BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

OBJECTIVE: To describe survival trends and global patterns of esophageal cancer (EC) using survival data from population-based cancer registries. METHODS: We systematically searched PubMed, EMBASE, Web of Science, SEER, and SinoMed databases for articles published up to 31 December 2023. Eligible EC survival estimates were evaluated according to country or region, period, sex, age group, pathology, and disease stage. RESULTS: After 2010, Jordan exhibited the highest age-standardized 5-year relative survival rates (RSRs)/net survival rates (NSRs) at 41.1% between 2010 and 2014, while India had the lowest, at 4.1%. Survival rates generally improved with diagnostic age across most countries, with significant increases in South Korea and China, of 12.7% and 10.5% between 2000 and 2017, respectively. Survival was higher among women compared to men, ranging from 0.4%-10.9%. Survival rates for adenocarcinoma and squamous cell carcinoma were similar, differing by about 4%. In China, the highest age-standardized RSRs/NSRs was 33.4% between 2015 and 2017. Meanwhile, the lowest was 5.3%, in Qidong (Jiangsu province) between 1992-1996. CONCLUSION Global EC survival rates have improved significantly in recent decades, but substantial geographical, sex, and age disparities still exist. In Asia, squamous cell carcinoma demonstrated superior survival rates compared to adenocarcinoma, while the opposite trend was observed in Western countries. Future research should clarify the prognostic factors influencing EC survival and tailor prevention and screening strategies to the changing EC survival patterns.
Humans ; Esophageal Neoplasms/mortality* ; Registries ; Male ; Female ; Survival Analysis ; Middle Aged ; Survival Rate ; Aged ; Global Health

Objective To investigate and compare the epidemiological characteristics of common respiratory viruses among influenza-like illness(ILI)and severe acute respiratory infection(SARI)cases in Huzhou,Zhejiang Province before and after the COVID-19 pandemic,so as to provide a basis for formulating and adjusting the prevention and control strategies for viral respiratory infectious diseases.Methods ILI and SARI cases at two influenza surveillance sentinel hospitals in Huzhou and had throat swab samples collected during Nov 2017 to Feb 2020(pre-COVID-19 pandemic period)and Dec 2022 to Apr 2024(post-COVID-19 mitigation phase)were selected as the participants.Seven common viral respiratory pathogens were tested,including influenza A virus(H1N1 and H3N2 subtypes),influenza B virus(Victoria lineage,FluB),respiratory syncytial virus(RSV),rhinovirus(HRV),adenovirus(ADV),and severe acute respiratory syndrome coronavirus-2(SARS-CoV-2).The positive rates of respiratory pathogens before and after the COVID-19 pandemic were compared across different age groups and different time.Results A total of 7 948 ILI samples and 2 294 SARI samples were included.The overall positive rate of ILI samples increased from 33.6%to 47.1%,primarily due to the increase in influenza and COVID-19 infections;the overall positive rate of SARI samples decreased from 31.4%to 24.8%,mainly due to the reduction in HRV and ADV infections.During the post-COVID-19 mitigation phase,SARS-CoV-2(22.1%),H3N2(12.7%),and FluB(6.0%)were the primary pathogens in ILI samples,while RSV(7.1%),H3N2(5.3%),and HRV(4.5%)dominated in SARI samples.During the post-COVID-19 mitigation phase,the influenza virus circulation period was shortened.Before the COVID-19 pandemic,RSV was mainly detected in autumn and winter,while during the post-COVID-19 mitigation phase,out-of-season RSV epidemics were observed in spring and summer.Co-infection rate in ILI cases increased significantly in the post-COVID-19 mitigation phase,predominantly consisting of co-infections of COVID-19 and influenza A virus,while co-infection rate in SARI cases showed a decline.Conclusion We found important epidemiological changes in respiratory viruses in Huzhou during the post-COVID-19 mitigation phase compared to pre-COVID-19 period,including increased positive rates of influenza and COVID-19,and disruptions to the seasonal patterns of influenza and RSV.The prevention and control strategies should be adjusted in a timely manner based on the monitoring data.

