Background: Recurrent pregnancy loss undermines the physical and mental health of women. Recent randomized controlled trials have reported some effects of traditional Chinese medicine (TCM); however, whether various TCM methods have different effectiveness remains unclear. Objective: To comprehensively evaluate the efficacy and adverse events of TCM for patients with RPL and to explore whether various TCM methods have different effectiveness. Methods: Ten databases were searched up to May 27, 2024. The risk of bias was assessed using the RoB2 tool. The certainty of the evidence was evaluated using the grading of Recommendations, Assessment, Development, and Evaluation tool. Pairwise and network analyses were conducted using Stata 18.0. Results: A total of 47 randomized controlled trials enrolling 6678 women with RPL were included. Pairwise analysis showed that use of TCM had a significantly lower miscarriage rate (RR 0.50 [95% CI 0.45, 0.55]), lower preterm birth rate (RR 0.81 [95% CI 0.67, 0.98), and lower adverse event rate (RR 0.46 [95% CI 0.37, 0.58]). Moreover, use of TCM was associated with a higher alive-fetus rate (RR 1.21 [95% CI 1.15, 1.26]), live-birth rate (RR 1.20 [95% CI 1.15, 1.25]), and full-term rate (RR 1.37 [95% CI 1.23, 1.53]) compared with nonuse of TCM. Network analysis demonstrated that Bushenshugan combined with conventional Western medicine was ranked the best for the reduction of miscarriage rate. Discussion: Use of TCM is more likely to improve pregnancy outcomes and reduce adverse events compared with nonuse of TCM in patients with RPL. Different TCM methods have differences in reducing the miscarriage rate. The Bushenshugan method might be a potential optimal TCM therapy, but more high-quality evidence is needed to further validate and evaluate the efficacy and safety.

OBJECTIVE To construct a closed-loop management model for externally dispensed intravenous prescriptions， and to provide reference for standardized management of externally dispensed intravenous prescriptions. METHODS Based on the Expert Consensus on Closed-loop Management of Externally Dispensed Intravenous Prescriptions in Guangxi Zhuang Autonomous Region previously formulated by our hospital， risk points during the entire process were systematically identified through multidisciplinary team brainstorming and a fishbone diagram. A series of strategies were subsequently formulated and implemented， including qualifying designated external dispensing pharmacies and the drug catalogs， operating and maintaining the hospital information system and the Pharmacy Intravenous Admixture Service （PIVAS） intelligent management platform， and strengthening differentiated training for staff in the whole workflow. A whole-process closed-loop management system was constructed with PIVAS as the co re hub and the daytime chemotherapy center as the safety terminal. RESULTS A total of 3 cooperating pharmacies and an initial drug list comprising 35 product specifications were selected. A closed‑loop management process encompassing hospital outpatient prescribing， patient drug purchase in designated pharmacies， PIVAS drug dispensing， and medication use in daytime chemotherapy center was successfully established. This system enabled the mandatory grouping and association of externally dispensed intravenous prescriptions with in-hospital diluents， full-process verification based on drug traceability codes， intelligent monitoring of infusion parameters， and whole-process data traceability. CONCLUSIONS The constructed model effectively resolves the coordination and safety oversight during the use of externally dispensed intravenous drugs from out-of-hospital circulation to in-hospital use， and has preliminarily enabled procedural standardization， whole-process information traceability， and proactive control of medication risks.

Primary biliary cholangitis(PBC)is a chronic progressive autoimmune liver disease that is often comorbid with other connective tissue diseases(CTDs),and such comorbidity can significantly alter the natural course or clinical phenotype of PBC or CTDs,limiting available therapeutic drugs and complicating clinical decision-making.Due to the involvement of the interdisciplinary subjects of hepatology,rheumatology,and clinical immunology and a paucity of large-scale cohort data and in-depth basic research,there is a limited understanding of such comorbidity in clinical practice,which increases the complexity of clinical diagnosis and treatment.This article summarizes the comorbidity of PBC with common CTDs such as Sj?gren's syndrome,systemic sclerosis,systemic lupus erythematosus,and idiopathic inflammatory myopathies,and analyzes related immune mechanisms,clinical manifestations,diagnostic challenges,treatment strategies,and prognosis.It is expected to establish PBC-CTD comorbidity cohorts through future multidisciplinary collaborations,focus on genetic background,immune mechanisms,and multi-omics approaches,elucidate pathogenesis and novel therapeutic targets,and improve the prognosis of patients by optimizing treatment strategies through precision medicine and artificial intelligence.

