BACKGROUND: Previous evidence showed that ambient air pollution and cardiovascular mortality are related. However, there is a lack of evidence towards the modification effect of long-term lifestyle on the association between short-term ambient air pollution and death from cardiovascular events. METHOD: A total of 14,609 death from major adverse cardiovascular events (MACE) were identified among the China Kadoorie Biobank participants from 2013 to 2018. Ambient air pollution exposure including particulate matter 2.5 (PM_2.5), SO₂, NO₂, CO, and O₃ from the same period were obtained from space-time model reconstructions based on remote sensing data. Case-crossover design and conditional logistic regression was applied to estimate the effect of short-term exposure to air pollutants on MACE mortality. RESULTS: We found MACE mortality was significantly associated with PM_2.5 (relative percent increase 2.91% per 10 µg/m³ increase, 95% CI 1.32-4.53), NO₂ (5.37% per 10 µg/m³ increase, 95% CI 1.56-9.33), SO₂ (6.82% per 10 µg/m³ increase, 95% CI 2.99-10.80), and CO (2.24% per 0.1 mg/m³ increase, 95% CI 1.02-3.48). Stratified analyses indicated that drinking was associated with elevated risk of MACE mortality with NO₂ and SO₂ exposure; physical inactivity was associated with higher risk of death from MACE when exposed to PM_2.5; and people who had balanced diet had lower risk of MACE mortality when exposed to CO and NO₂. CONCLUSIONS The study results showed that short-term exposure to ambient PM_2.5, NO₂, SO₂, and CO would aggravate the risk of cardiovascular mortality, yet healthy lifestyle conduct might mitigate such negative impact to some extent.
Humans ; Cardiovascular Diseases/epidemiology* ; China/epidemiology* ; Male ; Female ; Air Pollution/adverse effects* ; Middle Aged ; Air Pollutants/analysis* ; Particulate Matter/analysis* ; Environmental Exposure/adverse effects* ; Life Style ; Aged ; Adult ; Risk Factors ; Cross-Over Studies ; East Asian People

Objective To review the damage outcomes of patients in medical damage events and to analyze the influencing factors of medical causality determination in medical damage events in Tianjin city,with a view to reducing the occurrence of medical damage events by avoiding risk factors and standardizing the diagnostic and therapeutic activities of medical personnel.Methods 316 cases of medical damage events handled by the Medical Damage Identification Office of Tianjin Medical Association from 2017 to 2023 were selected as the research object,and descriptive analysis was used to summarize the basic situation of medical damage events,and the medical fault factors affecting the magnitude of the cause force of the medical side of medical damage events were explored through single-factor analysis and the construction of multiomal logistic regression models.Results Medical malpractice(OR=3.140)and incomplete preoperative assessment(OR=6.008)are factors that influence the determination of the liability of the medical institution in medical malpractice events(P＜0.05),and all three regression coefficients were greater than 0,all three were positively correlated with the probability that the medical cause power was judged to be greater than or equal to the equivalent cause.Conclusion The number of medical damage incidents in Tianjin shows a fluctuating downward trend.In Tianjin,the number of medical injury incidents showed a fluctuating downward trend,and the number of medical injury incidents in tertiary public general hospitals was the largest.Therefore,medical institutions should establish and improve multidisciplinary diagnosis and treatment mode to improve the level of diagnosis and treatment.Strengthen preoperative evaluation to avoid surgical risk.

