Objective To discusse the application effects of the informatization of the review center and the homogeneity of pharmacists on the rationality of emergency department prescriptions.Methods Based on the system rules of the rational drug use management system and manually set custom rules,the changes in pharmacist's review quality,efficiency homogeneity,and prescription rationality were compared before(February 2023 to July 2023)and after(August 2023 to January 2024)the construction of the review center,according to the informatization and process standardization management.Results After the establishment of the review center,analysis of variance showed that the approval rate of pharmacist's review significantly increased compared to before the establishment of the review center(P＜0.05),while the average time consumption increased significantly(P＜0.01).The average review time,average approval time,and average review return time have been extended from(4.50±0.58),(4.50±0.58),and(4.75±0.96)s to(11.67±1.03),(8.50±0.55)and(13.17±0.98)s,respectively.The trend chi-square test showed that the irrationality rate of emergency department prescriptions decreased monthly from 6.27％in August 2023 to 0.93％in January 2024(P＜0.01).Correlation analysis between the number of intervention system rules since the establishment of the review center and the irrationality rate of emergency department prescriptions revealed a significant correlation(P=0.004 4).Conclusions By utilizing the platform of the review center,establishing dedicated review pharmacists and an information pharmacist team,and implementing informatization and standardized management processes,it can contribute to improving the quality and efficiency of prescription review,increasing the qualification rate of prescriptions,ensuring rational drug use,and enhancing the management level and medical quality of hospitals.

Objective To discusse the application effects of the informatization of the review center and the homogeneity of pharmacists on the rationality of emergency department prescriptions.Methods Based on the system rules of the rational drug use management system and manually set custom rules,the changes in pharmacist's review quality,efficiency homogeneity,and prescription rationality were compared before(February 2023 to July 2023)and after(August 2023 to January 2024)the construction of the review center,according to the informatization and process standardization management.Results After the establishment of the review center,analysis of variance showed that the approval rate of pharmacist's review significantly increased compared to before the establishment of the review center(P＜0.05),while the average time consumption increased significantly(P＜0.01).The average review time,average approval time,and average review return time have been extended from(4.50±0.58),(4.50±0.58),and(4.75±0.96)s to(11.67±1.03),(8.50±0.55)and(13.17±0.98)s,respectively.The trend chi-square test showed that the irrationality rate of emergency department prescriptions decreased monthly from 6.27％in August 2023 to 0.93％in January 2024(P＜0.01).Correlation analysis between the number of intervention system rules since the establishment of the review center and the irrationality rate of emergency department prescriptions revealed a significant correlation(P=0.004 4).Conclusions By utilizing the platform of the review center,establishing dedicated review pharmacists and an information pharmacist team,and implementing informatization and standardized management processes,it can contribute to improving the quality and efficiency of prescription review,increasing the qualification rate of prescriptions,ensuring rational drug use,and enhancing the management level and medical quality of hospitals.

Objective:Construction of deep learning classification models based on functional magnetic resonance imaging (fMRI) data assists the clinicians to achieve better diagnosis of bipolar disorder (BD), which can improve the recognition rate of BD by identifying the critical imaging features.Methods:A total of 146 patients who met the diagnosis criteria of BD according to DSM-Ⅳ and 234 healthy control (HC) were recruited for fMRI scans. Regional homogeneity (ReHo) and amplitude of low frequency fluctuation (ALFF) were used to analyze fMRI data. Based on ReHo and ALFF, the classification models were constructed by deeping neural network (DNN) and dual-channel convolution neural network (DCNN) respectively, and the best classification model was developed by comparing the accuracy and area under curve (AUC) of the two models. Based on each brain region divided by anatomical automatic labeling (AAL), the support vector machine (SVM) classification model was constructed using imaging index with a better performance, and the critical imaging features were identified by comparing the accuracy of each brain region.Results:The performances of the DCNN classification model (accuracy = 75.3%, and 72.6%, respectively, based on ReHo and ALFF) were significantly better than the DNN classification model (accuracy = 67.1%, and 65.1%, respectively). Meanwhile, the accuracy of classification model constructed using ReHo was higher than ALFF. Based on the SVM classification model, critical brain regions were identified above the accuracy of 65.0%, including the occipital lobe (middle occipital gyrus, superior occipital gyrus and lingual gyrus), hippocampus, and thalamus.Conclusion:The computational model based on DCNN using ReHo can help the clinicians to achieve better diagnosis of BD. Furthermore, occipital lobe, hippocampus and thalamus may be the critical imaging features for the auxiliary recognition of BD.

