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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: Evaluating mortality in intensive care units: contribution of competing risks analyses. | Available online http ccforum.eom content 10 1 R5 Research Evaluating mortality in intensive care units contribution of competing risks analyses Matthieu Resche-Rigon1 Elie Azoulay2 and Sylvie Chevret3 Open Access 1Medical Doctor Biostatistics Department Saint Louis Teaching Hospital-Assistance Publique-Hôpitaux de Paris 1 avenue Claude Vellefaux Paris 75010 France 2Medical Doctor Medical Intensive Care Unit Saint Louis Teaching Hospital-Assistance Publique-Hôpitaux de Paris 1 avenue Claude Vellefaux Paris 75010 France 3Medical Doctor Biostatistics Department Saint Louis Teaching Hospital-Assistance Publique-Hôpitaux de Paris 1 avenue Claude Vellefaux Paris 75010 France Corresponding author Elie Azoulay elie.azoulay@sls.ap-hop-paris.fr Received 20 May 2005 Revisions requested 27 May 2005 Revisions received 8 Sep 2005 Accepted 27 Oct 2005 Published 1 Dec 2005 Critical Care 2006 10 R5 doi 10.1186 cc3921 This article is online at http ccforum.com content 10 1 R5 2005 Resche-Rigon et al. licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Introduction Kaplan-Meier curves and logistic models are widely used to describe and explain the variability of survival in intensive care unit ICU patients. The Kaplan-Meier approach considers that patients discharged alive from hospital are non-informatively censored for instance representative of all other individuals who have survived to that time but are still in hospital this is probably wrong. Logistic models are adapted to this so-called competing risks setting but fail to take into account censoring and differences in exposure time. To address these issues we exemplified the usefulness of standard competing risks methods namely cumulative incidence function CIF curves and the .
