ObjectiveTo develop a full-process data platform of renal rehabilitation, diagnosis and quality control information. MethodsA hierarchical architectural design was proposed, adhering to clinical pathway models and standardized data protocols. The platform comprehensively covered assessment, intervention, follow-up and quality control for maintenance hemodialysis (MHD) patients. By integrating multidisciplinary resources and standardizing rehabilitation workflows, it delivered standardized and intelligent rehabilitation services. ResultsThe platform achieved standardized and intelligent management of rehabilitation services, effectively improved the physiological function, psychological state and quality of life convenience for MHD patients, while significantly reduced the economic and care burden on patients' families and society. ConclusionThe rehabilitation service model based on a full-process data platform may provide scientific and systematic support for MHD patients.

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

Objective:Exploring the association rules of factors influencing high hospitalization costs for cancer patients, providing references for hospitals to optimize medical cost management measures.Methods:In the inpatient case information system of a tertiary general hospital, the medical record homepages of inpatients in the DRG groups of the oncology department in 2022 were obtained. The upper four scores of hospitalization costs was used as the threshold for patient grouping. Patients with hospitalization costs≥this threshold were the high-cost group, while other patients were control group; 12 factors, including age, gender, and admission condition, etc, were considered as potential influencing factors of high hospitalization costs. FP-Growth and Apriori algorithms were used to excavate the potential association rules between the influencing factors of high hospitalization costs. Logistic regression was used to analyze the independent influencing factors of high hospitalization costs.Results:A total of 5 512 hospitalized patients were included, including 1 378 patients in the high-cost group. Thirteen validated strong association rules for factors influencing high hospitalization costs were obtained, of which the rule antecedents included age (≥70 years), number of days in hospital (≥7 days), other diagnoses (≥5), surgery, planned readmission, use of antibiotics, admission (general/critical), living admission score (61~99), level of care (level 1/level 2), non-day ward, criticality during hospitalisation. Logistic regression results showed that all nine influencing factors except gender, use of antibiotics, and readmission plans were independent influences on high hospitalization costs ( P<0.05). Conclusions:The joint application of FP-Growth and Apriori algorithm could effectively explore the association rules of high hospitalization costs for oncology patients. The early warning information mainly included the number of hospitalization days, the number of other diagnoses, surgeries, and so on. It was suggested that medical institutions can reasonably control the high hospitalization costs through clinical pathway management, diagnosis and treatment process reengineering, admission risk assessment, and multidisciplinary collaborative diagnosis and treatment strategies.

Objective:Exploring the association rules of factors influencing high hospitalization costs for cancer patients, providing references for hospitals to optimize medical cost management measures.Methods:In the inpatient case information system of a tertiary general hospital, the medical record homepages of inpatients in the DRG groups of the oncology department in 2022 were obtained. The upper four scores of hospitalization costs was used as the threshold for patient grouping. Patients with hospitalization costs≥this threshold were the high-cost group, while other patients were control group; 12 factors, including age, gender, and admission condition, etc, were considered as potential influencing factors of high hospitalization costs. FP-Growth and Apriori algorithms were used to excavate the potential association rules between the influencing factors of high hospitalization costs. Logistic regression was used to analyze the independent influencing factors of high hospitalization costs.Results:A total of 5 512 hospitalized patients were included, including 1 378 patients in the high-cost group. Thirteen validated strong association rules for factors influencing high hospitalization costs were obtained, of which the rule antecedents included age (≥70 years), number of days in hospital (≥7 days), other diagnoses (≥5), surgery, planned readmission, use of antibiotics, admission (general/critical), living admission score (61~99), level of care (level 1/level 2), non-day ward, criticality during hospitalisation. Logistic regression results showed that all nine influencing factors except gender, use of antibiotics, and readmission plans were independent influences on high hospitalization costs ( P<0.05). Conclusions:The joint application of FP-Growth and Apriori algorithm could effectively explore the association rules of high hospitalization costs for oncology patients. The early warning information mainly included the number of hospitalization days, the number of other diagnoses, surgeries, and so on. It was suggested that medical institutions can reasonably control the high hospitalization costs through clinical pathway management, diagnosis and treatment process reengineering, admission risk assessment, and multidisciplinary collaborative diagnosis and treatment strategies.

