Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19.

RATIONALE & OBJECTIVE: Patients hospitalized with COVID-19 are at increased risk for major adverse kidney events (MAKE). We sought to identify plasma biomarkers predictive of MAKE in patients hospitalized with COVID-19. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: A total of 576 patients hospitalized with COVID-19 between March 2020 and January 2021 across 3 academic medical centers. EXPOSURE: Twenty-six plasma biomarkers of injury, inflammation, and repair from first available blood samples collected during hospitalization. OUTCOME: MAKE, defined as KDIGO stage 3 acute kidney injury (AKI), dialysis-requiring AKI, or mortality up to 60 days. ANALYTICAL APPROACH: Cox proportional hazards regression to associate biomarker level with MAKE. We additionally applied the least absolute shrinkage and selection operator (LASSO) and random forest regression for prediction modeling and estimated model discrimination with time-varying C index. RESULTS: The median length of stay for COVID-19 hospitalization was 9 (IQR, 5-16) days. In total, 95 patients (16%) experienced MAKE. Each 1 SD increase in soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 was significantly associated with an increased risk of MAKE (adjusted HR [AHR], 2.30 [95% CI, 1.86-2.85], and AHR, 2.26 [95% CI, 1.73-2.95], respectively). The C index of sTNFR1 alone was 0.80 (95% CI, 0.78-0.84), and the C index of sTNFR2 was 0.81 (95% CI, 0.77-0.84). LASSO and random forest regression modeling using all biomarkers yielded C indexes of 0.86 (95% CI, 0.83-0.89) and 0.84 (95% CI, 0.78-0.91), respectively. LIMITATIONS: No control group of hospitalized patients without COVID-19. CONCLUSIONS: We found that sTNFR1 and sTNFR2 are independently associated with MAKE in patients hospitalized with COVID-19 and can both also serve as predictors for adverse kidney outcomes. PLAIN-LANGUAGE SUMMARY: Patients hospitalized with COVID-19 are at increased risk for long-term adverse health outcomes, but not all patients suffer long-term kidney dysfunction. Identification of patients with COVID-19 who are at high risk for adverse kidney events may have important implications in terms of nephrology follow-up and patient counseling. In this study, we found that the plasma biomarkers soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 measured in hospitalized patients with COVID-19 were associated with a greater risk of adverse kidney outcomes. Along with clinical variables previously shown to predict adverse kidney events in patients with COVID-19, both sTNFR1 and sTNFR2 are also strong predictors of adverse kidney outcomes.

Geographic and Temporal Trends in COVID-Associated Acute Kidney Injury in the National COVID Cohort Collaborative.

BACKGROUND: AKI is associated with mortality in patients hospitalized with coronavirus disease 2019 (COVID-19); however, its incidence, geographic distribution, and temporal trends since the start of the pandemic are understudied. METHODS: Electronic health record data were obtained from 53 health systems in the United States in the National COVID Cohort Collaborative. We selected hospitalized adults diagnosed with COVID-19 between March 6, 2020, and January 6, 2022. AKI was determined with serum creatinine and diagnosis codes. Time was divided into 16-week periods (P1-6) and geographical regions into Northeast, Midwest, South, and West. Multivariable models were used to analyze the risk factors for AKI or mortality. RESULTS: Of a total cohort of 336,473, 129,176 (38%) patients had AKI. Fifty-six thousand three hundred and twenty-two (17%) lacked a diagnosis code but had AKI based on the change in serum creatinine. Similar to patients coded for AKI, these patients had higher mortality compared with those without AKI. The incidence of AKI was highest in P1 (47%; 23,097/48,947), lower in P2 (37%; 12,102/32,513), and relatively stable thereafter. Compared with the Midwest, the Northeast, South, and West had higher adjusted odds of AKI in P1. Subsequently, the South and West regions continued to have the highest relative AKI odds. In multivariable models, AKI defined by either serum creatinine or diagnostic code and the severity of AKI was associated with mortality. CONCLUSIONS: The incidence and distribution of COVID-19-associated AKI changed since the first wave of the pandemic in the United States.

COVID-19 and the Kidney: Recent Advances and Controversies.

