Objective:To construct a risk classification model for adverse events of medical consumables,so as to achieve automatic evaluation for risk level of such events,and enhance the capability for risk management of adverse events of medical consumables,and ensure the safety of medical apparatuses.Methods:The data of adverse events of medical consumables of 370 cases of 148 types that were reported by Shandong Provincial Third Hospital from 2020 to 2023 were selected,and they were divided into high-risk and low-risk types.Eight key factors of them,which included the number of cases,injury level,type of registration certificate,with source and without source,high-value and low-value,domestic and imports,product classification,and risk levels,were counted to form a dataset.K-nearest neighbor(KNN),support vector machine(SVM)and decision tree algorithms in machine learning were used to construct a risk classification model for adverse events of medical consumables.The data of 12 adverse events of medical consumables of 5 types of our hospital,which were newly reported in 2024,were integrated for their parameters.Then,the accuracy rate and prediction performance of the model were further analyzed.Results:By comparing the KNN,SVM and decision tree algorithm models,the effect of SVM algorithm model was better,and its accuracy rate was 90.54%,and its area under curve(AUC)value of the receiver operating characteristic(ROC)curve was 0.944,and its Kolmogorov-Smirnov(KS)test value was 0.808.The model had favorable predictive performance.The results,that invoked SVM algorithm model to conduct verification of actual prediction for 12 adverse events of medical consumables of 5 types,indicated it was same between predictive outcomes and risk levels of manual evaluation.Conclusion:The risk classification model of adverse events of medical consumables has established an operational model for assessing the risk level of such events,which can assist monitoring personnel for adverse event of medical apparatuses to quickly and accurately find risk signals of adverse events of medical consumables,and improve the monitoring capability of them for these adverse events.

Objective:To construct a risk classification model for adverse events of medical consumables,so as to achieve automatic evaluation for risk level of such events,and enhance the capability for risk management of adverse events of medical consumables,and ensure the safety of medical apparatuses.Methods:The data of adverse events of medical consumables of 370 cases of 148 types that were reported by Shandong Provincial Third Hospital from 2020 to 2023 were selected,and they were divided into high-risk and low-risk types.Eight key factors of them,which included the number of cases,injury level,type of registration certificate,with source and without source,high-value and low-value,domestic and imports,product classification,and risk levels,were counted to form a dataset.K-nearest neighbor(KNN),support vector machine(SVM)and decision tree algorithms in machine learning were used to construct a risk classification model for adverse events of medical consumables.The data of 12 adverse events of medical consumables of 5 types of our hospital,which were newly reported in 2024,were integrated for their parameters.Then,the accuracy rate and prediction performance of the model were further analyzed.Results:By comparing the KNN,SVM and decision tree algorithm models,the effect of SVM algorithm model was better,and its accuracy rate was 90.54%,and its area under curve(AUC)value of the receiver operating characteristic(ROC)curve was 0.944,and its Kolmogorov-Smirnov(KS)test value was 0.808.The model had favorable predictive performance.The results,that invoked SVM algorithm model to conduct verification of actual prediction for 12 adverse events of medical consumables of 5 types,indicated it was same between predictive outcomes and risk levels of manual evaluation.Conclusion:The risk classification model of adverse events of medical consumables has established an operational model for assessing the risk level of such events,which can assist monitoring personnel for adverse event of medical apparatuses to quickly and accurately find risk signals of adverse events of medical consumables,and improve the monitoring capability of them for these adverse events.

