Suppression of Fibrinolysis and Hypercoagulability, Severity of Hypoxemia, and Mortality in COVID-19 Patients: A Retrospective Cohort Study

From April 2020 to October 2020, 55 SARS-CoV-2 positive patients requiring ICU-level care were screened and enrolled in the study. Eligible patients were men and women ages 18 yr old and above who were admitted to an adult ICU at a quaternary hospital center with SARS-CoV-2 infection confirmed by polymerase chain reaction testing. Eighty-nine percent of the cohort was intubated, requiring ventilation, and the remainder either required vasopressor support or high-flow oxygen support. Written informed consent was obtained from the patient or their legally authorized representative if they lacked decision-making capacity. Patients were ineligible for enrollment if they were enrolled in a blood conservation program or were incarcerated. Citrated whole blood was collected on days 1, 3, 7, 14, and 21 after enrollment or until discharge from ICU or death. The average time from entry to ICU to day 1 of study was 6.9 (SD, 5.3) days. These samples were centrifuged and stored at –80°C for analysis. All patients received prophylactic low-molecular-weight heparin (0.5 mg/kg twice daily) or unfractionated heparin (5,000 IU every 8 h) dosing for venous thromboembolic prophylaxis excluding ECMO patients who received full dose titrated unfractionated heparin to a partial thromboplastin time goal of 50 to 60 s. The study was approved by the academic center’s institutional review board and is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology guidelines (Supplemental Digital Content 1 table S1, https://links.lww.com/ALN/C849).

The clinical data were extracted from the electronic medical record. Vital signs; laboratory data; codes for comorbidity analysis from the International Statistical Classification of Diseases, Tenth Revision; and demographic data were extracted from the Oracle electronic medical record database across the cohort’s ICU encounters using SQL queries.

The ratio of arterial partial pressure of oxygen (Pao₂) to fraction of inspired oxygen (Fio₂) was calculated from ventilator and clinical laboratory data at each episode of blood collection for each patient. Pao₂/Fio₂ thresholds of 300 to 200, 199 to 100, and less than 100 were classified as mild, moderate, and severe ARDS, respectively, per the Berlin criteria.¹⁶  In addition, stratification of disease severity based on a patient’s lowest Pao₂/Fio₂ during their ICU course was completed, and an outcomes analysis was performed. All patients requiring ECMO were classified as having severe ARDS as the Pao₂/Fio₂ ratios for ECMO patients fail to take into account the additional oxygenation provided by the ECMO circuit itself, resulting in a Pao₂/Fio₂ ratio that does not reflect the severity of the patient’s respiratory distress. All laboratory values were associated with the patient’s Pao₂/Fio₂ severity level at the same date and time of blood collection.

The following activity assays and enzyme-linked immunosorbent assays (ELISAs) were performed per the manufacturers’ instructions using citrated plasma at dilutions indicated for each assay: Factor VIII Chromogenix Coamatic activity assay (K822585, Diapharma, USA), 1:800 dilution; microparticle-bound tissue factor (Zymuphen 521196), undiluted plasma; A disintegrin and metalloproteinase with a thrombospondin type 1 motif, member 13 (ADAMTS13; ab234559, Abcam, United Kingdom), 1:1,000; vWF (ab223864, Abcam), 1:8,000; Factor IX (ab188393, Abcam), 1:1,000; tissue factor pathway inhibitor (ab274392, Abcam), 1:100; and plasminogen activator inhibitor 1 (ab269373, Abcam), 1:20. All plates were read on a 96-well plate reader (Spectral Max i3; Molecular Devices, USA).

Healthy population means are depicted by dotted lines in figures 1 to 3 and were determined from clinical laboratory normal ranges for d-dimer and fibrinogen and from previous reports for vWF,¹⁷  ADAMTS13,¹⁸  tissue factor pathway inhibitor,¹⁹  and plasminogen activator inhibitor 1.²⁰  Healthy mean values for factor VIII activity were determined by assessment of plasma from eight healthy young adult volunteers. This was in part due to a lack of consistent reported health population means. Validation of ELISA data from COVID-19 patients was performed via within-assay comparison to healthy plasma from donors matched for age, race, ethnicity, and body mass index of COVID-19 patients purchased from Innovative Research (USA).

