Effect of losartan on hospitalized patients with COVID-19-induced lung injury: A randomized clinical trial (preprint)

Background SARS-CoV-2 viral entry may disrupt angiotensin II (Ang II) homeostasis in part via ACE2 downregulation, potentially contributing to COVID-19 induced lung injury. Preclinical models of viral pneumonias that utilize ACE2 demonstrate Ang II type 1 receptor (AT1R) blockade mitigates lung injury, though observational COVID-19 data addressing the effect of AT1R blockade remain mixed. Methods Multicenter, blinded, placebo-controlled randomized trial of losartan (50 mg PO twice daily for 10 days) versus placebo. Hospitalized patients with COVID-19 and a respiratory sequential organ failure assessment score of at least 1 and not already taking a renin-angiotensin-aldosterone system (RAAS) inhibitor were eligible. The primary outcome was the imputed partial pressure of oxygen to fraction of inspired oxygen (PaO 2 /FiO 2 ) ratio at 7 days. Secondary outcomes included ordinal COVID-19 severity, oxygen, ventilator, and vasopressor-free days, and mortality. Losartan pharmacokinetics (PK) and RAAS components [Ang II, angiotensin-(1–7) (Ang-(1–7)), ACE, ACE2] were measured in a subgroup of participants. Findings From April 2020 - February 2021, 205 participants were randomized, 101 to losartan and 104 to placebo. Compared to placebo, losartan did not significantly affect PaO 2 /FiO 2 ratio at 7 days [difference of -24.8 (95% -55.6 to 6.1; p=0.12)]. Losartan did not improve any secondary clinical outcome, but worsened vasopressor-free days. PK data were consistent with appropriate steady-state concentrations, but we observed no significant effect of losartan on RAAS components. Interpretation Initiation of orally administered losartan to hospitalized patients with COVID-19 and acute lung injury does not improve PaO 2 / FiO 2 ratio at 7 days. These data may have implications for ongoing clinical trials. Trial Registration Losartan for Patients With COVID-19 Requiring Hospitalization ( NCT04312009 ), https://clinicaltrials.gov/ct2/show/NCT04312009

Characterizing COVID-19 Clinical Phenotypes and Associated Comorbidities and Complication Profiles (preprint)

Background: There is limited understanding of heterogeneity in outcomes across hospitalized patients with coronavirus disease 2019 (COVID-19). Identification of distinct clinical phenotypes may facilitate tailored therapy and improve outcomes. Objective: Identify specific clinical phenotypes across COVID-19 patients and compare admission characteristics and outcomes. Design, Settings, and Participants: Retrospective analysis of 1,022 COVID-19 patient admissions from 14 Midwest U.S. hospitals between March 7, 2020 and August 25, 2020. Methods: Ensemble clustering was performed on a set of 33 vitals and labs variables collected within 72 hours of admission. K-means based consensus clustering was used to identify three clinical phenotypes. Principal component analysis was performed on the average covariance matrix of all imputed datasets to visualize clustering and variable relationships. Multinomial regression models were fit to further compare patient comorbidities across phenotype classification. Multivariable models were fit to estimate the association between phenotype and in-hospital complications and clinical outcomes. Main outcomes and measures: Phenotype classification (I, II, III), patient characteristics associated with phenotype assignment, in-hospital complications, and clinical outcomes including ICU admission, need for mechanical ventilation, hospital length of stay, and mortality. Results: The database included 1,022 patients requiring hospital admission with COVID-19 (median age, 62.1 [IQR: 45.9-75.8] years; 481 [48.6%] male, 412 [40.3%] required ICU admission, 437 [46.7%] were white). Three clinical phenotypes were identified (I, II, III); 236 [23.1%] patients had phenotype I, 613 [60%] patients had phenotype II, and 173 [16.9%] patients had phenotype III. When grouping comorbidities by organ system, patients with respiratory comorbidities were most commonly characterized by phenotype III (p=0.002), while patients with hematologic (p<0.001), renal (p<0.001), and cardiac (p<0.001) comorbidities were most commonly characterized by phenotype I. The adjusted odds of respiratory (p<0.001), renal (p<0.001), and metabolic (p<0.001) complications were highest for patients with phenotype I, followed by phenotype II. Patients with phenotype I had a far greater odds of hepatic (p<0.001) and hematological (p=0.02) complications than the other two phenotypes. Phenotypes I and II were associated with 7.30-fold (HR: 7.30, 95% CI: (3.11-17.17), p<0.001) and 2.57-fold (HR: 2.57, 95% CI: (1.10-6.00), p=0.03) increases in the hazard of death, respectively, when compared to phenotype III. Conclusion: In this retrospective analysis of patients with COVID-19, three clinical phenotypes were identified. Future research is urgently needed to determine the utility of these phenotypes in clinical practice and trial design.