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Abstract Background Sham acupuncture is a widely accepted control in acupuncture clinical trials. Given the nature of acupuncture, it is warranted to assess the blinding of sham-controlled trials. Despite the sham acupuncture design having been widely used, the overall blinding of sham acupuncture and the characteristics of blinding assessment in acupuncture trials are unclear. This research aims to assess the blinding status of acupuncture clinical trials and explore the blinding assessment characteristics in acupuncture trials. Methods This meta-analysis included all the acupuncture clinical trials published in English that performed blinding assessments and reported the results. We searched PubMed, Embase, and Web of Science for randomized controlled trials (RCTs) from inception to April 2024. The primary outcome is Bang’s Blinding Index (Bang’s BI) and 95% credibility interval (CrI) was pooled using a Bayesian hierarchical model. The study adheres to the PRISMA guidelines. Results Sixty-four eligible studies published from 1999 to 2024 were included. The mean of Bang’s BI was − 0.24 (95% CrI − 0.34 to − 0.14, tau2 = 0.13) for the sham acupuncture group and 0.41 (95% CrI 0.32 to 0.49, tau2 = 0.10) for the verum acupuncture group. The characteristics of blinding showed that 62.50% of the trials had a Bang’s BI greater than 0 in the verum group and less than 0 in the sham group; in 28.15% of the trials, the Bang’s BI was greater than 0 in the verum group and greater than 0 in the sham group. Subgroup analysis revealed that area, number of research centers, treatment sessions, acupoints number, and evaluation timepoint can influence blinding results. Conclusion Overall blinding status in current acupuncture clinical trials shows a majority correctly guessing for the verum group and opposite guessing for the sham group. However, in some acupuncture trials, the blinding of sham acupuncture might be compromised. Factors such as the Asian population, penetrating sham needling, and querying participants about their group assignment during the study increase the risk of unblinding and warrant careful consideration in sham acupuncture control design. Furthermore, researchers should closely monitor the blinding status of sham acupuncture and transparently report details of blinding assessments. Systematic review registration PROSPERO CRD42023403595.

Abstract Background Timely and accurate prediction of disease progress is crucial for facilitating early intervention and treatment for various chronic diseases. However, due to the complicated and longitudinal nature of disease progression, the capacity and completeness of clinical data required for training deep learning models remains a significant challenge. This study aims to explore a new method that reduces data dependency and achieves predictive performance comparable to existing research. Methods This study proposed DAPNet, a deep learning-based disease progression prediction model that solely utilizes the comorbidity duration (without relying on multi-modal data or comprehensive medical records) and disease associations from biomedical knowledge graphs to deliver high-performance prediction. DAPNet is the first to apply multi-view graph contrastive learning to disease progression prediction tasks. Compared with other studies on comorbidities, DAPNet innovatively integrates molecular-level disease association information, combines disease co-occurrence and ICD10, and fully explores the associations between diseases; Results This study validated DAPNet using a de-identified clinical dataset derived from medical claims, which includes 2,714 patients and 10,856 visits. Meanwhile, a kidney dataset (606 patients) based on MIMIC-IV has also been constructed to fully validate its performance. The results showed that DAPNet achieved state-of-the-art performance on the severe pneumonia dataset (F1=0.84, with an improvement of 8.7%), and outperformed the six baseline models on the kidney disease dataset (F1=0.80, with an improvement of 21.3%). Through case analysis, we elucidated the clinical and molecular associations identified by the DAPNet model, which facilitated a better understanding and explanation of potential disease association, thereby providing interpretability for the model. Conclusions The proposed DAPNet, for the first time, utilizes comorbidity duration and disease associations network, enabling more accurate disease progression prediction based on a multi-view graph contrastive learning, which provides valuable insights for early diagnosis and treatment of patients. Based on disease association networks, our research has enhanced the interpretability of disease progression predictions.