Objective:To investigate the pathogen distribution, temporal trends in the rates of antimicrobial resistance, and susceptibility of bloodstream isolates and comparatively explore the epidemiological characteristics of bloodstream infections in hematology departments across 56 healthcare facilities in Guangdong Province from 2020 to 2024.Methods:A multicenter analysis was conducted to evaluate the constituent ratio of different pathogens isolated from clinical isolate data from bloodstream specimens in hematology, respiratory, and intensive care unit (ICU) departments across 56 healthcare facilities in Guangdong Province (2020-2024), and antimicrobial resistance trends in pathogens with high-detection rate over 5 years were assessed. Carbapenem-resistant Gram-negative organisms (CRO) were randomly sampled for carbapenemase gene detection and in vitro antimicrobial susceptibility tests with novel antimicrobial agents.Results:From 2020 to 2024, a total of 8 968, 6 440, and 25 511 bloodstream isolates were identified in the hematology, respiratory, and ICU departments, respectively, across 56 participating facilities in Guangdong Province, with significant differences in the pathogen constituent ratio among departments ( P<0.001). Notably, the hematology department demonstrated a predominance of Escherichia coli (24.1%), Klebsiella pneumoniae (17.5%), Pseudomonas aeruginosa (11.7%), coagulase-negative Staphylococci (15.2%), and Staphylococcus aureus (5.1%). In the resistance analysis, the rates of meropenem resistance of Escherichia coli and Klebsiella pneumonia increased from 6.7% and 5.8% (2020) to 14.0% and 15.8% (2024), respectively. Conversely, Pseudomonas aeruginosa exhibited a declining trend in the rate of meropenem resistance (6.2% to 1.9%) and imipenem (10.2% to 6.1%) during the same period. Acinetobacter baumannii demonstrated a biphasic resistance pattern to common antimicrobial agents, characterized by an initial decline, followed by a rebound. In this study, the susceptibility rates to conventional antimicrobial agents were significantly higher in Staphylococcus aureus versus coagulase-negative Staphylococci, with no glycopeptide- or linezolid-resistant strains detected. Notably, the prevalence of vancomycin-resistant Enterococcus faecium increased from 0 in 2020 to 23.1% in 2024. CRO carbapenemase phenotypes through active surveillance revealed that 80% Escherichia coli isolates were carrying blaNDM, 90% Klebsiella pneumoniae isolates were carrying blaKPC, 10% Pseudomonas aeruginosa isolates were carrying blaVIM, and 100% Acinetobacter baumannii were carrying blaOXA-23. The results of the antimicrobial susceptibility test in CRO revealed that carbapenem-resistant Escherichia coli (CRECO) demonstrated a 0 resistance rate to tigecycline, polymyxin B, and aztreonam/avibactam, whereas carbapenem-resistant Klebsiella pneumoniae exhibited a 0 resistance rate to aztreonam/avibactam, ceftazidime/avibactam, and imipenem/relebactam. Carbapenem-resistant Pseudomonas aeruginosa exhibited a 95.0% susceptibility rate to amikacin and polymyxin B, with a 45.0% resistance rate to ceftazidime/avibactam. In contrast, carbapenem-resistant Acinetobacter baumannii demonstrated complete susceptibility (100.0%) to sulbactam/durlobactam (MIC90=2 μg/ml), whereas eravacycline showed MIC50 and MIC90 values of 1 and 2 μg/ml, respectively. Conclusion:The pathogen constituent ratio of bloodstream isolates differed significantly among hematology, respiratory, and ICU departments. Notably, although CRO exhibited an escalating prevalence, it sustained high susceptibility to novel antimicrobial agents.

Objective:To investigate the accuracy of risk perception for atherosclerotic cardiovascular disease (ASCVD) among community residents in Jining and analyze its influencing factors.Methods:Using a multistage cluster random sampling method, community residents from eight communities in Jining were selected between September 2022 and December 2023. Data were collected using a general demographic questionnaire, objective ASCVD risk assessment, the Chinese version of the Attitudes and Beliefs about Cardiovascular Disease Risk Questionnaire-Chinese Version (ABCD-C), the 2018 National Health Literacy Monitoring Survey, and a Self-reported Health Status Questionnaire.Results:Among 955 residents, 325 accurately estimated their ASCVD risk, 173 underestimated it, and 457 overestimated it. Education level and health literacy were influencing factors for overestimating ASCVD risk ( P<0.05), while education level, health literacy, family history of ASCVD, and self-reported health status were influencing factors for underestimating ASCVD risk ( P<0.05) . Conclusions:A significant proportion of Jining community residents underestimated their ASCVD risk. Nurses conducting ASCVD primary prevention education should provide tailored health education based on the local characteristics and cultural background of Jining. Special attention should be given to residents with lower education levels and health literacy, as well as those without a family history of ASCVD or with self-perceived good health, to prevent underestimation of their ASCVD risk.