All assays were performed on a clinical rotational thromboelastometry (ROTEM) machine (ROTEM delta; Tem Innovations, Germany) according to the manufacturer’s instructions including fibrin-based extrinsically activated test with tissue factor and the platelet inhibitor cytochalasin D (FIBTEM), extrinsically activated test with tissue factor (EXTEM), intrinsically activated test using ellagic acid (INTEM), and INTEM assay performed in the presence of heparinase (HEPTEM). EXTEM and FIBTEM were performed for all patients, and either INTEM or HEPTEM was performed depending on patient’s heparization status, with HEPTEM was performed if the patient was therapeutically heparinized. The ROTEM machine was calibrated daily, and reagents were calibrated weekly.

There were no missing data within the study period, which included the total duration of the ICU stay, after enrollment in the study. Before accessing the data, a statistical analysis plan was formulated. The clinical data were analyzed using R code (R Foundation for Statistical Computing, Austria). Assuming an event rate of 25%, power analysis demonstrated that with an α of 0.05 and 80% power, a sample size of 52 would be sufficient to detect a 50% difference in biomarker levels between survivors and nonsurvivors. Primary outcomes included mortality, major thrombotic events (deep vein thrombosis, pulmonary embolism, cerebrovascular accident), and ARDS severity per the Berlin criteria mild (Pao₂/Fio₂ 200 to 300), moderate (Pao₂/Fio₂ 100 to 199), and severe (Pao₂/Fio₂ less than 100).¹⁶  The lowest Pao₂/Fio₂ ratio during a patient’s hospitalization was used to determine the severity of their ARDS. This excluded patients on ECMO. Explanatory variables included coagulopathy biomarkers and thromboelastometric measures. Laboratory values were measured multiple times each day during the ICU hospitalization. A maximum, minimum, or average of these measurements was used to represent the worst effect the variable had on clinical outcome in each ICU. Furthermore, Wilcoxcon rank sum tests were used to associate each log₂-transformed biomarker on ICU day 1, study day 1, or ICU day before a clinical event of interest with each outcome. A P value less than 0.05 was regarded as statistically significant. Logistic regression models were used to assess the association between each biomarker and each clinical outcome. Two-way analysis of variance (ANOVA) and mean ± SD of laboratory values were analyzed with GraphPad Prism 9 software for ECMO versus non-ECMO analysis. Only laboratory data and biomarkers from the first day of the ICU stay were used to avoid repeated measures in the analysis of the ECMO data. Potential confounding variables including age, race, and comorbidities were assessed via stratification analysis and reported in tables for each outcome measure. Homogeneity of variance for each continuous measure was assessed via residual plot, and normality of distribution was assessed via Q-Q plot. Dotted lines are used to indicate the mean of normal clinical values, and gray is shading used to indicate the range of normal clinical values where applicable.

The median age was 57 yr (SD 6), and 14 of 55 (25%) of the cohort were female (table 1). Thirty percent of the cohort identified as Black, and 14 of 55 (25%) identified as Latino. The most common comorbidities were obesity (31 of 55 [55%]), hypertension (23 of 55 [41%]), type 2 diabetes mellitus (20 of 55 [36%]), and cardiovascular disease (11 of 55 [20%]). The average time from the first polymerase chain reaction positive test to day 1 of study was 8 days. Average time from entry to ICU to day 1 of study was 3 days. Of the cohort, 53 of 55 (96%) of the cohort required mechanical ventilation, and 9 of 55 (16%) required ECMO. A total of 13 of 55 (23%) died during the index hospitalization, 27 of 55 (48%) of patients developed ventilator associated pneumonia, 10 of 55 (17.8%) of patients required continuous renal replacement therapy, and 3 of 55 (5.3%) of patients developed heart failure due to myocarditis. Mean duration of mechanical ventilation was 21 days; 9 of 55 (16%) of patients developed major hemorrhage, most of whom were on ECMO support; and 14 (25%) of patients developed major thrombosis defined as deep vein thrombosis in upper and/or lower extremities, pulmonary embolism, and/or stroke (Supplemental Digital Content 2 table S2, https://links.lww.com/ALN/C850). Analysis of clinical characteristics and comorbidities between survivors, nonsurvivors, and ECMO patients demonstrated that patients on ECMO were on average younger with fewer comorbidities, which correlates with criteria for clinical ECMO eligibility. The nonsurvivor group had less obesity, as well as less cardiovascular disease and chronic lung disease compared to the survivor group in contrast to previous studies.²¹  The rates of diabetes and renal disease were similar across survivor and nonsurvivor groups but decreased in ECMO patients. Nonsurvivors and ECMO patients had more hypertension compared to survivors.

