Objective:To explore the implementation effects of an proactive health management model for elderly patients with multimorbidity in comprehensive hospitals based on the concept of people-centered integrated care (PCIC).Methods:This study was a randomized controlled trial. Elderly patients who were hospitalized in the Department of General Practice at Shanghai East Hospital Tongji University and also suffered from hypertension, type 2 diabetes and dyslipidemia from November 2022 to January 2024 were included, and were divided into the control group (traditional health management, n=25) and the intervention group (proactive health management, n=25) using the random number table method. A research team comprising experts in general medicine, pharmacy, nutrition, rehabilitation medicine, psychology, and other relevant specialties was formed. Based on literature analysis, clinical experience, and hospital resources, the team collaborated to develop a comprehensive, hospital-based proactive health management model for elderly patients with comorbidities based on the PCIC concept. Patients in the control group were managed using the traditional health management model. Patients in the intervention group were managed using the proactive health management model. Baseline clinical data was collected and the patients were followed up for 6 months. At the 6-month follow-up, data on blood pressure, fasting blood glucose, and blood lipids were collected, as well as information on polypharmacy, activities of daily living (ADL) ability, 10-year atherosclerotic cardiovascular disease (ASCVD) risk, and unplanned rehospitalization were recorded. Results:A total of 50 patients were enrolled, with 25 patients in each group. The control group had an average age of (70.40±6.54) years, with 15 males(60.0%). The intervention group had an average age of (71.20±5.14) years, with 16 males(64.0%). At the 6-month follow-up, the standardization rates of blood pressure, fasting blood glucose, glycated hemoglobin, low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), and triglycerides (TG) in both groups were higher than those in the baseline (all P<0.05).In addition, patients in the intervention group had the compliance rates for higher blood pressure, fasting blood glucose, 2-hour postprandial blood glucose, HbA1c, LDL-C, non-HDL-C, and TG than the control group (all P<0.05).At the 6-month follow-up, the 10-year ASCVD high-risk patient percentage decreased in the intervention group compared with baseline ( P=0.023) and was lower than that of the control group ( P=0.045), and the unanticipated readmission rate of patients in the intervention group was also lower than that of the control group ( P=0.042). Conclusions:A proactive health management model for elderly patients with geriatric multimorbidity in a comprehensive hospital, based on the concept of PCIC, was applied to an elderly population with concurrent hypertension, type 2 diabetes and dyslipidemia. The results of the management were favorable.

Objective:To explore the implementation effects of an proactive health management model for elderly patients with multimorbidity in comprehensive hospitals based on the concept of people-centered integrated care (PCIC).Methods:This study was a randomized controlled trial. Elderly patients who were hospitalized in the Department of General Practice at Shanghai East Hospital Tongji University and also suffered from hypertension, type 2 diabetes and dyslipidemia from November 2022 to January 2024 were included, and were divided into the control group (traditional health management, n=25) and the intervention group (proactive health management, n=25) using the random number table method. A research team comprising experts in general medicine, pharmacy, nutrition, rehabilitation medicine, psychology, and other relevant specialties was formed. Based on literature analysis, clinical experience, and hospital resources, the team collaborated to develop a comprehensive, hospital-based proactive health management model for elderly patients with comorbidities based on the PCIC concept. Patients in the control group were managed using the traditional health management model. Patients in the intervention group were managed using the proactive health management model. Baseline clinical data was collected and the patients were followed up for 6 months. At the 6-month follow-up, data on blood pressure, fasting blood glucose, and blood lipids were collected, as well as information on polypharmacy, activities of daily living (ADL) ability, 10-year atherosclerotic cardiovascular disease (ASCVD) risk, and unplanned rehospitalization were recorded. Results:A total of 50 patients were enrolled, with 25 patients in each group. The control group had an average age of (70.40±6.54) years, with 15 males(60.0%). The intervention group had an average age of (71.20±5.14) years, with 16 males(64.0%). At the 6-month follow-up, the standardization rates of blood pressure, fasting blood glucose, glycated hemoglobin, low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), and triglycerides (TG) in both groups were higher than those in the baseline (all P<0.05).In addition, patients in the intervention group had the compliance rates for higher blood pressure, fasting blood glucose, 2-hour postprandial blood glucose, HbA1c, LDL-C, non-HDL-C, and TG than the control group (all P<0.05).At the 6-month follow-up, the 10-year ASCVD high-risk patient percentage decreased in the intervention group compared with baseline ( P=0.023) and was lower than that of the control group ( P=0.045), and the unanticipated readmission rate of patients in the intervention group was also lower than that of the control group ( P=0.042). Conclusions:A proactive health management model for elderly patients with geriatric multimorbidity in a comprehensive hospital, based on the concept of PCIC, was applied to an elderly population with concurrent hypertension, type 2 diabetes and dyslipidemia. The results of the management were favorable.

