Afessa Bekele, Keegan Mark T
Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota 55905, USA.
Crit Care. 2007;11(1):109. doi: 10.1186/cc5683.
Most prognostic models rely on variables recorded within 24 hours of admission to predict the mortality rate of patients in the intensive care unit (ICU). Although a significant number of patients die after discharge from the ICU, there is a paucity of data related to predicting hospital mortality based on information obtained at ICU discharge. It is likely that experienced intensivists may be able to predict the likelihood of hospital death at ICU discharge accurately if they incorporate patients' age, preferences regarding life support, comorbidities, prehospital quality of life, and clinical course in the ICU into their prediction. However, if it is to be generalizable and reproducible and to perform well without bias, then a good prediction model should be based on objectively defined variables.
大多数预后模型依靠入院后24小时内记录的变量来预测重症监护病房（ICU）患者的死亡率。尽管有相当数量的患者在从ICU出院后死亡，但基于在ICU出院时获得的信息来预测医院死亡率的数据却很匮乏。如果经验丰富的重症监护医生将患者的年龄、对生命支持的偏好、合并症、院前生活质量以及在ICU的临床病程纳入预测中，他们很可能能够准确预测患者在ICU出院时发生医院死亡的可能性。然而，如果要使其具有普遍性、可重复性且无偏差地良好运行，那么一个好的预测模型应该基于客观定义的变量。
