Choudhary Tilendra, Upadhyaya Pulakesh, Davis Carolyn M, Yang Philip, Tallowin Simon, Lisboa Felipe A, Schobel Seth A, Coopersmith Craig M, Elster Eric A, Buchman Timothy G, Dente Christopher J, Kamaleswaran Rishikesan
Duke University School of Medicine.
Emory University School of Medicine.
Res Sq. 2024 Apr 30:rs.3.rs-4307475. doi: 10.21203/rs.3.rs-4307475/v1.
Septic patients who develop acute respiratory failure (ARF) requiring mechanical ventilation represent a heterogenous subgroup of critically ill patients with widely variable clinical characteristics. Identifying distinct phenotypes of these patients may reveal insights about the broader heterogeneity in the clinical course of sepsis. We aimed to derive novel phenotypes of sepsis-induced ARF using observational clinical data and investigate their generalizability across multi-ICU specialties, considering multi-organ dynamics.
We performed a multi-center retrospective study of ICU patients with sepsis who required mechanical ventilation for ≥24 hours. Data from two different high-volume academic hospital systems were used as a derivation set with N=3,225 medical ICU (MICU) patients and a validation set with N=848 MICU patients. For the multi-ICU validation, we utilized retrospective data from two surgical ICUs at the same hospitals (N=1,577). Clinical data from 24 hours preceding intubation was used to derive distinct phenotypes using an explainable machine learning-based clustering model interpreted by clinical experts.
Four distinct ARF phenotypes were identified: A (severe multi-organ dysfunction (MOD) with a high likelihood of kidney injury and heart failure), B (severe hypoxemic respiratory failure [median P/F=123]), C (mild hypoxia [median P/F=240]), and D (severe MOD with a high likelihood of hepatic injury, coagulopathy, and lactic acidosis). Patients in each phenotype showed differences in clinical course and mortality rates despite similarities in demographics and admission co-morbidities. The phenotypes were reproduced in external validation utilizing an external MICU from second hospital and SICUs from both centers. Kaplan-Meier analysis showed significant difference in 28-day mortality across the phenotypes (p<0.01) and consistent across both centers. The phenotypes demonstrated differences in treatment effects associated with high positive end-expiratory pressure (PEEP) strategy.
The phenotypes demonstrated unique patterns of organ injury and differences in clinical outcomes, which may help inform future research and clinical trial design for tailored management strategies.
发生急性呼吸衰竭(ARF)且需要机械通气的脓毒症患者是临床特征差异很大的危重症患者中的一个异质性亚组。识别这些患者的不同表型可能有助于深入了解脓毒症临床过程中更广泛的异质性。我们旨在利用观察性临床数据得出脓毒症诱导的ARF的新表型,并考虑多器官动态变化,研究其在多个重症监护病房(ICU)专科中的普遍性。
我们对需要机械通气≥24小时的脓毒症ICU患者进行了一项多中心回顾性研究。来自两个不同的高容量学术医院系统的数据被用作推导集,其中有3225例医学重症监护病房(MICU)患者,另有848例MICU患者作为验证集。对于多ICU验证,我们利用了同一医院两个外科ICU的回顾性数据(n = 1577)。使用由临床专家解释的基于可解释机器学习的聚类模型,将插管前24小时的临床数据用于得出不同的表型。
识别出四种不同的ARF表型:A(严重多器官功能障碍(MOD),有很高的肾损伤和心力衰竭可能性)、B(严重低氧性呼吸衰竭[中位P/F = 123])、C(轻度缺氧[中位P/F = 240])和D(严重MOD,有很高的肝损伤、凝血病和乳酸性酸中毒可能性)。尽管各表型患者在人口统计学和入院合并症方面相似,但临床过程和死亡率存在差异。这些表型在使用第二家医院的外部MICU和两个中心的外科ICU进行的外部验证中得到了重现。Kaplan-Meier分析显示各表型的28天死亡率存在显著差异(p<0.01),且在两个中心均一致。这些表型在与高呼气末正压(PEEP)策略相关的治疗效果方面存在差异。
这些表型显示出独特的器官损伤模式和临床结局差异,这可能有助于为未来针对个性化管理策略的研究和临床试验设计提供信息。