Báo cáo khoa học: "Survival methods, including those using competing risk analysis, are not appropriate for intensive care unit outcome studie"

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: Survival methods, including those using competing risk analysis, are not appropriate for intensive care unit outcome studies. | Available online http content 10 1 103 Commentary Survival methods including those using competing risk analysis are not appropriate for intensive care unit outcome studies David Schoenfeld Professor of Medicine Harvard Medical School Massachusetts General Hospital Biostatistics Center Staniford Street Boston MA 02114 USA Corresponding author David Schoenfeld dschoenfeld@ Published 9 December 2005 This article is online at http content 10 1 103 2005 BioMed Central Ltd Critical Care 2006 10 103 doi cc3949 See related research by Resche-Rigon et al. in this issue http content 10 1 R5 Abstract The preferred analysis for studies of mortality among patients treated in an intensive care unit should compare the proportions of patients who died during hospitalization. Studies that look for prognostic covariates should use logistic regression. Survival methods such as the proportional hazards model or methods based on competing risk analysis are not appropriate because prolonged survival among patients that die during their hospitalization does not benefit the patient and therefore should not be measured in the statistical analysis. Introduction In Evaluating Mortality in Intensive Care Units Contribution of Competing Risks Analysis 1 the authors introduce the use of the Fine and Grey regression model 2 based on the cumulative incidence function CIF to analyze data from outcome studies in the intensive care unit ICU . They show that this model can be used to provide a valid analysis of hospital or ICU mortality. The authors prefer this model to analyzing mortality as a binary variable lived versus died using binary data analysis techniques such as logistic regression. I argue that mortality should be analyzed as a binary variable because patients who die in the ICU do not benefit if the duration of their survival is prolonged. Because survival methods including those based on the CIF measure this increase in survival .

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