BackgroundThe novel coronavirus infection is widespread in the world, resulting in more pneumoconiosis patients complicated with coronavirus disease 2019 (COVID-19). ObjectiveTo understand the clinical characteristics and prognosis of hospitalized COVID-19 patients complicated with or without pneumoconiosis. MethodsA total of 36 COVID-19 patients admitted to the Shandong Provincial Occupational Disease Hospital from 10 December to 31 December 2022 were selected, including 21 cases in the complication group (pneumoconiosis complicated with COVID-19) and 15 cases in the COVID-19 group without pneumoconiosis. Symptoms, signs, laboratory test results(e.g. routine blood test), imaging findings, treatment plans and prognosis of the two groups were observed and compared.ResultsRegarding symptoms and signs in the complication group and the COVID-19 group, the proportions of dyspnea (57.14% vs 0.00%), lung wheezing (28.57% vs 0.00%), wet rales (76.19% vs 33.30%), and fever (61.90% vs 93.33%) were significantly different (P

Abstract Norcoclaurine synthase from Thalictrum flavum (TfNCS) demonstrated high stereospecificity and yield in catalyzing the Pictet-Spengler reaction of dopamine with chiral aldehydes, achieving kinetic resolution of aldehydes. However, the mechanism and the factors contributing to the stereoselectivity remain unclear. Herein, by using quantum chemical calculations, the mechanisms of TfNCS-catalyzed reactions of dopamine with both enantiomers of α-methyl-phenylacetaldehyde are studied. The calculations reveal a mechanism mirroring the reaction of natural substrates, for which the deprotonation of the C5−H of the cyclized intermediate is rate-limiting. The calculated overall barriers are 20.1 kcal mol-1 and 21.6 kcal mol-1 for the reactions of (R)- and (S)-α-methyl-phenylacetaldehyde, respectively. The M97 and L72 residues are proposed to be the key residues contributing to the stereospecificity. The obtained detailed information is helpful for designing new variants of TfNCS with extended substrate scope, and also advancing our understanding of TfNCS reactions for potential applications.

Abstract Symptom phenotypes have continuously been an important clinical entity for clinical diagnosis and management. However, non-specificity of symptom phenotypes for clinical diagnosis is one of the major challenges that need be addressed to advance symptom science and precision health. Network medicine has delivered a successful approach for understanding the underlying mechanisms of complex disease phenotypes, which will also be a useful tool for symptom science. Here, we extracted symptom co-occurrences from clinical textbooks to construct phenotype network of symptoms with clinical co-occurrence and incorporated high-quality symptom-gene associations and protein–protein interactions to explore the molecular network patterns of symptom phenotypes. Furthermore, we adopted established network diversity measure in network medicine to quantify both the phenotypic diversity (i.e., non-specificity) and molecular diversity of symptom phenotypes. The results showed that the clinical diversity of symptom phenotypes could partially be explained by their underlying molecular network diversity (PCC = 0.49, P-value = 2.14E-08). For example, non-specific symptoms, such as chill, vomiting, and amnesia, have both high phenotypic and molecular network diversities. Moreover, we further validated and confirmed the approach of symptom clusters to reduce the non-specificity of symptom phenotypes. Network diversity proposes a useful approach to evaluate the non-specificity of symptom phenotypes and would help elucidate the underlying molecular network mechanisms of symptom phenotypes and thus promotes the advance of symptom science for precision health.

Abstract Objectives This study aimed to explore the spatial distribution of brain metastases (BMs) from small cell lung cancer (SCLC) a homogenous sample, and to identify the metastatic risk levels in brain regions. Methods T1-enhanced magnetic resonance imaging (MRI) from SCLC patients were retrospectively reviewed from three medical institutions in China. All images were registered to the standard brain template provided by the Montreal Neurological Institute (MNI) 152 database, followed by transformation of the location of all BMs to the space of standard brain. The MNI structural atlas and Anatomical Automatic Labeling (AAL) atlas were then used to identify the anatomical brain regions, and the observed and expected rates of BMs were compared using 2-tailed proportional hypothesis testing. The locations and sizes of brain lesions were analyzed after image standardization. Results A total of 215 eligible patients with 1033 lesions were screened by MRI, including 157 (73%) males and 58 (27%) females. The incidence of crucial structures were as follows: hippocampus 0.68%, parahippocampal 0.97%, brainstem 2.05%, cauate 0.68%, putamen 0.68%, pallidum 0.2%, thalamus 1.36%. No BMs were found in the amygdala, pituitary gland, or pineal gland. The cumulative frequency of the important structures was 6.62%. Based on the results of MNI structural atlas, the cerebellum, deep white matter and brainstem was identified as a higher risk region than expected for BMs (P = 9.80 ×10−15, 9.04 ×10−6), whereas temporal lobe were low-risk regions (P = 1.65 ×10−4). More detailed AAL atlas revealed that the low-risk regions for BMs was inferior frontal gyrus (P = 6.971 ×10−4), while the high-risk regions for BMs was cerebellar hemispheres (P = 1.177 ×10−9). Conclusion Many crucial structures including the hippocampus, parahippocampus, pituitary gland and thalamus etc. have low frequency of brain metastases in a population of SCLC patients. This study provides the help to investigate the clinical feasibility of HA-WBRT and non-uniform dose of PCI in a population of SCLC patients.

