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.

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 To explore the independent factors affecting tissue inflammatory cells changes in recurrent nasal polyps.METHODS The clinical data of 31 patients with nasal polyps who underwent endoscopic surgery at the Department of Otolaryngology Head and Neck Surgery,Yantai Yuhuanding Hospital from December 2007 to December 2021 were selected and analyzed by stepwise regression logistic analysis.RESULTS The number of tissue inflammatory cells in recurrent nasal polyps changed compared with that in primary nasal polyps,and the number and percentage of neutrophils in recurrent polyps increased(P<0.05).Logistic analysis revealed that smoking was an independent risk factor for eosinophilia in recurrent nasal polyps,increasing age was an independent factor for lowering neutrophils,and the comorbid allergic rhinitis and the time interval of recurrence were independent factors for lowering and increasing lymphocytes,respectively.CONCLUSION The number of tissue-infiltrating cells is altered in recurrent polyps compared with primary polyps.Smoking is an independent risk factor for eosinophilia in recurrent polyps.

Objective: To systematically evaluate the influencing factors for medication compliance in patients with comorbidities of chronic diseases, so as to provide the evidence for improving medication compliance. Methods: Literature on influencing factors for medication compliance in patients with comorbidities of chronic diseases were retrived from CNKI, Wanfang Data, VIP, SinoMed, PubMed, Web of Science, Cochrane Library and Embase from inception to January 20, 2024. After independent literature screening, data extraction, and quality assessment by two researchers, a meta-analysis was performed using RevMan 5.4 and Stata 16.0 softwares. Literature were excluded one by one for sensitivity analysis. Publication bias was assessed using Egger's test. Results: Initially, 7 365 relevant articles were retrieved, and 35 of them were finally included, with a total sample size of about 150 000 individuals. There were 30 cross-sectional studies and 5 cohort studies; and 11 high-quality studies and 24 medium-quality studies. The meta-analysis showed that the demographic factors of lower level of education (OR=2.148, 95%CI: 1.711-2.696), lower economic income (OR=1.897, 95%CI: 1.589-2.264), male (OR=0.877, 95%CI: 0.782-0.985), living alone (OR=2.833, 95%CI: 1.756-4.569) and unmarried (OR=2.784, 95%CI: 1.251-6.196); the medication treatment factors of polypharmacy (OR=1.794, 95%CI: 1.190-2.706), potentially inappropriate medication (OR=2.988, 95%CI: 1.527-5.847), low frequency of daily medication (OR=0.533, 95%CI: 0.376-0.754) and adverse drug reactions (OR=3.319, 95%CI: 1.967-5.602); the disease factors of long course of disease (OR=2.118, 95%CI: 1.643-2.730), more comorbidities (OR=1.667, 95%CI: 1.143-2.431) and cognitive impairment (OR=2.007, 95%CI: 1.401-2.874); and the psychosocial factors of poor belief in taking medication (OR=1.251, 95%CI: 1.011-1.547), poor self-rated health (OR=1.990, 95%CI: 1.571-2.522) and being guided by healthcare professionals (OR=0.151, 95%CI: 0.062-0.368) were the influencing factors for medication compliance in patients with chronic comorbidities. Conclusion The medication compliance in patients with comorbidities of chronic diseases is associated with demographic factors, pharmacological factors, disease factors and psychosocial factors, mainly including living alone, adverse drug reactions, course of disease, number of comorbidities and medication beliefs.

Objective To investigate the dietary patterns of rural residents in the high-incidence areas of esophageal cancer (EC), and to explore the clustering and influencing factors of risk factors associated with high-incidence characteristics. Methods A special structured questionnaire was applied to conduct a face-to-face survey on the dietary patterns of rural residents in Yanting county of Sichuan Province from July to August 2021. Univariate and multivariate logistic regression models were used to analyze the influencing factors of risk factor clustering for EC. Results There were 838 valid questionnaires in this study. A total of 90.8% of rural residents used clean water such as tap water. In the past one year, the people who ate fruits and vegetables, soybean products, onions and garlic in high frequency accounted for 69.5%, 32.8% and 74.5%, respectively; the people who ate kimchi, pickled vegetables, sauerkraut, barbecue, hot food and mildew food in low frequency accounted for 59.2%, 79.6%, 68.2%, 90.3%, 80.9% and 90.3%, respectively. The clustering of risk factors for EC was found in 73.3% of residents, and the aggregation of two risk factors was the most common mode (28.2%), among which tumor history and preserved food was the main clustering pattern (4.6%). The logistic regression model revealed that the gender, age, marital status and occupation were independent influencing factors for the risk factors clustering of EC (P<0.05). Conclusion A majority of rural residents in high-incidence areas of EC in Yanting county have good eating habits, but the clustering of some risk factors is still at a high level. Gender, age, marital status, and occupation are influencing factors of the risk factors clustering of EC.