ECMO-naive COVID-19 patients requiring ICU care had hypercoagulability on viscoelastic testing with ROTEM compared to the normal reference range (Supplemental Digital Content 2 table S2, https://links.lww.com/ALN/C850; fig. 1) characterized by shortened clot formation time and increased α angle on EXTEM and INTEM, indicative of increased activity of both clotting factors and platelets (fig. 1, B, C, G, and H).^22,23  Our cohort also demonstrated elevated maximum clot firmness on FIBTEM, EXTEM, and INTEM, aligning with the hyperfibrinogenemic state of severe COVID-19 (fig. 1, D, I, and M). Furthermore, lysis indices at 30 min of 100% despite elevated d-dimer levels are consistent with fibrinolysis inhibition (fig. 1, E and J). The median lysis index at 45 min was 100%, and the mean was 99%, providing further evidence for fibrinolytic suppression.

There was no difference in ROTEM tracings of ECMO-naive survivors versus nonsurvivors in this cohort (Supplemental Digital Content 2 table S2, https://links.lww.com/ALN/C850). In contrast, COVID-19 patients placed on ECMO support did not consistently manifest the typical procoagulant phenotypes of severe COVID-19 as assessed by ROTEM analyses, with significantly increased clot formation time and reduced α angle and maximum clot firmness compared to ECMO naïve patients (Supplemental Digital Content 2 table S2, https://links.lww.com/ALN/C850; fig. 1). When measured over time, some patients placed on ECMO lost the procoagulant pattern characteristic of this ROTEM tracing but regained the phenotype after decannulation (Supplemental Digital Content 3 fig. S1, https://links.lww.com/ALN/C851). Others were shown to become more procoagulable over time. These observations demonstrate variability in coagulation changes in patients on ECMO. The loss of procoagulant phenotype seen in some ECMO persisted even after discontinuation of heparin for hemorrhage. Platelet counts were analyzed over time, and there was no significant change in platelet count corresponding to changes in maximum clot firmness in ROTEM. Given these findings, we separated ECMO-naïve patients from the nine ECMO-requiring patients for analysis.

Patients who survived their hospitalization were less likely to have higher levels of procoagulant acute phase reactants including microparticle-bound tissue factor (odds ratio, 0.14 [0.02, 0.99]; P = 0.049). Survivors were also noted to have lower vWF levels compared to nonsurvivors, although this result did not meet significance in a log₂-transformed analysis with Wilcoxon rank sum test (survivors, 5.4 ± 0.04 vs. nonsurvivors, 6.2 ± 0.4; P = 0.063). Furthermore, patients who did not experience major bleeding events had significantly smaller changes in ADAMTS13 levels, an enzyme that shortens large procoagulant vWF multimers, compared to patients who did not have major bleeding events during their hospitalization (odds ratio, 0.05 [0.7]; P = 0.026).

