COVID-19 subphenotypes at hospital admission are associated with mortality: a cross-sectional study

Abstract

Background: We have an incomplete understanding of COVID-19 characteristics at hospital presentation and whether underlying subphenotypes are associated with clinical outcomes and therapeutic responses.

Methods: For this cross-sectional study, we extracted electronic health data from adults hospitalized between 1 March and 30 August 2020 with a PCR-confirmed diagnosis of COVID-19 at five New York City Hospitals. We obtained clinical and laboratory data from the first 24 h of the patient's hospitalization. Treatment with tocilizumab and convalescent plasma was assessed over hospitalization. The primary outcome was mortality; secondary outcomes included intubation, intensive care unit (ICU) admission and length of stay (LOS). First, we employed latent class analysis (LCA) to identify COVID-19 subphenotypes on admission without consideration of outcomes and assigned each patient to a subphenotype. We then performed robust Poisson regression to examine associations between COVID-19 subphenotype assignment and outcome. We explored whether the COVID-19 subphenotypes had a differential response to tocilizumab and convalescent plasma therapies.

Results: A total of 4620 patients were included. LCA identified six subphenotypes, which were distinct by level of inflammation, clinical and laboratory derangements and ranged from a hypoinflammatory subphenotype with the fewest derangements to a hyperinflammatory with multiorgan dysfunction subphenotypes. Multivariable regression analyses found differences in risk for mortality, intubation, ICU admission and LOS, as compared to the hypoinflammatory subphenotype. For example, in multivariable analyses the moderate inflammation with fever subphenotype had 3.29 times the risk of mortality (95% CI 2.05, 5.28), while the hyperinflammatory with multiorgan failure subphenotype had 17.87 times the risk of mortality (95% CI 11.56, 27.63), as compared to the hypoinflammatory subphenotype. Exploratory analyses suggested that subphenotypes may differential respond to convalescent plasma or tocilizumab therapy.

Conclusion: COVID-19 subphenotype at hospital admission may predict risk for mortality, ICU admission and intubation and differential response to treatment.KEY MESSAGEThis cross-sectional study of COVID patients admitted to the Mount Sinai Health System, identified six distinct COVID subphenotypes on admission. Subphenotypes correlated with ICU admission, intubation, mortality and differential response to treatment.

Keywords: COVID-19; SARS CoV-2 infection; mortality; subphenotypes.

Figure 1.

Distribution of clinical and laboratory variables on admission amongst the six COVID-19 subphenotypes. Clinical and laboratory variables on admission normalized and divided into quintiles. Latent class analysis identified six underlying COVID-19 subphenotypes which were notable for varying levels of inflammation, vital sign abnormalities and/or organ dysfunction. T max: maximum temperature; O2 Sat min: minimum oxygen saturation; HR max: maximum heart rate; SBP min: minimum systolic blood pressure; DBP min: minimum diastolic blood pressure; Na: sodium; K: potassium; Ca: calcium; HCO3: bicarbonate; BUN: blood urea nitrogen; Cr: creatinine; BNP: brain natriuretic peptide; WBC: white blood cell count; Hgb: hemoglobin; Plt: platelet count; PT: prothrombin time; PTT: partial thromboplastin time; AST: aspartate aminotransferase; ALT: alanine transaminase; T bili: total bilirubin; IL-6: interleukin 6; IL-1B: interleukin 1B; LDH: lactate dehydrogenase; CRP: c-reactive protein; ESR: erythrocyte sedimentation rate; Procal: procalcitonin.

Figure 2.

Associations between COVID-19 subphenotype and (A) mortality; (B) intubation; (C) intensive care unit (ICU) admission; and (D) length of stay amongst survivors. Robust Poisson regression to determine the relative risk of outcomes by subphenotype as compared to hypoinflammatory subphenotype where circles represent estimate and bars represent 95% confidence intervals. Multivariable model (shown here) adjusted for onset time, hospital, self-identified race/ethnicity and insurance provider. Hypoinflam.: Hypoinflammatory; Mod inflam. Fever: Moderate inflammation with fever; Hyperinflam. Liver dysfunc.: Hyperinflammatory with liver dysfunction; Mod inflam. Coagulopathy: Moderate inflammation with coagulopathy; Hyperinflam. Renal dysfunc: Hyperinflammatory with renal dysfunction; Hyperinflam. Multiorgan dysfunc.: Hyperinflammatory with multiorgan dysfunction.

Figure 3.

Risk of dying by subphenotype in those who did (blue bars) and did not (red bars) receive convalescent plasma. Robust Poisson regression models adjusted for onset time, hospital, self-identified race/ethnicity and insurance provider stratified by receiving convalescent plasma versus not. P-interaction terms generated by robust Poisson multivariable regression with introduction of an interaction term. P-interaction terms of less than 0.10 are shown. Hypoinflam.: Hypoinflammatory; Mod inflam. Fever: Moderate inflammation with fever; Hyperinflam. Liver dysfunc.: Hyperinflammatory with liver dysfunction; Mod inflam. Coagulopathy: Moderate inflammation with coagulopathy; Hyperinflam. Renal dysfunc: Hyperinflammatory with renal dysfunction; Hyperinflam. Multiorgan dysfunc.: Hyperinflammatory with multiorgan dysfunction. Number at risk per subphenotype (those who received convalescent plasma/those who did not): Hypoinflammatory (2/19), Moderate inflammation, fever (10/82), Hyperinflammatory, liver dysfunction (18/179), Moderate inflammation, coagulopathy (25/253), Hyperinflammatory, renal dysfunction (11/186), Hyperinflammatory multiorgan dysfunction (27/530).

Figure 4.

Risk of dying by subphenotype in those who did (blue bars) and did not (red bars) receive tocilizumab. Robust Poisson regression models adjusted for onset time, hospital, self-identified race/ethnicity and insurance provider stratified by receiving tocilizumab versus not. P-interaction terms generated by robust Poisson multivariable regression with introduction of an interaction term. P-interaction terms of less than 0.10 are shown. Hypoinflam.: Hypoinflammatory. Mod inflam. Fever: Moderate inflammation with fever; Hyperinflam. Liver dysfunc.: Hyperinflammatory with liver dysfunction; Mod inflam. Coagulopathy: Moderate inflammation with coagulopathy; Hyperinflam. Renal dysfunc: Hyperinflammatory with renal dysfunction; Hyperinflam. Multiorgan dysfunc.: Hyperinflammatory with multiorgan dysfunction. Number at risk per subphenotype (those who received tocilizumab/those who did not): Hypoinflammatory (1/20), Moderate inflammation, fever (14/78), Hyperinflammatory, liver dysfunction (37/160), Moderate inflammation, coagulopathy (26/252), Hyperinflammatory, renal dysfunction (6/191), Hyperinflammatory multiorgan dysfunction (34/523).