Objective To construct the theoretical framework of rehabilitation big data based on International Classification of Func-tioning,Disability and Health(ICF). Methods Drawing upon international rehabilitation policy documents,such as the World Health Organization's Rehabili-tation in health systems;Rehabilitation in health systems:guide for action;Rehabilitation indicator menu:a tool accompanying the Framework for Rehabilitation Monitoring and Evaluation(FRAME);Template for Rehabilita-tion Information Collection(TRIC):a tool accompanying the Systematic Assessment of Rehabilitation Situation(STARS);and Framework and Standards for Country Health Information Systems;this study examined the com-position and function of rehabilitation big data.The content structure of the rehabilitation big data domain was an-alyzed using the World Health Organization Family of International Classifications(WHO-FICs).Furthermore,the generation patterns of rehabilitation big data was constructed drawing on the Health Metrics Network and big data hierarchical classification. Results Within the six primary elements of the health service system,the information system element was particularly significant,encompassing a substantial branch known as rehabilitation big data.There were three components of rehabilitation big data:health condition,health-related factors and health services.The content framework for this data was derived from the WHO-FICs framework,which covered three dimensions:health and function,dis-ease and function,and disease,function and intervention.A comprehensive model for generating and applying re-habilitation big data in rehabilitation services was developed in line with the requirements for constructing big da-ta architectures.The sources of this data included population censuses,social registration information,population surveys,resources,services and personal records.The result chain of rehabilitation big data encompassed five major processes:input,process,output,outcome and impact.The processing and utilization of this data involved collection,storage,management,analysis and application. Conclusion A theoretical framework for rehabilitation big data has been constructed based on the ICF theory.

Objective To explore and organize the standards of rehabilitation big data. Methods The connotation and extension of rehabilitation big data were discussed based on International Classification of Functioning,Disability and Health(ICF)framework.Referring to the documents of Guidance on the analysis and use of routine health information systems rehabilitation module,Rehabilitation in health systems:guide for action,Rehabilitation indicator menu:a tool accompanying the Framework for Rehabilitation Monitoring and Evaluation(FRAME),and Data quality assurance.Module 1.Framework and metrics,the sources,patterns,clas-sification systems and coding standards were discussed under the ICF theory,and the metadata standards were ex-plored.The application and management of rehabilitation big data standards were discussed according to Nation-al Health Medical Big Data Standards,Security and Service Management Measures(Trial). Results The rehabilitation big data included rehabilitation service data and personal health data,coming from population-based and institution-based data,covering macro,meso and micro levels.The pattern of rehabilitation data flow corresponded to the interaction and source of the entire process of rehabilitation service,to organize and manage rehabilitation big data.The classification system included object classes,object feature classes,participant role classes,relationship classes,and activity and event classes,each of which was further subdivided into subcatego-ries to cover the entities,features,roles,relationships and activities involved in the rehabilitation process.The metadata standards included three levels:core,general and specialized metadata,ensuring standardized manage-ment,sharing and interoperability of rehabilitation data. Conclusion This study delves into the standardization of rehabilitation big data based on the ICF framework,encompass-ing multiple dimensions such as the connotation and extension of rehabilitation big data,data sources,data mod-els,classification systems,coding standards,and metadata standards.The construction of a rehabilitation big data standard system involves standardization efforts in various aspects,including data content,data structure,data coding,and metadata.These standards not only adhere to the norms of data flow,but also take into account the complexity of data composition.This system aligns with health big data standards,ensuring data consistency,ac-curacy,and interoperability,thus providing a foundation for effective exchange and comparison between different data sources.The establishment of a rehabilitation big data standard system not only ensures the standardized pro-cessing of rehabilitation big data,but also lays a solid foundation for effective exchange between rehabilitation big data and other health data,as well as for the widespread application of rehabilitation big data.This provides crucial support for improving the quality and efficiency of rehabilitation services,ensuring that patients receive appropriate care,rehabilitation and support.It holds significant theoretical and practical implications for promot-ing the development of the rehabilitation field.