AIM: To investigate the influence of relevant inflammatory markers in peripheral blood on the progression of neovascular glaucoma(NVG)secondary to diabetic retinopathy(DR)patients.METHODS: Retrospective case-control study. Patients were categorized into two groups based on the presence or absence of NVG: those with proliferative diabetic retinopathy(PDR)alone(PDR group, n=148)and those with NVG secondary to PDR(NVG secondary to PDR group, n=142). Peripheral blood inflammatory markers were evaluated, including white blood cell-related indices, neutrophil-to-lymphocyte ratio(NLR), platelet-to-lymphocyte ratio(PLR), monocyte-to-lymphocyte ratio(MLR), and systemic immune-inflammation index(SII). The distinctions in peripheral blood inflammatory markers between the two groups of patients and their relationships with NVG secondary to PDR were analyzed.RESULTS:No statistically significant differences were observed in basic characteristics between the two groups, confirming their comparability. However, significant differences were found in eosinophil percentage and MLR between the PDR group and the NVG secondary to PDR group(all P<0.05), with both values being significantly higher in the NVG secondary to PDR group. Multivariate Logistic regression analysis revealed that the eosinophil percentage and the MLR were factors influencing the development of patients with NVG secondary to PDR.CONCLUSION: Eosinophil percentage and MLR may be associated with the progression of PDR to NVG, and could serve as potential predictive markers for NVG development in PDR patients.

Objective:This study aims to construct a quality evaluation index system for specialized disease databases. Through systematic assessment and optimization, it seeks to comprehensively enhance the quality and standardization of specialized disease cohort data. This initiative will provide more precise and reliable data support for disease research, the development of innovative drugs and medical devices, as well as policy formulation.Methods:By conducting a thorough analysis of domestic and international literature and policies related to clinical research data quality evaluation systems, preliminary quality evaluation indicators for specialized disease databases were established. Utilizing the Delphi method in two rounds, a quality evaluation system for specialized disease databases was constructed. The Analytic Hierarchy Process (AHP) and YAAHP 7.5 software were then employed to calculate the relative weights of indicators at various levels and their composite weights.Results:The two rounds of expert consultation achieved a 100.00% valid response rate, with an expert authority coefficient of 0.81 in both rounds. In the second round, the Kendall′s coordination coefficients for the first-level and second-level indicators reached 0.311 and 0.218, respectively ( P<0.05), indicating a good level of consensus among experts. The final specialized disease database quality evaluation system consists of 3 first-level indicators, 10 second-level indicators, and 32 third-level indicators. The first-level indicators include database construction, data quality, and cohort development, with weight coefficients of 31.82%, 41.49%, and 26.69%, respectively. The scientific validity of the indicator system was confirmed through reliability and validity analyses. When applied to assessing 58 specialized disease database projects from 36 medical institutions in a certain city, the results showed significant improvements in scores for database construction, data quality, and cohort development, with the most notable improvement observed in database construction. Conclusions:This study successfully developed a scientific, practical, and rationally weighted quality evaluation system for specialized disease databases, demonstrating high expert consensus and broad applicability.Validation studies have shown that this system effectively enhances the standardization and data quality of databases, providing robust technical support and assurance for specialized disease research and data resource sharing.