Twenty-five percent of patients had clinically significant thrombotic events, including deep vein thrombosis in upper and/or lower extremities, pulmonary embolism, and stroke. Patients requiring ECMO had a higher frequency of thrombotic events (7 of 9 [78%]) compared to non-ECMO patients (7 of 47 [18%]). We next explored which coagulation factors were associated with thrombotic events, separating the ECMO-naïve from ECMO-requiring given the ECMO-associated differences in coagulative profile described above (Supplemental Digital Content 4 table S3, https://links.lww.com/ALN/C852). Non-ECMO patients who experienced a thrombotic event were more likely to have significantly elevated d-dimer and plasminogen activator inhibitor 1 levels on day 1 of ICU hospitalization compared to those without (odds ratio, 1.95 [1.21, 3.14]; P = 0.006; and odds ratio, 3.52 [0.99, 12.48]; P = 0.05, respectively).

A two-way ANOVA of coagulation parameters, also measured on day 1 of a patient’s ICU stay, for clotting × ECMO was performed. A significant amount of variation in d-dimer levels was associated with clotting (fig. 2B; P_clot < 0.001, mean for no clot, 5,301 ± 12,239 ng/ml vs. clot, 16,540 ± 21,233 ng/ml). However, this effect was largely driven by elevation in d-dimer values within the ECMO population, as illustrated in figure 2B (ECMO (P_ecmo < 0.001) and ECMO × clot (P_{clot x ecmo} = 0.001; means for ECMO-naive, 5,835 ± 11,270 ng/ml vs. ECMO, 23,491 ± 25,806 ng/ml).

Plasminogen activator inhibitor 1 levels accounted for a significant source of variation in thrombotic events (fig. 2C; P_clot = 0.003; mean no clot, 26.3 ± 17.8 ng/ml vs. clot, 38.8 ± 15.2 ng/ml), as well as factor VIII activity (fig. 2D; P_clot = 0.003; mean no clot, 1.15 ± 0.28 OD650 vs. clot, 1.42 ± 0.31 OD650) and vWF levels (fig. 2E; P_clot = 0.096; mean no clot, 36.9 ± 22.5 µg/ml vs. clot, 45.2 ± 22.1 µg/ml). This suggests that fibrinolytic suppression and endothelial damage–associated factor release contribute to clinically significant thrombotic events regardless of ECMO status. In non-ECMO patients, ADAMTS13 levels showed an inverse association with vWF levels (mean no clot, 486 ± 184 ng/ml vs. clot, 399 ± 139 ng/ml), although this pattern was not observed in patients requiring ECMO (fig. 2E). Changes in fibrinogen levels were not associated with thrombotic events (fig. 2A). Supplemental Digital Content 4 table S3 (https://links.lww.com/ALN/C852) further reports ECMO and non-ECMO patient characterization with and without thrombotic events. Patients with thrombotic events had a higher incidence of ventilator-associated pneumonia, dialysis, and mortality independent of ECMO status.

Table 2 summarizes the means of laboratory values of all patient time points stratified by the Berlin Criteria for ARDS severity at time of blood collection.¹⁶  In Supplemental Digital Content 5 table S4 (https://links.lww.com/ALN/C853), patients who at one point during their hospitalization met criteria for severe ARDS had higher mortality and morbidity, including elevated rates of ventilator-associated PNA, major hemorrhagic events, and major thrombotic events, as previously described, compared to patients who remained in either mild or moderate ARDS throughout their ICU course. As seen in table 2, plasminogen activator inhibitor 1 levels were significantly elevated during periods of severe ARDS compared to mild and moderate ARDS (severe, 44.2 ± 14.9 ng/ml vs. mild, 31.8 ± 14.7 ng/ml and moderate, 33.1 ± 15.9 ng/ml; P = 0.029 and 0.039, respectively; fig. 3). Elevation of microparticle-bound tissue factor, a marker of endothelial damage and thromboimmune activity, was also observed in severe ARDS, although this did not reach significance (severe, 1.8 ± 1.5 pg/ml; moderate, 1.2 ± 1.0 pg/ml; mild, 1.2 ± 0.8 pg/ml; P = 0.116; table 2; fig. 3). Additional nonsignificant differences associated with worsening Pao₂/Fio₂ ratios include elevation of tissue factor pathway inhibitor and vWF along with a reduction of ADAMTS13 (table 2).

