Objective:Radiotherapy is the primary treatment for nasopharyngeal carcinoma,but it frequently leads to radiotherapy-induced temporal lobe injury(RTLI).Magnetic resonance imaging(MRI)is the main diagnostic method for RTLI after radiotherapy for nasopharyngeal carcinoma,but it is prone to missed diagnoses.This study aims to investigate the causes of missed diagnoses of RTLI in nasopharyngeal carcinoma patients undergoing MRI after radiotherapy. Methods:Clinical and MRI data from nasopharyngeal carcinoma patients diagnosed and treated with radiotherapy at Xiangya Hospital of Central South University,from January 2010 to April 2021,were collected.Two radiologists reviewed all head and neck MRIs(including nasopharyngeal and brain MRIs)before and after radiotherapy of identify cases of late delayed response-type RTLI for the first time.If the original diagnosis of the initial RTLI in nasopharyngeal carcinoma patients did not report temporal lobe lesions,it was defined as a missed diagnosis.The first diagnosis of RTLI cases was divided into a missed diagnosis group and a non-missed diagnosis group.Clinical and imaging data were compared between the 2 groups,and multivariate logistic regression analysis was used to identify independent risk factors for MRI missed diagnoses of initial RTLI. Results:A total of 187 nasopharyngeal carcinoma with post-radiotherapy RTLI were included.The original diagnostic reports missed 120 cases and accurately diagnosed 67 cases,with an initial RTLI diagnosis accuracy rate of 35.8%and a missed diagnosis rate of 64.2%.There were statistically significant differences between the missed diagnosis group and the non-missed diagnosis group in terms of lesion size,location,presence of contralateral temporal lobe lesions,white matter high signal,cystic degeneration,hemorrhage,fluid attenuated inversion recovery(FLAIR),and examination site(all P<0.05).Multivariate logistic regression analysis showed that lesions≤25 mm,non-enhancing lesions,lesions without cystic degeneration or hemorrhage,lesions located only in the medial temporal lobe,and MRI examination only of the nasopharynx were independent risk factors for missed MRI diagnosis of initial RTLI(all P<0.05). Conclusion:The missed diagnosis of initial RTLI on MRI is mainly related to lesion size and location,imaging characteristics,and MRI examination site.

Nanozymes are nanoscale materials with enzyme-mimicking catalytic properties.Nanozymes can mimic the mechanism of natural enzyme molecules.By means of advanced chemical synthesis technology,the size,shape,and surface characteristics of nanozymes can be accurately regulated,and their catalytic properties can be customized according to the specific need.Nanozymes can mimic the function of natural enzymes,including catalase(CAT),superoxide dismutase(SOD),and glutathione peroxidase(GPx),to scavenge reactive oxygen species(ROS).Reported findings have shown that nanozymes have the advantages of excellent stability,low cost,and adjustable catalytic activity,thereby showing great potential and broad prospects in the application of disease treatment.Herein,we reviewed the advances in the application of nanozymes in the treatment of joint diseases.The common clinical manifestations of joint diseases include joint pain,swelling,stiffness,and limited mobility.In severe cases,joint diseases may lead to joint destruction,deformity,and functional damage,entailing crippling socioeconomic burdens.ROS is a product of oxidative stress.Increased ROS in the joints can induce macrophage M1 type polarization,which in turn induces and aggravates arthritis.Therefore,the key to the treatment of joint diseases lies in ROS scavenging and increasing oxygen(O2)content.Nanozymes have demonstrated promising application potential in the treatment of joint diseases,including rheumatoid arthritis,osteoarthritis,and gouty arthritis.However,how to ensure their biosafety,reduce the toxicity,and increase enzyme activity remains the main challenge in current research.Precise control of the chemical composition,size,shape,and surface modification of nanomaterials is the main development direction for the future.

Objective:To evaluate and compare the inpatient medical services of secondary public and private general hospitals by using disease risk adjustment model, and to explore the application of disease risk adjustment model in medical service evaluation of different ownership hospitals.Methods:Based on 1 032 865 front pages of medical records in Chengdu in 2017 and 2018, a regression model with mortality, average length of stay, total hospitalization expenses, medical service fees, drug costs and surgical consumables costs as dependent variables and related influencing factors as independent variables was established by using disease management intelligent analytic and evaluation system. The risk adjusted case mix index(ACMI) was calculated. The mortality, average length of stay, hospitalization expenses and other indicators were predicted. The ratio of observed value to expected value(O/E value) of each index in public and private secondary general hospitals was obtained and compared.Results:The ACMI value of secondary public general hospital was 4.63, slightly higher than that of private hospitals(4.55). The technical difficulty and resource consumption of the public hospitals were slightly higher than that of the private hospitals.From the O/E value, the management of disease mortality, medical service fees and inpatient drug costs of secondary public hospitals was generally good, and the O/E values of hospitalization expenses of each secondary private general hospital were quite different, and there was a possibility that the costs were unreasonable. The O/E value of surgical consumables cost in secondary public general hospital was 1.54, and there was room for improvement in cost management.Conclusions:The disease risk adjustment model fully considers the characteristics of different types and severity of diseases in different institutions, which can not be simply compared. Based on individual cases, it realizes the comparability of different ownership hospitals, and provides a new means for the evaluation of medical service ability and quality.

Objective: To study new ways and tools for assessing the inpatient disease management and improving refined management of the hospital. Methods: By using homepages of medical records of the patients discharged from 21 tertiary general hospitals in a city in 2016, we completed the modeling and predicted value calculation within each DRGs with the Disease Management Intelligent Analytic & Evaluation System (DMIAES System). Results: 2 192 predication models were built, to compute the theoretic values of the mortality rate, length of stay, medical fee, medical service fee, and drug cost of each inpatient. Such values were compared with the observed results to gain the O/E index. If O/E is less than 1, it indicates that the inpatient′s disease management is good and better than expected. On the other hand, O/E index greater than 1 indicates poorer disease management than expected and rooms of further improvement. With the help of O/E index, we made multidimensional comparisons assessment and analysis of different hospitals, clinical disciplines, diseases and doctors. Conclusions The DMIAES System can take risk factors of inpatients′ outcomes into account, assessing the major indicators of inpatient outcomes by means of big data and modelling. This approach proves effective in enabling administrators and doctors to rapidly analyze problems for identifying solutions and enhancing management, thus having great potential in hospital management, supervision and assessment.