A Practical Nomogram for Predicting the Bleeding Risk in Patients with a History of Myocardial Infarction Treating with Aspirin.

BACKGROUND: Aspirin is a widely used antiplatelet medication to prevent blood clots, reducing the risk of cardiovascular event. Healthcare providers need to be mindful of the risk of aspirin-induced bleeding and carefully balancing its benefits against potential risks. The objective of this study was to create a practical nomogram for predicting bleeding risk in patients with a history of myocardial infarction treating with aspirin. METHODS: A total of 2099 myocardial infarction patients with aspirin were enrolled. The patients were randomly divided into two groups, with a 7:3 ratio, for model development and internal validation. Boruta analysis was utilized to identify clinically significant features associated with bleeding. Logistic regression model based on independent bleeding risk factors was constructed and presented as a nomogram. Model performance was assessed from three aspects: identification, calibration, and clinical utility. RESULTS: Boruta analysis identified eight clinical features from 25, and further multivariate logistic regression analysis selected four independent risk factors: hemoglobin, platelet count, previous bleeding, and sex. A visual nomogram was created based on these variables. The model achieved an area under the curve of 0.888 (95% CI: 0.845-0.931) in the training dataset and 0.888 (95% CI: 0.808-0.968) in the test dataset. Calibration curve analysis showed close approximation to the ideal curve. Decision curve analysis demonstrated favorable clinical net benefit for the model. CONCLUSIONS: Our study focused on creating and validating a model to evaluate bleeding risk in patients with a history of myocardial infarction treated with aspirin, which demonstrated outstanding performance in discrimination, calibration, and net clinical benefit.

LASSO-derived model for the prediction of bleeding in aspirin users.

Aspirin is widely used for both primary and secondary prevention of panvascular diseases, such as stroke and coronary heart disease (CHD). The optimal balance between reducing panvascular disease events and the potential increase in bleeding risk remains unclear. This study aimed to develop a predictive model specifically designed to assess bleeding risk in individuals using aspirin. A total of 58,415 individuals treated with aspirin were included in this study. Detailed data regarding patient demographics, clinical characteristics, comorbidities, medical history, and laboratory test results were collected from the Affiliated Dongyang Hospital of Wenzhou Medical University. The patients were randomly divided into two groups at a ratio of 7:3. The larger group was used for model development, while the smaller group was used for internal validation. To develop the prediction model, we employed least absolute shrinkage and selection operator (LASSO) regression followed by multivariate logistic regression. The performance of the model was assessed through metrics such as the area under the receiver operating characteristic (ROC) curve (AUC), calibration curves, and decision curve analysis (DCA). The LASSO-derived model employed in this study incorporated six variables, namely, sex, operation, previous bleeding, hemoglobin, platelet count, and cerebral infarction. It demonstrated excellent performance at predicting bleeding risk among aspirin users, with a high AUC of 0.866 (95% CI 0.857-0.874) in the training dataset and 0.861 (95% CI 0.848-0.875) in the test dataset. At a cutoff value of 0.047, the model achieved moderate sensitivity (83.0%) and specificity (73.9%). The calibration curve analysis revealed that the nomogram closely approximated the ideal curve, indicating good calibration. The DCA curve demonstrated a favorable clinical net benefit associated with the nomogram model. Our developed LASSO-derived predictive model has potential as an alternative tool for predicting bleeding in clinical settings.

Development and validation of a novel model to predict pulmonary embolism in cardiology suspected patients: A 10-year retrospective analysis.

As there are no predictive models for pulmonary embolism (PE) in patients with suspected PE at cardiology department. This study developed a predictive model for the probability of PE development in these patients. This retrospective analysis evaluated data from 995 patients with suspected PE at the cardiology department from January 2012 to December 2021. Patients were randomly divided into the training and validation cohorts (7:3 ratio). Using least absolute shrinkage and selection operator regression, optimal predictive features were selected, and the model was established using multivariate logistic regression. The features used in the final model included clinical and laboratory factors. A nomogram was developed, and its performance was assessed and validated by discrimination, calibration, and clinical utility. Our predictive model showed that six PE-associated variables (age, pulse, systolic pressure, syncope, D-dimer, and coronary heart disease). The area under the curve - receiver operating characteristic curves of the model were 0.721 and 0.709 (95% confidence interval: 0.676-0.766 and 0.633-0.784), respectively, in both cohorts. We also found good consistency between the predictions and real observations in both cohorts. In decision curve analysis, the numerical model had a good net clinical benefit. This novel model can predict the probability of PE development in patients with suspected PE at cardiology department.