Kidney involvement is common in coronavirus disease-2019 (COVID-19), and our understanding of the effects of COVID-19 on short- and long-term kidney outcomes has evolved over the course of the pandemic. Initial key questions centered on the spectrum and degree of acute kidney injury (AKI) in patients hospitalized with severe COVID-19. Investigators worldwide have explored the association between COVID-19-associated AKI and short-term outcomes, including inpatient mortality and disease severity. Even as treatments evolved, vaccinations were developed, and newer viral variants arose, subsets of patients were identified as at continued high risk for major adverse kidney outcomes. In this review, we explore key topics of continued relevance including the following: (1) a comparison of COVID-19-associated AKI with AKI developing in other clinical settings; (2) the ongoing controversy over kidney tropism in the setting of COVID-19 and the potential for competitive binding of the severe acute respiratory syndrome coronavirus 2 virus with angiotensin converting enzyme-2 to prevent viral cell entry; and (3) the identification of high-risk patients for adverse outcomes to inform long-term outpatient management. Patients at particularly high risk for adverse kidney outcomes include those with APOL1 high-risk genotype status. Biomarkers of injury, inflammation, tubular health, and repair measured in both the blood and urine may hold prognostic significance.

COVID-19 and the Kidney: Recent Advances and Controversies

Kidney involvement is common in COVID-19, and our understanding of the effects of COVID-19 on short- and long-term kidney outcomes has evolved over the course of the pandemic. Initial key questions centered on the spectrum and degree of acute kidney injury (AKI) in patients hospitalized with severe COVID-19. Investigators worldwide explored the association between COVID-19–associated AKI and short-term outcomes, including inpatient mortality and disease severity. Even as treatments evolved, vaccinations were developed, and newer viral variants arose, subsets of patients were identified as at continued high risk for major adverse kidney outcomes. In this review, we explore key topics of continued relevance including: 1) a comparison of COVID-19–associated AKI with AKI developing in other clinical settings;2) the ongoing controversy over kidney tropism in the setting of COVID-19 and the potential for competitive binding of the SARS-CoV-2 virus with ACE2 to prevent viral cell entry;and 3) the identification of high-risk patients for adverse outcomes in order to inform long-term outpatient management. Patients at particularly high risk for adverse kidney outcomes include those with APOL1 high-risk genotype status, and biomarkers of injury, inflammation, and tubular health and repair measured in both the blood and urine may hold prognostic significance.

Protocol for Local On-Site Dialysate Production for Continuous Renal Replacement Therapy during the COVID-19 Pandemic.

AKI frequently occurs in patients with COVID-19, and kidney injury severe enough to require RRT is a common complication among patients who are critically ill. During the surge of the pandemic, there was a high demand for dialysate for continuous RRT, and this increase in demand, coupled with vulnerabilities in the supply chain, necessitated alternative approaches, including internal production of dialysate. Using a standard hemodialysis machine and off-the-shelf supplies, as per Food and Drug Administration guidelines, we developed a method for on-site dialysate production that is adaptable and can be used to fill multiple bags at once. The use of a central reverse osmosis unit, dedicated hemodialysis machine, sterile bags with separate ports for fill and use, and frequent testing will ensure stability, sterility, and-therefore-safety of the produced dialysate. The dialysate made in house was tested and it showed both stability and sterility for at least 30 hours. This detailed description of our process for generating dialysate can serve as a guide for other programs experiencing similar vulnerabilities in the demand versus supply of dialysate.

Endothelial thrombomodulin downregulation caused by hypoxia contributes to severe infiltration and coagulopathy in COVID-19 patient lungs.

BACKGROUND: Thromboembolism is a life-threatening manifestation of coronavirus disease 2019 (COVID-19). We investigated a dysfunctional phenotype of vascular endothelial cells in the lungs during COVID-19. METHODS: We obtained the lung specimens from the patients who died of COVID-19. The phenotype of endothelial cells and immune cells was examined by flow cytometry and immunohistochemistry (IHC) analysis. We tested the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the endothelium using IHC and electron microscopy. FINDINGS: The autopsy lungs of COVID-19 patients exhibited severe coagulation abnormalities, immune cell infiltration, and platelet activation. Pulmonary endothelial cells of COVID-19 patients showed increased expression of procoagulant von Willebrand factor (VWF) and decreased expression of anticoagulants thrombomodulin and endothelial protein C receptor (EPCR). In the autopsy lungs of COVID-19 patients, the number of macrophages, monocytes, and T cells was increased, showing an activated phenotype. Despite increased immune cells, adhesion molecules such as ICAM-1, VCAM-1, E-selectin, and P-selectin were downregulated in pulmonary endothelial cells of COVID-19 patients. Notably, decreased thrombomodulin expression in endothelial cells was associated with increased immune cell infiltration in the COVID-19 patient lungs. There were no SARS-CoV-2 particles detected in the lung endothelium of COVID-19 patients despite their dysfunctional phenotype. Meanwhile, the autopsy lungs of COVID-19 patients showed SARS-CoV-2 virions in damaged alveolar epithelium and evidence of hypoxic injury. INTERPRETATION: Pulmonary endothelial cells become dysfunctional during COVID-19, showing a loss of thrombomodulin expression related to severe thrombosis and infiltration, and endothelial cell dysfunction might be caused by a pathologic condition in COVID-19 patient lungs rather than a direct infection with SARS-CoV-2. FUNDING: This work was supported by the Johns Hopkins University, the American Heart Association, and the National Institutes of Health.