Abstract Background Syndrome differentiation aims at dividing patients into several types according to their clinical symptoms and signs, which is essential for traditional Chinese medicine (TCM). Several previous works were devoted to employing the classical algorithms to classify the syndrome and achieved delightful results. However, the presence of ambiguous symptoms substantially disturbed the performance of syndrome differentiation, This disturbance is always due to the diversity and complexity of the patients’ symptoms. Methods To alleviate this issue, we proposed an algorithm based on the multilayer perceptron model with an attention mechanism (ATT-MLP). In particular, we first introduced an attention mechanism to assign different weights for different symptoms among the symptomatic features. In this manner, the symptoms of major significance were highlighted and ambiguous symptoms were restrained. Subsequently, those weighted features were further fed into an MLP to predict the syndrome type of AIDS. Results Experimental results for a real-world AIDS dataset show that our framework achieves significant and consistent improvements compared to other methods. Besides, our model can also capture the key symptoms corresponding to each type of syndrome. Conclusion In conclusion, our proposed method can learn these intrinsic correlations between symptoms and types of syndromes. Our model is able to learn the core cluster of symptoms for each type of syndrome from limited data, while assisting medical doctors to diagnose patients efficiently.

Abstract Background Poor ovarian response (POR), a manifestation of low ovarian reserve and ovarian aging, leads to a significant reduction in the pregnancy rate after in vitro fertilization-embryo transfer. Acupuncture has increasingly been used to improve the ovarian reserve. The purpose of this study will be to evaluate the effect of acupuncture on increasing the number of retrieved oocytes after controlled ovarian hyperstimulation in women with POR. Methods This will be a multicenter randomized controlled trial. A total of 140 women with POR will be randomly assigned to receive acupuncture or nontreatment for 12 weeks before controlled ovarian hyperstimulation. The primary outcome will be the number of retrieved oocytes. The secondary outcomes will be antral follicle counts, serum levels of anti-Müllerian hormone, basal serum levels of follicle stimulating hormone, luteinizing hormone and estradiol levels, scores from the self-rating anxiety scale, fertilization rates, cleavage rates, available embryo rates, and high-quality embryo rates. The safety of acupuncture will also be assessed. Discussion The results of this trial will help to determine the effectiveness of acupuncture in the treatment of POR. This may provide a new treatment option for patients with POR and their physicians. Trial registration AMCTR-IPR-18000198 . Registered on 10 August 2018.

Background Several systematic reviews have suggested that acupuncture is effective against functional constipation, but it is unknown whether variations in treatment effect across subgroups remain consistent. Our purpose of this study is to explore the heterogeneity of treatment effect of acupuncture on functional constipation across subgroups. Methods We will search eleven English and Chinese electronic databases and three clinical trial registries from inception to December 2021. Randomized controlled trials that evaluate acupuncture compared with sham acupuncture or no treatment for functional constipation will be eligible if they report at least one primary outcome. The primary outcomes will include the change in weekly complete spontaneous bowel movements or spontaneous bowel movements from baseline. Two authors will independently identify the relevant studies, assess the risk of bias using the Cochrane RoB 2 tool and contact the primary researchers of the eligible trials for individual patient data. Individual patient data obtained from the original trial author will be standardized and all trial data will be combined into a single database. Generalized linear mixed effects model will be used to determine possible subgroup effects by adding an interaction term for predefined subgroup and treatment. Systematic review registration International Prospective Register of Systematic Reviews (Number: CRD42020188366).

