Objective Based on the assumption of spatial heterogeneity,the distribution pattern and risk characteristics of health poverty in middle-aged and elderly people with chronic diseases are described from the perspective of spatial differentiation.In order to providing a theoretical basis for the optimization of subsequent poverty reduction policies and a model policy for other countries.Methods It used factor detector and interaction detector to capture the role of single-factor and multi-factor interactions on the spatial differentiation of health poverty,and risk detectors were utilized to explore the high-risk factors in risky areas Results The single factor explanation of medical assistance and health education activities is prominent,and the factors such as PM2.5,old-age dependency ratio and urban unemployment rate have strong interaction.Furthermore,it identified high-risk factor characteristics in areas at high risk of health poverty.Conclusion The spatial differentiation pattern of health poverty among the middle-aged and elderly chronic disease population in China is the result of the synergistic driving effect of multidimensional factors,and there is variability in the risk characteristics among regions.The government should establish a contextual optimization strategy and pay attention to the joint effect of multiple factors to establish a synergistic management system.

Objective:To investigate the association of serum/body fluid heparin-binding protein (HBP) and blood lactate levels with disease severity and their impact on prognosis in intensive care unit (ICU) patients with sepsis.Methods:Clinical data from 100 sepsis patients admitted to Ma'anshan Shiqiye Hospital ICU (January 2023-September 2024) were retrospectively analyzed. According to Sepsis-3.0 criteria, patients were divided into: uncomplicated sepsis (general group, n=28), sepsis with organ failure/hypotension (severe group, n=61), and septic shock (shock group, n=11). Comparisons included serum/body fluid HBP, lactate, APACHE Ⅱ scores, and mortality across severity groups and laboratory parameters between survivors and non-survivors. Logistic regression was used to identify prognostic predictors. Non-normally distributed data were presented as M(Q1,Q3), comparison between groups were completed by Kruskal-Wallis H test and Mann-Whitney U tests. Spearman correlation was used to analyze relationships between biomarkers and APACHE Ⅱ scores. Categorical data were presented as n(%), and comparison between groups were completed by χ2 test or Fisher's exact tests. ROC curves was used to evaluate predictive value. Results:Shock group demonstrated significantly higher serum HBP [13.3 (12.6-16.4) μg/L], infection-site HBP [230.3 (226.3-241.1) μg/L], lactate [5.4 (4.9-5.6) mmol/L], and APACHE Ⅱ[22.0 (21.0-24.0)] than severe group [9.6 (8.9-10.5) μg/L; 208.9 (200.5-216.1) μg/L; 2.7 (2.6-2.8) mmol/L; 18.0 (17.0-19.0)] and general group [7.4 (6.3-8.1) μg/L; 190.6 (180.5-202.1) μg/L; 1.5 (1.4-1.7) mmol/L; 13.0 (12.0-14.0)] (all P<0.001). There was statistically significant difference in the mortality rate during hospita lization among three groups of patients ( χ2=30.49, P<0.001). Mortality was higher in shock group than severe group than general group [72.7% (8/11) vs. 11.5% (7/61) vs. 3.6% (1/28), all P<0.001]. Non-survivors exhibited elevated lactate [4.8 (2.7-5.5) vs. 2.6 (1.7-2.8) mmol/L, Z=-4.13, P=0.001], serum HBP [12.2 (9.2-13.3) vs. 9.3 (7.8-10.4) μg/L, Z=-3.12, P=0.002], and infection-site HBP [226.8 (209.9-237.6) vs. 203.6 (194.0-212.8) μg/L, Z=-4.32, P<0.001] vs. survivors. Serum HBP ( r=0.74), infection-site HBP ( r=0.64), and lactate ( r=0.86) were all positively correlated with APACHE Ⅱ (all P<0.001). After adjusting for age and APACHE Ⅱ, elevated serum HBP ( OR=3.743, 95% CI:1.834-7.640), infection-site HBP ( OR=3.540, 95% CI:1.932-6.486), and lactate ( OR=5.155, 95% CI:1.868-14.229) independently predicted mortality (all P<0.001). Combined biomarker detection showed superior predictive value (AUC=0.909) versus individual markers (serum HBP:0.747, infection-site HBP:0.842, lactate:0.827, all P<0.001). Conclusion:Elevated blood lactate and serum/infection-site HBP levels correlate with sepsis severity and independently predict mortality. The biomarker combination provides optimal prognostic stratification.

