Risk of bias reporting in the recent animal focal cerebral ischaemia literature

Zsanett Bahor, Jing Liao, Malcolm R. Macleod, Alexandra Bannach-Brown, Sarah K. McCann, Kimberley E. Wever, James Thomas, Thomas Ottavi, David W. Howells, Andrew Rice, Sophia Ananiadou, Emily Sena

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Abstract

Background: Findings from in vivo research may be less reliable where studies do not report 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 experimental models of stroke. Methods: We developed and used text analytic approaches to automatically ascertain reporting of measures to reduce risk of bias from full-text articles describing animal experiments 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 lacunar stroke literature. Accuracy of automated annotation of risk of bias in theMCAO literature was 86% (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 animal research modelling stroke, particularly in the lacunar stroke literature. Further, automated 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
Pages (from-to)2525-2532
Number of pages8
JournalClinical Science
Volume131
Issue number20
DOIs
Publication statusPublished - 15 Oct 2017
Externally publishedYes

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Brain Ischemia
Lacunar Stroke
Random Allocation
Sample Size
Middle Cerebral Artery Infarction
Stroke
Theoretical Models
Outcome Assessment (Health Care)
Research

Cite this

Bahor, Z., Liao, J., Macleod, M. R., Bannach-Brown, A., McCann, S. K., Wever, K. E., ... Sena, E. (2017). Risk of bias reporting in the recent animal focal cerebral ischaemia literature. Clinical Science, 131(20), 2525-2532. https://doi.org/10.1042/CS20160722
Bahor, Zsanett ; Liao, Jing ; Macleod, Malcolm R. ; Bannach-Brown, Alexandra ; McCann, Sarah K. ; Wever, Kimberley E. ; Thomas, James ; Ottavi, Thomas ; Howells, David W. ; Rice, Andrew ; Ananiadou, Sophia ; Sena, Emily. / Risk of bias reporting in the recent animal focal cerebral ischaemia literature. In: Clinical Science. 2017 ; Vol. 131, No. 20. pp. 2525-2532.
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author = "Zsanett Bahor and Jing Liao and Macleod, {Malcolm R.} and Alexandra Bannach-Brown and McCann, {Sarah K.} and Wever, {Kimberley E.} and James Thomas and Thomas Ottavi and Howells, {David W.} and Andrew Rice and Sophia Ananiadou and Emily Sena",
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Bahor, Z, Liao, J, Macleod, MR, Bannach-Brown, A, McCann, SK, Wever, KE, Thomas, J, Ottavi, T, Howells, DW, Rice, A, Ananiadou, S & Sena, E 2017, 'Risk of bias reporting in the recent animal focal cerebral ischaemia literature' Clinical Science, vol. 131, no. 20, pp. 2525-2532. https://doi.org/10.1042/CS20160722

Risk of bias reporting in the recent animal focal cerebral ischaemia literature. / Bahor, Zsanett; Liao, Jing; Macleod, Malcolm R.; Bannach-Brown, Alexandra; McCann, Sarah K.; Wever, Kimberley E.; Thomas, James; Ottavi, Thomas; Howells, David W.; Rice, Andrew; Ananiadou, Sophia; Sena, Emily.

In: Clinical Science, Vol. 131, No. 20, 15.10.2017, p. 2525-2532.

Research output: Contribution to journalReview articleResearchpeer-review

TY - JOUR

T1 - Risk of bias reporting in the recent animal focal cerebral ischaemia literature

AU - Bahor, Zsanett

AU - Liao, Jing

AU - Macleod, Malcolm R.

AU - Bannach-Brown, Alexandra

AU - McCann, Sarah K.

AU - Wever, Kimberley E.

AU - Thomas, James

AU - Ottavi, Thomas

AU - Howells, David W.

AU - Rice, Andrew

AU - Ananiadou, Sophia

AU - Sena, Emily

PY - 2017/10/15

Y1 - 2017/10/15

N2 - Background: Findings from in vivo research may be less reliable where studies do not report 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 experimental models of stroke. Methods: We developed and used text analytic approaches to automatically ascertain reporting of measures to reduce risk of bias from full-text articles describing animal experiments 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 lacunar stroke literature. Accuracy of automated annotation of risk of bias in theMCAO literature was 86% (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 animal research modelling stroke, particularly in the lacunar stroke literature. Further, automated 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.

AB - Background: Findings from in vivo research may be less reliable where studies do not report 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 experimental models of stroke. Methods: We developed and used text analytic approaches to automatically ascertain reporting of measures to reduce risk of bias from full-text articles describing animal experiments 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 lacunar stroke literature. Accuracy of automated annotation of risk of bias in theMCAO literature was 86% (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 animal research modelling stroke, particularly in the lacunar stroke literature. Further, automated 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.

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U2 - 10.1042/CS20160722

DO - 10.1042/CS20160722

M3 - Review article

VL - 131

SP - 2525

EP - 2532

JO - Clinical Science and Molecular Medicine

JF - Clinical Science and Molecular Medicine

SN - 0143-5221

IS - 20

ER -