Prognostic Significance of Urinary Biomarkers in Patients Hospitalized With COVID-19.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) is common in patients with coronavirus disease 2019 (COVID-19) and associated with poor outcomes. Urinary biomarkers have been associated with adverse kidney outcomes in other settings and may provide additional prognostic information in patients with COVID-19. We investigated the association between urinary biomarkers and adverse kidney outcomes among patients hospitalized with COVID-19. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: Patients hospitalized with COVID-19 (n=153) at 2 academic medical centers between April and June 2020. EXPOSURE: 19 urinary biomarkers of injury, inflammation, and repair. OUTCOME: Composite of KDIGO (Kidney Disease: Improving Global Outcomes) stage 3 AKI, requirement for dialysis, or death within 60 days of hospital admission. We also compared various kidney biomarker levels in the setting of COVID-19 versus other common AKI settings. ANALYTICAL APPROACH: Time-varying Cox proportional hazards regression to associate biomarker level with composite outcome. RESULTS: Out of 153 patients, 24 (15.7%) experienced the primary outcome. Twofold higher levels of neutrophil gelatinase-associated lipocalin (NGAL) (HR, 1.34 [95% CI, 1.14-1.57]), monocyte chemoattractant protein (MCP-1) (HR, 1.42 [95% CI, 1.09-1.84]), and kidney injury molecule 1 (KIM-1) (HR, 2.03 [95% CI, 1.38-2.99]) were associated with highest risk of sustaining primary composite outcome. Higher epidermal growth factor (EGF) levels were associated with a lower risk of the primary outcome (HR, 0.61 [95% CI, 0.47-0.79]). Individual biomarkers provided moderate discrimination and biomarker combinations improved discrimination for the primary outcome. The degree of kidney injury by biomarker level in COVID-19 was comparable to other settings of clinical AKI. There was evidence of subclinical AKI in COVID-19 patients based on elevated injury biomarker level in patients without clinical AKI defined by serum creatinine. LIMITATIONS: Small sample size with low number of composite outcome events. CONCLUSIONS: Urinary biomarkers are associated with adverse kidney outcomes in patients hospitalized with COVID-19 and may provide valuable information to monitor kidney disease progression and recovery.

Association of Multiple Plasma Biomarker Concentrations with Progression of Prevalent Diabetic Kidney Disease: Findings from the Chronic Renal Insufficiency Cohort (CRIC) Study.

BACKGROUND: Although diabetic kidney disease is the leading cause of ESKD in the United States, identifying those patients who progress to ESKD is difficult. Efforts are under way to determine if plasma biomarkers can help identify these high-risk individuals. METHODS: In our case-cohort study of 894 Chronic Renal Insufficiency Cohort Study participants with diabetes and an eGFR of <60 ml/min per 1.73 m2 at baseline, participants were randomly selected for the subcohort; cases were those patients who developed progressive diabetic kidney disease (ESKD or 40% eGFR decline). Using a multiplex system, we assayed plasma biomarkers related to tubular injury, inflammation, and fibrosis (KIM-1, TNFR-1, TNFR-2, MCP-1, suPAR, and YKL-40). Weighted Cox regression models related biomarkers to progression of diabetic kidney disease, and mixed-effects models estimated biomarker relationships with rate of eGFR change. RESULTS: Median follow-up was 8.7 years. Higher concentrations of KIM-1, TNFR-1, TNFR-2, MCP-1, suPAR, and YKL-40 were each associated with a greater risk of progression of diabetic kidney disease, even after adjustment for established clinical risk factors. After accounting for competing biomarkers, KIM-1, TNFR-2, and YKL-40 remained associated with progression of diabetic kidney disease; TNFR-2 had the highest risk (adjusted hazard ratio, 1.61; 95% CI, 1.15 to 2.26). KIM-1, TNFR-1, TNFR-2, and YKL-40 were associated with rate of eGFR decline. CONCLUSIONS: Higher plasma levels of KIM-1, TNFR-1, TNFR-2, MCP-1, suPAR, and YKL-40 were associated with increased risk of progression of diabetic kidney disease; TNFR-2 had the highest risk after accounting for the other biomarkers. These findings validate previous literature on TNFR-1, TNFR-2, and KIM-1 in patients with prevalent CKD and provide new insights into the influence of suPAR and YKL-40 as plasma biomarkers that require validation.