ObjectiveTo investigate the awareness and clinical practice of guidelines for the prevention and treatment of chronic hepatitis B （2022 edition） among clinicians. MethodsFrom July 19 to December 31， 2024， a self-designed electronic questionnaire was distributed via the WeChat mini program to collect related data from 1 588 clinicians nationwide， including their awareness and practice based on 18 questions regarding testing and referral， diagnosis and treatment， and follow-up. ResultsAmong all respondents， only 350 clinicians correctly understood all the updated key points of antiviral indications and treatment for special populations in the 2022 edition of guidelines for the prevention and treatment of chronic hepatitis B， with an overall awareness rate of 22.0%. Only 20% ‍—‍ ‍40% of the patients with positive HBV DNA and an age of >30 years receive antiviral therapy， while 80% ‍—‍ ‍100% of the patients with positive HBV DNA and a family history of hepatitis B cirrhosis or hepatocellular carcinoma receive antiviral therapy. The median follow-up rates at 1 year， 3 years， and 5 years were 67.5% 57.5% and 47.5%，respectively， showing a trend of gradual reduction， which might be associated with the influencing factors such as insufficient time for follow-up management by clinicians， insufficient awareness of the disease among patients， and poor adherence to follow-up. ConclusionThere is a gap between the awareness and practice of guidelines for the prevention and treatment of chronic hepatitis B （2022 edition） among clinicians. It is recommended to further strengthen training and focus on the whole process of “detection， diagnosis， treatment， and management” for patients with chronic hepatitis B in healthcare institutions， in order to promote the implementation of the guidelines.

OBJECTIVE: To identify the optimal machine learning algorithm for predicting post-stroke epilepsy (PSE) within one year following acute stroke, establish a nomogram model based on this algorithm, and perform external validation to achieve accurate prediction of secondary epilepsy. METHODS: A total of 870 acute stroke patients admitted to the emergency department of Xiang'an Hospital of Xiamen University from June 2019 to June 2023 were enrolled for model development (model group). An external validation cohort of 435 acute stroke patients admitted to the Fifth Hospital of Xiamen during the same period was used to validate the machine learning algorithms and nomogram model. Patients were classified into control and epilepsy groups based on the development of PSE within one year. Clinical and laboratory data, including baseline characteristics, stroke location, vascular status, complications, hematologic parameters, and National Institutes of Health Stroke Scale (NIHSS) score, were collected for analysis. Nine machine learning algorithms such as logistic regression, CN2 rule induction, K-nearest neighbors, adaptive boosting, random forest, gradient boosting, support vector machine, naive Bayes, and neural network were applied to evaluate predictive performance. The area under the curve (AUC) of receiver operator characteristic curve (ROC curve) was used to identify the optimal algorithm. Logistic regression was used to screen risk factors for PSE, and the top 10 predictors were selected to construct the nomogram model. The predictive performance of the model was evaluated using the ROC curve in both the model and validation groups. RESULTS: Among the 870 patients in the model group, 29 developed PSE within one year. Among the nine algorithms tested, logistic regression demonstrated the best performance and generalizability, with an AUC of 0.923. Univariate logistic regression identified several risk factors for PSE, including platelet count, white blood cell count, red blood cell count, glycated hemoglobin (HbA1c), C-reactive protein (CRP), triglycerides, high-density lipoprotein (HDL), aspartate aminotransferase (AST), alanine aminotransferase (ALT), activated partial thromboplastin time (APTT), thrombin time, D-dimer, fibrinogen, creatine kinase (CK), creatine kinase-MB (CK-MB), lactate dehydrogenase (LDH), serum sodium, lactic acid, anion gap, NIHSS score, brain herniation, periventricular stroke, and carotid artery plaque. Further multivariate logistic regression analysis showed that white blood cell count, HDL, fibrinogen, lactic acid and brain herniation were independent risk factors [odds ratio (OR) were 1.837, 198.039, 47.025, 11.559, 70.722, respectively, all P < 0.05]. In the external validation group, univariate logistic regression analysis showed that platelet count, white blood cell count, CRP, triacylglycerol, APTT, D-dimer, fibrinogen, CK, CK-MB, LDH, NIHSS score, and cerebral herniation were risk factors for PSE one year after acute stroke. Further multiple logistic regression analysis showed that APTT and cerebral herniation were independent predictors (OR were 0.587 and 116.193, respectively, both P < 0.05). The nomogram model, constructed using 10 key variables-brain herniation, periventricular stroke, carotid artery plaque, white blood cell count, triglycerides, thrombin time, D-dimer, serum sodium, lactic acid, and NIHSS score-achieved an AUC of 0.908 in the model group and 0.864 in the external validation group. CONCLUSIONS The logistic regression-based prediction model for epilepsy one year after acute stroke, developed using machine learning algorithms, showed optimal predictive performance. The nomogram model based on the logistic regression-derived predictors showed strong discriminative power and was successfully validated externally, suggesting favorable clinical applicability and generalizability.
Humans ; Machine Learning ; Stroke/complications* ; Nomograms ; Epilepsy/etiology* ; Algorithms ; Male ; Female ; Logistic Models ; Middle Aged ; Aged ; Risk Factors ; Bayes Theorem

