The value of vital sign trends for detecting clinical deterioration on the wards
The value of vital sign trends for detecting clinical deterioration on the wards
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DOI：
10.1016/j.resuscitation.2016.02.005
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发表时间：
2016-05-01
期刊：
影响因子：
6.5
通讯作者：
Edelson, Dana P.
中科院分区：
文献类型：
--
作者：
Churpek, Matthew M.;Adhikari, Richa;Edelson, Dana P.
目的：及早发现病房临床恶化可能会改善结果，并且大多数早期预警评分仅利用患者当前的生命体征。随着时间的推移，生命体征趋势的附加价值很难被描述。我们调查了添加趋势是否可以提高准确性以及哪些方法最适合对趋势进行建模。方法：这项观察性队列研究纳入了五年内入住五家医院的患者，其中 60% 的数据用于模型推导，40% 用于验证。利用生命体征来预测心脏骤停、重症监护病房转移和死亡的综合结果。使用受试者工作特征曲线下面积 (AUC) 比较使用当前值和不同趋势方法的模型的准确性。结果：总共纳入了 269,999 名入院患者，得出 16,452 个结果。总体而言，与仅包含当前生命体征的模型相比，趋势提高了准确性（AUC 0.78 vs. 0.74；p < 0.001）。导致准确率平均提高最大的方法是生命体征斜率（AUC 改善 0.013）和最小值（AUC 改善 0.012），而与之前值的变化导致 AUC 平均恶化（AUC 变化 - 0.002）。添加趋势后，收缩压的 AUC 增加最多（AUC 改善 0.05）。结论：生命体征趋势提高了旨在检测病房危重疾病的模型的准确性。我们的研究结果对床边的临床医生和早期预警评分的制定具有重要意义。 (C) 2016 Elsevier Ireland Ltd. 保留所有权利。
Aim: Early detection of clinical deterioration on the wards may improve outcomes, and most early warning scores only utilize a patient's current vital signs. The added value of vital sign trends over time is poorly characterized. We investigated whether adding trends improves accuracy and which methods are optimal for modelling trends.Methods: Patients admitted to five hospitals over a five-year period were included in this observational cohort study, with 60% of the data used for model derivation and 40% for validation. Vital signs were utilized to predict the combined outcome of cardiac arrest, intensive care unit transfer, and death. The accuracy of models utilizing both the current value and different trend methods were compared using the area under the receiver operating characteristic curve (AUC).Results: A total of 269,999 patient admissions were included, which resulted in 16,452 outcomes. Overall, trends increased accuracy compared to a model containing only current vital signs (AUC 0.78 vs. 0.74; p < 0.001). The methods that resulted in the greatest average increase in accuracy were the vital sign slope (AUC improvement 0.013) and minimum value (AUC improvement 0.012), while the change from the previous value resulted in an average worsening of the AUC (change in AUC - 0.002). The AUC increased most for systolic blood pressure when trends were added (AUC improvement 0.05).Conclusion: Vital sign trends increased the accuracy of models designed to detect critical illness on the wards. Our findings have important implications for clinicians at the bedside and for the development of early warning scores. (C) 2016 Elsevier Ireland Ltd. All rights reserved.