Machine Learning Prediction of Death in Critically Ill Patients With Coronavirus Disease 2019.

OBJECTIVES: Critically ill patients with coronavirus disease 2019 have variable mortality. Risk scores could improve care and be used for prognostic enrichment in trials. We aimed to compare machine learning algorithms and develop a simple tool for predicting 28-day mortality in ICU patients with coronavirus disease 2019. DESIGN: This was an observational study of adult patients with coronavirus disease 2019. The primary outcome was 28-day inhospital mortality. Machine learning models and a simple tool were derived using variables from the first 48 hours of ICU admission and validated externally in independent sites and temporally with more recent admissions. Models were compared with a modified Sequential Organ Failure Assessment score, National Early Warning Score, and CURB-65 using the area under the receiver operating characteristic curve and calibration. SETTING: Sixty-eight U.S. ICUs. PATIENTS: Adults with coronavirus disease 2019 admitted to 68 ICUs in the United States between March 4, 2020, and June 29, 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The study included 5,075 patients, 1,846 (36.4%) of whom died by day 28. eXtreme Gradient Boosting had the highest area under the receiver operating characteristic curve in external validation (0.81) and was well-calibrated, while k-nearest neighbors were the lowest performing machine learning algorithm (area under the receiver operating characteristic curve 0.69). Findings were similar with temporal validation. The simple tool, which was created using the most important features from the eXtreme Gradient Boosting model, had a significantly higher area under the receiver operating characteristic curve in external validation (0.78) than the Sequential Organ Failure Assessment score (0.69), National Early Warning Score (0.60), and CURB-65 (0.65; p < 0.05 for all comparisons). Age, number of ICU beds, creatinine, lactate, arterial pH, and Pao2/Fio2 ratio were the most important predictors in the eXtreme Gradient Boosting model. CONCLUSIONS: eXtreme Gradient Boosting had the highest discrimination overall, and our simple tool had higher discrimination than a modified Sequential Organ Failure Assessment score, National Early Warning Score, and CURB-65 on external validation. These models could be used to improve triage decisions and clinical trial enrichment.

Overview of acute kidney manifestations and management of patients with COVID-19.

Since the start of the COVID-19 pandemic, several manifestations of kidney involvement associated with infection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus have been described, including proteinuria, hematuria, and acute kidney injury. A growing body of literature has explored the risk factors and pathogenesis of COVID-19-associated acute kidney injury (AKI), including direct and indirect mechanisms, as well as early postdischarge outcomes that may result from various manifestations of kidney involvement. In this review, we explore the current state of knowledge of the epidemiology of COVID-19-associated AKI, potential mechanisms and pathogenesis of AKI, and various management strategies for patients in the acute setting. We highlight how kidney replacement therapy for patients with COVID-19-associated AKI has been affected by the increasing demand for dialysis and how the postacute management of patients, including outpatient follow-up, is vitally important. We also review what is presently known about long-term kidney outcomes after the initial recovery from COVID-19. We provide some guidance as to the management of patients hospitalized with COVID-19 who are at risk for AKI as well as for future clinical research in the setting of COVID-19 and the significance of early identification of patients at highest risk for adverse kidney outcomes.

Sample Processing and Stability for Urine Biomarker Studies.

