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OBJECTIVES:. To evaluate the study design and feasibility of drug administration and safety in a randomized clinical trial of recombinant human annexin A5 (SY-005), a constitutively expressed protein with anti-inflammatory, antiapoptotic, and anticoagulant properties, in patients with severe coronavirus disease 2019 (COVID-19). DESIGN:. Double-blind, randomized clinical trial. SETTING:. Two ICUs at an academic medical center. PATIENTS/SUBJECTS:. Adults admitted to the ICU with a confirmed diagnosis of COVID-19 and requiring ventilatory or vasopressor support. INTERVENTIONS:. SY-005, a recombinant human annexin A5, at 50 or 100 µg/kg IV every 12 hours for 7 days. MEASUREMENTS AND MAIN RESULTS:. We enrolled 18 of the 55 eligible patients (33%) between April 21, 2021, and February 3, 2022. We administered 82% (196/238) of the anticipated doses of study medication and 86% (169/196) were given within 1 hour of the scheduled time. There were no drug-related serious adverse events. We captured 100% of the data that would be required for measuring clinical outcomes in a phase 2 or 3 trial. LIMITATIONS:. The small sample size was a result of decreasing admissions of patients with COVID-19, which triggered a stopping rule for the trial. CONCLUSIONS:. Although enrollment was low, administration of SY-005 to critically ill patients with COVID-19 every 12 hours for up to 7 days was feasible and safe. Further clinical trials of annexin A5 for the treatment of COVID-19 are warranted. Given reduction of severe COVID-19 disease, future studies should explore the safety and effectiveness of SY-005 use in non-COVID-related sepsis.

IMPORTANCE:. Coronavirus disease 2019 patients have an increased risk of thrombotic complications that may reflect immunothrombosis, a process characterized by blood clotting, endothelial dysfunction, and the release of neutrophil extracellular traps. To date, few studies have investigated longitudinal changes in immunothrombosis biomarkers in these patients. Furthermore, how these longitudinal changes differ between coronavirus disease 2019 patients and noncoronavirus disease septic patients with pneumonia are unknown. OBJECTIVES:. In this pilot observational study, we investigated the utility of immunothrombosis biomarkers for distinguishing between coronavirus disease 2019 patients and noncoronavirus disease septic patients with pneumonia. We also evaluated the utility of the biomarkers for predicting ICU mortality in these patients. DESIGN, SETTING, AND PARTICIPANTS:. The participants were ICU patients with coronavirus disease 2019 (n = 14), noncoronavirus disease septic patients with pneumonia (n = 19), and healthy age-matched controls (n = 14). MAIN OUTCOMES AND MEASURES:. Nine biomarkers were measured from plasma samples (on days 1, 2, 4, 7, 10, and/or 14). Analysis was based on binomial logit models and receiver operating characteristic analyses. RESULTS:. Cell-free DNA, d-dimer, soluble endothelial protein C receptor, protein C, soluble thrombomodulin, fibrinogen, citrullinated histones, and thrombin-antithrombin complexes have significant powers for distinguishing coronavirus disease 2019 patients from healthy individuals. In comparison, fibrinogen, soluble endothelial protein C receptor, antithrombin, and cell-free DNA have significant powers for distinguishing coronavirus disease 2019 from pneumonia patients. The predictors of ICU mortality differ between the two patient groups: soluble thrombomodulin and citrullinated histones for coronavirus disease 2019 patients, and protein C and cell-free DNA or fibrinogen for pneumonia patients. In both patient groups, the most recent biomarker values have stronger prognostic value than their ICU day 1 values. CONCLUSIONS AND RELEVANCE:. Fibrinogen, soluble endothelial protein C receptor, antithrombin, and cell-free DNA have utility for distinguishing coronavirus disease 2019 patients from noncoronavirus disease septic patients with pneumonia. The most important predictors of ICU mortality are soluble thrombomodulin/citrullinated histones for coronavirus disease 2019 patients, and protein C/cell-free DNA for noncoronavirus disease pneumonia patients. This hypothesis-generating study suggests that the pathophysiology of immunothrombosis differs between the two patient groups.