OBJECTIVE Aimed to investigate the impact of comorbid asthma on chronic rhinosinusitis with nasal polyps(CRSwNP)and identify key proteins and signaling pathways.METHODS Proteomic methods were employed to analyze differentially expressed proteins(DEPs)in nasal lavage fluid(NLF)from control,CRSwNP,and CRSwNP with asthma groups.DIA quantitative analysis technology was used to assess the gradient changes of DEPs among the three groups to determine key proteins affected by comorbid asthma in CRSwNP.RESULTS Compared to the control group,1 377 and 1 006 DEPs were identified in the CRSwNP and CRSwNP with asthma groups,respectively.Peroxiredoxin-5(PRDX5),Ran-Binding Protein 1(RanBP1)(upregulated),and Keratin 9(KRT9)(downregulated)were identified as key proteins affecting CRSwNP with asthma.CONCLUSION Comorbid asthma may promote the occurrence and development of nasal polyps through specific key proteins and signaling pathways,providing new molecular insights into the interaction between CRSwNP and asthma.

Objective To investigate the seroprevalence of antibody against Toxoplasma gondii among patients with hematological malignancies, and compare it with that among health individuals, so as to provide insights into unraveling the pathogenesis of hematological malignancies. Methods A total of 225 patients with hematological malignancies in Department of Hematology, Xuzhou Central Hospital and 300 healthy individuals in the same hospital were enrolled from 2017 to 2024. Blood samples were collected from all subjects, and the serum IgG and IgM antibodies against T. gondii were detected using chemiluminescent immunoassay. Demographic and clinical features were collected from patients with hematological malignancies, including gender, age, contact with cats, consumption of raw or undercooked meat, type of malignancy, clinical symptoms, blood transfusion and treatment, and the seroprevalence of anti-T. gondii antibody was compared among patients with different characteristics. Results The age (t = 0.72, P > 0.05) and gender (χ² = 0.93, P > 0.05) were compared between patients with hematological malignancies and healthy individuals. The seroprevalence of T. gondii infection was 20.89% among patients with hematological malignancies and 4.33% among healthy individuals (χ² = 34.81, P < 0.01), and the seroprevalence of anti-T. gondii IgG antibody was 20.89% among patients with hematological malignancies and 4.33% among healthy individuals (χ² = 34.81, P < 0.01), while there was no significant difference in the seroprevalence of anti-T. gondii IgM antibody between patients with hematological malignancies and healthy individuals (1.33% vs. 0; corrected χ² = 2.02, P > 0.05). The seroprevalence of T. gondii infection was 23.08% among patients with leukemia, 16.67% among patients with lymphoma, 19.23% among patients with multiple myeloma, 24.00% among patients with myeloproliferative neoplasm, and 26.09% among patients with myelodysplastic syndrome (χ² = 1.44, P > 0.05), and was all higher than among healthy individuals (corrected χ² = 23.92, 10.74, 13.76, 12.84 and 14.54; all P values < 0.01). In addition, there were no significant differences in the detection of anti-T. gondii antibody among patients with hematological malignancies in terms of gender, age, contact with cats, consumption of raw or undercooked meat, chemotherapy or blood transfusion (χ² = 0.76, 1.97, 0, 2.81, 2.38 and 0.66; all P values > 0.05). Conclusions There is a high risk of T. gondii infection among patients with hematological malignancies, and intensified surveillance of T. gondii infection is recommended among patients with hematological malignancies.

