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追踪与触发系统及国家早期预警评分的局限性。第1部分：争议领域。

Limitations of track and trigger systems and the National Early Warning Score. Part 1: areas of contention.

作者信息

Grant Steven

机构信息

Senior Lecturer, Birmingham City University.

出版信息

Br J Nurs. 2018 Jun 14;27(11):624-631. doi: 10.12968/bjon.2018.27.11.624.

DOI:10.12968/bjon.2018.27.11.624
PMID:29894258
Abstract

Evidence suggests that the identification and response to the deteriorating patient continues to be an ongoing concern, despite the widespread use of track and trigger score (TTS) systems. This article discusses the variations in the parameters included in the different TTS systems in use across the NHS and their sensitivity. Clinical guidelines and physiological theory are used to appraise the parameters allocated in the National Early Warning Score (NEWS 1 and 2), highlighting potential limitations of the tool. The findings lead to the conclusion that registered nurses should not rely solely on NEWS, but should use it to support their clinical judgement.

摘要

有证据表明，尽管轨迹与触发评分（TTS）系统已广泛应用，但对病情恶化患者的识别与应对仍是一个持续存在的问题。本文讨论了英国国家医疗服务体系（NHS）中使用的不同TTS系统所包含参数的差异及其敏感性。运用临床指南和生理学理论对国家早期预警评分（NEWS 1和2）中的参数进行评估，突出该工具的潜在局限性。研究结果得出结论，注册护士不应仅依赖NEWS，而应利用它来支持其临床判断。

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Br J Nurs. 2018 Jun 14;27(11):624-631. doi: 10.12968/bjon.2018.27.11.624.
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Explainable machine learning for real-time deterioration alert prediction to guide pre-emptive treatment.可解释机器学习在实时恶化预警预测中的应用，以指导预防性治疗。
Sci Rep. 2022 Jul 11;12(1):11734. doi: 10.1038/s41598-022-15877-1.
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