Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, Via Loredan 18, 35121, Padova, Italy.
ClinOpsHub s.r.l., Via Manfredi Svevo 30 B, 72023, Mesagne, Brindisi, Italy.
Syst Rev. 2023 Mar 15;12(1):44. doi: 10.1186/s13643-023-02211-7.
Extracorporeal membrane oxygenation (ECMO) has been increasingly used in the last years to provide hemodynamic and respiratory support in critically ill patients. In this scenario, prognostic scores remain essential to choose which patients should initiate ECMO. This systematic review aims to assess the current landscape and inform subsequent efforts in the development of risk prediction tools for ECMO.
PubMed, CINAHL, Embase, MEDLINE and Scopus were consulted. Articles between Jan 2011 and Feb 2022, including adults undergoing ECMO reporting a newly developed and validated predictive model for mortality, were included. Studies based on animal models, systematic reviews, case reports and conference abstracts were excluded. Data extraction aimed to capture study characteristics, risk model characteristics and model performance. The risk of bias was evaluated through the prediction model risk-of-bias assessment tool (PROBAST). The protocol has been registered in Open Science Framework ( https://osf.io/fevw5 ).
Twenty-six prognostic scores for in-hospital mortality were identified, with a study size ranging from 60 to 4557 patients. The most common candidate variables were age, lactate concentration, creatinine concentration, bilirubin concentration and days in mechanical ventilation prior to ECMO. Five out of 16 venous-arterial (VA)-ECMO scores and 3 out of 9 veno-venous (VV)-ECMO scores had been validated externally. Additionally, one score was developed for both VA and VV populations. No score was judged at low risk of bias.
Most models have not been validated externally and apply after ECMO initiation; thus, some uncertainty whether ECMO should be initiated still remains. It has yet to be determined whether and to what extent a new methodological perspective may enhance the performance of predictive models for ECMO, with the ultimate goal to implement a model that positively influences patient outcomes.
体外膜肺氧合（ECMO）在过去几年中越来越多地被用于为危重症患者提供血液动力学和呼吸支持。在这种情况下，预后评分仍然是选择应启动 ECMO 的患者的关键。本系统评价旨在评估当前的情况，并为随后开发 ECMO 风险预测工具的工作提供信息。
检索了 PubMed、CINAHL、Embase、MEDLINE 和 Scopus。纳入了 2011 年 1 月至 2022 年 2 月期间接受 ECMO 治疗并报告新开发和验证的死亡率预测模型的成人文章。排除了基于动物模型、系统评价、病例报告和会议摘要的研究。数据提取旨在捕获研究特征、风险模型特征和模型性能。通过预测模型风险偏倚评估工具（PROBAST）评估风险偏倚。该方案已在开放科学框架（https://osf.io/fevw5）上注册。
确定了 26 个用于院内死亡率的预后评分，研究规模从 60 例到 4557 例不等。最常见的候选变量是年龄、乳酸浓度、肌酐浓度、胆红素浓度和 ECMO 前机械通气天数。16 个静脉-动脉（VA）-ECMO 评分中的 5 个和 9 个静脉-静脉（VV）-ECMO 评分中的 3 个已在外部验证。此外，还有一个评分适用于 VA 和 VV 人群。没有一个评分被认为风险较低。
大多数模型尚未在外部验证，并且在 ECMO 启动后应用；因此，对于是否应该启动 ECMO，仍然存在一些不确定性。尚不清楚新的方法学观点是否以及在多大程度上可以提高 ECMO 预测模型的性能，最终目标是实施一个对患者预后产生积极影响的模型。