Continuing medical education for general practitioners is an important measure to upgrade the quality of primary health care services in China, which is still facing various challenges and need to be further developed and improved. This article analyzes the status quo and existing problems of continuing medical education for general practitioners in China, and proposes suggestions based on the concept of people centered and integrated health care (PCIC), including faculty development, training contents, assessment methods, and experience learning, to provide references for the improvement of continuing medical education for general practitioners.

Multimorbidity management for the elderly is a big challenge for China′s healthcare system and the people centered integrated care (PCIC) is a new concept in health care reform, and the application of the PCIC in multimorbidity management can better improve the health servece for elderly patients. This article applies SWOT analysis to assess the internal strengths and weaknesses as well as external opportunities and threats of applying the PCIC to the geriatric management of multimorbidity; also proposes strategies of geriatric management for elderly patients with Chinese characteristics based on concept of PCIC. The proposed stretegies optimize the personalized assessment with the digital technology, promotes the management with close-knit healthcare system, and strengthen the role of primary medical institutions to improve the long-term management mechanism of multimorbidity.

Shanghai East Hospital has built a general practice residency training information system based on "Internet +" technology since 2017. This training system effectively promoted the training quality, improved the clinical and research ability of general practitioners, and strengthened the supervision of the training. It has improved the training satisfaction, increased passing rate of national medical licensing examination and graduation comprehensive examination of trainees. This training system can largely break the time and space limitations, and has strong replicability. It may provide reference to optimize the general practice standardized residency training for other institutions.

Objective:To explore the diagnostic value of radiomics based on arterial-venous mixed images derived from dual-energy CT (DECT) data in diagnosis of cervical lymph nodes (LNs) metastasis of papillary thyroid cancer (PTC).Methods:From June 2017 to December 2018, eighty-four patients with preoperatively DECT scanning and pathologically confirmed PTC (129 non-metastatic LNs and 97 metastatic LNs) in the First Affiliated Hospital of Nanjing Medical University were included in this study. The clinical and imaging data of all patients were retrospectively analyzed. The training cohort consisted of 62 PTC cases with 156 LNs (91 non-metastatic LNs and 65 metastatic LNs). An independent validation cohort consisted of 22 PTC patients with 70 LNs (38 non-metastatic LNs and 32 metastatic LNs). Semi-automatic LNs segmentation was conducted on arterial-venous mixed images derived from DECT using Syngo.via Frontier Radiomics software. Totally 1 226 radiomics features were extracted from arterial-venous mixed images for each LN. The least absolute shrinkage and selection operator (LASSO) regression was applied for radiomics features selection and signature building. The logistic regression modeling was used to construct diagnostic models based on the CT image features of LNs (model 1), the radiomics signature (model 2) and the combination of the CT image features and radiomics signature (model 3). An intuitive nomogram was plotted for model 3. The ROC curve analyses and area under the curve (AUC) were performed to evaluate the diagnostic efficiency of the three models, with the performances compared using the Delong test.Results:Model 1 was developed with LNs shape, degree of enhancement, pattern of enhancement, calcification and extra nodal extension. Three arterial phase radiomics features were selected and used to establish radiomics signature using LASSO regression (model 2). Model 3 was developed with LNs size, shape, degree of enhancement and radiomics signature. In both the training and validation cohort, model 3 showed the best diagnostic performance (AUC=0.965, 0.933), followed by model 2 (AUC=0.947, 0.910), and both these two models significantly outperformed model 1 (AUC=0.850, 0.846) (training cohort, Z=4.066 and 3.758, P both<0.001; validation cohort, Z=2.871 and 1.998, P=0.017 and 0.042) respectively. Conclusion:The radiomics model based on arterial-venous mixed images derived from DECT data can realize effective diagnosis of LNs metastasis in patients with PTC; and the combination model of radiomics signature with CT image features can further improve the diagnostic accuracy.

Objective: To study the clinical effects of acupuncture therapy for acute stroke. Methods: 150 patients suffered from acute stroke were randomly divided into two groups: drug group, acupuncture group. To apply routine drug treatment of Neurology for drug group: pisacetam 250mL, Salvia injection 20mL added into normal sodium 250mL for intravenous drip, once a day. For acupuncture group applied calm the liver and suppress yang acupuncture therapy beside drugs. Modified Scandinavian Stroke Scale (SSS) and activities of daily living (ADL) scale (Barthel Index) were used for evaluation, as well as biochemistry\hemorheology determination. Results: The scale showed significant difference as compared with the drug group, biochemistry index had non-significant difference, and hemorheological index had partly improved. Conclusion: The scale could synchronously reflect the clinical symptom and changes of patient with stroke.Acupuncture therapy has a significant improvement of acute stroke treatment.