Objective To investigate and compare the epidemiological characteristics of common respiratory viruses among influenza-like illness(ILI)and severe acute respiratory infection(SARI)cases in Huzhou,Zhejiang Province before and after the COVID-19 pandemic,so as to provide a basis for formulating and adjusting the prevention and control strategies for viral respiratory infectious diseases.Methods ILI and SARI cases at two influenza surveillance sentinel hospitals in Huzhou and had throat swab samples collected during Nov 2017 to Feb 2020(pre-COVID-19 pandemic period)and Dec 2022 to Apr 2024(post-COVID-19 mitigation phase)were selected as the participants.Seven common viral respiratory pathogens were tested,including influenza A virus(H1N1 and H3N2 subtypes),influenza B virus(Victoria lineage,FluB),respiratory syncytial virus(RSV),rhinovirus(HRV),adenovirus(ADV),and severe acute respiratory syndrome coronavirus-2(SARS-CoV-2).The positive rates of respiratory pathogens before and after the COVID-19 pandemic were compared across different age groups and different time.Results A total of 7 948 ILI samples and 2 294 SARI samples were included.The overall positive rate of ILI samples increased from 33.6%to 47.1%,primarily due to the increase in influenza and COVID-19 infections;the overall positive rate of SARI samples decreased from 31.4%to 24.8%,mainly due to the reduction in HRV and ADV infections.During the post-COVID-19 mitigation phase,SARS-CoV-2(22.1%),H3N2(12.7%),and FluB(6.0%)were the primary pathogens in ILI samples,while RSV(7.1%),H3N2(5.3%),and HRV(4.5%)dominated in SARI samples.During the post-COVID-19 mitigation phase,the influenza virus circulation period was shortened.Before the COVID-19 pandemic,RSV was mainly detected in autumn and winter,while during the post-COVID-19 mitigation phase,out-of-season RSV epidemics were observed in spring and summer.Co-infection rate in ILI cases increased significantly in the post-COVID-19 mitigation phase,predominantly consisting of co-infections of COVID-19 and influenza A virus,while co-infection rate in SARI cases showed a decline.Conclusion We found important epidemiological changes in respiratory viruses in Huzhou during the post-COVID-19 mitigation phase compared to pre-COVID-19 period,including increased positive rates of influenza and COVID-19,and disruptions to the seasonal patterns of influenza and RSV.The prevention and control strategies should be adjusted in a timely manner based on the monitoring data.

Objective To construct a rational and efficient bed resource allocation management model to reduce pre-hos-pital waiting times,ensure patient safety,and improve satisfaction.Methods Based on lean management principles,a bed re-source allocation management model was developed and continuously optimized.The study compared bed turnover rates and effi-ciency indices,as well as preoperative waiting times for surgical patients,average length of stay,patient satisfaction,and anxiety incidence before and after the implementation of the lean model to evaluate its effectiveness.Results After implementing the lean bed resource allocation model,the bed efficiency index increased by 14.29％,and bed turnover rates improved by 3.34％.The average preoperative waiting time for surgical patients decreased by 100％,and the average length of stay reduced by 87.71％.Patient satisfaction increased by 2.4％,while anxiety incidence dropped by 28.1％.Conclusion The implementa-tion of a lean bed resource allocation model can enhance hospital bed efficiency,shorten preoperative waiting times for surgical patients,reduce average length of stay,and improve patient satisfaction.

The inflammatory effect of dietary is strongly related to the development of cancer,therefore,the diet-related inflammatory index was developed as a methodological tool to investigate the relationship between dietary,inflammation and tumors.In this paper,we summarized the results on diet-related inflammatory indices and common cancers of the digestive system based on relevant cancer epidemiological studies.The available epidemiological evidence suggests that pro-inflammatory diet is associated with an increased risk of gastrointestinal malignancies,with the strongest association with colorectal cancer,followed by esophageal and gastric cancers,and then pancreatic cancer,and the least evidence of studies with liver cancer.Among these studies,the level of evidence for esophageal cancer is lower than colorectal cancer,the study of gastric cancer has gender differences and problems in adjusting for confounders,and the study of pancreatic cancer has heterogeneous results.In view of the current research progress and deficiencies,prospective studies or population-based cohort studies,as well as strengthening nutritional epidemiological studies related to common tumors such as liver cancer could be considered in the future.This review is expecting to provide basic information and scientific basis for strengthening the related healthy eating behavior promotion in the prevention and control of digestive system tumors.

