Assessing Repeated Patient Information in Systematic Reviews Published Early in the COVID-19 Pandemic

Pablo J. Moreno-Peña,1 Miguel Zambrano-Lucio,1 Francisco J. Barrera,1,2,3 Andrea Flores Rodríguez,1 Skand Shekhar,4 Rachel Wurth,5 Michelle Hajdenberg,6 Neri A. Alvarez-Villalobos,1,2,3,7 Janet E. Hall,4 Ernesto L. Schiffrin,8 Juan P. Brito,2 Stefan R. Bornstein,9,10,11 Constantine A. Stratakis,5 Fady Hannah-Shmouni,5 René Rodríguez-Gutiérrez1,2,3,7


The inclusion of duplicate publications in systematic reviews (SRs) has led to repeated patient information (RPI).1,2 Repeated patient information in SRs is the inclusion of a patient’s information multiple times, with the assumption that they are different participants. This could result in the overestimation or underestimation of results, which can lead to substantial clinical implications through misleading estimates.1 A proportion of studies with shared timing and location was identified in SRs by evaluating an early-stage sample of COVID-19 SRs. According to the International Committee of Medical Journal Editors, a duplicate publication overlaps substantially with a published article without clear reference to the initial publication.3 The proportion of studies with shared characteristics that could suggest RPI was assessed in this study.


This study was an umbrella review of SRs with clinical data for patients with COVID-19. An experienced librarian performed a comprehensive search strategy for peer-reviewed articles in the English language published between December 1, 2019, and April 6, 2020, in databases that included Ovid MEDLINE In-Process & Other Non-Indexed Citations, Ovid MEDLINE, Ovid Embase, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, and Scopus. Studies included in SRs were grouped into clusters depending on characteristics including time frame and location. The frequency of studies that met the definition of at risk of including RPI was measured according to shared timing and location in the same SR.


Fifteen SRs were included, with a total population of 172,558 participants. A median (IQR) of 9 (6-20) studies were included in each SR, and 6 (2-10) studies included by each SR were considered at risk. Of these, 14 (93.3%) had risk of RPI. Subsequently, 103 clusters were generated. A median (IQR) of 3 (1-6) at-risk clusters were included in each SR. Eleven SRs (73.3%) included articles with RPI from a single hospital.


Risk of RPI was prevalent in COVID-19 SRs published early in the pandemic, and RPI may also be common in SRs of topics outside COVID-19. The impact of RPI on SRs could dilute their validity. Statements about effect sizes should be made carefully, ensuring studies have carefully selected their population to include unique participants. The following are suggestions to improve the often-complex process of identifying RPI: (1) journals should ask authors to state if any data have been published and, if so, to provide a reference; (2) reporting guidelines (CONSORT, STARD, CARE, STROBE, and PRISMA) should include a domain asking the authors if any of the data has been published elsewhere; and (3) the quality assessment tool for SRs (AMSTAR) should include a domain that evaluates whether the authors evaluate the inclusion of RPI.


1. Choi WS, Song SW, Ock SM, et al. Duplicate publication of articles used in meta-analysis in Korea. SpringerPlus. 2014;3(1):182.

2. von Elm E, Poglia G, Walder B, Tramèr MR. Different patterns of duplicate publication: an analysis of articles used in systematic reviews. JAMA. 2004;291(8):974-980.

3. Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly work in Medical Journals. International Committee of Medical Journal Editors. Updated May 2022. Accessed January 29, 2022. http://icmje.org/recommendations/

1Plataforma INVEST-KER Unit Mayo Clinic (KER Unit Mexico), School of Medicine, Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico, renerodriguezgtz@hotmail.com; 2Knowledge and Evaluation Research, Mayo Clinic, Rochester, MN, USA; 3Endocrinology Division, Internal Medicine Department, Hospital Universitario Dr José Eleuterio González, Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico; 4Clinical Research Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA; 5Section on Endocrinology & Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA; 6College of Arts and Sciences at Washington University in St Louis, St Louis, MO, USA; 7Research Unit, School of Medicine and Hospital Universitario Dr José Eleuterio González, Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo León, Mexico; 8Department of Medicine, Sir Mortimer B. Davis-Jewish General Hospital, McGill University, Montreal, Montreal, QC, Canada; 9Department of Medicine III, University Hospital Carl Gustav Carus, Dresden, Germany; 10Department of Diabetes, School of Life Course Science & Medicine, King’s College London Strand, London, UK; 11Klinik für Endokrinologie, Diabetologie und Klinische Ernährung, University Hospital of Zürich, Zürich, Switzerland

Conflict of Interest Disclosures

None reported.


This study was funded in part by the intramural research program of the National Institutes of Health.

Role of the Funder/Sponsor

The sponsor was not involved in the design or conduct of the study, the preparation of the abstract, or the decision to submit the abstract.

Additional Information

Pablo J. Moreno-Peña and Miguel Zambrano-Lucio share equal credit as co–first authors. Fady Hannah-Shmouni is a co–corresponding author.