Pharmacoepidemiology is an interdisciplinary field that applies epidemiological methods to study drug use,effectiveness,and associated risk in populations.Standardizing research methods in this field is crucial for ensuring research quality and promote the development of the discipline.Based on the Guide on Methodological Standards in Pharmacoepidemiology in China(2nd edition),this article interprets the relevant contents about classic research types and their derivative designs.It aims to clarify the types of study methodological designs in pharmacoepidemiology,systematically describe the characteristics and applications classical derivative designs,and compare these with research design frameworks outlined in international pharmacoepidemiological guidelines.Compared to the first edition,the second edition of the guideline has updated and detailed the types of research,updating the research design to original research(interventional research and non-interventional research),secondary research(systematic review,Meta-analysis,economic analysis,etc.),and tertiary research(umbrella review,etc.).Additionally,a variety of derivative designs have been added,including target trial emulation,nested case-control and case-cohort studies,case-crossover designs,self-controlled case series and self-controlled risk interval designs,case-population studies,interrupted time-series analysis,and case-coverage(ecological)designs for vaccine surveillance.This article strengthens the operability of the theoretical guidance of pharmacoepidemiological research methods in practice and provides a reference for conducting high-quality pharmacoepidemiological research.

Dupilumab is a fully human monoclonal antibody that exerts its effects by targeting and binding to the interleukin (IL)-4 receptor alpha subunit, thereby blocking IL-4/13 signaling and downregulating Type 2 inflammation. It has been approved in China for the treatment of moderate-to-severe atopic dermatitis (AD) in patients aged 6 months and older, as well as prurigo nodularis (PN) and bullous pemphigoid in adults. Given its approval age and safety profile, the application of Dupilumab in children has unique advantages, and it has been widely used in the treatment of various Type 2 inflammation-associated and other pediatric dermatologic conditions.Early and proactive management of type 2 inflammatory dermatoses may have preventive and therapeutic implications for modulating the atopic march and type 2 inflammatory comorbidities. This article reviews and summarizes the recent applications of dupilumab in pediatric dermatological diseases.

Objective:To construct a recommended list of high-alert medication (HAM) based on big data from medication error (ME) reports in China, providing reference for preventing and reducing HAM-related risks.Methods:The drugs involved in the serious ME reports of the National Monitoring Network for Clinical Safe Medication (Monitoring Network) were collected (as of December 31, 2023), and the candidate drugs were preliminarily determined referring to the HAM list of China 2023 (Chinese list) and the latest three lists of American Institute for Safe Medication Practices (ISMP). Candidate drugs that were included in both the Chinese list and ISMP lists, as well as those existed in the Chinese list but had never been included in the ISMP lists were included in the current list, and their risk levels followed the original risks in the Chinese list. Candidate drugs that existed in the Chinese list but had been excluded from the ISMP lists, and those existed in the ISMP lists but had not been included in the Chinese list were listed as suspected drugs. For the other candidate drugs, those did not meet the definition of HAM were excluded firstly, and those related to ME that had caused serious harm were listed as suspected drugs, according to the judicial cases on ME of China Judgements Online and PKULAW database. Two methods, including Delphi expert consultation and questionnaire survey, were used to determine whether the above suspected drugs were included in the HAM list and their risk levels.Results:A total of 138 drugs were obtained through the initial screening, 106 of which were directly included in the current list, and 32 of which were listed as drugs requiring further assessment. After 2 rounds of Delphi expert consultation by 18 experts and surveys with 136 valid questionnaires, 32 suspected drugs did not meet the inclusion criteria. Finally, a total of 106 drugs were included in the current list, including 51 A-class drugs in 9 categories, 33 B-class drugs in 9 categories, and 22 C-class drugs in 5 categories.Conclusion:Based on the big data of the ME reports in China, a HAM list is constructed, which is accurate and concise and better fits the actual clinical drug risks in China, helping to improve the drug safety management.

