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Objective:To construct the risk prediction nomogram model of acute kidney injury (AKI) with R language and traditional statistical methods based on the large sample clinical database, and verify the accuracy of the model.Methods:It was a a retrospective case control study. The patients who met the diagnostic criteria of AKI in Tongji Hospital of Tongji University from January 1 to December 31, 2021 were screened in the clinical database, and the patients with monitored serum creatinine within 48 hours but without AKI were included as the control group. The demographic data, disease history, surgical history, medication history and laboratory test data were collected to screen the risk factors of AKI in clinic.Firstly, based on multivariate logistic regression analysis and forward stepwise logistic regression analysis, the selected risk factors were included to construct the nomogram model. At the same time, cross validation, bootstrap validation and randomly split sample validation were used for internal verification, and clinical data of patients in the sane hospital after one year (January to December, 2022) were collected for external verification. The receiver-operating characteristic curve was used to determine the discrimination of the model, and calibration curve and decision curve analysis were carried out to evaluate the accuracy and clinical net benefit, respectively.Results:A total of 5 671 patients were enrolled in the study, with 1 884 AKI patients (33.2%) and 3 787 non-AKI patients (66.7%). Compared with non-AKI group, age, and proportions of surgical history, renal replacement therapy, hypertension, diabetes, cerebrovascular accident,chronic kidney disease, drug use histories and mortality in AKI group were all higher (all P<0.05). Multivariate logistic regression analysis showed that the independent influencing factors of AKI were surgical history, hypertension, cerebrovascular accident, diabetes, chronic kidney disease, diuretics, nitroglycerin, antidiuretic hormones, body temperature, serum creatinine, C-reactive protein, red blood cells, white blood cells, D-dimer, myoglobin, hemoglobin, blood urea nitrogen, brain natriuretic peptide, aspartate aminotransferase, alanine aminotransferase, triacylglycerol, lactate dehydrogenase, total bilirubin, activated partial thromboplastin time, blood uric acid and potassium ion (all P<0.05). Finally, the predictive factors in the nomogram were determined by forward stepwise logistic regression analysis, including chronic kidney disease, hypertension, myoglobin, serum creatinine and blood urea nitrogen, and the area under the curve of the prediction nomogram model was 0.926 [95% CI 0.918-0.933, P<0.001]. The calibration curve showed that the calibration effect of nomogram was good ( P>0.05). The decision curve showed that when the risk threshold of nomogram model was more than 0.04, the model construction was useful in clinic. In addition, the area under the curve of receiver-operating characteristic curve predicted by nomograph model in external validation set was 0.876 (95% CI 0.865-0.886), which indicated that nomograph model had a high discrimination degree. Conclusion:A nomogram model for predicting the occurrence of AKI is established successfully, which is helpful for clinicians to find high-risk AKI patients early, intervene in time and improve the prognosis.
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@#Objective To design an interactive and shared electronic database for long-term follow-up management of patients with acute minor stroke (NIHSS≤5) using REDCap,and to explore the value of establishing this database,trying to provide new ideas for clinical treatment. Methods The CRF table of case report was designed according to the relevant data of patients in hospital and the requirements of follow-up management. The nosocomial case data of patients with acute minor stroke (NIHSS≤5) from 3 stroke centers in Shanxi Province were collected and recorded on the CRF form of case reports. An interactive shared electronic database was designed by REDCap,and the data in CRF table were checked and revised and entered into the database. Patients were followed up at 3 months and 1 year after onset. Results Based on REDCap system,a database of acute minor stroke ( NIHSS≤5) in Shanxi Province was established and used in clinical practice. The number of patients expected to be included has been achieved. Its data entry,data quality control,user rights management and data export functions can be stable operation. Conclusion The interactive sharing clinical database of acute minor stroke ( NIHSS≤5) is established by redcap,which has the advantages of simple interface operation,convenient communication,timely entry,and multi-access. It provides a powerful tool for longitudinal data collection,reducing deviation in research,and comprehensively implementing and coordinating project research. It ensures the reliability of research results and has clinical research value.
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The development of clinical medicine depends on high-quality evidence from clinical research .Strengthening clini-cal research is important for the advancement of new clinical technology and improvement of clinical diagnosis and treatment .In the present paper , the author discusses how to carry out and analyzes the value of clinical research in medical development , offering young clinicians some experience for reference in promoting their clinical research ability and the development of clinical medicine .