Objectives:. Coronavirus disease 2019 continues to spread worldwide with high levels of morbidity and mortality. We performed anticoronavirus immunoglobulin G profiling of critically ill coronavirus disease 2019 patients to better define their underlying humoral response. Design:. Blood was collected at predetermined ICU days to measure immunoglobulin G with a research multiplex assay against four severe acute respiratory syndrome coronavirus 2 proteins/subunits and against all six additionally known human coronaviruses. Setting:. Tertiary care ICU and academic laboratory. Subjects:. ICU patients suspected of being infected with severe acute respiratory syndrome coronavirus 2 had blood collected until either polymerase chain reaction testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative) or until death or discharge if the patient tested polymerase chain reaction positive (coronavirus disease 2019 positive). Interventions:. None MEASUREMENTS AND MAIN RESULTS:. Age- and sex-matched healthy controls and ICU patients who were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients had greater body mass indexes, presented with bilateral pneumonias more frequently, and suffered lower Pao2:Fio2 ratios, when compared with coronavirus disease 2019 negative patients (p < 0.05). Mortality rate for coronavirus disease 2019 positive patients was 50%. On ICU days 1–3, anti–severe acute respiratory syndrome coronavirus 2 immunoglobulin G was significantly elevated in coronavirus disease 2019 positive patients, as compared to both healthy control subjects and coronavirus disease 2019 negative patients (p < 0.001). Weak severe acute respiratory syndrome coronavirus immunoglobulin G serologic responses were also detected, but not other coronavirus subtypes. The four anti–severe acute respiratory syndrome coronavirus 2 immunoglobulin G were maximal by ICU day 3, with all four anti–severe acute respiratory syndrome coronavirus 2 immunoglobulin G providing excellent diagnostic potential (severe acute respiratory syndrome coronavirus 2 Spike 1 protein immunoglobulin G, area under the curve 1.0, p < 0.0005; severe acute respiratory syndrome coronavirus receptor binding domain immunoglobulin G, area under the curve, 0.93–1.0; p ≤ 0.0001; severe acute respiratory syndrome coronavirus 2 Spike proteins immunoglobulin G, area under the curve, 1.0; p < 0.0001; severe acute respiratory syndrome coronavirus 2 Nucleocapsid protein immunoglobulin G area under the curve, 0.90–0.95; p ≤ 0.0003). Anti–severe acute respiratory syndrome coronavirus 2 immunoglobulin G increased and/or plateaued over 10 ICU days. Conclusions:. Critically ill coronavirus disease 2019 patients exhibited anti–severe acute respiratory syndrome coronavirus 2 immunoglobulin G, whereas serologic responses to non–severe acute respiratory syndrome coronavirus 2 antigens were weak or absent. Detection of human coronavirus immunoglobulin G against the different immunogenic structural proteins/subunits with multiplex assays may be useful for pathogen identification, patient cohorting, and guiding convalescent plasma therapy.

Objectives:. Coronavirus disease 2019 continues to spread rapidly with high mortality. We performed metabolomics profiling of critically ill coronavirus disease 2019 patients to understand better the underlying pathologic processes and pathways, and to identify potential diagnostic/prognostic biomarkers. Design:. Blood was collected at predetermined ICU days to measure the plasma concentrations of 162 metabolites using both direct injection-liquid chromatography-tandem mass spectrometry and proton nuclear magnetic resonance. Setting:. Tertiary-care ICU and academic laboratory. Subjects:. Patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome coronavirus 2, using standardized hospital screening methodologies, had blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative) or until ICU day 10 if the patient tested positive (coronavirus disease 2019 positive). Interventions:. None. Measurements and Main Results:. Age- and sex-matched healthy controls and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well balanced with the exception that coronavirus disease 2019 positive patients suffered bilateral pneumonia more frequently than coronavirus disease 2019 negative patients. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. Feature selection identified the top-performing metabolites for identifying coronavirus disease 2019 positive patients from healthy control subjects and was dominated by increased kynurenine and decreased arginine, sarcosine, and lysophosphatidylcholines. Arginine/kynurenine ratio alone provided 100% classification accuracy between coronavirus disease 2019 positive patients and healthy control subjects (p = 0.0002). When comparing the metabolomes between coronavirus disease 2019 positive and coronavirus disease 2019 negative patients, kynurenine was the dominant metabolite and the arginine/kynurenine ratio provided 98% classification accuracy (p = 0.005). Feature selection identified creatinine as the top metabolite for predicting coronavirus disease 2019-associated mortality on both ICU days 1 and 3, and both creatinine and creatinine/arginine ratio accurately predicted coronavirus disease 2019-associated death with 100% accuracy (p = 0.01). Conclusions:. Metabolomics profiling with feature classification easily distinguished both healthy control subjects and coronavirus disease 2019 negative patients from coronavirus disease 2019 positive patients. Arginine/kynurenine ratio accurately identified coronavirus disease 2019 status, whereas creatinine/arginine ratio accurately predicted coronavirus disease 2019-associated death. Administration of tryptophan (kynurenine precursor), arginine, sarcosine, and/or lysophosphatidylcholines may be considered as potential adjunctive therapies.