BACKGROUND: Current methods of processing and storing urine samples have not been compared systematically to determine optimal conditions for advancing research on urinary biomarkers. Often, preanalytical handling is nonideal, especially considering the COVID-19 pandemic; consequently, we compared the effects of different short-term storage and processing methods on urinary biomarker measurements. METHODS: Spot urine samples were collected via a Foley catheter from 20 hospitalized patients from the Yale New Haven Hospital within 48 hours postcardiac surgery. The effects of 3 urine storage and processing methods on biomarkers were tested: (a) 48-hour temporary storage at 4 °C prior to freezing at -80 °C, (b) 48-hour temporary storage at 25 °C prior to freezing at -80 °C, and (c) no centrifugation and immediate storage at -80 °C. Established Meso-Scale Device assay methods were used to measure the urine concentrations of 18 biomarkers: interferon gamma (IFN-É£), interleukin (IL)-10, IL-12p70, IL-13, IL-1ß, IL-2, IL-4, IL-6, IL-8, IL-18, tumor necrosis factor alpha (TNF-α), epidermal growth factor (EGF), neutrophil gelatinase-associated lipocalin (NGAL), osteopontin (OPN), uromodulin (UMOD), kidney injury molecule-1 (KIM-1), monocyte chemoattractant protein-1 (MCP-1), and chitinase-3-like protein 1 (YKL-40). RESULTS: Measurements of most biomarkers investigated remained stable after temporary storage at 4 °C. IL-6, IL-8, KIM-1, MCP-1, YKL-40, EGF, and NGAL were stable across all 3 processing conditions. IL-12p70 and IL-4 demonstrated significant differences in all tested conditions compared to the reference standard. CONCLUSIONS: We identified several notable biomarkers that are robust to variations in preanalytical techniques and can be reliably investigated with nonideal handling conditions.

Factors Associated With Death in Critically Ill Patients With Coronavirus Disease 2019 in the US.

Importance: The US is currently an epicenter of the coronavirus disease 2019 (COVID-19) pandemic, yet few national data are available on patient characteristics, treatment, and outcomes of critical illness from COVID-19. Objectives: To assess factors associated with death and to examine interhospital variation in treatment and outcomes for patients with COVID-19. Design, Setting, and Participants: This multicenter cohort study assessed 2215 adults with laboratory-confirmed COVID-19 who were admitted to intensive care units (ICUs) at 65 hospitals across the US from March 4 to April 4, 2020. Exposures: Patient-level data, including demographics, comorbidities, and organ dysfunction, and hospital characteristics, including number of ICU beds. Main Outcomes and Measures: The primary outcome was 28-day in-hospital mortality. Multilevel logistic regression was used to evaluate factors associated with death and to examine interhospital variation in treatment and outcomes. Results: A total of 2215 patients (mean [SD] age, 60.5 [14.5] years; 1436 [64.8%] male; 1738 [78.5%] with at least 1 chronic comorbidity) were included in the study. At 28 days after ICU admission, 784 patients (35.4%) had died, 824 (37.2%) were discharged, and 607 (27.4%) remained hospitalized. At the end of study follow-up (median, 16 days; interquartile range, 8-28 days), 875 patients (39.5%) had died, 1203 (54.3%) were discharged, and 137 (6.2%) remained hospitalized. Factors independently associated with death included older age (≥80 vs <40 years of age: odds ratio [OR], 11.15; 95% CI, 6.19-20.06), male sex (OR, 1.50; 95% CI, 1.19-1.90), higher body mass index (≥40 vs <25: OR, 1.51; 95% CI, 1.01-2.25), coronary artery disease (OR, 1.47; 95% CI, 1.07-2.02), active cancer (OR, 2.15; 95% CI, 1.35-3.43), and the presence of hypoxemia (Pao2:Fio2<100 vs ≥300 mm Hg: OR, 2.94; 95% CI, 2.11-4.08), liver dysfunction (liver Sequential Organ Failure Assessment score of 2-4 vs 0: OR, 2.61; 95% CI, 1.30-5.25), and kidney dysfunction (renal Sequential Organ Failure Assessment score of 4 vs 0: OR, 2.43; 95% CI, 1.46-4.05) at ICU admission. Patients admitted to hospitals with fewer ICU beds had a higher risk of death (<50 vs ≥100 ICU beds: OR, 3.28; 95% CI, 2.16-4.99). Hospitals varied considerably in the risk-adjusted proportion of patients who died (range, 6.6%-80.8%) and in the percentage of patients who received hydroxychloroquine, tocilizumab, and other treatments and supportive therapies. Conclusions and Relevance: This study identified demographic, clinical, and hospital-level risk factors that may be associated with death in critically ill patients with COVID-19 and can facilitate the identification of medications and supportive therapies to improve outcomes.

AKI Treated with Renal Replacement Therapy in Critically Ill Patients with COVID-19.