We evaluated critically ill ICU patients with ARDS from SARS-CoV-2 infection to further characterize COVID-19-associated coagulopathy. While our cohort size is small, a stratified comorbidities analysis demonstrates that survivors and nonsurvivors had similar rates of cardiovascular disease, chronic lung injury, kidney disease, and diabetes. Interestingly, the survivor cohort had higher body mass indices compared to nonsurvivors. Obesity is associated with worse coagulopathy in the literature, presumably through baseline endothelial inflammation.^21,24,25  Our cohort did not demonstrate this association, as survivors had higher body mass indices than nonsurvivors, likely due to the small sample size. This suggests that the coagulopathy and the associated ARDS severity we describe are less dependent on the presence of higher body mass index or other identified chronic diseases.

Severe COVID-19 coagulopathy is associated with macrothrombotic events such as deep vein thrombosis, pulmonary embolism, and cerebrovascular accident leading to increased morbidity and mortality in this patient population. Fibrinogen, d-dimer, and vWF levels and reduced ADAMTS13 levels (an enzyme that shortens vWF long multimers) characterize the hypercoagulable state in COVID-19 patients with ARDS. Our study redemonstrates that patients with COVID-19 coagulopathy have shortened clot formation time and increased maximal clot firmness on viscoelastic testing.²⁶  We also found that levels of fibrinolysis-inhibiting plasminogen activator inhibitor 1 were elevated with no evidence of clot lysis on ROTEM (LI30 and LI45), a finding consistent with fibrinolytic suppression in COVID-19. Furthermore, patients experiencing a clinically significant thrombotic event during their hospital course had elevated plasminogen activator inhibitor 1 levels, vWF levels, and factor VIII activity compared to those that did not experience such events despite prophylactic anticoagulation (fig. 2).^27,28  These findings are consistent with recent studies of ICU patients with COVID-19 that have identified plasminogen activator inhibitor 1 and inhibition of fibrinolysis as predictors of mortality.¹⁵ 

Elevations in vWF, tissue factor pathway inhibitor, microparticle-bound tissue factor, and plasminogen activator inhibitor 1 were also observed in patients with severe ARDS, revealing an association between coagulopathy and ARDS severity in COVID-19 (fig. 3; table 2). Although previous studies have commented on the association between fibrinolytic inhibition and major thrombotic events in COVID-19,^29–34  our report links biomarkers, viscoelastic determination of hypercoagulability, and fibrinolytic suppression to the severity of hypoxemia in these patients. Our results describe this mechanism through elevations in endotheliopathic biomarkers and fibrinolytic inhibition, which may cause the extensive pulmonary microcirculatory thrombosis seen in ARDS secondary to COVID-19 leading to severe hypoxemia.^7,8 

While these microthrombotic changes and increased d-dimer levels are also seen in patients with disseminated intravascular coagulation (DIC), patients with severe COVID-19 present with normal platelet counts and prothrombin times (Supplemental Digital Content 2 table S2, https://links.lww.com/ALN/C850) unlike patients with DIC.³⁴  COVID-19 patients also lack the systemic vasoplegia and consumptive coagulopathy seen with DIC, likely due to the initial localized endothelial injury and subsequent thrombosis within the pulmonary microcirculation caused by SARS-CoV-2 infection.^7,35  When accompanied by upregulation of acute-phase reactants such as fibrinogen and vWF, COVID-19–associated coagulopathy most aligns with a thrombotic microangiopathic disorder originating at the alveolar–capillary interface, subsequently engendering the patients’ hypoxic state.

