Department of Critical Care, NHS Greater Glasgow and Clyde, Glasgow Royal Infirmary, Glasgow, UK.
School of Informatics, University of Edinburgh, Edinburgh, UK.
Anaesthesia. 2024 Jun;79(6):638-649. doi: 10.1111/anae.16222. Epub 2024 Feb 1.
The planned withdrawal of life-sustaining treatment is a common practice in the intensive care unit for patients where ongoing organ support is recognised to be futile. Predicting the time to asystole following withdrawal of life-sustaining treatment is crucial for setting expectations, resource utilisation and identifying patients suitable for organ donation after circulatory death. This systematic review evaluates the literature for variables associated with, and predictive models for, time to asystole in patients managed on intensive care units. We conducted a comprehensive structured search of the MEDLINE and Embase databases. Studies evaluating patients managed on adult intensive care units undergoing withdrawal of life-sustaining treatment with recorded time to asystole were included. Data extraction and PROBAST quality assessment were performed and a narrative summary of the literature was provided. Twenty-three studies (7387 patients) met the inclusion criteria. Variables associated with imminent asystole (<60 min) included: deteriorating oxygenation; absence of corneal reflexes; absence of a cough reflex; blood pressure; use of vasopressors; and use of comfort medications. We identified a total of 20 unique predictive models using a wide range of variables and techniques. Many of these models also underwent secondary validation in further studies or were adapted to develop new models. This review identifies variables associated with time to asystole following withdrawal of life-sustaining treatment and summarises existing predictive models. Although several predictive models have been developed, their generalisability and performance varied. Further research and validation are needed to improve the accuracy and widespread adoption of predictive models for patients managed in intensive care units who may be eligible to donate organs following their diagnosis of death by circulatory criteria.
计划终止生命支持治疗是重症监护病房中常见的做法,对于持续器官支持被认为是无效的患者。预测停止生命支持治疗后发生心搏骤停的时间对于设定预期、资源利用和确定适合循环死亡后器官捐献的患者至关重要。本系统评价评估了与重症监护病房管理的患者心搏骤停时间相关的文献和预测模型。我们对 MEDLINE 和 Embase 数据库进行了全面的结构化搜索。纳入了评估在成人重症监护病房接受生命支持治疗停止并记录心搏骤停时间的患者的研究。进行了数据提取和 PROBAST 质量评估,并提供了文献的叙述性总结。23 项研究(7387 名患者)符合纳入标准。与即将发生的心搏骤停(<60 分钟)相关的变量包括:氧合恶化;角膜反射消失;咳嗽反射消失;血压;使用升压药;使用舒适药物。我们总共确定了 20 个使用广泛变量和技术的独特预测模型。这些模型中的许多也在进一步的研究中进行了二次验证,或者被改编以开发新的模型。本综述确定了与停止生命支持治疗后心搏骤停时间相关的变量,并总结了现有的预测模型。尽管已经开发了几种预测模型,但它们的通用性和性能各不相同。需要进一步的研究和验证,以提高适用于可能符合循环标准诊断死亡后有资格捐献器官的重症监护病房患者的预测模型的准确性和广泛应用。