Objectives:. Coronavirus disease 2019 patients admitted to the ICU have high mortality. The host response to coronavirus disease 2019 has only been partially elucidated, and prognostic biomarkers have not been identified. We performed targeted proteomics on critically ill coronavirus disease 2019 patients to better understand their pathophysiologic mediators and to identify potential outcome markers. Design:. Blood was collected at predetermined ICU days for proximity extension assays to determine the plasma concentrations of 1,161 proteins. Setting:. Tertiary care ICU and academic laboratory. Subjects:. All patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome coronavirus 2, using standardized hospital screening methodologies, had blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative) or until ICU day 10 if the patient positive (coronavirus disease 2019 positive). Interventions:. None. Measurements and Main Results:. Age- and sex-matched healthy control subjects and ICU patients who were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients suffered bilateral pneumonia more frequently than coronavirus disease 2019 negative patients. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. Feature selection identified the top performing proteins for identifying coronavirus disease 2019 positive ICU patients from both healthy control subjects and coronavirus disease 2019 negative ICU patients (classification accuracies 100%). The coronavirus disease 2019 proteome was dominated by interleukins and chemokines, as well as several membrane receptors linked to lymphocyte-associated microparticles and/or cell debris. Mortality was predicted for coronavirus disease 2019 positive patients based on plasma proteome profiling on both ICU day 1 (accuracy 92%) and ICU day 3 (accuracy 83%). Promising prognostic proteins were then narrowed down to six, each of which provided excellent classification performance for mortality when measured on ICU day 1 CMRF-35-like molecule, interleukin receptor-12 subunit B1, cluster of differentiation 83 [CD83], family with sequence similarity 3, insulin-like growth factor 1 receptor and opticin; area-under-the-curve =1.0; p = 0.007). Conclusions:. Targeted proteomics with feature classification easily distinguished both healthy control subjects and coronavirus disease 2019 tested negative ICU patients from coronavirus disease 2019 tested positive ICU patients. Multiple proteins were identified that accurately predicted coronavirus disease 2019 tested positive patient mortality.

Objectives:. Coronavirus disease 2019 is caused by the novel severe acute respiratory syndrome coronavirus 2 virus. Patients admitted to the ICU suffer from microvascular thrombosis, which may contribute to mortality. Our aim was to profile plasma thrombotic factors and endothelial injury markers in critically ill coronavirus disease 2019 ICU patients to help understand their thrombotic mechanisms. Design:. Daily blood coagulation and thrombotic factor profiling with immunoassays and in vitro experiments on human pulmonary microvascular endothelial cells. Setting:. Tertiary care ICU and academic laboratory. Subjects:. All patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome coronavirus 2, using standardized hospital screening methodologies, had daily blood samples collected until testing was confirmed coronavirus disease 2019 negative on either ICU day 3 or ICU day 7 if the patient was coronavirus disease 2019 positive. Interventions:. None. Measurement and Main Results:. Age- and sex-matched healthy control subjects and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well balanced with the exception that coronavirus disease 2019 positive patients were more likely than coronavirus disease 2019 negative patients to suffer bilateral pneumonia. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. Compared with healthy control subjects, coronavirus disease 2019 positive patients had higher plasma von Willebrand factor (p < 0.001) and glycocalyx-degradation products (chondroitin sulfate and syndecan-1; p < 0.01). When compared with coronavirus disease 2019 negative patients, coronavirus disease 2019 positive patients had persistently higher soluble P-selectin, hyaluronic acid, and syndecan-1 (p < 0.05), particularly on ICU day 3 and thereafter. Thrombosis profiling on ICU days 1–3 predicted coronavirus disease 2019 status with 85% accuracy and patient mortality with 86% accuracy. Surface hyaluronic acid removal from human pulmonary microvascular endothelial cells with hyaluronidase treatment resulted in depressed nitric oxide, an instigating mechanism for platelet adhesion to the microvascular endothelium. Conclusions:. Thrombosis profiling identified endothelial activation and glycocalyx degradation in coronavirus disease 2019 positive patients. Our data suggest that medications to protect and/or restore the endothelial glycocalyx, as well as platelet inhibitors, should be considered for further study.