Effect of tDCS on corticomuscular coupling and the brain functional network of stroke patients.

Transcranial direct current stimulation (tDCS) is an emerging brain intervention technique that has gained growing attention in recent years in the rehabilitation area. In this paper, we investigated the efficacy of tDCS in the rehabilitation process of stroke patients, utilizing corticomuscular coupling (CMC) and brain functional network analysis. Specifically, we examined changes in CMC relationships between the treatment and control groups before and after rehabilitation by transfer entropy (TE), and constructed brain functional networks by TE. We further calculated features of the functional networks, including node degree, global efficiency, clustering coefficient, characteristic path length, and small world index. Our results demonstrate that CMC in patients increased significantly after treatment, with greater improvements in the tDCS group, particularly within the beta and gamma bands. In addition, the functional brain network analysis revealed enhanced connectivity between brain regions, improved information processing capacity, and increased transmission efficiency in patients as their condition improved. Notably, treatment with tDCS resulted in more significant improvements than the sham group, with a statistically significant difference observed after rehabilitation treatment (p < 0.05). These findings provide compelling evidence regarding the role of tDCS in the treatment of stroke and highlight the potential of this approach in stroke rehabilitation. The use of tDCS for therapeutic interventions in stroke rehabilitation can significantly improve the coupling of patients' functional brain networks. Also, using Transfer Entropy (TE) as a characteristic of CMC, tDCS was found to significantly enhance patients' TE, i.e. enhanced CMC.

A nomogram for predicting the risk of pulmonary embolism in neurology department suspected PE patients: A 10-year retrospective analysis.

Objective: The purpose of this retrospective study was to establish a numerical model for predicting the risk of pulmonary embolism (PE) in neurology department patients. Methods: A total of 1,578 subjects with suspected PE at the neurology department from January 2012 to December 2021 were considered for enrollment in our retrospective study. The patients were randomly divided into the training cohort and the validation cohort in the ratio of 7:3. The least absolute shrinkage and selection operator regression were used to select the optimal predictive features. Multivariate logistic regression was used to establish the numerical model, and this model was visualized by a nomogram. The model performance was assessed and validated by discrimination, calibration, and clinical utility. Results: Our predictive model indicated that eight variables, namely, age, pulse, systolic pressure, hemoglobin, neutrophil count, low-density lipoprotein, D-dimer, and partial pressure of oxygen, were associated with PE. The area under the receiver operating characteristic curve of the model was 0.750 [95% confidence interval (CI): 0.721-0.783] in the training cohort and 0.742 (95% CI: 0.689-0.787) in the validation cohort, indicating that the model showed a good differential performance. A good consistency between the prediction and the real observation was presented in the training and validation cohorts. The decision curve analysis in the training and validation cohorts showed that the numerical model had a good net clinical benefit. Conclusion: We established a novel numerical model to predict the risk factors for PE in neurology department suspected PE patients. Our findings may help doctors to develop individualized treatment plans and PE prevention strategies.

SARS-CoV-2 RdRp is a versatile enzyme with proofreading activity and ability to incorporate NHC into RNA by using diphosphate form molnupiravir as a substrate

The coronavirus disease 2019 (COVID-19) has been ravaging throughout the world for more than two years and has severely impaired both human health and the economy. The causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) employs the viral RNA-dependent RNA polymerase (RdRp) complex for genome replication and transcription, making RdRp an appealing target for antiviral drug development. Here, we reveal that RdRp can recognize and utilize nucleoside diphosphates (NDPs) as a substrate to synthesize RNAs with an efficiency of about two thirds of using nucleoside triphosphates (NTPs) as a substrate. NDPs incorporation is also template-specific and has high fidelity. Moreover, RdRp can incorporate {beta}-d-N4-hydroxycytidine (NHC) into RNA while using diphosphate form molnupiravir (MDP) as a substrate. We also observed that MDP is a better substrate for RdRp than the triphosphate form molnupiravir (MTP).

