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Latent Class Analysis Reveals COVID-19-related Acute Respiratory Distress Syndrome Subgroups with Differential Responses to Corticosteroids.
American Journal of Respiratory and Critical Care Medicine ( IF 19.3 ) Pub Date : 2021-12-01 , DOI: 10.1164/rccm.202105-1302oc
Pratik Sinha 1 , David Furfaro 2 , Matthew J Cummings 2 , Darryl Abrams 2 , Kevin Delucchi 3 , Manoj V Maddali 4 , June He 1 , Alison Thompson 2 , Michael Murn 2 , John Fountain 5 , Amanda Rosen 5 , Shelief Y Robbins-Juarez 6 , Matthew A Adan 6 , Tejus Satish 6 , Mahesh Madhavan 7 , Aakriti Gupta 7 , Alexander K Lyashchenko 8 , Cara Agerstrand 2 , Natalie H Yip 2 , Kristin M Burkart 2 , Jeremy R Beitler 2 , Matthew R Baldwin 2 , Carolyn S Calfee 9, 10, 11 , Daniel Brodie 2 , Max R O'Donnell 2, 12
Affiliation  

Rationale: Two distinct subphenotypes have been identified in acute respiratory distress syndrome (ARDS), but the presence of subgroups in ARDS associated with coronavirus disease (COVID-19) is unknown. Objectives: To identify clinically relevant, novel subgroups in COVID-19-related ARDS and compare them with previously described ARDS subphenotypes. Methods: Eligible participants were adults with COVID-19 and ARDS at Columbia University Irving Medical Center. Latent class analysis was used to identify subgroups with baseline clinical, respiratory, and laboratory data serving as partitioning variables. A previously developed machine learning model was used to classify patients as the hypoinflammatory and hyperinflammatory subphenotypes. Baseline characteristics and clinical outcomes were compared between subgroups. Heterogeneity of treatment effect for corticosteroid use in subgroups was tested. Measurements and Main Results: From March 2, 2020, to April 30, 2020, 483 patients with COVID-19-related ARDS met study criteria. A two-class latent class analysis model best fit the population (P = 0.0075). Class 2 (23%) had higher proinflammatory markers, troponin, creatinine, and lactate, lower bicarbonate, and lower blood pressure than class 1 (77%). Ninety-day mortality was higher in class 2 versus class 1 (75% vs. 48%; P < 0.0001). Considerable overlap was observed between these subgroups and ARDS subphenotypes. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RT-PCR cycle threshold was associated with mortality in the hypoinflammatory but not the hyperinflammatory phenotype. Heterogeneity of treatment effect to corticosteroids was observed (P = 0.0295), with improved mortality in the hyperinflammatory phenotype and worse mortality in the hypoinflammatory phenotype, with the caveat that corticosteroid treatment was not randomized. Conclusions: We identified two COVID-19-related ARDS subgroups with differential outcomes, similar to previously described ARDS subphenotypes. SARS-CoV-2 PCR cycle threshold had differential value for predicting mortality in the subphenotypes. The subphenotypes had differential treatment responses to corticosteroids.

中文翻译:

潜在类别分析揭示了 COVID-19 相关的急性呼吸窘迫综合征亚组对皮质类固醇的不同反应。

理由:在急性呼吸窘迫综合征 (ARDS) 中已发现两种不同的亚表型,但与冠状病毒病 (COVID-19) 相关的 ARDS 中是否存在亚组尚不清楚。目的:确定 COVID-19 相关 ARDS 中临床相关的新亚组,并将其与先前描述的 ARDS 亚表型进行比较。方法:符合条件的参与者是哥伦比亚大学欧文医学中心患有 COVID-19 和 ARDS 的成年人。潜在类别分析用于识别具有基线临床、呼吸和实验室数据作为划分变量的亚组。先前开发的机器学习模型用于将患者分类为低炎症和高炎症亚表型。比较亚组之间的基线特征和临床结果。测试了亚组中使用皮质类固醇的治疗效果的异质性。测量和主要结果:从 2020 年 3 月 2 日到 2020 年 4 月 30 日,483 名 COVID-19 相关 ARDS 患者符合研究标准。两类潜在类分析模型最适合人群 (P = 0.0075)。与 1 级 (77%) 相比,2 级 (23%) 具有更高的促炎标志物、肌钙蛋白、肌酐和乳酸、更低的碳酸氢盐和更低的血压。2 级的 90 天死亡率高于 1 级(75% 对 48%;P < 0.0001)。在这些亚组和 ARDS 亚表型之间观察到相当大的重叠。严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) RT-PCR 循环阈值与低炎症死亡率相关,但与高炎症表型无关。观察到皮质类固醇治疗效果的异质性(P = 0.0295),高炎症表型死亡率提高,低炎症表型死亡率降低,但需要注意的是皮质类固醇治疗不是随机的。结论:我们确定了两个与 COVID-19 相关的 ARDS 亚组,其结果不同,类似于之前描述的 ARDS 亚表型。SARS-CoV-2 PCR 循环阈值在预测亚表型死亡率方面具有不同的价值。亚表型对皮质类固醇有不同的治疗反应。类似于先前描述的 ARDS 亚表型。SARS-CoV-2 PCR 循环阈值在预测亚表型死亡率方面具有不同的价值。亚表型对皮质类固醇有不同的治疗反应。类似于先前描述的 ARDS 亚表型。SARS-CoV-2 PCR 循环阈值在预测亚表型死亡率方面具有不同的价值。亚表型对皮质类固醇有不同的治疗反应。
更新日期:2021-09-20
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