OBJECTIVES: To compare the commonly used methods for analyzing treatment switching in clinical trials to facilitate selection of optimal methods in different scenarios. METHODS: Based on the data characteristics of patient conversion in oncology clinical trials, we simulated the survival time of patients across different scenarios and compared the bias, mean square error and coverages of the treatment effects derived from different methods. RESULTS: The sample size had an almost negligible impact on the outcomes of the various methods. Compared to conventional methods, more complex methods (RPSFTM, IPCW, TSE, and IPE) resulted in lower errors across different scenarios. The IPCW method could cause a significant increase in errors in cases where the probability of conversion was high. The TSE method had the lowest error and mean squared error when the risk was low and the probability of conversion was high. The IPE method had an obvious advantage in the scenario with a low probability of conversion, but it may slightly underestimate the treatment effect when the inflation factor was small. CONCLUSIONS The choice of a specific method for analyzing cohort transition should be made based on considerations of both the probability of conversion and inflation factor in different scenarios.
Humans ; Clinical Trials as Topic/methods* ; Neoplasms/therapy*

Objective This study aimed to explore the correlation between abnormal hand features and coronary atherosclerotic heart disease(CHD)to provide clinical data support for digitalized traditional Chinese medicine(TCM)hand diagnosis.Methods A palm key point prediction algorithm was used to automatically capture and collect detailed features of the palm and nails through image analysis and data mining using the hand diagnosis information collection technology based on the NVIDIA Jetson platform and Qt framework.A total of 438 cardiac patients who underwent coronary artery computed tomography angiography(CACTA)in the Department of Cardiology,Dongzhimen Hospital,Beijing University of Chinese Medicine,from December 2023 to April 2024 were included and divided into CHD(148 cases)and non-CHD groups(290 cases)based on the CACTA results.The hand features of the two groups were compared,and abnormal hand features associated with CHD were screened using random forest analysis as well as univariate and multivariate logistic regression analyses.Results Based on the results of univariate logistic regression and random forest analyses,a set of hand-related features associated with CHD were identified and subsequently included in the multivariate logistic regression analysis.These features included the morphology of the thenar eminence,the wrinkles of the thenar eminence,nail shape,nail texture,and the length of the blood vessel in the middle finger.Multivariate logistic regression analysis revealed that hypertrophic thenar eminence[odds ratio(OR):3.049,95%confidence interval(CI):1.430-6.503,P=0.004],presence of wrinkles on the thenar eminence(OR:2.206,95%CI:1.119-4.348,P=0.022),presence of gray-black vertical stripes on the nails(OR:1.981,95%CI:1.173-3.347,P=0.011),uneven nail surface(OR:3.130,95%CI:1.822-5.378,P<0.001),and inward-bending nail surface(OR:5.727,95%CI:1.812-18.102,P=0.003)were positively associated with CHD.In contrast,the blood vessel in the middle finger longer than 1/3 of the phalanx was negatively associated with CHD(OR:0.405,95%CI:0.234-0.702,P=0.001).Conclusion Certain hand features are significantly associated with CHD,providing the valuable clinical data to support for the digitalization of TCM hand diagnosis.

