Suppr超能文献

使用电子病历数据预测不稳定创伤患者血流动力学稳定的时间。

PREDICTION OF TIME TO HEMODYNAMIC STABILIZATION OF UNSTABLE INJURED PATIENT ENCOUNTERS USING ELECTRONIC MEDICAL RECORD DATA.

机构信息

Feinberg School of Medicine, Northwestern University, Chicago, Illinois.

Department of Neurology, University of Chicago, Chicago, Illinois.

出版信息

Shock. 2024 Nov 1;62(5):644-649. doi: 10.1097/SHK.0000000000002420. Epub 2024 Jul 1.

Abstract

Background : This study sought to predict time to patient hemodynamic stabilization during trauma resuscitations of hypotensive patient encounters using electronic medical record (EMR) data. Methods: This observational cohort study leveraged EMR data from a nine-hospital academic system composed of Level I, Level II, and nontrauma centers. Injured, hemodynamically unstable (initial systolic blood pressure, <90 mm Hg) emergency encounters from 2015 to 2020 were identified. Stabilization was defined as documented subsequent systolic blood pressure of >90 mm Hg. We predicted time to stabilization testing random forests, gradient boosting, and ensembles using patient, injury, treatment, EPIC Trauma Narrator, and hospital features from the first 4 hours of care. Results: Of 177,127 encounters, 1,347 (0.8%) arrived hemodynamically unstable; 168 (12.5%) presented to Level I trauma centers, 853 (63.3%) to Level II, and 326 (24.2%) to nontrauma centers. Of those, 747 (55.5%) were stabilized with a median of 50 min (interquartile range, 21-101 min). Stabilization was documented in 94.6% of unstable patient encounters at Level I, 57.6% at Level II, and 29.8% at nontrauma centers ( P < 0.001). Time to stabilization was predicted with a C-index of 0.80. The most predictive features were EPIC Trauma Narrator measures, documented patient arrival, provider examination, and disposition decision. In-hospital mortality was highest at Level I, 3.0% vs. 1.2% at Level II, and 0.3% at nontrauma centers ( P < 0.001). Importantly, nontrauma centers had the highest retriage rate to another acute care hospital (12.0%) compared to Level II centers (4.0%, P < 0.001). Conclusion: Time to stabilization of unstable injured patients can be predicted with EMR data.

摘要

背景

本研究旨在利用电子病历(EMR)数据预测低血压患者创伤复苏期间患者血流动力学稳定的时间。

方法

本观察性队列研究利用了由一级、二级和非创伤中心组成的九个医院学术系统的 EMR 数据。从 2015 年至 2020 年,确定了受伤、血流动力学不稳定(初始收缩压<90mmHg)的急诊就诊。稳定定义为记录到随后的收缩压>90mmHg。我们使用患者、损伤、治疗、EPIC 创伤叙述者以及前 4 小时护理中的医院特征,通过随机森林、梯度提升和集成来预测稳定时间测试。

结果

在 177127 次就诊中,有 1347 次(0.8%)到达时血流动力学不稳定;168 次(12.5%)就诊于一级创伤中心,853 次(63.3%)就诊于二级,326 次(24.2%)就诊于非创伤中心。其中,747 次(55.5%)通过中位数为 50 分钟(四分位距,21-101 分钟)的治疗得到稳定。一级不稳定患者就诊中 94.6%稳定,二级为 57.6%,非创伤中心为 29.8%(P<0.001)。稳定时间的预测准确率为 0.80。最具预测性的特征是 EPIC 创伤叙述者的措施、记录的患者到达、提供者检查和处置决策。一级的院内死亡率最高,为 3.0%,二级为 1.2%,非创伤中心为 0.3%(P<0.001)。重要的是,非创伤中心与二级中心相比(4.0%,P<0.001),再分诊到另一家急性护理医院的比例最高(12.0%)。

结论

利用 EMR 数据可以预测不稳定受伤患者的稳定时间。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验