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Exploring the Gantt chart as a tool to highlight double report in case series published during the first wave of the COVID-19 pandemic
BACKGROUND: During the COVID-19 pandemic, some studies describing different aspects of the infection included very similar participants, rising suspicion about double reporting. We aimed to evaluate the Gantt chart as a tool to highlight possible double reporting. The chart is routinely used in busi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9338517/ https://www.ncbi.nlm.nih.gov/pubmed/35908036 http://dx.doi.org/10.1186/s13643-022-02024-0 |
Sumario: | BACKGROUND: During the COVID-19 pandemic, some studies describing different aspects of the infection included very similar participants, rising suspicion about double reporting. We aimed to evaluate the Gantt chart as a tool to highlight possible double reporting. The chart is routinely used in business applications to depict tasks of a project, by plotting horizontal bars against time, showing their time span and overlaps. METHODS: All case reports and case series of pregnant women with COVID-19, published by July 15, 2020, were included. Initial and final dates of participants’ enrollment, country, city, hospital, and number of pregnancies were plotted in the Gantt chart. Bars stand for enrollment dates of each study, according to hospital and city, thus allowing comparisons. RESULTS: We included 116 articles in the present analysis. The Gantt chart highlighted papers in which some participants were likely the same, thus allowing easier identification of double reporting of cases. Combining all information and pregnancy characteristics and outcomes helped to recognize duplications when the authors did not acknowledged the previous publication. CONCLUSIONS: Unintended double reporting may occur, especially in exceptional times. The Gantt chart may help researchers to visually identify potential duplications, thus avoiding biased estimates in systematic reviews or meta-analysis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13643-022-02024-0. |
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