Objective:To investigate the role of clinical pharmacists in the anti-infective treatment of one patient with complexity urinary tract infection with septic shock induced by cellulitis. Methods:Clinical pharmacists participated in one case of complexity uri-nary tract infection with septic shock induced by cellulitis, and according to the clinical curative effect and the patient' s condition change, clinical pharmacists adjusted the medication nine times and provided individualized pharmaceutical care and service in the whole process. Results:Physician accepted the suggestions of clinical pharmacists, the infection was controlled after the 38-day treat-ment, and then the patient was discharged from the hospital. Conclusion:Clinical pharmacists should participate in the clinical treat-ment, provide whole process of pharmaceutical care for severe patients and assist physician in drug treatment decisions to promote safe, effective and economical drug use.

Background Preferred practice pattern (PPP) is an evidence-based documents which can be used for reference to standardize medical practice by ophthalmologists.So far it has been promoted for more than 10 years in China.However,there is no report about the popularization and application of PPP in China.Objective This study was to investigate the cognitions of ophthalmologists to PPP from the view of clinical questions.Methods A questionnaire-based study was conducted.Questionnaires were dispensed during September 17 to 21,2014 to inquiry into the cognitions of ophthalmologists to PPP in the 19th Congress of Chinese Ophthalmological Society.A selfadministered questionnaire was designed and discussed according to the article published in the past by our research group.It included personal basic information and cognitions to PPP,and the latter consisted of self-assessment and cognition scoring.The constituent ratios of aware,quite aware,unaware and fully unaware ophthalmologists were counted.The cognitions were divided into low level (0-4 scores),moderate level (5-8 scores) and high level (9-12 scores) based on the effective answer sheets.The questionnaires were filled out anonymously and incomplete questionnaires were excluded.Results Among the 300 distributed questionnaires,282 were retrieved and 209 were valid,with the effective rate 74.1％.The ophthalmologists of awareness to PPP were 46.4％ (97/209),and 53.6％ (112/209) of respondents did not know PPP very well.A positive correlation was found between the awareness to PPP and the cognition scores to clinical issues (r,=0.143,P ＜ 0.05).The cognition scores to clinical issues were significantly different among different educational backgrounds (F =12.26,P ＜ 0.05),and cognition scores were significantly reduced in the ophthalmologists with lower master degree in comparison with the ophthalmologists with doctoral degree (all at P＜0.05).The coincide ratio between cognitions of ophthalmologists to different clinical issues and suggestions in PPP were evidently different in the ophthalmologists,with the highest coincide ratio 83％ and the lowest coincide ratio 1％.Conclusions The awareness to PPP is not adequate in Chinese eye doctors,which reduces the cognition level to clinical issues.There is a poor coincide ratio between cognitions of Chinese ophthalmologists to clinical issues and suggestions in PPP.This study emphasizes the need for effective awareness programs towards clinical issues based on PPP.

Objective To identify post?marketing active surveillance systems for vaccine safety around the world and understand their features and mechanisms, in order to provide guidance for vaccine administration activities in China. Methods Following the steps of scoping review, literature about active surveillance system for vaccine safety and published by 30 June 2018 were identified by searching electronic databases, including PubMed, Scopus, and Cochrane Library. Grey literature were also sought by exploring relevant websites. Identified literature were screened according to eligibility criteria, and informative data from included literature were then charted. Framework Synthesis and Thematic Analysis were performed to integrate the charted data. Results 97 pieces of literature were included for review, and 11 active surveillance systems for vaccine safety were identified, mostly located in developed countries. These systems were constructed by 3 types of organizations: administration departments, academic or research institutions, and health care providers. Their data sources included immunization registries, electronic medical records, claims data, case reports of adverse events following immunization electronic questionnaires, and epidemiologic study data. According to their operation procedures, these systems were grouped into 4 modes of active surveillance: Data Linkage, Investigator Network, Automatic Follow?up System, Studies Consortium. Conclusion Practice of active surveillance for vaccine safety greatly varies across countries, with different conditions and advantages. It is suggested that developing countries should choose suitable mode of active surveillance considering their local situations.

Objective To identify post?marketing active surveillance systems for vaccine safety around the world and understand their features and mechanisms, in order to provide guidance for vaccine administration activities in China. Methods Following the steps of scoping review, literature about active surveillance system for vaccine safety and published by 30 June 2018 were identified by searching electronic databases, including PubMed, Scopus, and Cochrane Library. Grey literature were also sought by exploring relevant websites. Identified literature were screened according to eligibility criteria, and informative data from included literature were then charted. Framework Synthesis and Thematic Analysis were performed to integrate the charted data. Results 97 pieces of literature were included for review, and 11 active surveillance systems for vaccine safety were identified, mostly located in developed countries. These systems were constructed by 3 types of organizations: administration departments, academic or research institutions, and health care providers. Their data sources included immunization registries, electronic medical records, claims data, case reports of adverse events following immunization electronic questionnaires, and epidemiologic study data. According to their operation procedures, these systems were grouped into 4 modes of active surveillance: Data Linkage, Investigator Network, Automatic Follow?up System, Studies Consortium. Conclusion Practice of active surveillance for vaccine safety greatly varies across countries, with different conditions and advantages. It is suggested that developing countries should choose suitable mode of active surveillance considering their local situations.