Objective:To compare the clinical effects of plasma exchange（PE）combined with continuous veno-venous hemodiafiltration（CVVHDF）at different time points in children with Kawasaki disease shock syndrome（KDSS）.Methods:Thirty-five children with KDSS admitted to the intensive care unit of Hunan Children's Hospital from January 2018 to December 2022 were enrolled.According to whether PE combined with CVVHDF was performed within 24 hours after reaching the blood purification criteria for KDSS，the patients were divided into the early treatment group(8 cases) and the control group (27 cases).The clinical and laboratory indicators and prognosis were compared between the two groups.Results:There were no statistically significant differences in age，gender，mean arterial pressure，and pediatric critical illness score between the two groups before treatment（ P>0.05）.In the early treatment group,the vasoactive inotropic score (VIS) gradually decreased,and was significantly lower than that in the control group after 24 hours of treatment.The duration of vasopressor use，pediatric logistic organ dysfunction score（PELOD），inflammatory markers，total hospitalization time，and PICU stay were all lower in the early treatment group than in the control group（ P<0.05）.The incidence of coronary artery involvement within 6 months post-discharge was lower in the early treatment group than in the control group（ P<0.05）.Among the 12 children who underwent PE combined with CVVHDF，four cases were in the late treatment group.The duration of CVVHDF，PICU stay，and PELOD scores were lower in the early treatment group than in the late treatment group（ P<0.05）.Additionally，the concentrations of interleukin-6，tumor necrosis factor-α，heparin-binding protein，and N-terminal pro-brain natriuretic peptide before PE were lower in the early treatment group than in the late treatment group（ P<0.05）. Conclusion:Early PE combined with CVVHDF treatment for KDSS patients can reduce inflammatory response，shorten the course of the disease，and reduce the duration of vasopressor use.However，most patients' conditions can be controlled with active conventional treatment.

Objective This study aimed to explore the correlation between abnormal hand features and coronary atherosclerotic heart disease(CHD)to provide clinical data support for digitalized traditional Chinese medicine(TCM)hand diagnosis.Methods A palm key point prediction algorithm was used to automatically capture and collect detailed features of the palm and nails through image analysis and data mining using the hand diagnosis information collection technology based on the NVIDIA Jetson platform and Qt framework.A total of 438 cardiac patients who underwent coronary artery computed tomography angiography(CACTA)in the Department of Cardiology,Dongzhimen Hospital,Beijing University of Chinese Medicine,from December 2023 to April 2024 were included and divided into CHD(148 cases)and non-CHD groups(290 cases)based on the CACTA results.The hand features of the two groups were compared,and abnormal hand features associated with CHD were screened using random forest analysis as well as univariate and multivariate logistic regression analyses.Results Based on the results of univariate logistic regression and random forest analyses,a set of hand-related features associated with CHD were identified and subsequently included in the multivariate logistic regression analysis.These features included the morphology of the thenar eminence,the wrinkles of the thenar eminence,nail shape,nail texture,and the length of the blood vessel in the middle finger.Multivariate logistic regression analysis revealed that hypertrophic thenar eminence[odds ratio(OR):3.049,95%confidence interval(CI):1.430-6.503,P=0.004],presence of wrinkles on the thenar eminence(OR:2.206,95%CI:1.119-4.348,P=0.022),presence of gray-black vertical stripes on the nails(OR:1.981,95%CI:1.173-3.347,P=0.011),uneven nail surface(OR:3.130,95%CI:1.822-5.378,P<0.001),and inward-bending nail surface(OR:5.727,95%CI:1.812-18.102,P=0.003)were positively associated with CHD.In contrast,the blood vessel in the middle finger longer than 1/3 of the phalanx was negatively associated with CHD(OR:0.405,95%CI:0.234-0.702,P=0.001).Conclusion Certain hand features are significantly associated with CHD,providing the valuable clinical data to support for the digitalization of TCM hand diagnosis.

