Latent Class Analysis Reveals COVID-19-related Acute Respiratory Distress Syndrome Subgroups with Differential Responses to Corticosteroids

Abstract

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.

Keywords: ARDS; COVID-19; latent class analysis; phenotyping.

Figure 1.

Standardized values for continuous class-defining variables used in the latent class models. The variables are sorted from left to right in descending order for the highest values in the hyperinflammatory subphenotype. Standardized values were calculated by assigning the mean of the variables as 0 and SD as 1. ALC = absolute lymphocyte count; APTT  = activated partial thromboplastin time; BMI = body mass index; CT = cycle threshold; LDH = lactate dehydrogenase; PBW = predicted body weight; PEEP = positive end-expiratory pressure; RR = respiratory rate; SBP = systolic blood pressure; VR = ventilatory ratio; WBC = white blood cell count.

Figure 2.

Alluvial plot showing the crossover between the COVID-19–related ARDS classes and the ARDS subphenotypes (percentages represent the proportion of patients from a given subgroup that redistributed to the alternative schema’s phenotypes). ARDS = acute respiratory distress syndrome; CARDS = COVID-19–related ARDS; COVID-19 = coronavirus disease.

Figure 3.

(A and B) Kaplan-Meier survival plots censored at Day 90 stratified by COVID-19–related ARDS classes (A) and ARDS subphenotypes (B). ARDS = acute respiratory distress syndrome; CARDS = COVID-19–related ARDS; COVID-19 = coronavirus disease.

Figure 4.

Top 10 most important variables in the XGBoost COVID-19–related ARDS mortality predictor model. ARDS = acute respiratory distress syndrome; BMI = body mass index; COVID-19 = coronavirus disease; CRP=C-reactive protein; CT = cycle threshold; INR = international normalized ratio.

Figure 5.

(A and B) Boxplot of the distribution of PCR cycle threshold stratified by mortality at Day 90 in the hypoinflammatory (A) and hyperinflammatory (B) phenotypes. P value represents the Student’s t test.