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Abstract Background Research Electronic Data CAPture (REDCap) is a web application for creating and managing online surveys and databases. Clinical data management is an essential process before performing any statistical analysis to ensure the quality and reliability of study information. Processing REDCap data in R can be complex and often benefits from automation. While there are several R packages available for specific tasks, none offer an expansive approach to data management. Results The REDCapDM is an R package for accessing and managing REDCap data. It imports data from REDCap to R using either an API connection or the files in R format exported directly from REDCap. It has several functions for data processing and transformation, and it helps to generate and manage queries to clarify or resolve discrepancies found in the data. Conclusion The REDCapDM package is a valuable tool for data scientists and clinical data managers who use REDCap and R. It assists in tasks such as importing, processing, and quality-checking data from their research studies.

Abstract Background The contribution of the postoperative process to developing or worsening urinary incontinence (UI) after hip fracture surgery (HFS) remains unclear. We aimed to evaluate UI incidence and worsening among older patients undergoing HFS, and explore associated risk factors. Methods This prospective cohort study included patients ≥ 75 years admitted between October 2019 and October 2021 to the Traumatology Service of three hospitals in the Consorci Sanitari de Alt-Penedès i Garraf (Barcelona, Spain) with hip fracture requiring surgical treatment. UI was assessed using the first two questions of the International Consultation on Incontinence Questionnaire - Short Form (ICIQ-SF) at baseline and at days 30 (± 3 days) and 90 (± 3 days) after HFS. Surgery-related data and post-surgical complications were recorded. Results A total of 248 patients with a mean (SD) age of 85.8 (6.78) years were included; 77.8% were female and 154 (62.1%) had UI at baseline. After HFS, 3.24% experienced urinary tract infections (UTIs), 3.64%, acute urinary retention (AUR), 8.57%, constipation, and 53.9%, prolonged catheterization (> 24 h). Fifty-eight patients without baseline UI developed UI at 30 days, resulting in a UI incidence of 61.7% (95% CI 51.1–71.54) between days 0 and 30. Of the 248 patients, 146 (59.1%) experienced worsening of UI. AUR and UTIs were identified as risk factors for UI development and worsening after HFS, respectively. Conclusion The incidence of UI in older patients after HFS is significant. Patient management protocols should consider AUR and UTIs to reduce or eliminate the incidence of UI in older patients undergoing HFS.

BackgroundOnly 5% of the molecules tested in oncology phase 1 trials reach the market after an average of 7.5 years of waiting and at a cost of tens of millions of dollars. To reduce the cost and shorten the time of discovery of new treatments, “drug repurposing” (research with molecules already approved for another indication) and the use of secondary data (not collected for the purpose of research) have been proposed. Due to advances in informatics in clinical care, secondary data can, in some cases, be of equal quality to primary data generated through prospective studies. ObjectiveThe objective of this study is to identify drugs currently marketed for other indications that may have an effect on the prognosis of patients with cancer. MethodsWe plan to monitor a cohort of patients with high-lethality cancers treated in the public health system of Catalonia between 2006 and 2012, retrospectively, for survival for 5 years after diagnosis or until death. A control cohort, comprising people without cancer, will also be retrospectively monitored for 5 years. The following study variables will be extracted from different population databases: type of cancer (patients with cancer cohort), date and cause of death, pharmacological treatment, sex, age, and place of residence. During the first stage of statistical analysis of the patients with cancer cohort, the drugs consumed by the long-term survivors (alive at 5 years) will be compared with those consumed by nonsurvivors. In the second stage, the survival associated with the consumption of each relevant drug will be analyzed. For the analyses, groups will be matched for potentially confounding variables, and multivariate analyses will be performed to adjust for residual confounding variables if necessary. The control cohort will be used to verify whether the associations found are exclusive to patients with cancer or whether they also occur in patients without cancer. ResultsWe anticipate discovering multiple significant associations between commonly used drugs and the survival outcomes of patients with cancer. We expect to publish the initial results in the first half of 2024. ConclusionsThis retrospective study may identify several commonly used drugs as candidates for repurposing in the treatment of various cancers. All analyses are considered exploratory; therefore, the results will have to be confirmed in subsequent clinical trials. However, the results of this study may accelerate drug discovery in oncology. International Registered Report Identifier (IRRID)DERR1-10.2196/48925