Lesionia: a digital data management system to enhance collaborative management of epidemiological and clinical data of cutaneous leishmaniases patients.

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES
Emna Harigua-Souiai, Youssef Ben Salem, Maaoui Hariga, Yusr Saadi, Hejer Souguir, Hamed Chouaieb, Olufemi Adedokun, Imen Mkada, Zeineb Moussa, Akila Fathallah-Mili, Meryem Lemrani, Nabil Haddad, Ayoade Oduola, Oussama Souiai, Insaf Bel Hadj Ali, Ikram Guizani
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引用次数: 0

Abstract

Digital Systems for Data Management (DSDM) have become a critical cornerstone in collaborative biomedical research and clinical trials involving multiple investigators, institutions, and populations. DSDM provide unique features that ensure that data meet the standards of FAIR (Findability, Accessibility, Interoperability and Reusability). We herein present Lesionia, a DSDM designed to support the PEER518 consortium that aimed at developing new cutaneous leishmaniases (CL) diagnostics using samples and data collected from patients suspected of having CL in countries in the MENA region and West Africa. The consortium involved nine institutions across five countries: Tunisia, Morocco, Lebanon, Mali, and the USA, and informally Scientists from Algeria and Nigeria. The guidelines on the data to be collected by the clinicians and biologists during the project were used for the development of a Questionnaire that served as a basis for the implementation of a dedicated web-based DSDM.Lesionia was developed and validated for the management and the analysis of clinical and epidemiological data in the diagnosis of CL. It consists of a relational database, a web-based user interface (WUI) and a tool for experimental data handling and analysis of clinical and epidemiological data of CL cases. The platform was deployed and validated during the PEER518 project using data collected across the involved teams. Lesionia is expandable to include further collaborators, partners, and projects. It is designed for data handling from the consented patient interview and sample collection to the samples' storage and investigation. The WUI permits data entry, fetching, visualization and analysis. Rigorous controls on data entry were implemented to reduce discrepancies. It also offers a set of analysis tools that range from descriptive statistics to variable correlation analysis. Lesionia is accessible in a secure manner to all users of the consortium through a web browser.Lesionia will be a valuable tool for collaborative and integrative management of clinical and epidemiological data. It is an open-source software that can broadly serve the scientific community interested in studying, controlling, reporting, and diagnosing CL and similar cutaneous diseases.

Lesionia:一个数字数据管理系统,以加强对皮肤利什曼病患者的流行病学和临床数据的协同管理。
数据管理数字系统(DSDM)已经成为涉及多个研究者、机构和人群的协同生物医学研究和临床试验的关键基石。DSDM提供了独特的功能,确保数据符合FAIR(可查找性、可访问性、互操作性和可重用性)的标准。我们在此介绍Lesionia,这是一个DSDM,旨在支持PEER518联盟,该联盟旨在开发新的皮肤利什曼病(CL)诊断方法,使用从中东和北非地区和西非国家疑似患有CL的患者收集的样本和数据。该联盟包括来自五个国家的九个机构:突尼斯、摩洛哥、黎巴嫩、马里和美国,以及来自阿尔及利亚和尼日利亚的非正式科学家。关于临床医生和生物学家在项目期间收集的数据的指导方针被用于开发一份问卷,该问卷作为实施专门的基于网络的DSDM的基础。开发并验证了Lesionia用于CL诊断的临床和流行病学数据的管理和分析。它包括一个关系数据库、一个基于网络的用户界面(WUI)和一个用于处理实验数据和分析CL病例临床和流行病学数据的工具。该平台是在PEER518项目期间部署和验证的,使用的是相关团队收集的数据。Lesionia是可扩展的,可以包括更多的合作者、合作伙伴和项目。它设计用于从同意的患者访谈和样本收集到样本存储和调查的数据处理。WUI允许数据输入、获取、可视化和分析。严格控制数据输入,以减少差异。它还提供了一组分析工具,范围从描述性统计到变量相关性分析。该联盟的所有用户都可以通过网络浏览器以安全的方式访问Lesionia。Lesionia将成为临床和流行病学数据协作和综合管理的宝贵工具。它是一个开源软件,可以广泛地服务于对研究、控制、报告和诊断CL和类似皮肤疾病感兴趣的科学界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Research Notes
BMC Research Notes Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
3.60
自引率
0.00%
发文量
363
审稿时长
15 weeks
期刊介绍: BMC Research Notes publishes scientifically valid research outputs that cannot be considered as full research or methodology articles. We support the research community across all scientific and clinical disciplines by providing an open access forum for sharing data and useful information; this includes, but is not limited to, updates to previous work, additions to established methods, short publications, null results, research proposals and data management plans.
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