We found that nonsurvivors had higher levels of vWF and microparticle-bound tissue factor. Patients experiencing a major bleeding event had lower levels of ADAMTS13 compared to patients who did not. This demonstrates that markers consistent with severe endotheliopathy and thromboinflammatory response can distinguish outcomes even among the sickest patients.³⁶  While increased levels of vWF can reflect a normal host inflammatory response to infection, elevated levels can demonstrate endothelial injury. Elevated vWF is known to increase prothrombotic effects through multiple mechanisms including platelet activation and aggregation, as well as stabilization of factor VIII, the only intrinsic pathway factor produced by endothelium. Notably, the immediate upstream intrinsic clotting factor IX, produced by the liver, was not elevated in these patients. The decrease of ADAMTS13 results in larger procoagulant vWF multimers, which further exacerbates this endothelial-driven hypercoagulability. The degree of these changes can distinguish between differing severity of disease and survivors from nonsurvivors in critically ill patients.^37–40 

As a potential therapeutic strategy, lytic therapy is currently being investigated.⁴¹  Specific inhibition of plasminogen activator inhibitor 1 may also have utility in this disease process, and future studies from our group will explore the impact of an aptamer that inhibits the antiproteolytic activity of plasminogen activator inhibitor 1 in COVID-19.^42,43  These approaches are important as current studies involving therapeutic dose anticoagulation in the ICU have stopped due to futility based on the Accelerating COVID-19 Therapeutic Interventions and Vaccines studies.⁴⁴ 

We conclude that COVID-19–associated coagulopathy in ECMO patients should be considered separately from ECMO-naïve patients. Patients requiring ECMO have severe refractory hypoxemia resulting from pulmonary microcirculatory injury with subsequent higher risk of thrombotic and hemorrhagic events.⁴⁰  Rates of major thrombotic events were 7 of 9 (78%) in ECMO patients compared to 4 of 11 (36%) and 3 of 36 (8.3%) in non-ECMO nonsurvivors and survivors, respectively. Significant hemostatic changes observed on ROTEM viscoelastic testing demonstrated variability including the loss of the characteristic procoagulant profile of hemostatic biomarkers in some ECMO patients when compared to non-ECMO COVID-19 patients with severe ARDS (fig. 1; Supplemental Digital Content 3 fig. S1, https://links.lww.com/ALN/C851). Studies using ROTEM on COVID-19 patient samples describe a high rate of prothrombotic events for ECMO (90%) compared to non-ECMO (46%) patients but did not separate these cohorts when generating models predictive of thrombotic events.²⁶  Although ECMO patients demonstrated a loss in the procoagulant profile from a biomarker perspective, they have increased thrombotic outcomes, likely due to the addition of ECMO circulation, which provides a nonendothelial interface for contact activation of the coagulation cascade despite heparin anticoagulation.^45–47  This prothrombotic interface exacerbates the thromboinflammatory response observed in COVID-19, increasing risk for thrombotic and bleeding events through subsequent consumptive coagulopathy. This ECMO difference is reflected by procoagulant biomarkers through relative reduction of fibrinogen and vWF levels and apparent normalization of ROTEM tracings.⁴⁴  The tissue factor pathway inhibitor levels observed in our cohort’s ECMO patients are also higher than the tissue factor pathway inhibitor levels reported in the non–COVID-19 ECMO cohort by Mazzeffi et al.⁴⁸  (Supplemental Digital Content 2 table S2, https://links.lww.com/ALN/C850). This difference is likely due to widespread endotheliopathy associated with severe COVID-19 and tissue factor pathway inhibitor’s primary location on the endothelial surface and indicates the compounding coagulopathic insults of ECMO and SARS-CoV-2 infection.

The therapeutic heparinization required to maintain ECMO circuit patency in this hypercoagulable disease state increases risk of hemorrhagic events in these patients over their ECMO-naive counterparts, who generally receive prophylactic doses of low-molecular-weight heparin. Of note, 54 of 55 (96.4%) patients observed received either prophylactic or therapeutic anticoagulation with heparin products during hospitalization. Investigation into the combined effects of ECMO and COVID-19 versus other viral infections is needed to understand each prothrombotic stimuli and its contribution to the associated pathophysiology.