Objective:To explore a factor analysis method for job training needs based on "P4 medicine", and to provide evidence-based support for optimizing continuing education systems for medical staff in military rest homes and sanatoriums.Methods:A cross-sectional study was conducted with 95 medical staff from military rest homes and sanatoriums within the support system who participated in job training at Xinqiao Hospital. A structured questionnaire was developed based on the "P4 medicine" framework. After two rounds of Delphi expert consultation, 46 core indicators were selected. A principal component analysis was used to extract common factors, and a model of hierarchical needs was constructed by combining varimax rotation and entropy weight methods.Results:Four common factors were extracted, accounting for 81.564% cumulative variance. The first factor "dynamic updating of geriatric medical knowledge" (31.83%) covered clinical core competencies in managing geriatric comorbidities and recognizing critical values. The second factor "emergency responsiveness and personalized care" (26.05%) focused on military medical regulations, emergency treatment protocols, and tailored interventions. The third factor "multidisciplinary collaboration and leadership development" (12.41%) emphasized team reorganization in combat-ready scenarios. The fourth factor "integration of intelligent technologies" (11.29%) reflected data-driven decision-making needs. Entropy weight analysis highlighted dynamic medical knowledge updates (e.g., emergency skills with a weight of 0.050) and AI applications with a weight of 0.019 among the top 10% high-weight indicators.Conclusions:The "P4 medicine" effectively delineates the multidimensional training needs of grassroots medical personnel. Its four-dimensional structure (predictive, normative, collaborative, and innovative) provides a theoretical framework for curriculum design. We recommend constructing tiered training modules prioritizing technology-enabled mechanisms to enhance the precision and sustainability of geriatric healthcare services.

Lung cancer has the highest incidence and mortality among malignant tumors in China.Persistent subsolid nodules(SSNs)are closely associated with early-stage lung adenocarcinoma.Artificial intelligence(AI),as an emerging technology,is capable of performing in-depth analysis of large-scale imaging data through autonomous learning and possesses the ability to predict outcomes from new data,demonstrating great potential and application prospects in the assessment of SSNs.AI can not only effectively assist radiologists in diagnosis and treatment,but also improve work efficiency while reducing misdiagnosis and missed diagnosis rates.This review summarizes the recent applications and research progress of AI in the assessment of SSNs,to provide new insights for the diagnosis and treatment of SSNs.

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Objective:To investigate the clinical characteristics of urea cycle disorder (UCD), the efficacy and safety of glyceryl phenylbutyrate (GPB) therapy in pediatric patients with UCD.Methods:This study was a retrospective, single-arm, multicenter clinical study. The clinical data of 20 pediatric patients with UCD who received GPB treatment at 9 hospitals nationwide between December 2021 and August 2024 were collected. The clinical manifestations, laboratory results, and molecular genetic characteristics were analyzed, ammonia levels and other laboratory results were evaluated pre-post GPB therapy by paired t-tests or Wilcoxon tests. Results:Among the 20 pediatric patients with UCD, there were 8 males and 12 females, and the onset age was 2.8 (1.4, 5.7) years. The ammonia levels were 174 (125, 342) μmol/L at first onset. The symptoms included vomiting in 6 cases, drowsiness in 5 cases, epilepsy in 5 cases, developmental delay in 5 cases, psychiatric and behavioral abnormalities in 3 cases, and lethargy in 1 case, and 18 cases exhibited abnormal liver function. Twenty cases included 6 UCD subtypes, with 11 cases being ornithine transcarbamylase deficiency. A total of 27 variants were identified, 11 (41%) of which were novel. The age of patients who began GPB therapy was 4.0 (1.5, 6.6) years. Ten cases stopped GPB after 4.2 (3.4, 5.3) months, with 4 patients undergoing liver transplantation and 6 discontinuing for financial reasons. The remaining ten patients continued GPB therapy for 11.6 (8.6, 14.0) months. The duration of GPB treatment was 6.0 (4.2, 12.3) months, at the final visit, the levels of ammonia, platelets and aspartate aminotransferase were lower compared to those of pre-treatment (all P<0.05). The serum albumin level was higher than that of pre-treatment ( P=0.016). Two patients suffered only one episode of acute hyperammonaemia, with ammonia levels of 232 and 141 μmol/L, respectively. Nine cases experienced adverse effects potentially related to GPB, decreased appetite in 6 cases, vomiting in 3 cases, abnormal skin oil odor in 2 cases, somnolence, fatigue and diarrhea each in 1 case, with symptoms improved within 6 (3, 10) days. Conclusions:UCD primarily manifests with neurological and gastrointestinal symptoms, and early diagnosis of UCD could be achieved through the analysis of ammonia. GPB may effectively reduce ammonia levels in UCD pediatric patients, with favorable safety and tolerability.

