Unidade de Bioestatística, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.
Serviço de Ginecologia e Obstetrícia, Hospital de Clínicas de Porto Alegre and Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
Syst Rev. 2022 Jul 30;11(1):155. doi: 10.1186/s13643-022-02024-0.
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.
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.
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.
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.
在 COVID-19 大流行期间,一些描述感染不同方面的研究包括非常相似的参与者,这引起了对重复报告的怀疑。我们旨在评估甘特图作为突出可能重复报告的工具。该图表在商业应用中通常用于描绘项目的任务,通过在时间上绘制水平条来显示其时间跨度和重叠。
纳入所有发表于 2020 年 7 月 15 日之前的 COVID-19 孕妇的病例报告和病例系列。在甘特图中绘制参与者入组的初始和最终日期、国家、城市、医院和妊娠次数。条表示根据医院和城市入组的每个研究的日期,从而可以进行比较。
我们在本分析中纳入了 116 篇文章。甘特图突出显示了一些参与者可能相同的论文,从而更容易识别病例的重复报告。当作者没有承认先前的出版物时,结合所有信息和妊娠特征及结果有助于识别重复。
可能会发生意外的重复报告,尤其是在特殊时期。甘特图可以帮助研究人员直观地识别潜在的重复,从而避免系统评价或荟萃分析中的偏倚估计。