Corticosteroids for infectious critical illness: A multicenter target trial emulation stratified by predicted organ dysfunction trajectory

Suraj Rajendran, Zhenxing Xu, Weishen Pan, Chengxi Zang, Ilias Siempos, Lisa K Torres, Jie Xu, Jiang Bian, Edward J Schenck, Fei Wang
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Abstract

Corticosteroids decrease the duration of organ dysfunction in a range of infectious critical illnesses, but their risk and benefit are not fully defined using this construct. This retrospective multicenter study aimed to evaluate the association between usage of corticosteroids and mortality of patients with infectious critical illness by emulating a target trial framework. The study employed a novel stratification method with predictive machine learning (ML) subphenotyping based on organ dysfunction trajectory. Our analysis revealed that corticosteroids' effectiveness varied depending on the stratification method. The ML-based approach identified four distinct subphenotypes, two of which had a large enough sample size in our patient cohorts for further evaluation: "Rapidly Improving" (RI) and "Rapidly Worsening," (RW) which showed divergent responses to corticosteroid treatment. Specifically, the RW group either benefited or were not harmed from corticosteroids, whereas the RI group appeared to derive harm. In the development cohort, which comprised of a combination of patients from the eICU and MIMIC-IV datasets, hazard ratio estimates for the primary outcome, 28-day mortality, in the RW group was 1.05 (95% CI: 0.96 - 1.04) whereas for the RW group, it was 1.40 (95% CI: 1.28 - 1.54). For the validation cohort, which comprised of patients from the Critical carE Database for Advanced Research, estimates for 28-day mortality for the RW and RI groups were 1.24 (95% CI: 1.05 - 1.46) and 1.34 (95% CI: 1.14 - 1.59), respectively. For secondary outcomes, the RW group had a shorter time to ICU discharge and time to cessation of mechanical ventilation with corticosteroid treatment, where the RI group again demonstrated harm. The findings support matching treatment strategies to empirically observed pathobiology and offer a more nuanced understanding of corticosteroid utility. Our results have implications for the design and interpretation of both observational studies and randomized controlled trials (RCTs), suggesting the need for stratification methods that account for the differential response to standard of care.
皮质类固醇治疗感染性危重症:根据预测的器官功能障碍轨迹进行分层的多中心目标试验模拟
皮质类固醇可缩短一系列感染性危重症患者器官功能障碍的持续时间,但其风险和益处并没有在这一概念中得到充分定义。这项多中心回顾性研究旨在通过模仿目标试验框架,评估皮质类固醇的使用与感染性危重症患者死亡率之间的关联。研究采用了一种新颖的分层方法,根据器官功能障碍轨迹进行预测性机器学习(ML)亚表型。我们的分析表明,皮质类固醇的效果因分层方法而异。基于 ML 的方法确定了四种不同的亚型,其中两种在我们的患者队列中具有足够大的样本量,可供进一步评估:"快速改善 "组(RI)和 "快速恶化 "组(RW)对皮质类固醇治疗的反应各不相同。具体来说,RW 组从皮质类固醇治疗中获益或无害,而 RI 组似乎受到了伤害。开发队列由来自 eICU 和 MIMIC-IV 数据集的患者组合而成,在开发队列中,RW 组主要结果(28 天死亡率)的危险比估计值为 1.05(95% CI:0.96 - 1.04),而 RW 组为 1.40(95% CI:1.28 - 1.54)。在验证队列(由危重症高级研究数据库的患者组成)中,RW 组和 RI 组的 28 天死亡率分别为 1.24(95% CI:1.05 - 1.46)和 1.34(95% CI:1.14 - 1.59)。在次要结果方面,RW 组的 ICU 出院时间和使用皮质类固醇治疗后停止机械通气的时间更短,而 RI 组再次显示出伤害性。这些研究结果支持将治疗策略与经验观察到的病理生物学相匹配,并使人们对皮质类固醇的作用有了更细致的了解。我们的研究结果对观察性研究和随机对照试验(RCT)的设计和解释都有影响,表明有必要采用分层方法来考虑对标准治疗的不同反应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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