重症监护中的预后
Prognosis in critical care.
作者信息
Ohno-Machado Lucila, Resnic Frederic S, Matheny Michael E
机构信息
Decision Systems Group, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA.
出版信息
Annu Rev Biomed Eng. 2006;8:567-99. doi: 10.1146/annurev.bioeng.8.061505.095842.
Prognostic risk prediction models have been employed in the intensive care unit (ICU) setting since the 1980s and provide health care providers with important information to help inform decisions related to treatment and prognosis, as well as to compare outcomes across institutions. Prognostic models for critical care are among the most widely utilized and tested predictive models in healthcare. In this article, we review and compare mortality prediction models, including the APACHE (1981), SAPS (1984), APACHE-II (1985), MPM (1987), APACHE-III (1991), SAPS-II (1993), and MPM-II (1993). We emphasize the importance of model calibration in this domain. In addition, we present a brief review of the statistical methodology, multiple logistic regression, which underlies most of the models currently used in critical care.
自20世纪80年代以来，预后风险预测模型已在重症监护病房（ICU）环境中得到应用，为医疗保健提供者提供重要信息，以帮助做出与治疗和预后相关的决策，并比较各机构的治疗结果。重症监护的预后模型是医疗保健领域应用最广泛且经过测试的预测模型之一。在本文中，我们回顾并比较了死亡率预测模型，包括急性生理与慢性健康状况评分系统（APACHE，1981年）、简化急性生理学评分（SAPS，1984年）、急性生理与慢性健康状况评分系统第二版（APACHE-II，1985年）、死亡率预测模型（MPM，1987年）、急性生理与慢性健康状况评分系统第三版（APACHE-III，1991年）、简化急性生理学评分第二版（SAPS-II，1993年）和死亡率预测模型第二版（MPM-II，1993年）。我们强调了模型校准在该领域的重要性。此外，我们简要回顾了作为当前重症监护中大多数模型基础的统计方法——多元逻辑回归。
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