Risk of bias reporting in the recent animal focalcerebral ischaemia literature

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review


  • Zsanett Bahor, University of Edinburgh, United Kingdom
  • Jing Liao, University of Edinburgh
  • ,
  • Malcolm Macleod, University of Edinburgh
  • ,
  • Alexandra Bannach-Brown
  • Sarah K McCann, University of Edinburgh
  • ,
  • Kimberley E Wever, Radboud University Medical Centre, Nijmegen, The Netherlands
  • ,
  • James Thomas, Institute of Education, London
  • ,
  • Thomas Ottavi, University of Tasmania
  • ,
  • David W Howells, University of Tasmania
  • ,
  • Andrew Rice, Imperial College London
  • ,
  • Sophia Ananiadou, University of Manchester
  • ,
  • Emily Sena, University of Edinburgh
Background: Findings from in vivo research may be less reliable where studies do not re-port measures to reduce risks of bias. The experimental stroke community has been at the forefront of implementing changes to improve reporting, but it is not known whether these efforts are associated with continuous improvements. Our aims here were firstly to validate an automated tool to assess risks of bias in published works, and secondly to assess the reporting of measures taken to reduce the risk of bias within recent literature for two exper-imental models of stroke.Methods: We developed and used text analytic approaches to automatically ascertain re-porting of measures to reduce risk of bias from full-text articles describing animal experi-ments inducing middle cerebral artery occlusion (MCAO) or modelling lacunar stroke.Results: Compared with previous assessments, there were improvements in the reporting of measures taken to reduce risks of bias in the MCAO literature but not in the lacunarstroke literature. Accuracy of automated annotation of risk of bias in the MCAO literature was86% (randomization), 94% (blinding) and 100% (sample size calculation); and in the lacunar stroke literature accuracy was 67% (randomization), 91% (blinding) and 96% (sample size calculation).Discussion: There remains substantial opportunity for improvement in the reporting of an-imal research modelling stroke, particularly in the lacunar stroke literature. Further, auto-mated tools perform sufficiently well to identify whether studies report blinded assessment of outcome, but improvements are required in the tools to ascertain whether randomization and a sample size calculation were reported.
Original languageEnglish
JournalClinical Science
Pages (from-to)2525-2532
Publication statusPublished - 13 Oct 2017

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