Despite having a large amount of data for analyses, this study was limited to the relatively small cohort size of this observational study. Due to inconsistent data across time points, we were unable to perform temporal analyses. To reduce bias through repeated measures, biomarker and laboratory data were either used on ICU day 1 or collapsed into maximum, minimum, and means during a patient’s ICU hospitalization. Possible selection bias could be present due to the limited sample size of participants. Larger population studies are needed to further characterize COVID-19 coagulopathy in ICU patients. This small cohort size also precludes detailed longitudinal analysis, which will be a valuable approach for future studies. Assessment of fibrinolytic inhibition would have been more robust with LI45 and LI60 data for all patients in the study, although the calculated mean difference of 1% between LI30 and LI45 indicates minimal clot dissolution between the two time points. Other groups have shown that fibrinolytic suppression measured by LI60 predicts thromboembolic complications in COVID-19 patients,^26,31,33  with even stronger predictive value if d-dimer levels are included.³¹  These findings demonstrate the clinical utility of ROTEM and the importance of these later time points in assessment of fibrinolytic abnormalities. Coagulation protein data were limited compared to clinical electronic health record data due to comparatively fewer time points for biorepository sampling and laboratory processing constraints. Additionally, an established link exists between obesity, poorer outcomes in COVID-19,^24,25  and the association between obesity and elevated markers of endothelial damage, including plasminogen activator inhibitor 1.^27,28  Future studies with larger patient cohorts will include the impact of body mass index on COVID-19 coagulopathy on ARDS severity given the elevated average of body mass index in our cohort.

We found that procoagulant biomarkers including those characteristic of endothelial injury are elevated in ICU patients with COVID-19 in association with severe hypoxemic respiratory failure. We note that ECMO-requiring COVID-19 patients need to be considered separately from the broader ICU cohort for analysis of coagulopathy given the consumptive coagulopathy engendered by the dual insult of SARS-CoV-2 infection and the ECMO circuit itself. We found evidence of fibrinolytic suppression on viscoelastic testing with elevated plasminogen activator inhibitor 1 levels that is more apparent in COVID-19 patients with severe disease who develop major thrombotic events. Coupled with markedly elevated d-dimer levels, these findings indicate that increased fibrin deposition occurs with decreased elimination in the microcirculation.²²  These findings warrant further investigation and encourage the development of potential therapeutic approaches limiting endothelial injury or working to counteract the pathologic sequela resulting from both the micro- and macrothrombotic pathology of severe COVID-19.

The authors thank the following people for their insightful conversations, technical and statistical guidance, and clinical research support: Gowthami M. Arepally, M.D., and Thomas Ortel, M.D., Ph.D. (Division of Hematology and Oncology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina); Tracey Truong, M.S., and Maragatha Kuchibhatla, Ph.D. (Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina); Maureane Hoffman, M.D., Ph.D. (Department of Pathology, Duke University School of Medicine, Durham, North Carolina); Nigel Mackman, Ph.D., and Alisa Wolberg, Ph.D. (Department of Pharmacology, University of North Carolina School of Medicine, Chapel Hill, North Carolina); Patty Lee, M.D., and Christina Barkauskas, M.D. (Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Duke University Medical Center, Durham, North Carolina); and Merry Jane Mullins, B.S., Allie Frear, B.S., and Raha Manyara, M.D., M.S.P.H. (Department of Surgery, Duke University School of Medicine, Durham, North Carolina).

Supported by National Institutes of Health, National Heart, Lung, and Blood Institute (Bethesda, Maryland) grant Nos. P01 283-2307 and K08130557 and discretionary funds from Duke University School of Medicine Department of Surgery (Durham, North Carolina; to Drs. Nair and Sullenger) and Department of Medicine/Division of Pulmonary, Allergy, and Critical Care Medicine (to Drs. Kraft, Chen, and Que).

Dr. Kraft declares the following financial relationships: Boehringer Ingelheim (Ingelheim, Germany), Shinonogi Inc. (Osaka, Japan), Paratek Pharmaceuticals (Boston, Massachusetts), La Jolla Pharmaceutical Company (La Jolla, California), Savara Pharmaceuticals (West Lake Hills, Texas), and American College of Chest Physicians (Northbrook, Illinois). Dr. Levy delares the following financial relationships: Instrumentation Labs (Bedford, Massachusetts), Merck (Darmstadt, Germany), and Octapharma (Lachen, Switzerland). The other authors declare no competing interests.