{"title":"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。","authors":"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","doi":"10.1186/s13104-025-07208-0","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":9234,"journal":{"name":"BMC Research Notes","volume":"18 1","pages":"160"},"PeriodicalIF":1.6000,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11987383/pdf/","citationCount":"0","resultStr":"{\"title\":\"Lesionia: a digital data management system to enhance collaborative management of epidemiological and clinical data of cutaneous leishmaniases patients.\",\"authors\":\"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\",\"doi\":\"10.1186/s13104-025-07208-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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. 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Lesionia: a digital data management system to enhance collaborative management of epidemiological and clinical data of cutaneous leishmaniases patients.
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.
BMC Research NotesBiochemistry, 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.