Abstract Background Disease comorbidity is popular and has significant indications for disease progress and management. We aim to detect the general disease comorbidity patterns in Chinese populations using a large-scale clinical data set. Methods We extracted the diseases from a large-scale anonymized data set derived from 8,572,137 inpatients in 453 hospitals across China. We built a Disease Comorbidity Network (DCN) using correlation analysis and detected the topological patterns of disease comorbidity using both complex network and data mining methods. The comorbidity patterns were further validated by shared molecular mechanisms using disease-gene associations and pathways. To predict the disease occurrence during the whole disease progressions, we applied four machine learning methods to model the disease trajectories of patients. Results We obtained the DCN with 5702 nodes and 258,535 edges, which shows a power law distribution of the degree and weight. It further indicated that there exists high heterogeneity of comorbidities for different diseases and we found that the DCN is a hierarchical modular network with community structures, which have both homogeneous and heterogeneous disease categories. Furthermore, adhering to the previous work from US and Europe populations, we found that the disease comorbidities have their shared underlying molecular mechanisms. Furthermore, take hypertension and psychiatric disease as instance, we used four classification methods to predicte the disease occurrence using the comorbid disease trajectories and obtained acceptable performance, in which in particular, random forest obtained an overall best performance (with F1-score 0.6689 for hypertension and 0.6802 for psychiatric disease). Conclusions Our study indicates that disease comorbidity is significant and valuable to understand the disease incidences and their interactions in real-world populations, which will provide important insights for detection of the patterns of disease classification, diagnosis and prognosis.

Abstract Background Both doctors’ and patients’ opinions are important in the process of treatment and healthcare of Chinese medicine. This study is to compare patients’ and doctors’ treatment satisfaction over the course of two visits in a Chinese medicine outpatient setting, and to explain their respective views. Methods Patients’ chief complaints were collected prior to the outpatient encounter. The doctor was then asked (through a questionnaire) to state what complaints he or she was prioritizing during the process of diagnosing disease and making a prescription for herbal medicine or acupuncture treatment. On the next visit, both the patient and the doctor completed a questionnaire assessing satisfaction with the treatment of Chinese medicine prescribed in the first visit and administered by the patient at home. A 5-point Likert scales was used to assess the patients’ and doctors’ satisfaction with treatment. The timing of the follow-up appointment was determined by the doctor. One chief specialist, one associate chief specialist and one attending practitioner in Chinese medicine, and 60 patients having a follow-up appointment with one of the doctors, participated in the study. Results For 11 patients, their most urgent complaint was different from what the doctor’s choose to focus on in his or her treatment. And only one patient refused to comply due to his or her dissatisfaction with the treatment focus of the doctor. Overall, 59 patients completed the satisfaction assessment, and 53 patients visited their doctors for a follow-up appointment. Patients’ total satisfaction was higher than their doctors’ (mean 3.55 vs. 3.45), and correlation of patients’ and doctors’ treatment satisfaction was moderate (r = 0.63, P

Abstract Objective Acupuncture therapy for chronic low back pain (CLBP) has received increasing attention. Nevertheless, the evidence of efficacy and safety of random controlled trials (RCTs) remains controversial. Acupuncture as a complex intervention influenced by many factors, its effectiveness in treating chronic low back pain in the real world is unknown. We will develop a network-based registry study to evaluate the effectiveness and safety of acupuncture for the treatment of chronic low back pain and explore key factors affecting efficacy in the real world. Methods A prospective, multi-center and dynamic registry study. All acupuncture related information will be collected through a high-quality structured network platform. Patients with CLBP included in the study met the following criteria: age from 16 to 80 years, using acupuncture as a main therapy and voluntarily signing the informed consent. At least 2000 patients, 27 acupuncturist, and 9 medical centers will be recruited under actual clinical settings at the first stage. Numeric rating scale (NRS), Oswestry Disability Index (ODI) and Effective rate will be measured in pain and functional disability assessment, respectively, as the primary outcome. Evaluation index will be collected at the baseline and follow-up in 1, 4, 12 weeks after the last visit. Hierarchical models and regression analysis will be used to explore the key factors affecting acupuncture effectiveness. Effects between propensity matching groups (Traditional Chinese acupuncture style vs Microacupuncture style, Local acupoint selection vs Non-local acupoint selection, Single Acupuncture vs Combined therapy) will be compared. Discussion This study will be conducted based on the characteristics of acupuncture therapy in the “Real World”. Fundamental factors affecting the clinical effectiveness of acupuncture and the preferred acupuncture regimen in the treatment of CLBP will be identified. Reliable acupuncture evidence for the treatment of CLBP through the registry will be a significant supplement to the RCTs. Trial registration Chinese Clinical Trial Registry, ChiCTR-OOC-17010751 and Acupuncture-Moxibustion Clinical Trial Registry, AMCTR-OOO-17000045. Registered date on 3 December 2016.

