BACKGROUND: Meta-analyses may be prone to generating misleading results because of a paucity of experimental studies (especially in surgery); publication bias; and heterogeneity in study design, intervention and the patient population of included studies. When investigating a specific clinical or scientific question on which several relevant meta-analyses may have been published, value judgments must be applied to determine which analysis represents the most robust evidence. These value judgments should be specifically acknowledged. We designed the Veritas plot to explicitly explore important elements of quality and to facilitate decision-making by highlighting specific areas in which meta-analyses are found to be deficient. Furthermore, as a graphic tool, it may be more intuitive than when similar data are presented in a tabular or text format. METHODS: The Veritas plot is an adaption of the radar plot, a graphic tool for the description of multiattribute data. Key elements of meta-analytical quality such as heterogeneity, publication bias and study design are assessed. Existing qualitative methods such as the Assessment of Multiple Systematic Reviews (AMSTAR) tool have been incorporated in addition to important considerations when interpreting surgical meta-analyses such as the year of publication and population characteristics. To demonstrate the potential of the Veritas plot to inform clinical practice, we apply the Veritas plot to the meta-analytical literature comparing the incidence of 30-day stroke in off-pump coronary artery bypass surgery and conventional coronary artery bypass surgery. RESULTS: We demonstrate that a visually-stimulating and practical evidence-synthesis tool can direct the clinician and scientist to a particular meta-analytical study to inform clinical practice. The Veritas plot is also cumulative and allowed us to assess the quality of evidence over time. CONCLUSION: We have presented a practical graphic application for scientists and clinicians to identify and interpret variability in meta-analyses. Although further validation of the Veritas plot is required, it may have the potential to contribute to the implementation of evidence-based practice.
BACKGROUND: Meta-analyses may be prone to generating misleading results because of a paucity of experimental studies (especially in surgery); publication bias; and heterogeneity in study design, intervention and the patient population of included studies. When investigating a specific clinical or scientific question on which several relevant meta-analyses may have been published, value judgments must be applied to determine which analysis represents the most robust evidence. These value judgments should be specifically acknowledged. We designed the Veritas plot to explicitly explore important elements of quality and to facilitate decision-making by highlighting specific areas in which meta-analyses are found to be deficient. Furthermore, as a graphic tool, it may be more intuitive than when similar data are presented in a tabular or text format. METHODS: The Veritas plot is an adaption of the radar plot, a graphic tool for the description of multiattribute data. Key elements of meta-analytical quality such as heterogeneity, publication bias and study design are assessed. Existing qualitative methods such as the Assessment of Multiple Systematic Reviews (AMSTAR) tool have been incorporated in addition to important considerations when interpreting surgical meta-analyses such as the year of publication and population characteristics. To demonstrate the potential of the Veritas plot to inform clinical practice, we apply the Veritas plot to the meta-analytical literature comparing the incidence of 30-day stroke in off-pump coronary artery bypass surgery and conventional coronary artery bypass surgery. RESULTS: We demonstrate that a visually-stimulating and practical evidence-synthesis tool can direct the clinician and scientist to a particular meta-analytical study to inform clinical practice. The Veritas plot is also cumulative and allowed us to assess the quality of evidence over time. CONCLUSION: We have presented a practical graphic application for scientists and clinicians to identify and interpret variability in meta-analyses. Although further validation of the Veritas plot is required, it may have the potential to contribute to the implementation of evidence-based practice.
Authors: Thanos Athanasiou; Sharif Al-Ruzzeh; Pankaj Kumar; Mary-Clare Crossman; Mohamed Amrani; John R Pepper; Rex Del Stanbridge; Roberto Casula; Brian Glenville Journal: Ann Thorac Surg Date: 2004-02 Impact factor: 4.330
Authors: William R Henderson; Vinay K Dhingra; Dean R Chittock; John C Fenwick; Juan J Ronco Journal: Intensive Care Med Date: 2003-08-12 Impact factor: 17.440