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使用连续单导联心电图分析来预测需要快速反应小组激活的患者病情恶化。

Use of a continuous single lead electrocardiogram analytic to predict patient deterioration requiring rapid response team activation.

作者信息

Lee Sooin, Benson Bryce, Belle Ashwin, Medlin Richard P, Jerkins David, Goss Foster, Khanna Ashish K, DeVita Michael A, Ward Kevin R

机构信息

Fifth Eye, Inc, Ann Arbor, Michigan, United States of America.

Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan, United States of America.

出版信息

PLOS Digit Health. 2024 Oct 24;3(10):e0000465. doi: 10.1371/journal.pdig.0000465. eCollection 2024 Oct.

DOI:10.1371/journal.pdig.0000465
PMID:39446712
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11500862/
Abstract

Identifying the onset of patient deterioration is challenging despite the potential to respond to patients earlier with better vital sign monitoring and rapid response team (RRT) activation. In this study an ECG based software as a medical device, the Analytic for Hemodynamic Instability Predictive Index (AHI-PI), was compared to the vital signs of heart rate, blood pressure, and respiratory rate, evaluating how early it indicated risk before an RRT activation. A higher proportion of the events had risk indication by AHI-PI (92.71%) than by vital signs (41.67%). AHI-PI indicated risk early, with an average of over a day before RRT events. In events whose risks were indicated by both AHI-PI and vital signs, AHI-PI demonstrated earlier recognition of deterioration compared to vital signs. A case-control study showed that situations requiring RRTs were more likely to have AHI-PI risk indication than those that did not. The study derived several insights in support of AHI-PI's efficacy as a clinical decision support system. The findings demonstrated AHI-PI's potential to serve as a reliable predictor of future RRT events. It could potentially help clinicians recognize early clinical deterioration and respond to those unnoticed by vital signs, thereby helping clinicians improve clinical outcomes.

摘要

尽管通过更好的生命体征监测和快速反应团队(RRT)激活有可能更早地对患者做出反应,但识别患者病情恶化的起始阶段仍具有挑战性。在本研究中,将一款基于心电图的软件作为一种医疗设备,即血流动力学不稳定预测指数分析软件(AHI-PI),与心率、血压和呼吸频率等生命体征进行了比较,评估其在RRT激活之前多早就能提示风险。与生命体征(41.67%)相比,AHI-PI提示风险的事件比例更高(92.71%)。AHI-PI能早期提示风险,平均在RRT事件发生前一天多。在AHI-PI和生命体征都提示风险的事件中,与生命体征相比,AHI-PI能更早地识别病情恶化。一项病例对照研究表明,需要RRT的情况比不需要的情况更有可能出现AHI-PI风险提示。该研究得出了一些见解,支持AHI-PI作为临床决策支持系统的有效性。研究结果表明AHI-PI有潜力作为未来RRT事件的可靠预测指标。它可能有助于临床医生识别早期临床恶化情况,并对那些生命体征未察觉的情况做出反应,从而帮助临床医生改善临床结果。

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