The implementation of new medical technology projects is a key way for hospitals to improve their medical technology level and core competitiveness. Standardizing medical technology management has become an important part of the construction of the medical quality system in public hospitals of China. In May 2022, a tertiary comprehensive hospital established a " 243" cross departmental collaborative management system, organically integrating multiple information systems within the hospital, and building a medical new technology whole-process information management platform covering the basic system layer, business platform layer, and system function layer. It was officially launched in November 2022, realizing the full process closed-loop management of medical new technology projects from application, approval, project initiation, tracking to completion, improving management quality and efficiency. As of March 2024, the platform had accepted 203 applications for new technologies, of which 139 had been approved and achieved good results, providing references for other hospitals to standardize the management of medical new technologies and reduce medical risks.

This article reported the diagnosis and management of a case of a child with Kabuki syndrome. Kabuki syndrome is characterized by distinct facial features, skeletal anomalies, abnormal skin texture, and intellectual disabilities, and is primarily caused by heterozygous mutations in the lysine methyltransferase 2D(KMT2D) gene. The onset in this patient was insidious, presenting with short stature and intellectual impairment. Genetic testing identified a pathogenic heterozygous variant in the KMT2D gene. This article focuses on analyzing the necessity and appropriateness of growth hormone therapy in children with Kabuki syndrome, and includes a review of relevant literature to improve clinicians′ understanding of this rare condition.

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.

The implementation of new medical technology projects is a key way for hospitals to improve their medical technology level and core competitiveness. Standardizing medical technology management has become an important part of the construction of the medical quality system in public hospitals of China. In May 2022, a tertiary comprehensive hospital established a " 243" cross departmental collaborative management system, organically integrating multiple information systems within the hospital, and building a medical new technology whole-process information management platform covering the basic system layer, business platform layer, and system function layer. It was officially launched in November 2022, realizing the full process closed-loop management of medical new technology projects from application, approval, project initiation, tracking to completion, improving management quality and efficiency. As of March 2024, the platform had accepted 203 applications for new technologies, of which 139 had been approved and achieved good results, providing references for other hospitals to standardize the management of medical new technologies and reduce medical risks.

Objective:To investigate the application value of dual-energy computer tomo-graphy (CT) multi-parameter imaging in predicting the pathological grade of pancreatic ductal adeno-carcinoma (PDAC).Methods:The retrospective cohort study was conducted. The clinicopatholo-gical data of 147 patients with PDAC who were admitted to The Fifth Affiliated Hospital of Wenzhou Medical University from January 2017 to August 2023 were collected. There were 102 males and 45 females, aged (59±10)years. All patients underwent preoperative dual-energy CT examination and postoperative histopathological examination. The 147 patients were divided into a training set of 103 cases and a test set of 44 cases by stratified random sampling at a ratio of 7∶3. The training set was used to construct the prediction model, and the test set was used to verify the effectiveness of prediction model. Observation indicators: (1) analysis of factors affecting the pathological grade of PDAC patients in the training set; (2) construction and evaluation of the fusion prediction model for pathological grade of PDAC. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), accuracy, sensitivity and specificity were calculated. The Delong test was used to analyze the effec-tiveness of model. The calibration curve and decision curve of Hosmer-Lemeshow test were used to evaluate the consistency and clinical application value of the nomogram, respectively. Results:(1) Analysis of factors affecting the pathological grade of PDAC patients in the training set. Results of multivariate analysis showed that tumor cystic necrosis, vascular invasion, standardized iodine concentration (NIC) in venous phase, effective atomic number (Zeff) in venous phase, and energy spectrum curve slope (λ HU) in venous phase were all independent factors affecting the pathological grade of PDAC patients in the training set ( odds ratio=4.326, 3.887, 4.155, 5.389, 3.164, 95% confidence interval as 1.167-16.033, 1.111-13.592, 1.707-10.113, 1.284-22.613, 1.247-8.028, P<0.05). (2) Construction and evaluation of the fusion prediction model for pathological grade of PDAC. Accor-ding to the results of multivariate analysis, tumor cystic necrosis, vascular invasion, NIC in venous phase, Zeff in venous phase and λ HU in venous phase were all included to construct the clinical-imaging fusion prediction nomogram model. The AUC, accuracy, sensitivity and specificity of the fusion prediction model in the training set were 0.938 (95% confidence interval as 0.896-0.981), 87.38%, 89.74% and 85.94%, respectively. The above indicators of the fusion prediction model in the test set were 0.893 (95% confidence interval as 0.802-0.985), 84.09%, 82.35% and 85.19%, respectively. Results of Delong test showed that there was no significant difference in AUC between the training set and the test set ( Z=0.343, P>0.05). Results of Hosmer-Lemeshow test showed that the fusion prediction model had a good fit in the training set and the test set ( χ2=3.042, 7.545, P>0.05). Results of calibration curve showed that the predictive ability of the fusion prediction model was good. Conclusions:Multiple parameters in venous phase of the dual-energy CT can be used as imaging markers for preoperative evaluation of the pathological grade of patients with PDAC. Establishing a clinical-imaging fusion prediction model can effectively predict the pathological grade of PDAC.

