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CURB-65 肺炎严重程度评估适用于电子决策支持。

CURB-65 pneumonia severity assessment adapted for electronic decision support.

机构信息

Department of Medicine, Division of Pulmonary and Critical Care Medicine, University of Utah, Salt Lake City, UT.

Department of Medical Informatics, Intermountain Medical Center, Murray, UT.

出版信息

Chest. 2011 Jul;140(1):156-163. doi: 10.1378/chest.10-1296. Epub 2010 Dec 16.

Abstract

BACKGROUND

Accurate severity assessment is crucial to the initial management of community-acquired pneumonia (CAP). The CURB-65 (confusion, uremia, respiratory rate, BP, age ≥ 65 years) score contains data that are entered routinely in electronic medical records and are, thus, electronically calculable. The aim of this study was to determine whether an electronically generated severity estimate using CURB-65 elements as continuous and weighted variables better predicts 30-day mortality than the traditional CURB-65.

METHODS

In a retrospective cohort study at a US university-affiliated community teaching hospital, we identified 2,069 patients aged 18 years or older with CAP confirmed by radiographic findings in the ED. CURB-65 elements were extracted from the electronic medical record, and 30-day mortality was identified with the Utah Population Database. Performance of a severity prediction model using continuous and weighted CURB-65 variables was compared with the traditional CURB-65 in the US derivation population and validated in the original 1,048 patients from the CURB-65 international derivation study.

RESULTS

The traditional, binary CURB-65 score predicted mortality in the US cohort with an area under the curve (AUC) of 0.82. Our severity prediction model generated from continuous, weighted CURB-65 elements was superior to the traditional CURB-65, with an out-of-bag AUC of 0.86 (P < .001). This finding was validated in the international database, with an AUC of 0.85 for the electronic model compared with 0.80 for the traditional CURB-65 (P = .01).

CONCLUSIONS

Using CURB-65 elements as continuous and weighted data improved prediction of 30-day mortality and could be used as a real-time, electronic decision support tool or to adjust outcomes by severity when comparing processes of care.

摘要

背景

准确的严重程度评估对于社区获得性肺炎(CAP)的初始管理至关重要。 CURB-65(意识障碍、血尿素氮、呼吸频率、血压、年龄≥65 岁)评分包含常规输入电子病历中的数据,因此可以通过电子方式计算。本研究旨在确定使用 CURB-65 元素作为连续和加权变量生成的电子严重程度估计是否比传统 CURB-65 更好地预测 30 天死亡率。

方法

在一家美国大学附属社区教学医院进行的回顾性队列研究中,我们确定了 2069 名年龄在 18 岁或以上的 CAP 患者,这些患者在急诊科通过影像学检查确诊。从电子病历中提取 CURB-65 元素,并使用犹他州人群数据库确定 30 天死亡率。在 US 推导人群中,使用连续和加权 CURB-65 变量的严重程度预测模型与传统 CURB-65 进行比较,并在原始的 1048 名来自 CURB-65 国际推导研究的患者中进行验证。

结果

传统的二进制 CURB-65 评分预测了美国队列中的死亡率,曲线下面积(AUC)为 0.82。我们从连续、加权 CURB-65 元素生成的严重程度预测模型优于传统 CURB-65,袋外 AUC 为 0.86(P<0.001)。这一发现得到了国际数据库的验证,电子模型的 AUC 为 0.85,而传统 CURB-65 的 AUC 为 0.80(P=0.01)。

结论

使用 CURB-65 元素作为连续和加权数据可提高 30 天死亡率的预测准确性,可作为实时电子决策支持工具,或在比较护理过程时根据严重程度调整结果。

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