ShinyLUTS—A Shiny web application for structured data management and analysis for patients with lower urinary tract symptoms (LUTS)

Christoph-Alexander Joachim von Klot, Cornelius Köpp, Markus Antonius Kuczyk and Mathias Wolters

PLOS ONE, 2023, vol. 18, issue 9, 1-9

Abstract: Objectives: Clinical, time-dependent, therapeutic and diagnostic data of patients with LUTS are highly complex. To better manage these data for therapists’ and researchers’ we developed the application ShinyLUTS. Material and methods: The statistical programming language R and the framework Shiny were used to develop a platform for data entry, monitoring of therapy and scientific data analysis. As part of a use case, ShinyLUTS was evaluated for patients with non-neurogenic LUTS who were receiving Rezum™ therapy. Results: The final database on patients with LUTS comprised a total of 8.118 time-dependent parameters in 11 data tables. Data entry, monitoring of therapy as well as data retrieval for scientific use, was deemed feasible, intuitive and well accepted. Conclusion: The ShinyLUTs application presented here is suitable for collecting, archiving, and managing complex data on patients with LUTS. Aside from the implementation in a scientific workflow, it is suited for monitoring treatment of patients and functional results over time.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0292117

DOI: 10.1371/journal.pone.0292117

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