A random forest model to predict acute kidney injury after acute myocardial infarction / 中华急诊医学杂志

Objective:Our study aims to predict acute kidney injury (AKI) in acute myocardial infarction (AMI) by establishing a random forest model.Methods:By using the clinical database from affiliated Dongyang Hospital of Wenzhou Medical University, a total of 1 363 AMI cases were included. Then, 75% of participants were analyzed as training subsets and the remaining 25% were testing subsets. The CARET package in R was used to filter variables and build random forest. The prediction ability of established model was evaluated by specificity, sensitivity, accuracy, relative operating characteristic curve (ROC curve) in testing subsets. In addition, the performance of random forest was compared with other 3 commonly used machine learning algorithms (Artificial Neural Network, Naive Bayes, and Support Vector Machine).Results:In this study, 30 variables including the demographic information, risk factors of cardiovascular disease, vital signs at admission, laboratory tests were identified and used to establish our random forest prediction model. The area under the curve of the testing subsets ROC was 0.893. The specificity and sensitivity of prediction model was 0.791 and 0.866, respectively. And the first creatinine, first blood urea nitrogen, and D-dimer after admission, age, mechanical ventilation were the top-five factors in this model. After comparing various machine learning algorithms, random forest model had a better performance.Conclusion:The random forest model would be used to predict the occurrence of AMI with AKI.

Expression of CCL2 in colorectal cancer and its role in carcinogenesis / 中华普通外科杂志

Objective To investigate the expression of CCL2 in colorectal cancer and its carcinogenesis mechanism associated with macrophages.Methods The expression level of CCL2 mRNA in 17 cases of colorectal cancer tissues and corresponding adjacent tissues were analyzed by PCR,and the phenotypes of macrophages in tumor infiltrating lymphocytes (TIL) were analyzed by flow cytometry.Human peripheral blood mononuclear cells were isolated and induced to differentiate into macrophages.After 12 h incubation with CCL2,the phenotypic changes of macrophages were analyzed by flow cytometry.The expression level of VEGF,COX-2 and IL-6 in the supernatant were measured by ELISA assay.Results The expression level of CCL2 in colorectal cancer tissues was significantly higher than that in corresponding adjacent mucosal tissues (t =4.017,P ＜ 0.05),and the macrophages in TIL had a high proportion of CCR2 phenotype.CCL2 was shown to induce increased CCR2 expression in macrophages (t =5.070,P ＜ 0.05),and promote the secretion of the tumor growth-associated factors such as VEGF,COX-2 and IL-6 (all P ＜ 0.05).Conclusion The levels of CCL2 in colorectal cancer were up-regulated suggesting that CCL2 may play a key role in tumor promotion by recruiting macrophages and influencing their function.

Application research of Four Topics method in the clinical ethics training of standardized resident training / 中华医学教育探索杂志

Due to the insufficient education of medical ethics and tending to medical moral educa-tion, the residents lack the ability to make ethical decisions. Therefore, we applied Four Topics method in the clinical ethics training of residents. The clinical ethics training was divided into three stages, and each stage had different training content and objectives. Dongyang People's Hospital adopted the form of lectures and panel discussions. During the group discussion, the group leader was in charge of case preparation, which came from clinical practice, and then all members applied the Four Topics method to analyze and discuss the ethical conflicts, and make the ethical decision. Through this process, residents' ability to solve ethical problems in clinical practice was enhanced.

Effects of phycocyanin on apoptosis of human laryngeal cancer HEP-2 cells / 中国病理生理杂志