Established in 2017, the Screening Cohort for Asian Nomadic descendants in China (Scan-China) has benefited over 180,000 members of a multi-ethnic population, particularly individuals of Mongolian descent compared with the general population (Han ethnicity), in the Inner Mongolia Autonomous Region, China. This cohort study aims to evaluate the effectiveness of cancer screening and serve as a real-world data platform for cancer studies. The 6 most prevalent cancers in China are considered—namely, breast, lung, colorectal, gastric, liver and esophageal cancer. After baseline cancer risk assessments and screening tests, both active and passive follow-up (based on the healthcare insurance database, cancer registry, the front page of hospital medical records, and death certificates) will be conducted to trace participants’ onset and progression of cancers and other prevalent chronic diseases. Scan-China has preliminarily found a disproportionately lower screening participation rate and higher incidence/mortality rates of esophageal and breast cancer among the Mongolian population than among their Han counterparts. Further research will explore the cancer burden, natural history, treatment patterns, and risk factors of the target cancers.

Traditional evidence-based medicine has been essential in medical practice and health decision-making. However, it has also continuously exposed shortcomings such as low efficiency in evidence generation, narrow scope of coverage, and imperfect integration strategies, making it challenging to serve clinical diagnosis and treatment and regulatory decision-making. Therefore, it is urgent to adapt to the development of cutting-edge technology and to expand and improve the concept of evidence-based medicine. Deep evidence-based medicine proposed in 2023 aims to advocate the innovative use of the latest artificial intelligence and natural language processing technologies, comprehensively expanding the breadth, depth, and integrability of evidence and improving the efficiency of evidence generation and integration. Building a new generation of evidence-based decision-making ecosystems based on deep evidence-based medicine has broad prospects for practical application. It can promote the development of evidence retrieval, generation, integration, dissemination, transformation, and application, deeply explore imaging, multi-omics, and real-world data to increase the utilization potential of real-world evidence, establish dynamic literature management platforms and decision support tools, reduce resource waste, and promote evidence flow. Utilizing this system can help obtain individual-centered comprehensive clinical evidence and play a significant role in talent training, reforming evidence-based teaching, popularizing science, and ultimately promoting the goal of "One Health".

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.

Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.

Objective:To construct a risk prediction model for diabetes kidney disease (DKD).Methods:Patients newly diagnosed with type 2 diabetes mellitus (T2DM) between January 1, 2015, and December 31, 2022, were selected as study subjects from the Yinzhou Regional Health Information Platform in Ningbo City. The Lasso method was used to screen the risk factors, and the DKD risk prediction model was established using Cox proportional hazard regression models. Bootstrap 500 resampling was applied for internal validation.Results:The study included 49 706 subjects, with an median ( Q1, Q3) age of 60.00 (50.00, 68.00) years old, and 55% were male. A total of 4 405 subjects eventually developed DKD. Age at first diagnosis of T2DM, BMI, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, past medical history (hyperuricemia, rheumatic diseases), triglycerides, and estimated glomerular filtration rate were included in the final model. The final model's C-index was 0.653, with an average of 0.654 after Bootstrap correction. The final model's area under the receiver operating characteristic curve for predicting 4-year, 5-year, and 6-year was 0.657, 0.659, and 0.664, respectively. The calibration curve was closely aligned with the ideal curve. Conclusions:This study constructed a DKD risk prediction model for newly diagnosed T2DM patients based on real-world data that is simple, easy to use, and highly practical. It provides a reliable basis for screening high-risk groups for DKD.

Objective: To identify post-marketing active surveillance systems for vaccine safety around the world and understand their features and mechanisms, in order to provide guidance for vaccine administration activities in China. Methods: Following the steps of scoping review, literature about active surveillance system for vaccine safety and published by 30 June 2018 were identified by searching electronic databases, including PubMed, Scopus, and Cochrane Library. Grey literature were also sought by exploring relevant websites. Identified literature were screened according to eligibility criteria, and informative data from included literature were then charted. Framework Synthesis and Thematic Analysis were performed to integrate the charted data. Results: 97 pieces of literature were included for review, and 11 active surveillance systems for vaccine safety were identified, mostly located in developed countries. These systems were constructed by 3 types of organizations: administration departments, academic or research institutions, and health care providers. Their data sources included immunization registries, electronic medical records, claims data, case reports of adverse events following immunization electronic questionnaires, and epidemiologic study data. According to their operation procedures, these systems were grouped into 4 modes of active surveillance: Data Linkage, Investigator Network, Automatic Follow-up System, Studies Consortium. Conclusion Practice of active surveillance for vaccine safety greatly varies across countries, with different conditions and advantages. It is suggested that developing countries should choose suitable mode of active surveillance considering their local situations.