Objective:Construction of deep learning classification models based on functional magnetic resonance imaging (fMRI) data assists the clinicians to achieve better diagnosis of bipolar disorder (BD), which can improve the recognition rate of BD by identifying the critical imaging features.Methods:A total of 146 patients who met the diagnosis criteria of BD according to DSM-Ⅳ and 234 healthy control (HC) were recruited for fMRI scans. Regional homogeneity (ReHo) and amplitude of low frequency fluctuation (ALFF) were used to analyze fMRI data. Based on ReHo and ALFF, the classification models were constructed by deeping neural network (DNN) and dual-channel convolution neural network (DCNN) respectively, and the best classification model was developed by comparing the accuracy and area under curve (AUC) of the two models. Based on each brain region divided by anatomical automatic labeling (AAL), the support vector machine (SVM) classification model was constructed using imaging index with a better performance, and the critical imaging features were identified by comparing the accuracy of each brain region.Results:The performances of the DCNN classification model (accuracy = 75.3%, and 72.6%, respectively, based on ReHo and ALFF) were significantly better than the DNN classification model (accuracy = 67.1%, and 65.1%, respectively). Meanwhile, the accuracy of classification model constructed using ReHo was higher than ALFF. Based on the SVM classification model, critical brain regions were identified above the accuracy of 65.0%, including the occipital lobe (middle occipital gyrus, superior occipital gyrus and lingual gyrus), hippocampus, and thalamus.Conclusion:The computational model based on DCNN using ReHo can help the clinicians to achieve better diagnosis of BD. Furthermore, occipital lobe, hippocampus and thalamus may be the critical imaging features for the auxiliary recognition of BD.

Surgical treatment for bone and soft tumors of pelvis and sacrum presents a big challenge, because of the complex anatomy of sacropelvic region, large tumor volume at presentation, rich blood supply to the tumor and visceral involvemen, et al. Therefore, surgical excision and reconstruction are technically difficult for sacropelvic tumors. Extensive intraoperative haemorrhage could be life-threatening, and this issue remains a major concern. How to effectively control bleeding during surgery is critical for successful operation and patient's favorable prognosis. Some previous attempts, such as interventional selective internal iliac artery embolization or manual ligation through an additional anterior approach, were tested to be ineffective. Inspired by the success of resuscitative endovascular balloon occlusion of the aorta (REBOA) which resemble an endovascular tourniquet for traumatic hemorrhagic shock, some researchers have applied this techinique to control surgical bleeding during pelvic or sacral tumor resection.The authors have performed REBOA for more than 1 500 sacropelvic tumr surgeries since 2003 in Peking University People's Hospital. The patient age, the diameter of femoral artery and aorta, atherosclerosis, as well as tumor location, volume and expansion and blood suppy, have to be thoroughly evaluated prior to REBOA administration. Admittedly, the application of REBOA do reduce intraoperative bleeding, shorten the operation duration, improve the safety of surgery, yet some complications were observed including local hematoma at the puncture site, acute arterial thrombosis, femoral artery pseudoaneurysm or occlusio, et al. The purpose of this study is to review the literature on REBOA administration in pelvic and sacral tumors excision, with the focus on its indications, performing procedure, the safety and efficacy, and complications. Moreover, in order to popularize the clinical application of aortic balloon occlusion in the future, we summarize our experience of abdominal aortic balloon occlusion over 10 years.

This thesis found the female homicide cases present its own characteristics because of differences in psychological, physiology characteristics, character between males and females through the statistical analysis of age distribution, the relationship between criminal suspects and victims, the classification of crime scenes, injury tools and the mortal wound positions of 116 female homicide cases in Lianyungang between 1993 to 2014. Mostly, the relationship between criminal suspects and victims is family, especially couple or valentine; the crime scenes are frequently indoor, especially bedrooms. They always choose production and life tools when victims are in deep sleep or drunk time to make the victims asphyxia, posioning or drowning. The injuries focus on vitals and usually hit many times lead to mortal wound, agonal trauma and postmortem injury.