0.567-0.710) of acupuncture's total effect. The proportional contribution of the placebo effect to acupuncture's total effect was 0.191, and the PIES was 0.189. When we modeled the exclusion of the insert-specific effect of sham acupuncture, the acupuncture treatment effect changed from no difference to a significant difference in 45.45% of the included RCTs, and in 40.91% of the external validated RCTs. CONCLUSION The insert-specific effect of sham acupuncture in RCTs represents 18.90% of acupuncture's total effect and significantly affects the evaluation of the acupuncture treatment effect. More than 40% of RCTs that used inserted sham acupuncture would draw different conclusions if the PIES had been controlled for. Considering the impact of the insert-specific effect of sham acupuncture, caution should be taken when using inserted sham acupuncture placebos in RCTs. Please cite this article as: Luo XC, Liu JL, Yao MH, Chen YM, Fan AY, Liang FR, Zhao JP, Zhao L, Zhou X, Zhong XY, Yang JH, Li B, Zhang Y, Sun X, Li L. Specific effect of inserted sham acupuncture and its impact on the estimation of acupuncture treatment effect in randomized controlled trials: A systematic survey. J Integr Med. 2025; 23(6):630-640.
Acupuncture Therapy/methods* ; Humans ; Randomized Controlled Trials as Topic ; Placebo Effect ; Placebos ; Treatment Outcome

PURPOSE: The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery. METHODS: A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications. RESULTS: In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram. CONCLUSION Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans ; COVID-19/complications* ; Male ; Female ; Middle Aged ; Postoperative Complications/epidemiology* ; SARS-CoV-2 ; Orthopedic Procedures/adverse effects* ; Aged ; Nomograms ; Adult ; Retrospective Studies ; Risk Factors

OBJECTIVE: To evaluate the efficacy and safety of a hospital-made resuscitation pack, a Chinese medicinal herbal compound formula designed to enhance recovery in post-bronchoscopy patients. METHODS: In this randomized, single-blind, placebo-controlled clinical trial, eligible patients were randomly assigned 1:1 to either the treatment or control groups. The patients in the treatment group applied the resuscitation pack, which contained aromatic compounded Chinese herbs. The patients in the control group applied a hospital-made, single herb placebo pack. Packs were placed on the Tiantu (CV 22) acupuncture point for 4 h as soon as the bronchoscopy finished. Efficacy indicators, such as recovery time, patients' symptoms including nausea and dizziness, and adverse events (AEs) were observed and compared. The outcome indices were evaluated at baseline, 1 and 24 h after the bronchoscopy. Subgroup analysis was further performed by patients' age and depth of sedation. RESULTS: When applying generalized estimating equations (GEE) to evaluate the intensity of post-bronchoscopy nausea and vomiting, the intensity was lower in the treatment group (163 cases) compared with the control group (162 cases; 95% CI: 0.004, 0.099, P=0.03]. Also, significantly lower intensity of nausea was observed in the 60-70 years of age subgroup (95% CI: 0.029, 0.169, P=0.006) and deep sedation subgroup (95% CI: 0.002, 0.124; P=0.04). There was no significant difference in dizziness between two groups by GEE (95% CI: -0.134, 0.297; P=0.459). In addition, no serious AEs were observed in either group. CONCLUSIONS Our study found that the resuscitation pack markedly improved patients' symptoms by reducing nausea and vomiting after bronchoscopy without AEs, compared with placebo in the perioperative period. (Trial registration No. ChiCTR2000038299).
Humans ; Male ; Middle Aged ; Female ; Bronchoscopy/adverse effects* ; Single-Blind Method ; Aged ; Drugs, Chinese Herbal/adverse effects* ; Treatment Outcome ; Resuscitation ; Adult ; Medicine, Chinese Traditional

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Bombesin receptor subtype-3 (BRS3) is an orphan G protein-coupled receptor (GPCR) that plays critical roles in energy homeostasis, glucose metabolism, and insulin secretion. Recent structural studies have elucidated BRS3 signaling mechanisms using synthetic ligands, including BA1 and MK-5046. However, the molecular basis of BRS3 activation by bioactive natural compounds and their derivatives, particularly those derived from traditional Chinese medicine, remains unclear. Here, we present high-resolution cryogenic electron microscopy (cryo-EM) structures of the human BRS3-G_q complex in both unliganded and active states bound by two herb-derived compounds (DSO-5a and oridonin), at resolutions of 2.9, 2.8, and 2.9 Å, respectively. These structures display distinct ligand recognition patterns between DSO-5a and oridonin. Although both compounds bind to the orthosteric pocket, they differentially engage the interaction network of BRS3, as demonstrated by mutagenesis studies assessing calcium mobilization and inositol phosphate 1 (IP1) accumulation. These findings enhance our understanding of BRS3 activation and provide valuable insights into the development of small-molecule BRS3 modulators with therapeutic potential.

Objective To compare the application value of three image post-processing techniques volume rendering(VR),multiplanar reformation(MPR)and curved planar reformation(CPR)in the identifi-cation of rib fracture malunion.Methods The types and numbers of rib fracture malunion in 75 pa-tients were recorded,and the sensitivity,specificity,accuracy and Youden index of VR,MPR and CPR in the diagnosis of rib fracture malunion were compared.Receiver operator characteristic(ROC)curve was drawn and area under the curve(AUC)was calculated,and the detection rates of three image post-processing techniques for different types of rib fracture malunion were compared.Results A total of 243 rib fractures were malunion in 75 patients.The diagnostic sensitivity of VR,MPR and CPR for rib fracture malunion was 52.67%,79.84%and 91.36%,the specificity was 99.58%,97.89%and 99.15%,the accuracy was 83.66%,91.76%and 96.51%,the Youden index was 0.52,0.78 and 0.91,the AUC was 0.761,0.889 and 0.953,respectively.Compared with VR,there were statistically signifi-cant differences in the number of broken rib end misalignment over 1/3,broken rib end overlap,bro-ken rib end angulation and intercostal bridge detected in MPR(P<0.05).Compared with VR,there was a statistically significant difference in the number of different types of rib fracture malunion de-tected by CPR(P<0.05).Compared with MPR,there were statistically significant differences in the number of broken rib end misalignment over 1/3,broken rib end separation and intercostal bridge de-tected in CPR(P<0.05).Conclusion The three image post-processing techniques are of great signifi-cance for the identification of rib fracture malunion.Especially CPR is highly effective in the diagno-sis of rib fracture malunion,and can be used as the main post-processing technique for forensic clini-cal identification of rib fracture malunion.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective:To seek a correlation between short-chain fatty acids (SCFAs) and skill in the activities of daily living (ADL) after an ischemic stroke.Methods:Ninety ischemic stroke survivors were assessed using the Barthel Index (BI). Fecal samples were collected and analyzed for the concentration of acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid, and isovaleric acid using gas chromatography. Spearman correlation analysis was conducted to identify SCFAs that correlated with the total BI score. Linear regressions were evaluated to explore the correlation between the total BI score and SCFAs.Results:The concentrations of propionic and butyric acids in the feces were found to correlate significantly with the total BI scores. Data including propionic acid and butyric acid levels, age, gender, body mass index, disease duration, any history of hypertension or diabetes, and other SCFAs were included in the regression models. Propionic and butyric acid levels were found to be potentially useful predictors of total BI scores.Conclusions:The concentration of propionic and butyric acids in the feces after an ischemic stroke can predict the survivor′s total BI score. Those concentrations could therefore be useful for predicting ADL ability.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.