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<p>In the year 2000, the Japan Cardiovascular Surgery Database (JCVSD) was created with the support of the Society of Thoracic Surgeons (STS). STS database software was translated to Japanese with the same definitions and in 2001, the data entry of adult cardiac surgeries was initiated online using University Hospital Medical Information Network, UMIN. In 2008, entry of the data of congenital heart surgeries was initiated in the congenital section of JCVSD and preoperative expected mortality (JapanSCORE) in adult cardiovascular surgeries was first calculated using the risk model of JCVSD. In 2011, the Japan Surgical Board system merged with JCVSD and all cardiovascular surgical data could be registered in JCVSD from 2012. The reports resulting from the analyses of data from JCVSD (Current Status of Cardiovascular Surgery in Japan, 2013 and 2014 : A report based on the JCVSD) will encourage further improvements in the quality of cardiovascular surgeries, patient safety, and medical care for patients in Japan.</p>
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<p>National Clinical Database (NCD) is a multidisciplinary clinical registry platform collecting patient case information throughout Japan in close linkage with the board certification systems for various Japanese professional medical societies. Since its initiation of data collection in 2011, NCD has grown in its size as more national level professional societies joined its activity. Its current case registration volume is above 150 million cases per year. In this commentary, we will introduce four patterns of utilization examples of NCD: 1) data use for the assessment and improvement of healthcare quality in Japan, 2) data use for conducting observational studies to answer physician generated clinical questions, 3) data use for health services research, and 4) Use of the registry platform for industry-government-academia collaboration. We will also go over some of the data quality management and improvement activities at NCD, which they regard as one of the top priority issues in the operation of the institution. These include: defining and designing of the data elements, administrative support from the office staffs, data error checking using the web based registration system, and data audit and validation.</p>
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The JCVSD (Japan Cardiovascular Surgery Database) was organized in 2000 to improve the quality of cardiovascular surgery in Japan. Web-based data harvesting on adult cardiac surgery was started (Japan Adult Cardiovascular Surgery Database, JACVSD) in 2001, and on congenital heart surgery (Japan Congenital Cardiovascular Surgery Database, JCCVSD) in 2008. Both databases grew to become national databases by the end of 2013. This was influenced by the success of the Society for Thoracic Surgeons' National Database, which contains comparable input items. In 2011, the Japanese Board of Cardiovascular Surgery announced that the JACVSD and JCCVSD data are to be used for board certification, which improved the quality of the first paperless and web-based board certification review undertaken in 2013. These changes led to a further step. In 2011, the National Clinical Database (NCD) was organized to investigate the feasibility of clinical databases in other medical fields, especially surgery. In the NCD, the board certification system of the Japan Surgical Society, the basic association of surgery was set as the first level in the hierarchy of specialties, and nine associations and six board certification systems were set at the second level as subspecialties. The NCD grew rapidly, and now covers 95% of total surgical procedures. The participating associations will release or have released risk models, and studies that use 'big data' from these databases have been published. The national databases have contributed to evidence-based medicine, to the accountability of medical professionals, and to quality assessment and quality improvement of surgery in Japan.
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Adult , Humans , Asian People , Certification , Evidence-Based Medicine , Japan , Patient Safety , Quality Improvement , Social Responsibility , Thoracic SurgeryABSTRACT
Based on the background,conception and the core ideas of the evidence-based medicine,the construction and application of domestic clinical cases database was discussed.Problems concerning statistics,management and application in scientific research encountered in the database devel opment were presented,and suggestions were proposed.
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In Japan, large scale health databases were constructed in a few years, such as National health insurance claim and health checkup database(NDB) and Japanese Sentinel project. But the there are some legal issues for making adequate balance between privacy and public benefit by using such databases. NDB is carried based on the act for elderly person's health care but in this act, nothing is mentioned for using this database for general public benefit. Therefore researchers who use this database are forced to pay much concern about anonimization and information security that may disturb the research work itself. Japanese Sentinel project is a National project to detecting drug adverse reaction using large scale distributed clinical databases of large hospitals. Although patients give the future consent for general such purpose for public good, it is still under discussion using insufficiently anonymized data. Generally speaking, researchers of study for public benefit will not infringe patient's privacy, but vague and complex requirements of legislation about personal data protection may disturb the researches. Medical science does not progress without using clinical information, therefore the adequate legislation that is simple and clear for both researchers and patient is strongly required. In Japan, fortunately, the specific act for balancing privacy and public benefit is planned to lay before Diet, but is still under discussion. The author recommended the researchers including the field of pharmacoepidemiology should pay attention to, participate in the discussion of, and make suggestion to this act. (Jpn J Pharmacoepidemiol 2012; 17(2): 101-107)
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Recently, the use of databases for clinical trials is being promoted. We used the Japan Adult Cardiovascular Surgery Database (JACVSD) data was used as a historical control in a clinical trial, and we analyzed following : the processes of using data and the efficiency of data collection, available variables for statistical analysis, and query functions for missing and invalid data. We chose available variables of JACVSD data and created rules for merging JACVSD data with interventional group data, in addition to analyzing the data collection processes for clinical trials. Subjects were selected from cases registered in the JACVSD. On statistical analysis, 63% of 76 variables were used ; variables related to the patients' symptoms had to be collected separately. Missing and invalid data were effectively excluded. We could conduct data collection efficiently by using the JACVSD as a historical control for clinical trials. Selecting subjects from the JACVSD could reduce the burden of selecting subjects from hospitals and prevent selection bias.