The emergence of antimicrobial resistance(AMR)of bacteria leads to a decrease or even failure in the effectiveness of antimicrobial treatment,poses a huge challenge to clinical anti-infective treatment,and seriously threatens human life.Therefore,coping with AMR of bacteria has become a major challenge and research hot spot in the field of global public health.Due to the wide sources and diverse biological activities,natural compounds play an important role in the practice of"reduction of antimicrobial agents,replacement for antimicrobial agents,and free of antimicrobial agents"in the breeding industry.In recent years,studies have discovered that a variety of natural compounds can serve as enhancer for antimicrobial agents,and the combined use of natural compounds with antimi-crobial agents can restore the antimicrobial sensitivity of antimicrobial-resistant bacteria and enhance antimicrobial effects.This indicates that natural compounds have the potential to serve as new strategies in coping with AMR of bacteria.This paper reviews the synergistic antibacterial mechanism of natural compounds combined with antimicro-bial agents based on the main resistance mechanisms of bacteria,and looks forward to their application prospects and challenges,in the hope of providing new ideas and strategies for coping with the crisis of bacteria AMR.

Objective:To investigate the effect of peripheral white blood cell(WBC) count on adverse pregnancy outcomes.Methods:A retrospective analysis was conducted on pregnant women who delivered at Minhang Hospital affiliated with Fudan University between January 2013 and June 2020. Demographic data, WBC counts, and diagnostic information on gestational diabetes mellitus(GDM), gestational hypertension, and preeclampsia/eclampsia were extracted from electronic medical records. Logistic regression models were used to evaluate the association between WBC counts in the first(WBC-1) and second trimesters(WBC-2) and metabolically related pregnancy outcomes.Results:A total of 24 143 pregnant women were included, with a mean age of(29.1±4.9) years and a mean pre-pregnancy body mass index(BMI) of(21.1±2.8) kg/m 2. The mean WBC counts in the first and second trimesters were 8.1×10 9/L and 8.9×10 9/L, respectively. The incidence rates of GDM, gestational hypertension, and preeclampsia/eclampsia were 5.6%, 4.8%, and 1.8%, respectively. After adjusting for relevant confounders, a core standard deviation( s) increase in WBC-1 was associated with a 6%, 18%, and 14% increased risk of GDM, gestational hypertension, and preeclampsia/eclampsia, respectively( P<0.001). Similarly, a one s increase in WBC-2 was associated with a 10% increased risk for all three adverse outcomes( P<0.001). Conclusion:Elevated peripheral WBC levels in the first and second trimesters are independently associated with increased risk of adverse pregnancy outcomes, independent of traditional risk factors.

Objective To learn the current status of informational development in public TCM hospitals in China,and to provide references for promoting the informational development.Methods It makes a comprehensive assessment of the informational level in 2 539 public TCM hospitals nationwide with comprehensive index method,and then analyse the index.Results(1)The construction rate of telemedicine systems in tertiary public TCM hospitals reached 76.96%,and the rate in secondary hospitals is 57.63%.(2)In terms of functional level of electronic medical record application,34.42%of tertiary public TCM hospitals failed to meet the requirement of Level 4,and 40.92%of secondary hospitals failed to meet the requirement of Level 3.In terms of Interconnection standardization maturity level,86.72%of tertiary public TCM hospitals failed to meet the requirement of Level 4.(3)The informational level is not balanced among different typesand different regions in tertiary public TCM hospitals.In secondary public TCM hospitals,there are differences among types of hospitals.Conclusion There are advantages on the development of Internet consultation and telemedicine systems in public TCM hospitals.The standardization of information may be a key factor that affect the lack of data connectivity and smart hospital management.There are differences in the level of informatization among different types of hospitals.So TCM hospitals is recommended to explore the way of development that suit for them.Some hospitalswell-developed should lead the way of development.

The 2021 version of the Baveno Ⅶ consensus on portal hypertension and the 2023 guidelines from the European Association for the Study of the Liver define recompensated cirrhosis as the restoration and stabilization of liver function, improvement of liver fibrosis, and absence of decompensated cirrhosis for a long time following effective treatment of the underlying etiology of cirrhosis. Recompensated cirrhosis has become an important research direction in the field with the gradually increasing number of these patients. Temporary recompensation, stable recompensation, and long-term recompensation are the three stages into which patients with cirrhosis are divided, based on varying recompensation stages. Clinical characteristics and prognosis are significantly different among different stages. Patients in the temporary compensation stage have significant fluctuations in their condition and poor stability, with a high risk of recurrent complications. The prognosis of patients in the stable recompensation stage is significantly affected by the cause and the type of initial decompensation event, while the condition of patients in the long-term recompensation stage is more stable, and the long-term prognosis is close to that of compensated cirrhosis. This article aims to summarize and explore the recompensation rates at different stages of liver cirrhosis, the occurrence risk of various complications and liver cancer, and long-term management and treatment following recompensation, providing new directions for future research in this field.