As a well-established multidrug combinations schema, traditional Chinese medicine (herbal prescription) has been used for thousands of years in real-world clinical settings. This paper uses a complex network approach to investigate the regularities underlying multidrug combinations in herbal prescriptions. Using five collected large-scale real-world clinical herbal prescription datasets, we construct five weighted herbal combination networks with herb as nodes and herbal combinational use in herbal prescription as links. We found that the weight distribution of herbal combinations displays a clear power law, which means that most herb pairs were used in low frequency and some herb pairs were used in very high frequency. Furthermore, we found that it displays a clear linear negative correlation between the clustering coefficients and the degree of nodes in the herbal combination network (HCNet). This indicates that hierarchical properties exist in the HCNet. Finally, we investigate the molecular network interaction patterns between herb related target modules (i.e., subnetworks) in herbal prescriptions using a network-based approach and further explore the correlation between the distribution of herb combinations and prescriptions. We found that the more the hierarchical prescription, the better the corresponding effect. The results also reflected a well-recognized principle called “Jun-Chen-Zuo-Shi” in TCM formula theories. This also gives references for multidrug combination development in the field of network pharmacology and provides the guideline for the clinical use of combination therapy for chronic diseases.

Traditional Chinese Medicine (TCM) has received increasing attention as a complementary approach or alternative to modern medicine. However, experimental methods for identifying novel targets of TCM herbs heavily relied on the current available herb-compound-target relationships. In this work, we present an Herb-Target Interaction Network (HTINet) approach, a novel network integration pipeline for herb-target prediction mainly relying on the symptom related associations. HTINet focuses on capturing the low-dimensional feature vectors for both herbs and proteins by network embedding, which incorporate the topological properties of nodes across multi-layered heterogeneous network, and then performs supervised learning based on these low-dimensional feature representations. HTINet obtains performance improvement over a well-established random walk based herb-target prediction method. Furthermore, we have manually validated several predicted herb-target interactions from independent literatures. These results indicate that HTINet can be used to integrate heterogeneous information to predict novel herb-target interactions. Keywords: Network medicine, Herb target prediction, Symptoms, Network embedding

Abstract Background Unplanned readmission within 31 days of discharge after stroke is a useful indicator for monitoring quality of hospital care. We evaluated the risk factors associated with 31-day unplanned readmission of stroke patients in China. Methods We identified 50,912 patients from 375 hospitals in 29 provinces, municipalities or autonomous districts across China who experienced an unplanned readmission after stroke between 2015 and 2016, and extracted data from the inpatients’ cover sheet data from the Medical Record Monitoring Database. Patients were grouped into readmission within 31 days or beyond for analysis. Chi-squared test was used to analyze demographic information, health system and clinical process-related factors according to the data type. Multilevel logistic modeling was used to examine the effects of patient (level 1) and hospital (level 2) characteristics on an unplanned readmission ≤31 days. Results Among 50,912 patients, 14,664 (28.8%) were readmitted within 31 days after discharge. The commonest cause of readmissions were recurrent stroke (34.8%), hypertension (22.94%), cardio/cerebrovascular disease (13.26%) and diabetes/diabetic complications (7.34%). Higher risks of unplanned readmissions were associated with diabetes (OR = 1.089, P = 0.001), use of clinical pathways (OR = 1.174, P

