Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To analyze the burden and trends of noncommunicable chronic disease(NCD) attributable to metabolic factors in China from 1990 to 2021.Methods:Data from the Global Burden of Diseases(GBD) 2021 database were utilized to describe changes in mortality and disability-adjusted life years(DALYs) of NCD in China from 1990 to 2021. Stratified analyses were conducted by age, sex, sociodemographic index(SDI), and related risk factors. Statistical analyses and predictions were conducted using the age-period-cohort model and the Nordpred model.Results:In 2021, the age-standardized mortality rate and age-standardized DALYs rate of NCD attributable to metabolic factors in China were 227.56 per 100 000 and 4 829.39 per 100 000, respectively. Their average annual percentage changes were -0.76%( P<0.001) and -0.77%( P<0.001). Overall, the burden decreased progressively with higher SDI levels. Analysis using the age-period-cohort model indicated reduced birth cohort and period effects for metabolic factor-attributable NCD, while age effects rose significantly. The minimum relative risk( RR) value was observed in the 15-19 age group( RR=0.01), and the maximum RR value occurred in the 95-99 age group( RR=996.86). The overall rising mortality trend indicated that age effects are the predominant driver at present. Projections estimate that by 2046, deaths from metabolic factor-attributable NCD in China will reach 8 189 563, with an age-standardized mortality rate of 236.95 per 100 000. Conclusions:China continues to face a substantial burden of NCD linked to metabolic factors, with older adults, males, and individuals with hypertension, diabetes, and prediabetes identified as key populations requiring targeted interventions.

OBJECTIVE To explore the diagnostic value of combined detection of microRNA(miRNA)and alpha-fetoprotein(AFP),protein induced by vitamin K absence or antagonist-Ⅱ(PIVKA-Ⅱ)in ascites and serum ex-tracellular vesicles(EVs)for hepatitis B virus(HBV)-related primary hepatocellular carcinoma(HCC).METHODS From Nov.2023 to Nov.2024,41 patients with liver cancer and 26 patients with liver cirrhosis who underwent ascites placement or ascites concentration and reinfusion procedures at the Fifth Medical Center of Chi-nese PLA General Hospital were selected as study subjects.Ascites and serum samples were collected.Real-time quantitative reverse transcription polymerase chain reaction(qRT-PCR)was used to detect the expression levels of miR-21,miR-125a,miR-150 and miR-200a in EVs.Chemiluminescence was used to measure the levels of AFP and PIVKA-Ⅱ in ascites,serum and EVs from ascites and serum.An artificial neural network was utilized to con-struct a combined diagnostic model of serum and ascites markers.RESULTS The area under the curve(AUC)for distinguishing HCC from liver cirrhosis using a combination of serum and other indicators was 0.933.The AUC for distinguishing HCC from liver cirrhosis using a combination of ascites and other indicators was 0.912.By screening all detected indicators using an artificial neural network and incorporating indicators with a relative im-portance＞0.5 into the diagnostic model,the model included four indicators:ascites AFP,ascites EVs miR-21,ascites EVs miR-200a and serum EVs miR-200a.This model had a sensitivity of 80.77％,a specificity of 87.80％and an AUC of 0.960 for distinguishing HCC from liver cirrhosis patients.CONCLUSION The combined diagnos-tic markers of miRNA,AFP and PIVKA-Ⅱ in ascites and serum-derived EVs have good application value in the diagnosis of HCC.

OBJECTIVE To explore the diagnostic value of combined detection of microRNA(miRNA)and alpha-fetoprotein(AFP),protein induced by vitamin K absence or antagonist-Ⅱ(PIVKA-Ⅱ)in ascites and serum ex-tracellular vesicles(EVs)for hepatitis B virus(HBV)-related primary hepatocellular carcinoma(HCC).METHODS From Nov.2023 to Nov.2024,41 patients with liver cancer and 26 patients with liver cirrhosis who underwent ascites placement or ascites concentration and reinfusion procedures at the Fifth Medical Center of Chi-nese PLA General Hospital were selected as study subjects.Ascites and serum samples were collected.Real-time quantitative reverse transcription polymerase chain reaction(qRT-PCR)was used to detect the expression levels of miR-21,miR-125a,miR-150 and miR-200a in EVs.Chemiluminescence was used to measure the levels of AFP and PIVKA-Ⅱ in ascites,serum and EVs from ascites and serum.An artificial neural network was utilized to con-struct a combined diagnostic model of serum and ascites markers.RESULTS The area under the curve(AUC)for distinguishing HCC from liver cirrhosis using a combination of serum and other indicators was 0.933.The AUC for distinguishing HCC from liver cirrhosis using a combination of ascites and other indicators was 0.912.By screening all detected indicators using an artificial neural network and incorporating indicators with a relative im-portance＞0.5 into the diagnostic model,the model included four indicators:ascites AFP,ascites EVs miR-21,ascites EVs miR-200a and serum EVs miR-200a.This model had a sensitivity of 80.77％,a specificity of 87.80％and an AUC of 0.960 for distinguishing HCC from liver cirrhosis patients.CONCLUSION The combined diagnos-tic markers of miRNA,AFP and PIVKA-Ⅱ in ascites and serum-derived EVs have good application value in the diagnosis of HCC.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To analyze the burden and trends of noncommunicable chronic disease(NCD) attributable to metabolic factors in China from 1990 to 2021.Methods:Data from the Global Burden of Diseases(GBD) 2021 database were utilized to describe changes in mortality and disability-adjusted life years(DALYs) of NCD in China from 1990 to 2021. Stratified analyses were conducted by age, sex, sociodemographic index(SDI), and related risk factors. Statistical analyses and predictions were conducted using the age-period-cohort model and the Nordpred model.Results:In 2021, the age-standardized mortality rate and age-standardized DALYs rate of NCD attributable to metabolic factors in China were 227.56 per 100 000 and 4 829.39 per 100 000, respectively. Their average annual percentage changes were -0.76%( P<0.001) and -0.77%( P<0.001). Overall, the burden decreased progressively with higher SDI levels. Analysis using the age-period-cohort model indicated reduced birth cohort and period effects for metabolic factor-attributable NCD, while age effects rose significantly. The minimum relative risk( RR) value was observed in the 15-19 age group( RR=0.01), and the maximum RR value occurred in the 95-99 age group( RR=996.86). The overall rising mortality trend indicated that age effects are the predominant driver at present. Projections estimate that by 2046, deaths from metabolic factor-attributable NCD in China will reach 8 189 563, with an age-standardized mortality rate of 236.95 per 100 000. Conclusions:China continues to face a substantial burden of NCD linked to metabolic factors, with older adults, males, and individuals with hypertension, diabetes, and prediabetes identified as key populations requiring targeted interventions.