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: Modeling longitudinal data in acute illness. | Available online http content 11 4 152 Commentary Modeling longitudinal data in acute illness Gilles Clermont CIRM Center for Inflammation and Regenerative Modeling Clinical Research Investigation and Systems Modeling in Acute Illness CRISMA laboratory Department of Critical Care Medicine Terrace St University of Pittsburgh Medical Center Pittsburgh Philadelphia 15261 USA Corresponding author Gilles Clermont clermontg@ Published 2 August 2007 This article is online at http content 11 4 152 2007 BioMed Central Ltd Critical Care 2007 11 152 doi cc5968 See related research by Kyr et al. http content 11 3 R70 Abstract Biomarkers of sepsis could allow early identification of high-risk patients in whom aggressive interventions can be life-saving. Among those interventions are the immunomodulatory therapies which will hopefully become increasingly available to clinicians. However optimal use of such interventions will probably be patient specific and based on longitudinal profiles of such biomarkers. Modeling techniques that allow proper interpretation and classification of these longitudinal profiles as they relate to patient characteristics disease progression and therapeutic interventions will prove essential to the development of such individualized interventions. Once validated these models may also prove useful in the rational design of future clinical trials and in the interpretation of their results. However only a minority of mathematicians and statisticians are familiar with these newer techniques which have undergone remarkable development during the past two decades. Interestingly critical illness has the potential to become a key testing ground and field of application for these emerging modeling techniques given the increasing availability of point-of-care testing and the need for titrated interventions in this patient population. Critical care physicians titrate care of individual patients based on .