It is believed that retention due to deficient qi is an important pathogenesis of endometriosis （EMs）. Deficient qi is the root of the disease， mainly manifested as spleen deficiency， while retention is the branch pathogenesis of the disease， mainly with blood stasis， complicated with constraint， phlegm， heat， toxin and other pathological factors. Therefore， it is proposed to follow the treatment principle of supplementing deficiency and unblocking stagnation， and take the methods of replenishing qi and fortifying the spleen， removing stasis and eliminating concretions. Self-made Fuzheng Huayu Formula （扶正化瘀方） is taken as the basic formula， and can be modified with the symptoms in menstrual and non-menstrual periods. Additionally， the methods of moving qi， dispelling phlegm， clearing heat， relieving toxin and others can be combined， and it is recommended to treat the root and the branch simultaneously.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous lung condition characterized by persistent airflow obstruction caused by long-term airway inflammation or alveolar abnormalities, often manifested as chronic respiratory symptoms and decreased lung function. In recent years, experimental research has shown that mesenchymal stem cells (MSC) have anti-inflammatory, immunomodulatory, and repairing properties of lung epithelial cells, which can be used to treat various diseases including COPD. This article is mainly based on the main findings of in vitro and in vivo animal model experiments and clinical studies of MSC treatment for COPD. It summarizes and discusses the possible mechanisms of action of MSC as a new therapy, and provides new ideas for clinical treatment of COPD.

Background::Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk among Chinese women and to simultaneously rank potential non-experimental risk factors.Methods::The Breast Cancer Cohort Study in Chinese Women, a large ongoing prospective dynamic cohort study, includes 122,058 women aged 25-70 years old from the eastern part of China. We developed multiple machine-learning risk prediction models using parametric models (penalized logistic regression, bootstrap, and ensemble learning), which were the short-term ensemble penalized logistic regression (EPLR) risk prediction model and the ensemble penalized long-term (EPLT) risk prediction model to estimate BC risk. The models were assessed based on calibration and discrimination, and following this assessment, they were externally validated in new study participants from 2017 to 2020.Results::The AUC values of the short-term EPLR risk prediction model were 0.800 for the internal validation and 0.751 for the external validation set. For the long-term EPLT risk prediction model, the area under the receiver operating characteristic curve was 0.692 and 0.760 in internal and external validations, respectively. The net reclassification improvement index of the EPLT relative to the Gail and the Han Chinese Breast Cancer Prediction Model (HCBCP) models for external validation was 0.193 and 0.233, respectively, indicating that the EPLT model has higher classification accuracy.Conclusions::We developed the EPLR and EPLT models to screen populations with a high risk of developing BC. These can serve as useful tools to aid in risk-stratified screening and BC prevention.

[ABSTRACT]OBJECTIVE To analyze the risk factors for relapse in patients with chronic rhinosinusitis with nasal polyps(CRSwNP)combined with asthm and provide favorable information for precise treatment and healthy prognosis of patients with CRSwNP combined with asthma.METHODS The clinical data of 161 patients with chronic rhinosinusitis with nasal polyps(CRSwNP)combined with asthm who underwent endoscopic surgery at the Department of Otolaryngology Head and Neck Surgery,Yantai Yuhuanding Hospital,affiliated to Qingdao University,from January 2016 to June 2021 were selected.Based on Lasso's Cox regression analysis and multifactorial Cox regression analysis,the associated risk factors were investigated,and the area under curve(AUC)was calculated to determine the performance of the model.Finally,the Kaplan-Meier(K-M)curves were plotted for the relevant influencing factors.RESULTS The Age[HR(95%CI):0.96(0.948-0.98),P<0.001],gender[HR(95%CI):1.94(1.21-3.14),P=0.006],tissue eosinophil percentage[HR(95%CI):1.01(1.01-1.02),P=0.004],and endoscopic nasal polyp score[HR(95%CI):0.86(0.78-0.96),P=0.005]were highly correlated with recurrence in patients with CRSwNP combined with asthma.Patients with CRSwNP combined with asthma had a higher likelihood of relapse after treatment when the tissue Eos%was>21.28%and the endoscopic nasal polyp score was>4.CONCLUSION The age,gender,tissue eosinophil percentage and endoscopic nasal polyp score are independent risk factors for disease recurrence in patients with CRSwNP combined with asthma.