Background: Data management is an important, complex and multidimensional process in clinical trials. The execution of this process is very difficult and expensive without the use of information technology. A clinical data management system is software that is vastly used for managing the data generated in clinical trials. The objective of this study was to review the technical features of clinical trial data management systems. Methods: Related articles were identified by searching databases, such as Web of Science, Scopus, Science Direct, ProQuest, Ovid and PubMed. All of the research papers related to clinical data management systems which were published between 2007 and 2017 (n=19) were included in the study. Results: Most of the clinical data management systems were web-based systems developed based on the needs of a specific clinical trial in the shortest possible time. The SQL Server and MySQL databases were used in the development of the systems. These systems did not fully support the process of clinical data management. In addition, most of the systems lacked flexibility and extensibility for system development. Conclusion: It seems that most of the systems used in the research centers were weak in terms of supporting the process of data management and managing clinical trial's workflow. Therefore, more attention should be paid to design a more complete, usable, and high quality data management system for clinical trials. More studies are suggested to identify the features of the successful systems used in clinical trials.
Background: A clinical data management system is a software supporting the data management process in clinical trials. In this system, the effective support of clinical data management dimensions leads to the increased accuracy of results and prevention of diversion in clinical trials. The aim of this review article was to investigate the dimensions of data management in clinical data management systems. Methods: This study was conducted in 2017. The used databases included Web of Science, Scopus, Science Direct, ProQuest, Ovid Medline and PubMed. The search was conducted over a period of 10 years from 2007 to 2017. The initial number of studies was 101 reaching 19 in the final stage. The final studies were described and compared in terms of the year, country and dimensions of the clinical data management process in clinical trials. Results: The research findings indicated that none of the systems completely supported the data management dimensions in clinical trials. Although these systems were developed for supporting the clinical data management process, they were similar to electronic data capture systems in many cases. The most significant dimensions of data management in such systems were data collection or entry, report, validation, and security maintenance. Conclusion: Seemingly, not sufficient attention has been paid to automate all dimensions of the clinical data management process in clinical trials. However, these systems could take positive steps towards changing the manual processes of clinical data management to electronic processes.
Background Several studies on various bariatric surgeries involving patients with type 2 diabetes mellitus (T2DM) showed an overall rate of remission of hyperglycemia. However, there is little known about predictive factors on remission after different types of surgeries. The aim of this study was to identify the T2DM remission rate and to determine the effects of preoperative factors characteristics of remission of type 2 diabetes in Iran. Methods We conducted a retrospective analysis of 1351 patients with T2DM operated by three different types of surgeries (Roux-en-Y gastric bypass (RYGB), sleeve gastrectomy (SG), and One Anastomosis Gastric Bypass (OAGB)). Diabetes remission was defined according to the American Diabetes Association (ADA) criteria. Binary logistic regression analyses were employed. Results A total of 1351 patients, 675 patients (50.0%) undergoing OAGB, 475 (35.2%) RYGB, and 201 (14.9%) SG. 80.6%, 84.2% of OAGB, 81.7%, 82.6% of RYGB, and 77.1%, 81.5% of SG participants were in T2DM remission after 1 and 3 years, respectively. 1- and 3-year remission were associated with preoperative age, duration of T2DM, FBS and HbA1c, BMI, insulin therapy, and a family history of obesity (p < 0.05). Conclusion The remission of T2DM after RYGB, SG, and OAGB surgery is dependent on various preoperative factors. Patients with younger age, shorter duration of T2DM, lower preoperative HbA1c and FBS, higher BMI, who were not on insulin therapy, and not having a family history of obesity were the best candidates to achieve a prolonged diabetes remission.
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