Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Objective:To investigate the predictive value of cardiopulmonary exercise test (CPET) indexes for major adverse cardiovascular events (MACE) in patients with coronary heart disease (CHD).Methods:This study was a retrospective cohort study. CHD patients were consecutively enrolled who procedure CPET before discharge from the Department of Cardiology, General Hospital of Northern Theater Command from November 2015 to September 2021 were enrolled. Demographic information, past medical history, CPET indexes and other baseline data were collected and the patients were followed up. Patients were divided into a MACE group and a control group according to the presence or absence of MACE. A multivariate Cox proportional hazard regression model was used to analyze the CPET indexes with predictive value for MACE in CHD patients.Results:A total of 3 800 patients were eligible for the criterion, age (57.2±8.8) years, 2 920 (76.84%) males. During a follow-up of 1 237 (695, 1 596) days, 390 (10.26%) patients were in MACE group, and 3 410 (89.74%) patients were in control group. In adjusted multivariable analysis, higher metabolic equivalent of tasks (MET) at anaerobic threshold (AT) is an independent protective factor for MACE in patients with CHD ( HR=0.75, 95% CI 0.62-0.90, P=0.002), higher VE/VCO 2 is an independent risk factor for MACE in CHD patients ( HR=1.05, 95% CI 1.02-1.07, P=0.001). Conclusion:In CPET, high MET at AT is an independent protective factor for MACE in patients with CHD, and high VE/VCO 2 is an independent risk factor for MACE in CHD patients.

Objective:To investigate the changes in cardiopulmonary exercise testing (CPET) characteristics before and after the outbreak of COVID-19 in patients with acute coronary syndrome (ACS) who underwent percutaneous coronary intervention (PCI).Methods:This is a cross-sectional study that included ACS patients who underwent PCI at the General Hospital of the Northern Theater Command from July 2018 to February 2023. Based on the timeline of the COVID-19 pandemic, patients were divided into two groups: the pre-pandemic group and the during-pandemic group, with January 2020 as the dividing line. Clinical data were collected from both groups, and a comparative analysis was performed on their postoperative CPET outcomes, including peak oxygen uptake (peak VO 2), peak metabolic equivalents (peak MET), and other indicators. Weber′s classification was used to assess cardiac function. In addition, the 7-tiem generalized anxiety disorder scale (GAD-7) and the patient health questionnaire-9 (PHQ-9) were used to assess the patients′ psychological anxiety and depression states, respectively. Multivariate logistic regression was used to analyze the influencing factors of CPET after PCI. Results:A total of 4 310 post-PCI ACS patients were included, with an average age of (58.7±9.1) years, and 3 464 (80.37%) were male. There were 1 698 patients in the pre-pandemic group and 2 612 patients in the during-pandemic group. The main indicator of the CPET, peak VO 2 (15.04±3.93) ml·min -1·kg -1 in the during-pandemic group, was lower than that in the pre-pandemic group (15.52±3.68) ml·min -1·kg -1, and the difference was statistically significant ( P<0.001). Multivariate logistic regression analysis showed that advanced age, female gender, high body mass index, elevated high-sensitivity C-reactive protein, reduced high-density lipoprotein cholesterol, smoking history, history of myocardial infarction, more severe ACS classification, and mild to moderate degree of depression were related to poor cardiopulmonary outcomes ( P<0.05). Conclusion:The COVID-19 pandemic had a negative impact on the cardiopulmonary outcomes of ACS patients after PCI. Reduced physical activity, and increased psychological stress should be given consideration and attention regarding their impact on patients′ cardiopulmonary function.

Objective:To investigate the study on the diagnostic value of multimodal ultrasound technique for the lesion of extensor carpi ulnaris(ECU)tendon in patients with rheumatoid arthritis(RA).Methods:A total of 175 RA patients who were confirmed by the department of rheumatology of Yantaishan Hospital of Yantai city from December 2021 to January 2023 were selected,and them were included into the RA group.Other 50 patients without RA but with clinical symptoms of wrist were included into the non-RA group,and 50 healthy volunteers were included into the healthy control group.All subjects underwent routine ultrasound and shear wave elastography(SWE)examination on wrist,and then,the characteristics of ultrasound images of wrists and the blood flow distribution of ECU power Doppler ultrasonography(PDUS)were recorded.SWE was used to measure ECU to obtain elastic modulus index(EI)and velocity modulus index(VI).The differences between three groups were compared,and the receiver operating characteristic(ROC)value of RA patients were drawn,so as to confirm the area under curve(AUC)value and optimize cutoff value.Results:There were significant differences in EI and VI of the ECU tendon among three groups(F=61.15,61.28,P<0.05),respectively.The optimal cut-off values of EI and VI were respectively 319.35 kPa and 10.55 m/s in RA patients.In RA patients,age and disease course had significant influences on EI(r=0.19,0.21,P<0.05),and age,disease course,ultrasound score of wrist joint,and grade of power Doppler ultrasonography PDUS of the ECU tendon(ECUPDUS)had significant influences on VI(r=0.19,0.15,-0.16,-0.17,P<0.05).Conclusion:SWE is able to quantitatively and non-invasively assess the stiffness information of the ECU tendon in RA patients.After the supplement of gray-scale ultrasound and PDUS,multimodal ultrasound technique can clearly judge the correlation of the lesions of ECU tendon of RA patients.

Objective:To assess the predictive value of dosiomics in predicting the occurrence of bone marrow suppression (BMS) in patients with pelvic tumors during radiotherapy.Methods:A retrospective analysis was conducted on the clinical data and radiotherapy planning documents of 129 patients with pelvic region tumors who underwent radiotherapy at the First Affiliated Hospital of Nanjing Medical University from January 2019 to January 2023. The region of interest (ROI) was outlined for bone marrow in the pelvic region by Accu Contour software in planning CT, and the ROI was exported together with the dose distribution file. According to a stratified randomization grouping method, the patients were divided into the training set and test set in an 8 vs. 2 ratio. The dosiomic features were extracted from the ROI, and the two independent samples t-test and the least absolute shrinkage and selection operator (LASSO) algorithm was employed to identify the best predictive characteristics. Subsequently, the dosiomic scores were calculated. Clinical predictors were identified through both univariant and multivariate logistic regression analyses. Predictive models were constructed by using clinical predictors alone and combining clinical predictors and dosiomic scores. The efficacy of predictive model was assessed by plotting the receiver operating characteristic (ROC) curve and evaluating its performance through the area under the ROC curve (AUC), the calibration curve, and decision curve analysis (DCA). Results:Fourteen dosiomic features that showed a strong correlation with the occurrence of BMS were screened and utilized to calculate the dosiomic scores. Based on both univariant and multivariate logistic regression analyses, chemotherapy, planning target volume (PTV) and V 5 Gy were identified as clinical predictors. According to the combined model, the AUC values for the training set and test set were 0.911 and 0.868, surpassing those of the clinical model (AUC=0.878 and 0.824). Furthermore, the analysis of both the calibration curve and DCA suggested that the combined model had higher calibration and net clinical benefit. Conclusion:The combined model has a high diagnostic value for predicting BMS in patients with pelvic tumors during radiotherapy.