Universidade do Oeste de Santa Catarina (UNOESC), Joaçaba, SC, Brazil; Programa de Pós-Graduação em Biociências e Saúde/Universidade do Oeste de Santa Catarina, Brazil; Hospital Universitário Santa Terezinha, Joaçaba, SC, Brazil.
Universidade do Oeste de Santa Catarina (UNOESC), Joaçaba, SC, Brazil.
J Crit Care. 2018 Dec;48:56-62. doi: 10.1016/j.jcrc.2018.08.023. Epub 2018 Aug 20.
To identify, describe and discuss the parameters used to predict weaning from mechanical ventilation and extubation outcomes.
Systematic review of scientific articles using four electronic databases: PubMed, Embase, PEDro and Cochrane Library. Search terms included "weaning", "extubation", "withdrawal" and "discontinuation", combined with "mechanical ventilation" and "predictive factors", "predictive parameters" and "predictors for success". In this study, we included original articles that presented predictive factors for weaning or extubation outcomes in adult patients and not restricted to a single disease. Articles not written in English were excluded.
A total of 43 articles were included, with a total of 7929 patients and 56 different parameters related to weaning and extubation outcomes. Rapid Shallow Breathing Index (RSBI) was the most common predictor, discussed in 15 studies (2159 patients), followed by Age and Maximum Inspiratory Pressure in seven studies. The other 53 parameters were found in less than six studies.
There are several parameters used to predict weaning and extubation outcomes. RSBI was the most frequently studied and seems to be an important measurement tool in deciding whether to wean/extubate a patient. Furthermore, the results demonstrated that weaning and extubation should be guided by several parameters, and not only to respiratory ones.
识别、描述和讨论用于预测机械通气撤机和拔管结局的参数。
使用四个电子数据库(PubMed、Embase、PEDro 和 Cochrane Library)对科学文献进行系统评价。搜索词包括“撤机”、“拔管”、“退出”和“停止”,并与“机械通气”和“预测因素”、“预测参数”和“成功预测因子”相结合。在这项研究中,我们纳入了针对成人患者撤机或拔管结局的预测因素的原始文章,不限于单一疾病。排除非英文撰写的文章。
共纳入 43 篇文章,共 7929 名患者和 56 个与撤机和拔管结局相关的不同参数。快速浅呼吸指数(RSBI)是最常见的预测因子,在 15 项研究(2159 名患者)中进行了讨论,其次是年龄和最大吸气压力,在 7 项研究中进行了讨论。其他 53 个参数在不到 6 项研究中被发现。
有几个参数用于预测撤机和拔管结局。RSBI 是研究最多的,似乎是决定是否对患者进行撤机/拔管的重要测量工具。此外,研究结果表明,撤机和拔管应该由多个参数指导,而不仅仅是呼吸参数。