Objective:To compare the clinical effects of plasma exchange（PE）combined with continuous veno-venous hemodiafiltration（CVVHDF）at different time points in children with Kawasaki disease shock syndrome（KDSS）.Methods:Thirty-five children with KDSS admitted to the intensive care unit of Hunan Children's Hospital from January 2018 to December 2022 were enrolled.According to whether PE combined with CVVHDF was performed within 24 hours after reaching the blood purification criteria for KDSS，the patients were divided into the early treatment group(8 cases) and the control group (27 cases).The clinical and laboratory indicators and prognosis were compared between the two groups.Results:There were no statistically significant differences in age，gender，mean arterial pressure，and pediatric critical illness score between the two groups before treatment（ P>0.05）.In the early treatment group,the vasoactive inotropic score (VIS) gradually decreased,and was significantly lower than that in the control group after 24 hours of treatment.The duration of vasopressor use，pediatric logistic organ dysfunction score（PELOD），inflammatory markers，total hospitalization time，and PICU stay were all lower in the early treatment group than in the control group（ P<0.05）.The incidence of coronary artery involvement within 6 months post-discharge was lower in the early treatment group than in the control group（ P<0.05）.Among the 12 children who underwent PE combined with CVVHDF，four cases were in the late treatment group.The duration of CVVHDF，PICU stay，and PELOD scores were lower in the early treatment group than in the late treatment group（ P<0.05）.Additionally，the concentrations of interleukin-6，tumor necrosis factor-α，heparin-binding protein，and N-terminal pro-brain natriuretic peptide before PE were lower in the early treatment group than in the late treatment group（ P<0.05）. Conclusion:Early PE combined with CVVHDF treatment for KDSS patients can reduce inflammatory response，shorten the course of the disease，and reduce the duration of vasopressor use.However，most patients' conditions can be controlled with active conventional treatment.

Previous studies mainly used β-amyloid and α-synuclein as the biomarkers for the diagnosis of neurodegenerative diseases. In recent years，studies have shown that telomeres at the end of chromosome can be used as an index to measure the degree of biological aging，and telomere length and telomerase activity may also be used as the blood markers to evaluate the risk，progression，and poor prognosis of neurodegenerative diseases in the elderly；however，there is still a lack of consistency between the research findings in China and globally. Understanding the role of telomere-related biomarkers in age-related diseases can help clinicians learn more about the mechanism of disease development and progression. This article reviews the latest research advances in the telomere-telomerase system in neurodegenerative diseases，in order to introduce the influence of telomere length and telomerase activity on neurodegenerative diseases and their potential mechanisms of action.
Telomere ; Telomerase ; Neurodegenerative Diseases ; Alzheimer Disease ; Parkinson Disease

The overall health condition of patients significantly affects the diagnosis,treatment,and prognosis of endodontic diseases.A systemic consideration of the patient's overall health along with oral conditions holds the utmost importance in determining the necessity and feasibility of endodontic therapy,as well as selecting appropriate therapeutic approaches.This expert consensus is a collaborative effort by specialists from endodontics and clinical physicians across the nation based on the current clinical evidence,aiming to provide general guidance on clinical procedures,improve patient safety and enhance clinical outcomes of endodontic therapy in patients with compromised overall health.

Objective:To construct a risk prediction model for the inter-hospital transfer of critically ill children using machine learning methods, identify key medical features affecting transfer outcomes, and improve the success rate of transfers.Methods:A prospective study was conducted on critically ill children admitted to the pediatric transfer center of Hunan Children's Hospital from January 2020 to January 2021. Medical data on critical care features and relevant data from the Pediatric Risk of Mortality (PRISMⅢ) scoring system were collected and processed. Three machine learning models, including logistic regression, decision tree, and Relief algorithm, were used to construct the risk prediction model. A back propagation neural network was employed to build a referral outcome prediction model to verify and analyze the selected medical features from the risk prediction model, exploring the key medical features influencing inter-hospital transfer risk.Results:Among the 549 transferred children included in the study, 222 were neonates (40.44%) and 327 were non-neonates (59.56%). There were 50 children in-hospital deaths, resulting in a mortality rate of 9.11%. After processing 151 critical care medical feature data points, each model selected the top 15 important features influencing transfer outcomes, with a total of 34 selected features. The decision tree model had an overlap of 72.7% with PRISMⅢ indicators, higher than logistic regression (36.4%) and Relief algorithm (27.3%). The training prediction accuracy of the decision tree model was 0.94, higher than the accuracy of 0.90 when including all features, indicating its clinical utility. Among the top 15 important features selected by the decision tree model, the impact on transfer outcomes was ranked as follows based on quantitative feature violin plots: base excess, total bilirubin, ionized calcium, total time, arterial oxygen pressure, blood parameters (including white blood cells, platelets, prothrombin time/activated partial thromboplastin time), carbon dioxide pressure, blood glucose, systolic blood pressure, heart rate, organ failure, lactate, capillary refill time, temperature, and cyanosis. Eight of these important features overlapped with PRISMⅢ indicators, including systolic blood pressure, heart rate, temperature, pupillary reflex, consciousness, acidosis, arterial oxygen pressure, carbon dioxide pressure, blood parameters, and blood glucose. The decision tree was used to select the top 15 medical features with high impact on the neonatal and non-neonatal datasets, respectively. A total of 19 features were selected, among which there were 8 differences and 11 overlap terms between the important features of the neonatal and non-neonatal.Conclusions:Machine learning models could serve as reliable tools for predicting the risk of inter-hospital transfer of critically ill children. The decision tree model exhibits superior performance and helps identify key medical features affecting inter-hospital transfer risk, thereby improving the success rate of inter-hospital transfers for critically ill children.