[ ABSTRACT] AIM:To investigate the effect of phycocyanin on the apoptosis of human laryngeal cancer HEP-2 cells and to explore the inhibitory mechanism of phycocyanin to tumor.METHODS:Highly purified phycocyanin was ex-tracted from spirulina.The effects of phycocyanin at different concentrations on the growth of human laryngeal cancer HEP-2 cells were detected by MTT assay.In addition, the cell structures were observed under electron microscope.The cell ap-optosis was analyzed by flow cytometry.The production of reactive oxygen species ( ROS) was measured by flow cytometry. Enzymatic activities of caspase-3,-8 and-9 were measured by chemical colorimatry.The expression of Bax, Bcl-2, Fas, P53, caspase-3 and caspase-9 at mRNA and protein levels was determined by RT-PCR and Western blot.RESULTS:MTT test confirmed that phycocyanin inhibited the cell activity of HEP-2 cells with time and dose dependent manners.The result of electron microscope observation and flow cytometry indicated that phycocyanin induced the apoptosis of HEP-2 cells.The intracellular content of ROS was increased.The activities of caspase-3, -8 and -9 were increased.RT-PCR showed that the mRNA expression of Bax, Fas, P53, caspase-3, caspase-9 was increased and Bcl-2 was decreased.The results of Western blot were consistent with the results of RT-PCR.CONCLUSION:Phycocyanin might induce apoptosis of HEP-2 cells by down-regulating Bcl-2, up-regulating Bax, Fas and P53, and the transduction of apoptotic signals in the human laryngeal cancer cells.

Education of evidence-based medicine in research practice in primary hospital / 中华医学科研管理杂志

Education of evidence-based medicine in clinical research is important in enhancing primary hospital clinical research capacity and quality.Dongyang People's Hospital of Zhejiang Province has carried out evidence-based medicine education and training,and greatly improved the performance of clinical research and development of scientific researchers.

Effectiveness of promotion and training of evidence-based medicine in primary hospital / 中华医学教育探索杂志

Clinical thinking of Clinicians in Dongyang People's Hospital is gradually shifting from ‘empirical medicine’ to ‘evidence-based medicine’ after popularizing of evidence-based medicine, training core members and implementing multi-layered, multi-channeled, comprehensive and sustainable resident doctor training mode with clear steps and purposes within three years. This paper discussed on reasonable clinical practice of evidence-based medicine in primary hospital and provided realistic basis for the further development and improvement of training of evidence-based medicine in primary hospital.

Clinical value of serum glypican 3 in the diagnosis of hepatocellular carcinoma / 中华全科医师杂志

Five groups were assigned to include intrahepatic cholangiocarcinoma ( ICC, n=30 ) , liver cirrhosis (LC,n=30),metastatic carcinoma (MCA,n=30) and 30 healthy subjects.The serum level of GPC3 was measured by a sandwich method of enzyme-linked immunosorbent assay ( ELISA ) and alpha-fetoprotein (AFP) by microparticle enzyme immunoassay (MEIA).The serum levels of GPC3 and AFP were significantly higher than those of other groups (P<0.05).At a cut-off value of 3.5μg/L,the sensitivity and specificity of GPC3 in the diagnosis of HCC was 83.3%and 76.7%respectively.The sensitivity of combined measurement of GPC3 and AFP was better than GPC3 or AFP alone.Detectable GPC3 was significantly correlated with the presence of viral hepatitis markers and tumor size.However there was no obvious difference in tumor thrombi in portal vein ( PVTT), tumor number, age, gender or hepatic function of HCC.Thus,as a sensitive serum diagnostic marker for HCC ,GPC3 may be a good supplement to AFP in differentiating HCC from non-malignant chronic liver diseases and other liver cancers.

Detecting Results of HBV-DNA,HBeAg and PreS1 of HBV Infected Sera:Analysis and Significance / 中华医院感染学杂志

OBJECTIVE To detect and analyze the results and significance of HBV-DNA,HBeAg and PreS1 of HBV infective sera.METHODS Routine detection and PreS1 antigen of 450 sera were tested by ELISA,and HBV-DNA was detected by fluorescent quantitation PCR.RESULTS The positive rates of HBV-DNA,HBeAg and PreS1 were 74.4%,48.9% and 63.3%,respectively,in 450 cases of HBV infective sera.Among 285 PreS1-positive samples,the positive cases of HBeAg and HBV-DNA were 190 and 270,respectively.There were significant difference(P0.05)among PreS1,HBV-DNA and PreS1,and they three were in positive correlation.CONCLUSIONS PreS1 and HBV-DNA are more sensitive than HBeAg,and PreS1 is better coincided with HBV-DNA.They can reflect the infection and replication condition of HBV.Therefore,it has important clinical meaning for the diagnosis and therapy of HBV to simultaneously used HBV-DNA,HBeAg and PreS1.