BACKGROUND: AKI is a common sequela of coronavirus disease 2019 (COVID-19). However, few studies have focused on AKI treated with RRT (AKI-RRT). METHODS: We conducted a multicenter cohort study of 3099 critically ill adults with COVID-19 admitted to intensive care units (ICUs) at 67 hospitals across the United States. We used multivariable logistic regression to identify patient-and hospital-level risk factors for AKI-RRT and to examine risk factors for 28-day mortality among such patients. RESULTS: A total of 637 of 3099 patients (20.6%) developed AKI-RRT within 14 days of ICU admission, 350 of whom (54.9%) died within 28 days of ICU admission. Patient-level risk factors for AKI-RRT included CKD, men, non-White race, hypertension, diabetes mellitus, higher body mass index, higher d-dimer, and greater severity of hypoxemia on ICU admission. Predictors of 28-day mortality in patients with AKI-RRT were older age, severe oliguria, and admission to a hospital with fewer ICU beds or one with greater regional density of COVID-19. At the end of a median follow-up of 17 days (range, 1-123 days), 403 of the 637 patients (63.3%) with AKI-RRT had died, 216 (33.9%) were discharged, and 18 (2.8%) remained hospitalized. Of the 216 patients discharged, 73 (33.8%) remained RRT dependent at discharge, and 39 (18.1%) remained RRT dependent 60 days after ICU admission. CONCLUSIONS: AKI-RRT is common among critically ill patients with COVID-19 and is associated with a hospital mortality rate of >60%. Among those who survive to discharge, one in three still depends on RRT at discharge, and one in six remains RRT dependent 60 days after ICU admission.

Association Between Early Treatment With Tocilizumab and Mortality Among Critically Ill Patients With COVID-19.

Importance: Therapies that improve survival in critically ill patients with coronavirus disease 2019 (COVID-19) are needed. Tocilizumab, a monoclonal antibody against the interleukin 6 receptor, may counteract the inflammatory cytokine release syndrome in patients with severe COVID-19 illness. Objective: To test whether tocilizumab decreases mortality in this population. Design, Setting, and Participants: The data for this study were derived from a multicenter cohort study of 4485 adults with COVID-19 admitted to participating intensive care units (ICUs) at 68 hospitals across the US from March 4 to May 10, 2020. Critically ill adults with COVID-19 were categorized according to whether they received or did not receive tocilizumab in the first 2 days of admission to the ICU. Data were collected retrospectively until June 12, 2020. A Cox regression model with inverse probability weighting was used to adjust for confounding. Exposures: Treatment with tocilizumab in the first 2 days of ICU admission. Main Outcomes and Measures: Time to death, compared via hazard ratios (HRs), and 30-day mortality, compared via risk differences. Results: Among the 3924 patients included in the analysis (2464 male [62.8%]; median age, 62 [interquartile range {IQR}, 52-71] years), 433 (11.0%) received tocilizumab in the first 2 days of ICU admission. Patients treated with tocilizumab were younger (median age, 58 [IQR, 48-65] vs 63 [IQR, 52-72] years) and had a higher prevalence of hypoxemia on ICU admission (205 of 433 [47.3%] vs 1322 of 3491 [37.9%] with mechanical ventilation and a ratio of partial pressure of arterial oxygen to fraction of inspired oxygen of <200 mm Hg) than patients not treated with tocilizumab. After applying inverse probability weighting, baseline and severity-of-illness characteristics were well balanced between groups. A total of 1544 patients (39.3%) died, including 125 (28.9%) treated with tocilizumab and 1419 (40.6%) not treated with tocilizumab. In the primary analysis, during a median follow-up of 27 (IQR, 14-37) days, patients treated with tocilizumab had a lower risk of death compared with those not treated with tocilizumab (HR, 0.71; 95% CI, 0.56-0.92). The estimated 30-day mortality was 27.5% (95% CI, 21.2%-33.8%) in the tocilizumab-treated patients and 37.1% (95% CI, 35.5%-38.7%) in the non-tocilizumab-treated patients (risk difference, 9.6%; 95% CI, 3.1%-16.0%). Conclusions and Relevance: Among critically ill patients with COVID-19 in this cohort study, the risk of in-hospital mortality in this study was lower in patients treated with tocilizumab in the first 2 days of ICU admission compared with patients whose treatment did not include early use of tocilizumab. However, the findings may be susceptible to unmeasured confounding, and further research from randomized clinical trials is needed.