Objectives:. Coronavirus disease 2019 is caused by severe acute respiratory syndrome-coronavirus-2 infection to which there is no community immunity. Patients admitted to ICUs have high mortality, with only supportive therapies available. Our aim was to profile plasma inflammatory analytes to help understand the host response to coronavirus disease 2019. Design:. Daily blood inflammation profiling with immunoassays. Setting:. Tertiary care ICU and academic laboratory. Subjects:. All patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome-coronavirus-2, using standardized hospital screening methodologies, had daily blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative), or until ICU day 7 if the patient was positive (coronavirus disease 2019 positive). Interventions:. None. Measurements and Main Results:. Age- and sex-matched healthy controls and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients were more likely than coronavirus disease 2019 negative patients to suffer bilateral pneumonia. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. We measured 57 inflammatory analytes and then analyzed with both conventional statistics and machine learning. Twenty inflammatory analytes were different between coronavirus disease 2019 positive patients and healthy controls (p < 0.01). Compared with coronavirus disease 2019 negative patients, coronavirus disease 2019 positive patients had 17 elevated inflammatory analytes on one or more of their ICU days 1–3 (p < 0.01), with feature classification identifying the top six analytes between cohorts as tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2. While tumor necrosis factor, granzyme B, heat shock protein 70, and interleukin-18 were elevated for all seven ICU days, interferon-gamma-inducible protein 10 transiently elevated on ICU days 2 and 3 and elastase 2 increased over ICU days 2–7. Inflammation profiling predicted coronavirus disease 2019 status with 98% accuracy, whereas elevated heat shock protein 70 was strongly associated with mortality. Conclusions:. While many inflammatory analytes were elevated in coronavirus disease 2019 positive ICU patients, relative to healthy controls, the top six analytes distinguishing coronavirus disease 2019 positive ICU patients from coronavirus disease 2019 negative ICU patients were tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2.

Objectives:. To determine if a set of time-varying biological indicators can be used to: 1) predict the sepsis mortality risk over time and 2) generate mortality risk profiles. Design:. Prospective observational study. Setting:. Nine Canadian ICUs. Subjects:. Three-hundred fifty-six septic patients. Interventions:. None. Measurements and Main Results:. Clinical data and plasma levels of biomarkers were collected longitudinally. We used a complementary log-log model to account for the daily mortality risk of each patient until death in ICU/hospital, discharge, or 28 days after admission. The model, which is a versatile version of the Cox model for gaining longitudinal insights, created a composite indicator (the daily hazard of dying) from the “day 1” and “change” variables of six time-varying biological indicators (cell-free DNA, protein C, platelet count, creatinine, Glasgow Coma Scale score, and lactate) and a set of contextual variables (age, presence of chronic lung disease or previous brain injury, and duration of stay), achieving a high predictive power (conventional area under the curve, 0.90; 95% CI, 0.86–0.94). Including change variables avoided misleading inferences about the effects of day 1 variables, signifying the importance of the longitudinal approach. We then generated mortality risk profiles that highlight the relative contributions among the time-varying biological indicators to overall mortality risk. The tool was validated in 28 nonseptic patients from the same ICUs who became septic later and was subject to 10-fold cross-validation, achieving similarly high area under the curve. Conclusions:. Using a novel version of the Cox model, we created a prognostic tool for septic patients that yields not only a predicted probability of dying but also a mortality risk profile that reveals how six time-varying biological indicators differentially and longitudinally account for the patient’s overall daily mortality risk.