Objective:To explore the causes of medication errors (ME) associated with deslanoside injection and put forward targeted preventive recommendations.Methods:ME reports related to deslanoside injection in the National Monitoring Network for Clinical Safe Medication (Monitoring Network) as of August 31, 2024 were collected, and sever ME cases of deslanoside injection were also collected though searching medical literature databases at home and abroad, China Judgements Online, and PKULAW database at the same period. The level of severity, occurrence link, error content, occurrence place, trigger personnel and patient outcomes of the MEs were retrospectively analyzed.Results:The Monitoring Network received a total of 41 ME reports of deslanoside injection from September 2012 to August 2024, and the number of reports showed an upward trend year by year. These MEs were classified as grade A in 1 case (2.4%), grade B in 18 cases (43.9%), grade C in 17 cases (41.5%), grade D in 4 cases (9.8%), and grade F in 1 case (2.4%). There were 63.4% (26/41) of MEs occurring in the prescription/doctor′s order prescribing and delivery links, mainly caused by physicians, and the common error contents included solvent errors, medication under contraindications, and having drug-drug interactions. In addition, 26.8% (11/41) of MEs occurred in the drug dispensing and distribution link, and 9.8% (4/41) occurred in the administration and monitoring links. A total of 4 severe MEs of deslanoside injection were collected from the Monitoring Network, medical literature and judicial cases, all of which occurred in the prescription/doctor′s order prescribing and delivery links. Among the 4 severe MEs, 2 ME cases of grade I occurred due to incorrect usage and dosage, resulting in patient death; 1 ME case of grade F was caused by interaction with traditional Chinese medicine, resulting in digitalis poisoning, and another case of grade F was that deslanoside injection was administered to a patient with digitalis poisoning (medication under contraindications).Conclusions:MEs of deslanoside injection often occurs in the prescription/doctor′s order prescribing and delivery links, mainly because of insufficient knowledge of doctors to the drug instructions. It is suggested to strengthen learning and training of medical staff centered around drug instructions, and improve the system interception and process management, so as to improve the medication safety.

Objective:To explore the impact of sleep disturbances on the symptoms and functional impairment outcomes in children with attention deficit hyperactivity disorder (ADHD) and their path analysis.Methods:A cross-sectional study was made.Two hundred and seventy-eight ADHD children aged 6-12 years were selected from the Center for Cognition and Sleep, the People′s Hospital of Guangxi Zhuang Autonomous Region from January 2022 to March 2023.The Swanson, Nolan and Pelham Rating Scale Ⅳ was used to evaluate the core symptoms of ADHD (namely, attention deficit and hyperactivity).The sleep disturbance scale for children was used to assess sleep disturbances [including disorders in initiating and maintaining sleep(DIMS), sleep breathing disorders, sleep-wake transition disorders (SWTD), disorders of arousal, disorders of excessive somnolence (DOES) and nocturnal hyperhidrosis].The Weiss Functional Impairment Rating Scale-Parent Report (WFIRS-P) was used to assess functional impairment (in family, learning and school, life skills, self-concept, social activities, and risky activities).The descriptive statistical analysis, t test, multivariate linear regression and path analysis were used for statistical analysis. Results:Compared with those without sleep disturbances, ADHD children with sleep disturbances had significantly more serious functional impairment in family [(0.87±0.42) scores vs.(0.63±0.45) scores, P<0.001], learning and school [(0.75±0.37) scores vs.(0.62±0.35) scores, P=0.011], life skills [(1.30±0.37) scores vs.(1.08±0.30) scores, P<0.001], self-concept [(1.20±0.57) scores vs.(0.92±0.49) scores, P<0.001], social activities [(0.88±0.44) scores vs.(0.67±0.42) scores, P<0.001] and risky activities [(0.28±0.24) scores vs.(0.21±0.21) scores, P=0.043].The results of multivariate linear regression analysis showed that after adjusting for gender, age, total intelligence quotient, and core symptoms of ADHD, the regression coefficients of DOES in domains of family ( B=0.02, P=0.042) and life skills ( B=0.03, P<0.001) and the regression coefficient of DIMS in self-concept were still statistically significant ( B=0.02, P=0.013).The path analysis results showed that DOES ( β=0.170, P=0.004), attention deficit ( β=0.223, P<0.001) and hyperactivity ( β=0.385, P<0.001) directly affected WFIRS-P.DOES indirectly affected WFIRS-P through attention deficit ( β=0.270, P<0.001), and SWTD indirectly affected WFIRS-P through hyperactivity ( β=0.199, P=0.004). Conclusions:Severer sleep disturbances are associated with severer functional impairment in children with ADHD, and sleep phenotypes can directly or indirectly affect functional impairment outcomes in different domains in children with ADHD through core symptoms of ADHD.