The traditional Chinese medicine Atractlodis Rhizoma is the dried rhizome of the Asteraceae herbal plant Atractylodes lancea, and it has the functions of drying dampness and strengthening the spleen, removing wind and dissipating cold, and brightening the eyes. The sesquiterpenoids in A. lancea are the main ingredients of its pharmacological activities in clinical practice, including atractylone, β-eudesmol, and hinesol, which possess anti-inflammation, antibacterial, antiviral, and hepatoprotective effects. This study focused on the biosynthesis of sesquiterpenoids in A. lancea, summarized the proportion of the main active ingredients in A. lancea from the genuine region and the non-genuine region, elaborated on the research progress of genes related to biosynthesis pathways, and systematically sorted out the biotic and abiotic factors affecting their biosynthesis, so as to provide a theoretical basis for further research on the biosynthetic mechanism of sesquiterpenoids in A. lancea and development of high-quality medicinal materials of A. lancea.
Atractylodes/metabolism* ; Sesquiterpenes/metabolism* ; Drugs, Chinese Herbal/pharmacology* ; Biosynthetic Pathways

Objective:To analyze the clinical characteristics of elderly-onset gouty arthritis and risk factors of tophi.Methods:A total of 1 239 gout patients were retrospective selected in the outpatient department of the Gout Clinical Medical Center of the Affiliated Hospital of Qingdao University from 2016 to 2022. According to age of onset, they were divided into the young and middle-aged group(aged<60) consisted of 826 cases, and the elderly group(aged≥60) consisted of 413 cases. Compare the clinical characteristics of elderly with Young and Middle-aged patients.Results:The systolic blood pressure, fasting blood glucose, creatinine, regular exercise, comorbidities, and tophi in the elderly group was higher than that in the middle-aged and young group. The proportion of diastolic blood pressure, serum triglycerides, eGFR, serum uric acid, alcohol consumption rate, and family history of gout was lower than that of young and middle-aged group( P<0.05); In the elderly-onset group, the initial site of arthritis was commonly observed in the first metatarsophalangeal joint. The proportion of the first attack with the upper limb joint was higher in old age group than in young and middle age group( P<0.05). Renal underexcretion type was the main subtype in the elderly group, and the proportion of overproduction type was higher than that of the young and middle-aged group( P<0.05). The logistic regression analysis showed that age, urea nitrogen, disease duration≥10 years and family history of gout were risk factors for tophi in elderly patients( P<0.05). Conclusion:The elderly-onset gout has unique clinical characteristics, characterized by a higher prevalence of tophi, a higher rate of complications. An initial site of arthritis commonly observed in the first metatarsophalangeal joint and the predominant type of uric acid excretion is renal excretion impairment. Early diagnosis and treatment, control of blood uric acid levels, smoking cessation and alcohol, regular exercise should be applied to prevent or delay the formation of tophi.

The "Medium and Long-term Plan for the Prevention and Control of Chronic Non-communicable Diseases in Shanghai (2018-2030)" was officially released in August 2018.From the perspective of public health, this paper analyzes the background of the plan from the epidemic situation, response and challenges Shanghai City is facing, expounds the comprehensive prevention and control system of chronic diseases including four functional systems, and explains the key preventive and control measures on the different stages of chronic diseases, comparing the evaluation indicators with those of the national plan.This paper will help to better understand the new blueprint for the prevention and control of chronic diseases in Shanghai in the next ten years.