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Data extraction methods: an analysis of internal reporting discrepancies in single manuscripts and practical advice.
Puljak, Livia; Riva, Nicoletta; Parmelli, Elena; González-Lorenzo, Marien; Moja, Lorenzo; Pieper, Dawid.
Afiliación
  • Puljak L; Center for Evidence-Based Medicine and Health Care, Catholic University of Croatia, Zagreb, Croatia. Electronic address: livia.puljak@unicath.hr.
  • Riva N; Department of Pathology, Faculty of Medicine and Surgery, University of Malta, Msida, Malta.
  • Parmelli E; Department of Epidemiology, Lazio Regional Health Service - ASL Roma 1, Rome, Italy.
  • González-Lorenzo M; Department of Biomedical Sciences, Humanitas University, Milan, Italy; IBD Center, Humanitas Clinical and Research Center, Milan, Italy.
  • Moja L; Policy, Access and Use (PAU), Essential Medicines and Health Products Department (EMP), World Health Organization, Geneva, Switzerland.
  • Pieper D; Witten/Herdecke University, School of Medicine, Cologne, Germany.
J Clin Epidemiol ; 117: 158-164, 2020 01.
Article en En | MEDLINE | ID: mdl-31541692
BACKGROUND: Data extraction from reports about experimental or observational studies is a crucial methodological step informing evidence syntheses, such as systematic reviews (SRs) and overviews of SRs. Reporting discrepancies were defined as pairs of statements that could not both be true. Authors of SRs and overviews of SRs can encounter reporting discrepancies among multiple sources when extracting data-a manuscript and a conference abstract, and a manuscript and a clinical trial registry. However, these discrepancies can also be found within a single manuscript published in a scientific journal. OBJECTIVES: Hereby, we describe examples of internal reporting discrepancies that can be found in a single source, with the aim of raising awareness among authors of SRs and overviews of SRs about such potential methodological issues. CONCLUSIONS: Authors of SRs and overviews of SRs should check whether the same information is reported in multiple places within a study and compare that information. Independent data extraction by two reviewers increases the chance of finding discrepancies, if they exist. We provide advice on how to deal with different types of discordances and how to report such discordances when conducting SRs and overviews of SRs.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Proyectos de Investigación / Análisis de Datos Tipo de estudio: Observational_studies / Overview / Prognostic_studies / Systematic_reviews Límite: Humans Idioma: En Revista: J Clin Epidemiol Asunto de la revista: EPIDEMIOLOGIA Año: 2020 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Proyectos de Investigación / Análisis de Datos Tipo de estudio: Observational_studies / Overview / Prognostic_studies / Systematic_reviews Límite: Humans Idioma: En Revista: J Clin Epidemiol Asunto de la revista: EPIDEMIOLOGIA Año: 2020 Tipo del documento: Article