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Báo cáo y học: "Bench-to-bedside review: Avoiding pitfalls in critical care meta-analysis — funnel plots, risk estimates, types of heterogeneity, baseline risk and the ecologic fallacy"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Critical Care giúp cho các bạn có thêm kiến thức về ngành y học đề tài: Bench-to-bedside review: Avoiding pitfalls in critical care meta-analysis — funnel plots, risk estimates, types of heterogeneity, baseline risk and the ecologic fallacy. | Available online http ccforum.eom content 12 4 220 Review Bench-to-bedside review Avoiding pitfalls in critical care meta-analysis - funnel plots risk estimates types of heterogeneity baseline risk and the ecologic fallacy Michael C Reade1 2 Anthony Delaney3 Michael J Bailey4 and Derek C Angus1 1CRISMA Laboratory Department of Critical Care Medicine University of Pittsburgh 3550 Terrace Street Pittsburgh PA 15261 USA 2Current address Austin Hospital University of Melbourne 145 Studley Road Heidelberg 3084 Australia 3Royal North Shore Hospital and Northern Clinical School University of Sydney Pacific Highway St Leonards NSW 2065 Australia 4Australian and New Zealand Intensive Care Research Centre Department of Epidemiology and Preventive Medicine Monash University The Alfred Hospital Commercial Road Melbourne 3004 Australia Corresponding author Michael C Reade mreade@doctors.net.uk Published 25 July 2008 This article is online at http ccforum.com content 12 4 220 2008 BioMed Central Ltd Critical Care 2008 12 220 doi 10.1186 cc6941 Abstract Meta-analysis can be a powerful tool for demonstrating the applicability of a concept beyond the context of individual clinical trials and observational studies including exploration of effects across different subgroups. Meta-analysis avoids Simpson s paradox in which a consistent effect in constituent trials is reversed when results are simply pooled. Meta-analysis in critical care medicine is made more complicated however by the heterogeneous nature of critically ill patients and the contexts within which they are treated. Failure to properly adjust for this heterogeneity risks missing important subgroup effects in for example the interaction of treatment with varying levels of baseline risk. When subgroups are defined by characteristics that vary within constituent trials such as age rather than features constant within each trial such as drug dose there is the additional risk of incorrect conclusions due to the ecological .