Objective:To develop a questionnaire on knowledge, attitude and practice of Helicobacter pylori (Hp) infection among physical examination population, and to verify its reliability and validity.Methods:This study was a cross-sectional survey. Based on the theory of knowledge, attitude and practice, the first draft of the questionnaire on knowledge, attitude and practice of Hp infection in physical examination population was designed by means of retrospective literature research, qualitative interview, discussion in the research group. The structure and items of the questionnaire were consulted and revised by the expert consultation method (Delphi method). Through pre investigation of 186 physical examination personnel from May to June in 2021, the final version of the "knowledge, attitude and practice questionnaire on Helicobacter pylori infection among physical examination population" was formed after adjustment and verification of the reliability and validity of the questionnaire.Results:The questionnaire of knowledge, attitude and practice of Hp infection in physical examination population included 3 dimensions and 28 items, and the cumulative variance contribution rate was 56.271%. The content validity index of each item level of the questionnaire was 0.75-1.00, and the content validity index of the total questionnaire was 0.94. The Cronbach alpha of knowledge, attitude and practice dimensions in this questionnaire were 0.862, 0.901 and 0.798 respectively. The overall Cronbach alpha of the questionnaire was 0.890, and the half reliability was 0.698. The test-retest reliability of the questionnaire was 0.919, and the test-retest reliability of each dimension was 0.924, 0.917 and 0.845.Conclusions:The questionnaire has good reliability and validity, and can be used to measure the level of knowledge, attitude and practice of Hp infection in physical examination population.

Objective To investigate the relationship between sleep duration and obesity, and the risk of common chronic diseases in the occupational population in Shanghai City. Methods A total of 18 775 occupational individuals were selected as the study subjects using convenience sampling method in Shanghai City. Data on personal lifestyle behaviors and medical examination results were collected. The relationship between sleep duration and different types of obesity with dyslipidemia, hyperuricemia, hypertension, and hyperglycemia was analyzed. Results The incidence of dyslipidemia, hyperuricemia, hypertension, and hyperglycemia among the study subjects was 24.9%, 16.2%, 11.5%, and 7.3%, respectively. The incidence of these four chronic diseases were higher in individuals with central obesity and suboptimal sleep compared to the control group (all P<0.01). Multivariate logistic regression analysis showed that suboptimal sleep combined with general obesity/overweight increased the risk of dyslipidemia, hyperuricemia, hypertension, and hyperglycemia in the study subjects ［odds ratio (OR) were 2.40, 3.47, 3.30, and 2.79, respectively; all P<0.01］, after adjusting for age, gender, education level, marital status, occupation type, labor intensity, smoking, and drinking. Suboptimal sleep combined with central obesity also potentially increased the risk of these four chronic diseases (OR were 2.25, 3.09, 3.09, and 2.98, respectively; all P<0.01). Conclusion The incidence of common chronic diseases is relatively high in the occupational population in Shanghai City. Suboptimal sleep combined with different types of obesity increases the risk of common chronic diseases.