Proposed Guideline for Minimum Information Stroke Research and Clinical Data Reporting

Authors

  • Judit Kumuthini Centre for Proteomic and Genomic Research, Cape Town
  • Lyndon Zass Centre for Proteomic and Genomic Research, Cape Town
  • Melek Chaouch Laboratory of Bioinformatics, Biomathematics and Biostatistics, Institut Pasteur de Tunis, Tunis
  • Michael Thompson National Institute of Mathematical Sciences, Kumasi
  • Paul Olowoyo Federal Teaching Hospital, Ido-Ekiti/Afe Babalola University, Ado-Ekiti
  • Mamana Mbiyavanga Computational Biology Division, IDM, University of Cape Town, Cape Town
  • Faniyan Moyinoluwalogo University of Ibadan, Ibadan
  • Gordon Wells Centre for Proteomic and Genomic Research, Cape Town
  • Victoria Nembaware Computational Biology Division, IDM, University of Cape Town, Cape Town
  • Nicola J. Mulder Computational Biology Division, IDM, University of Cape Town, Cape Town
  • Mayowa Owolabi University of Ibadan, Ibadan
  • H3ABioNet Consortium’s Data and Standard Working Group as members of the H3Africa Consortium

DOI:

https://doi.org/10.5334/dsj-2019-026

Keywords:

Stroke, minimum information requirement guideline, standardization, reporting guideline, data reporting, H3ABioNet

Abstract

The management and analyses of large datasets is one of the grand challenges of modern biomedical research. Establishing methods to harmonise and standardise data collection, reporting, sharing and the employed data dictionaries, can support the resolution of these challenges whilst improving research quality, data quality and integrity, allowing sustainable knowledge transfer through re-usability, interoperability, reproducibility. The current project aimed to develop and propose a standardised reporting guideline for stroke research and clinical data reporting. Through systematic consolidation and harmonization of published data collection and reporting standards, several recommendations were drafted for the proposed guideline. These recommendations were reviewed by domain-researchers and clinicians using an online survey, developed in REDCap. The survey was completed by 20 international stroke-specialists, majority of respondents were based in Africa (10), followed by America, Europe and Australia (10). Of these respondents; the majority were working as dual clinician-researchers (57%) with more than 10 years’ experience in the field (78%). Data elements within the reporting standard were classified as participant-, study- and experiment-level information, further subdivided into essential or optional information, and defined using existing ontologies. The proposed reporting guideline can be employed for research utility and adapted for clinical utility as well. It is accompanied with an associated XML schema for REDCap implementation, to increase the user friendliness of data capturing, sharing, reporting and governance. Ultimately, the adoption of common reporting in stroke research has the potential to ensure that researchers gain the maximum benefit from their generated data and data collections.

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Published

2019-06-27

Issue

Section

Research Papers