Background: Electroacupuncture (EA) has been shown to improve complete spontaneous bowel movements (CSBMs), but the duration of its effects remains unknown. The objective of this study was to explore the duration of acupuncture effects after treatment and its associated factors for chronic severe functional constipation (CSFC). Methods: This was a secondary analysis of a multicenter, randomized, sham-acupuncture (SA) controlled trial that included 1075 participants with CSFC. The primary outcome, the duration of acupuncture effects after treatment, was the number of weeks during the 12-week follow-up period that participants were to meet the weekly CSBM responder criteria. A weekly CSBM responder was defined as a participant who had at least three CSBMs for a given week and an increase from baseline of at least one CSBM for that same week. We performed a retrospective multivariate analysis to explore potential factors associated with sustained acupuncture effects. Results: The duration of acupuncture effects in the EA group (5.5 weeks) was significantly higher than the duration of SA effects in the SA group (2.2 weeks) with a between-group difference of 3.2 weeks (95% CI, 2.77–3.78; p

Acupuncture has been demonstrated to be effective and safe for chronic severe functional constipation (CSFC). However, which patients with CSFC will have a better response to acupuncture remains unclear.To explore factors related to acupuncture response in patients with CSFC.We performed a secondary analysis of a previous multicenter randomized controlled trial consisting of a 2-week run-in period, 8-week treatment, and 12-week follow-up without treatment in which patients with CSFC were randomly allocated to an electroacupuncture group or a sham electroacupuncture group. Responders were defined as participants with an increase of at least one complete spontaneous bowel movement (CSBM) in week 20 compared with the baseline period. The CSBM responder rate in both groups was described, and the baseline characteristics of participants potentially related to acupuncture response were mainly analyzed using logistic regression analysis with bootstrapping techniques.A total of 1021 participants were analyzed in this study, of whom 516 (50.5%) were classified as responders. The CSBM responder rate in week 20 was significantly greater in the electroacupuncture group than in the sham electroacupuncture group (62.9% vs. 37.9%, respectively; P

BACKGROUND:Acupuncture is a potential conservative therapy for women with stress urinary incontinence (SUI). There is limited evidence to support its effectiveness due to the poor quality of existing studies. METHODS:We performed a pilot randomized, controlled trial to preliminarily assess the efficacy of electroacupuncture (EA) in women with pure SUI. A total of 80 women with pure SUI were randomly assigned to receive EA with deep needling at BL33 and BL35 (n = 40) or sham EA with non-penetrating needling at sham acupoints (n = 40) three sessions per week for 6 weeks. The women were followed for 24 weeks. The primary outcome was the change from baseline in the amount of urine leakage measured by a 1-hour pad test after 6 weeks. The secondary outcomes included the 72-hour incontinence episode frequency (IEF), International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF) score, and patient self-evaluation of therapeutic effect. Adverse events (AEs) were monitored throughout the trial. RESULTS:The median decrease from baseline of urine leakage measured by the 1-hour pad test was 2.5 g [interquartile range (IQR): 1.80-14.6 in the EA group, which was greater than the median decrease of 0.05 g (IQR: -2.80-+0.50) in the sham EA group after 6 weeks (p

Mild hand, foot and mouth disease (HFMD) is at a critical stage owing to its ease of communicability and a higher risk of developing severe complications and death. Clinical diagnosis of mild HFMD was made by the presenting symptoms and signs (symptoms in brief) alone. We aim to evaluate the frequencies of symptoms in a retrospective case series study.We collected epidemiological, demographic, clinical, and laboratory data from outpatient and inpatient settings on the clinical data warehouse system. We principally described the frequencies of symptoms of mild HFMD. Correlations between symptoms with laboratory-confirmed cases were then analyzed.The clinical data warehouse system included 3649 probable cases, between 2010 and 2012, of which 956 (26.20%) were laboratory confirmed. The peak incidence was identified in children 2 years of age. A total of 370 of the 956 laboratory confirmed cases (38.70%) were associated with enterovirus 71 (EV71). Logistic regression analysis adjusted for geographical variables, age, sex, month of onset, and time from onset to diagnosis showed that the clinical features constipation (P