1. Achieving High Research Reporting Quality Through the Use of Computational Ontologies
- Author
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Ricardo Pietrobon, Edwin Sy Chan, Amrapali Zaveri, Beng Ti Ang, Jatin Shah, Olivier Dameron, Luciana Cofiel, Shreyasee Pradhan, Modélisation Conceptuelle des Connaissances Biomédicales, Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), and Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )
- Subjects
Evidence-based medicine ,medicine.medical_specialty ,Biomedical Research ,Standardized ,MESH: Clinical Trials as Topic ,Center of excellence ,Neurosurgery ,Context (language use) ,Ontology (information science) ,law.invention ,03 medical and health sciences ,0302 clinical medicine ,Cohen's kappa ,Meta-Analysis as Topic ,Randomized controlled trial ,law ,medicine ,Humans ,MESH: Meta-Analysis as Topic ,Medical physics ,030212 general & internal medicine ,Clinical Trials as Topic ,MESH: Neurosurgery ,MESH: Humans ,Ontology ,business.industry ,MESH: Biomedical Research ,General Neuroscience ,Computational Biology ,3. Good health ,Clinical trial ,Kappa coefficient ,Systematic review ,Reporting ,Meta-analyses ,[SDV.IB]Life Sciences [q-bio]/Bioengineering ,Periodicals as Topic ,business ,RCT ,MESH: Evidence-Based Medicine ,030217 neurology & neurosurgery ,Software ,MESH: Computational Biology ,MESH: Periodicals as Topic ,Information Systems - Abstract
International audience; Systematic reviews and meta-analyses constitute one of the central pillars of evidence-based medicine. However, clinical trials are poorly reported which delays meta-analyses and consequently the translation of clinical research findings to clinical practice. We propose a Center of Excellence in Research Reporting in Neurosurgery (CERR-N) and the creation of a clinically significant computational ontology to encode Randomized Controlled Trials (RCT) studies in neurosurgery. A 128 element strong computational ontology was derived from the Trial Bank ontology by omitting classes which were not required to perform meta-analysis. Three researchers from our team tagged five randomly selected RCT's each, published in the last 5 years (2004-2008), in the Journal of Neurosurgery (JoN), Neurosurgery Journal (NJ) and Journal of Neurotrauma (JoNT). We evaluated inter and intra observer reliability for the ontology using percent agreement and kappa coefficient. The inter-observer agreement was 76.4%, 75.97% and 74.9% and intra-observer agreement was 89.8%, 80.8% and 86.56% for JoN, NJ and JoNT respectively. The inter-observer kappa coefficient was 0.60, 0.54 and 0.53 and the intra-observer kappa coefficient was 0.79, 0.82 and 0.79 for JoN, NJ and JoNT journals respectively. The high degree of inter and intra-observer agreement confirms tagging consistency in sections of a given scientific manuscript. Standardizing reporting for neurosurgery articles can be reliably achieved through the integration of a computational ontology within the context of a CERR-N. This approach holds potential for the overall improvement in the quality of reporting of RCTs in neurosurgery, ultimately streamlining the translation of clinical research findings to improvement in patient care.
- Published
- 2010
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