Objective:To comprehensively evaluate the application of Common Data Model (CDM) of Observational Medical Outcomes Partnership (OMOP) in China, and provide reference for the implementation of data standardization and evidence sharing in China.Methods:PubMed, Embase, Web of Science, CNKI, VIP, WanFang and SinoMed databases were used for literature retrieval to collect the research papers of OMOP CDM application for data standardization in China until March 15, 2023. The information about institutions, types and numbers of patients were extracted.Results:A total of 14 research papers, including 9 in English and 5 in Chinese, were selected. The research papers published since 2018 were collected, which focused on patients with hypertension, diabetes, and depression. A total of 12 institutions or platforms transformed data into OMOP CDM. Jiangsu Provincial People's Hospital was the first one to apply the CDM and demonstrated its feasibility in China. Additionally, the regional information system in Yinzhou District of Ningbo, Zhejiang Province, standardized the multi-dimensional data of patients with diabetes and hypertension. Based on this platform, a series of prediction models for complications in patients with diabetes were constructed. Another major database in Beijing Anding Hospital applied OMOP CDM to analyze the characteristics of patients with late-life depression and dementia.Conclusions:This study analyzed the application of OMOP CDM in China. Through in-depth analysis of specific cases, the study provided guidance for the future cross-regional evidence sharing and collaboration.

Objective:To systematically review the progress in the method development and application of distributed learning in the estimation of epidemiological effect and provide methodological reference for multi-center studies.Methods:We conducted a literature retrieval for English papers published up to December 31, 2023 by using keywords of "health/medical big data" and "distributed/federated learning". After consulting experts, we set criteria of paper inclusion and exclusion and created a framework for data extraction. We collected information about basic study details, including method, application, and evaluation. Two researchers independently screened the papers and extracted information. We used EndNote 20 for the management of literatures and EpiData for the management of data.Results:A total of 3 444 papers were collected, and 29 papers were included in the final analysis. Most of the papers (25, 86.2%) were published in or after 2019, and the papers were mainly from the United States (21/29, 72.4%). For the estimation of epidemiological effects, 22 distributed learning methods had been developed, including methods for logistic regression (8), Cox regression (8), Poisson regression (2), and generalized linear mixed model (GLMM) (4), as well as three platforms for distributed analysis (VLP, Vantage6, AusCAT). The 29 papers described 45 applications, with 20 (44.4%) focusing on the establishment of prediction model and 25 (55.6%) on association analysis. Importantly, except for GLMM, current distributed learning methods can estimate effects with little bias in 1-3 rounds of communication. These methods show less bias compared with meta-analysis, especially in the address of data heterogeneity and rare outcomes. However, less studies examined how differences in data structure and sparse data affect results, an area that requires further research.Conclusion:While distributed learning shows promise in epidemiological effect estimation, it is still in early development, requiring further research on data heterogeneity handling and communication efficiency improvement.