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: Application of a population-based severity scoring system to individual patients results in frequent misclassification. | Available online http content 9 5 R522 Research Application of a population-based severity scoring system to individual patients results in frequent misclassification Frank V Booth1 Mary Short2 Andrew F Shorr3 Nancy Arkins4 Becky Bates5 Rebecca L Qualy6 and Howard Levy7 1Medical Fellow Eli Lilly and Company Indianapolis IN USA 2Associate Clinical Research Scientist Eli Lilly and Company Indianapolis IN USA 3Associate Director of Pulmonary Critical Care Medicine Pulmonary and Critical Care Medicine Washington Hospital Center Washington DC USA and Associate Professor of Medicine Georgetown University Washington DC USA 4Senior Clinical Development Associate Eli Lilly and Company Indianapolis IN USA 5Associate Senior Statistician Eli Lilly and Company Indianapolis IN USA 6Senior Scientific Communication Associate Eli Lilly and Company Indianapolis IN USA 7Medical Director Eli Lilly and Company Indianapolis IN USA Corresponding author Frank V Booth boothfv@ Received 6 May 2005 Revisions requested 15 Jun 2005 Revisions received 1 Jul 2005 Accepted 12 Jul 2005 Published 9 Aug 2005 Critical Care 2005 9 R522-R529 DOI 86 cc3790 This article is online at http content 9 5 R522 2005 Booth et al. licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Open Access Abstract Introduction APACHE II AP2 was developed to allow a systematic examination of intensive care unit outcomes in a risk adjusted manner. AP2 has been widely adopted in clinical trials to assure broad consistency amongst different groups. Although errors in calculating the true AP2 score may not be reducible below 15 the self-canceling effect of random errors reduces the importance of such errors when applied to large populations. It has been