Objective:To investigate the application value of dual-energy computer tomo-graphy (CT) multi-parameter imaging in predicting the pathological grade of pancreatic ductal adeno-carcinoma (PDAC).Methods:The retrospective cohort study was conducted. The clinicopatholo-gical data of 147 patients with PDAC who were admitted to The Fifth Affiliated Hospital of Wenzhou Medical University from January 2017 to August 2023 were collected. There were 102 males and 45 females, aged (59±10)years. All patients underwent preoperative dual-energy CT examination and postoperative histopathological examination. The 147 patients were divided into a training set of 103 cases and a test set of 44 cases by stratified random sampling at a ratio of 7∶3. The training set was used to construct the prediction model, and the test set was used to verify the effectiveness of prediction model. Observation indicators: (1) analysis of factors affecting the pathological grade of PDAC patients in the training set; (2) construction and evaluation of the fusion prediction model for pathological grade of PDAC. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), accuracy, sensitivity and specificity were calculated. The Delong test was used to analyze the effec-tiveness of model. The calibration curve and decision curve of Hosmer-Lemeshow test were used to evaluate the consistency and clinical application value of the nomogram, respectively. Results:(1) Analysis of factors affecting the pathological grade of PDAC patients in the training set. Results of multivariate analysis showed that tumor cystic necrosis, vascular invasion, standardized iodine concentration (NIC) in venous phase, effective atomic number (Zeff) in venous phase, and energy spectrum curve slope (λ HU) in venous phase were all independent factors affecting the pathological grade of PDAC patients in the training set ( odds ratio=4.326, 3.887, 4.155, 5.389, 3.164, 95% confidence interval as 1.167-16.033, 1.111-13.592, 1.707-10.113, 1.284-22.613, 1.247-8.028, P<0.05). (2) Construction and evaluation of the fusion prediction model for pathological grade of PDAC. Accor-ding to the results of multivariate analysis, tumor cystic necrosis, vascular invasion, NIC in venous phase, Zeff in venous phase and λ HU in venous phase were all included to construct the clinical-imaging fusion prediction nomogram model. The AUC, accuracy, sensitivity and specificity of the fusion prediction model in the training set were 0.938 (95% confidence interval as 0.896-0.981), 87.38%, 89.74% and 85.94%, respectively. The above indicators of the fusion prediction model in the test set were 0.893 (95% confidence interval as 0.802-0.985), 84.09%, 82.35% and 85.19%, respectively. Results of Delong test showed that there was no significant difference in AUC between the training set and the test set ( Z=0.343, P>0.05). Results of Hosmer-Lemeshow test showed that the fusion prediction model had a good fit in the training set and the test set ( χ2=3.042, 7.545, P>0.05). Results of calibration curve showed that the predictive ability of the fusion prediction model was good. Conclusions:Multiple parameters in venous phase of the dual-energy CT can be used as imaging markers for preoperative evaluation of the pathological grade of patients with PDAC. Establishing a clinical-imaging fusion prediction model can effectively predict the pathological grade of PDAC.

This article reported the diagnosis and management of a case of a child with Kabuki syndrome. Kabuki syndrome is characterized by distinct facial features, skeletal anomalies, abnormal skin texture, and intellectual disabilities, and is primarily caused by heterozygous mutations in the lysine methyltransferase 2D(KMT2D) gene. The onset in this patient was insidious, presenting with short stature and intellectual impairment. Genetic testing identified a pathogenic heterozygous variant in the KMT2D gene. This article focuses on analyzing the necessity and appropriateness of growth hormone therapy in children with Kabuki syndrome, and includes a review of relevant literature to improve clinicians′ understanding of this rare condition.

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.

ObjectiveTo explore the characteristics and associated risk factors of diabetes in patients with schizophrenia living in communities, and to provide a basis for the prevention of diabetes comorbidity in this population. MethodsA stratified cluster sampling was used to randomly select patients with schizophrenia in Shanghai who participated in the free health examination provided by the National Basic Public Health Services in 2020. Statistical methods were employed to analyze the general demographic data, clinical characteristics, and laboratory test results of the study subjects. ResultsThe study included 3 374 individuals with schizophrenia, among which the prevalence of diabetes was 17.01%. Statistically significant differences were observed in terms of age, education level, urban area type, marital status, employment status, duration of illness, blood pressure, body mass index, total cholesterol, and triglyceride levels (all P<0.05). Multivariate logistic regression analysis revealed that living in non-central urban areas (OR=1.76, 95%CI: 1.33‒2.32), disease duration of 6‒ years (OR=2.60, 95%CI: 1.07‒6.32), disease duration of 11‒ years (OR=2.72, 95%CI: 1.17‒6.35), disease duration of 16‒ years (OR=3.38, 95%CI: 1.54‒7.42), hypertension(OR=1.73, 95%CI: 1.27‒2.36), obesity (OR=1.52, 95%CI: 1.15‒2.00), and elevated triglyceride levels (OR=2.78, 95%CI: 2.22‒3.49) were risk factors for diabetes in patients with schizophrenia. ConclusionThe prevalence of diabetes in community-dwelling patients with schizophrenia is higher than that in the general population. It is recommended that appropriate health education and rehabilitation guidance be provided as part of community-based mental health services.

The incidence of chronic fatigue syndrome(CFS)has gradually increased in recent years.Although CFS can severely affect patient quality of life,its clinical diagnosis is easily overlooked.Elucidating the pathogenesis of CFS and treating it from both etiological and symptomatological perspectives are crucial for patient recovery;however,its unclear pathogenesis means that etiological treatment options are limited,and current treatments mainly focus on improving clinical symptoms.In this context,there is a need to establish and evaluate a suitable animal model.This article comprehensively integrates the diagnostic criteria of CFS and progress in related basic research.We also summarize the behavioral experimental method used to evaluate CFS models in basic research in the past 5 years and discuss these evaluations from the perspectives of general condition,fatigue state,cognitive function,emotional state,and pain degree.This review aims to present the current situation,expose problems,trigger reflection,and promote improvements in the behavioral evaluation of animal models of CFS.