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重症监护中的预后预测:ICNARC模型。

Outcome prediction in critical care: the ICNARC model.

作者信息

Harrison David A, Rowan Kathryn M

机构信息

Intensive Care National Audit & Research Centre, London, UK.

出版信息

Curr Opin Crit Care. 2008 Oct;14(5):506-12. doi: 10.1097/MCC.0b013e328310165a.

Abstract

PURPOSE OF REVIEW

To describe the background to, rationale for, and structure and performance of the Intensive Care National Audit & Research Centre risk prediction model.

RECENT FINDINGS

The Intensive Care National Audit & Research Centre model was published in 2007 as a new risk prediction model, predicting risk of death before ultimate discharge from acute hospital for all admissions to adult, general critical care units in the UK. It was developed using a high-quality clinical database of over 200,000 admissions to 163 critical care units and prospectively validated in over 30,000 admissions to 20 different units. The Intensive Care National Audit & Research Centre model was designed to address limitations of preexisting models, particularly exclusion of certain patient groups, and varying effects of physiological derangement in different underlying conditions.

SUMMARY

The Intensive Care National Audit & Research Centre model performs well in comparison with preexisting models when evaluated in independent validation data from UK critical care units. The use of interactions between the physiology score and diagnostic category produces better fit within individual diagnostic groups. The elimination of model exclusion criteria, for example age less than 16 years, means that the model compares the observed and expected outcomes for all patients admitted to a critical care unit providing a fairer method for comparative audit.

摘要

综述目的

描述重症监护国家审计与研究中心风险预测模型的背景、原理、结构及性能。

最新发现

重症监护国家审计与研究中心模型于2007年发布,作为一种新的风险预测模型,用于预测英国成人普通重症监护病房所有入院患者最终出院前的死亡风险。该模型基于超过20万例入住163个重症监护病房的高质量临床数据库开发,并在超过3万例入住20个不同病房的患者中进行了前瞻性验证。重症监护国家审计与研究中心模型旨在解决现有模型的局限性,特别是某些患者群体的排除以及不同基础疾病中生理紊乱的不同影响。

总结

在英国重症监护病房的独立验证数据中进行评估时,重症监护国家审计与研究中心模型与现有模型相比表现良好。生理评分与诊断类别之间相互作用的运用在各个诊断组内产生了更好的拟合效果。消除模型排除标准,例如年龄小于16岁,意味着该模型比较了入住重症监护病房的所有患者的观察结果和预期结果,为比较审计提供了更公平的方法。

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