Aim To investigate the effect of ellagic acid (EA) on cognitive function in APP/PS 1 double- transgenic mice, and to explore the regulatory mechanism of ellagic acid on the level of oxidative stress in the hippocampus of double-transgenic mice based on the phosphatidylinositol 3-kinase/protein kinase B/glycogen synthase kinase-3 (PI3K/AKT/GSK-3 β) signaling pathway. Methods Thirty-two SPF-grade 6-month-old APP/PS 1 double transgenic mice were randomly divided into four groups, namely, APP/PS 1 group, APP/PS1 + EA group, APP/PS1 + LY294002 group, APP/PS 1 + EA + LY294002 group, with eight mice in each group, and eight SPF-grade C57BL/6J wild type mice ( Wild type) were selected as the blank control group. The APP/PS 1 + EA group was given 50 mg · kg

Influenza is an acute respiratory infectious disease caused by influenza virus,which poses a serious risk to human health.People are generally susceptible to influenza virus.There is an international consensus that influ-enza vaccination is the most effective way to prevent and control influenza.In China,influenza vaccination is a non-immunization programme vaccine that is vaccinated voluntarily and at one's own expense.In some regions,immuni-zation policies are implemented for priority groups.In recent years,a number of health economic evaluations on in-fluenza vaccination have been conducted both at home and abroad,especially for key and high-risk populations such as pregnant women,children,elderly people aged ≥60 years old,people suffering from one or more chronic disea-ses,and health care workers.This paper analyzed the current status of researches on health economic evaluation of influenza vaccination through collating relevant literatures published at home and abroad in recent years,so as to provide a scientific basis for the formulation of influenza vaccination strategies in China.

Objective:To analyze the improvement effect of monk fruit on diabetic nephropathy(DN)by network pharmacology,and to elucidate its possible related mechanism.Methods:The Traditional Chinese Medicine Systems Pharmacology(TCMSP)Database was used to detect the active ingredients and their targets of monk fruit;the DN target genes were screened out by DisGeNET Database and Genecards Database;the key targets of monk fruit against DN were obtained by comparing the monk fruit with DN targets;protein-protein interaction(PPI)network diagram was constructed by STRING Database and Cytoscape software;Gene Ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analysis were performed by Cytoscape software.Molecular docking technology was used to predict the binding abilities of the core targets and the main active ingredients of monk fruit.Results:The TCMSP Database combined with the selection criteria was used to screen out a total of five active ingredients of monk fruit(ZINC03860434,Perlolyrine,beta-sitosterol,Kaempferol,and Flazin)as well as 85 targets represented by serine/threonine protein kinase 1(AKT1),transcription factor RELA,c-Jun N-terminal kinase(JUN),and tumor necrosis factor(TNF).Among them,Kaempferol contained the most targets.Among the 85 targets,34 were associated with DN.The GO functional enrichment analysis mainly included biological process(BP)such as oxidative stress,regulation of inflammation and apoptosis,and cell signaling transduction.The KEGG enrichment analysis included advanced glycosylation end product(AGE)-receptor of AGE(AGE-RAGE)signaling pathway,TNF signaling pathway,and C-type lectin receptor signaling pathway.The results molecular docking technology of the main active ingredients of monk fruit and DN target proteins showed that 5 kinds of molecular docking engergy were-8.00--5.00 kJ·mol-1.Conclusion:Kaempferol is the most effective active ingredient in the monk fruit for the treatment of DN,and its mechanism is mainly related to anti-inflammatory.