Objective:To investigate gut microbiota differences between individuals with and without colorectal adenoma(CRA)and to identify gut microbes associated with CRA.Methods:This cross-sectional study analyzed the gut microbiota of 100 patients with CRA and 68 individuals without CRA(aged 40-75 years)who underwent colonoscopies between March 2021 and March 2022 at Tianjin Nankai Hospital.Fecal samples were sequenced for the V3-V4 region of the bacterial 16S rRNA gene using the Illumina NovaSeq platform.Results:Compared to the non-CRA group,the CRA group exhibited reduced relative abundances of identified and unidentified Lachnospiraceae,with increased Faecalibacterium and Streptococcus.In the non-CRA group,the relative abundances of Coprococcus,unidentified Clostridiaceae,and Clostridium were higher.LEfSe analysis revealed significant enrichment of Gammaproteobacteria,Proteobacteria,Enterobacteriales,and Faecalibacterium in the CRA group,while the non-CRA group was enriched for Moraxellaceae,Acinetobacter,and Anaerostipes.Conclusions:These findings suggest a discernible disparity in the gut microbiota structure between CRA patients and individuals without adenoma.The enrichment of potential pathogenic taxa,such as Faecalibacterium and Streptococcus,in the CRA group suggests a possible association with adenoma development.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective:To investigate gut microbiota differences between individuals with and without colorectal adenoma(CRA)and to identify gut microbes associated with CRA.Methods:This cross-sectional study analyzed the gut microbiota of 100 patients with CRA and 68 individuals without CRA(aged 40-75 years)who underwent colonoscopies between March 2021 and March 2022 at Tianjin Nankai Hospital.Fecal samples were sequenced for the V3-V4 region of the bacterial 16S rRNA gene using the Illumina NovaSeq platform.Results:Compared to the non-CRA group,the CRA group exhibited reduced relative abundances of identified and unidentified Lachnospiraceae,with increased Faecalibacterium and Streptococcus.In the non-CRA group,the relative abundances of Coprococcus,unidentified Clostridiaceae,and Clostridium were higher.LEfSe analysis revealed significant enrichment of Gammaproteobacteria,Proteobacteria,Enterobacteriales,and Faecalibacterium in the CRA group,while the non-CRA group was enriched for Moraxellaceae,Acinetobacter,and Anaerostipes.Conclusions:These findings suggest a discernible disparity in the gut microbiota structure between CRA patients and individuals without adenoma.The enrichment of potential pathogenic taxa,such as Faecalibacterium and Streptococcus,in the CRA group suggests a possible association with adenoma development.

Objective:To explore a factor analysis method for job training needs based on "P4 medicine", and to provide evidence-based support for optimizing continuing education systems for medical staff in military rest homes and sanatoriums.Methods:A cross-sectional study was conducted with 95 medical staff from military rest homes and sanatoriums within the support system who participated in job training at Xinqiao Hospital. A structured questionnaire was developed based on the "P4 medicine" framework. After two rounds of Delphi expert consultation, 46 core indicators were selected. A principal component analysis was used to extract common factors, and a model of hierarchical needs was constructed by combining varimax rotation and entropy weight methods.Results:Four common factors were extracted, accounting for 81.564% cumulative variance. The first factor "dynamic updating of geriatric medical knowledge" (31.83%) covered clinical core competencies in managing geriatric comorbidities and recognizing critical values. The second factor "emergency responsiveness and personalized care" (26.05%) focused on military medical regulations, emergency treatment protocols, and tailored interventions. The third factor "multidisciplinary collaboration and leadership development" (12.41%) emphasized team reorganization in combat-ready scenarios. The fourth factor "integration of intelligent technologies" (11.29%) reflected data-driven decision-making needs. Entropy weight analysis highlighted dynamic medical knowledge updates (e.g., emergency skills with a weight of 0.050) and AI applications with a weight of 0.019 among the top 10% high-weight indicators.Conclusions:The "P4 medicine" effectively delineates the multidimensional training needs of grassroots medical personnel. Its four-dimensional structure (predictive, normative, collaborative, and innovative) provides a theoretical framework for curriculum design. We recommend constructing tiered training modules prioritizing technology-enabled mechanisms to enhance the precision and sustainability of geriatric healthcare services.