Objective:To observe macular vascular density and structural characteristics in children with transfusion-dependent β-thalassemia (TDT).Methods:A retrospective clinical study. From October 2022 to December 2023, 29 TDT children (58 eyes) diagnosed and examined at the Department of Hematology, Affiliated Hospital of Guangdong Medical University were included in the TDT group, along with 29 age- and gender-matched healthy children (58 eyes) as the control group. All participants underwent optical coherence tomography and angiography. Measurements included central macular thickness (CMT), subretinal choroidal thickness (SFCT), choroidal thickness (ChT), choroidal vascularity index, blood flow density in the superficial capillary plexus (SCP), deep capillary plexus (DCP), choriocapillaris layer (CC), and choroidal layer of the macular region, as well as the foveal avascular zone (FAZ) area of the SCP and DCP. A generalized estimating equation was used to compare differences in the above parameters between the two groups. Pearson correlation analysis was employed to examine the relationships between fundus structural parameters, blood flow density, and blood indices.Results:Compared with the control group, the TDT group showed significantly thinner CMT ( χ2=6.044) and ChT at 3.0 mm nasal ( χ2=4.451) and temporal ( χ2=4.767) to the fovea ( P<0.05). The TDT group also demonstrated reduced blood flow density in the inferior DCP ( χ2=5.254), whole CC ( χ2=3.996), and superior CC ( χ2=5.094), as well as enlarged FAZ area in DCP ( χ2=4.286) ( P<0.05). Correlation analysis revealed a negative correlation between SFCT and disease duration ( r=?0.357, P=0.006). Conclusions:In children with TDT, CMT and ChT become thinner and the area of FAZ expands. The blood flow densities of DCP and CC in the macular area decreased.

Anticipatory anxiety is a negative emotion that arises when individuals encounter potential threats or uncertainties in the future. It is the core symptom of a variety of anxiety disorders, and is closely associated with the occurrence, severity, treatment outcome, and prognosis of anxiety disorders, which has garnered a growing amount of focus in clinical practice. Nevertheless, scientific research on anticipatory anxiety continues to face obstacles such as unclear pathological mechanisms, the absence of simple and consistent self-assessment tools, and effective interventions. To improve understanding of the role of anticipatory anxiety in the diagnosis and treatment of anxiety disorders, this study reviews pertinent domestic and international literature, and briefly introduces the concept, assessment and measurement, activation paradigm, pathological mechanisms, and interventions of anticipatory anxiety.

Objectives:To investigate the incidence of tyrosine kinase inhibitor (TKI) withdrawal syndrome and psychological issues, and their associated factors, in patients with chronic-phase chronic myeloid leukemia (CML-CP) after TKI discontinuation.Methods:We retrospectively analyzed the clinical data of CML-CP patients who discontinued TKI therapy at Peking University People's Hospital after September 2012. Logistic regression models were used to identify independent factors associated with the occurrence of TKI withdrawal syndrome and psychological issues.Results:A total of 158 patients were included, of whom 92 (58%) were female. The median age at discontinuation was 50 ( IQR, 35-60) years. With a median follow-up of 25 ( IQR, 11-49) months, the 4-year rate of sustained major molecular response (MMR) was 60% (95% CI: 51%-70%) . Fifty-one (32%) patients experienced TKI withdrawal syndrome at a median of 1.3 ( IQR, 0.5-2.0) months after TKI discontinuation. Fifty-one (32%) patients reported psychological issues such as anxiety. These concerns stemmed from fears of fluctuating BCR::ABL1 levels or disease relapse, and, for those who discontinued TKI for pregnancy, worries about adverse fetal effects and/or the fetus inheriting CML. Multivariable analyses revealed that older age at discontinuation [ P=0.003 when adjusting for TKI therapy duration; P=0.002 when adjusting for deep molecular response (DMR) duration], longer TKI therapy duration ( P=0.010) , and longer DMR duration before discontinuation ( P=0.005) were significantly associated with a higher risk of TKI withdrawal syndrome; a university degree or higher ( P=0.010) and TKI discontinuation due to pregnancy or adverse events ( P=0.001) were significantly associated with psychological issues after discontinuation. The occurrence of TKI withdrawal syndrome or psychological issues had no impact on the probability of major molecular response loss after discontinuation. Conclusion:TKI withdrawal syndrome and psychological issues are common in CML patients who discontinue TKI therapy. Older age at discontinuation and longer TKI therapy duration or DMR duration are significantly associated with TKI withdrawal syndrome. Higher education level and TKI discontinuation due to pregnancy or adverse events are significantly associated with psychological issues.