Viscoelastometric Testing to Assess Hemostasis of COVID-19: A Systematic Review

Infection by SARS-CoV-2 is associated with a high risk of thrombosis. The laboratory documentation of hypercoagulability and impaired fibrinolysis remains a challenge. Our aim was to assess the potential usefulness of viscoelastometric testing (VET) to predict thrombotic events in COVID-19 patients according to the literature. We also (i) analyzed the impact of anticoagulation and the methods used to neutralize heparin, (ii) analyzed whether maximal clot mechanical strength brings more information than Clauss fibrinogen, and (iii) critically scrutinized the diagnosis of hypofibrinolysis. We performed a systematic search in PubMed and Scopus databases until 31st December 2020. VET methods and parameters, and patients' features and outcomes were extracted. VET was performed for 1063 patients (893 intensive care unit (ICU) and 170 non-ICU, 44 studies). There was extensive heterogeneity concerning study design, VET device used (ROTEM, TEG, Quantra and ClotPro) and reagents (with non-systematic use of heparin neutralization), timing of assay, and definition of hypercoagulable state. Notably, only 4 out of 25 studies using ROTEM reported data with heparinase (HEPTEM). The common findings were increased clot mechanical strength mainly due to excessive fibrinogen component and impaired to absent fibrinolysis, more conspicuous in the presence of an added plasminogen activator. Only 4 studies out of the 16 that addressed the point found an association of VETs with thrombotic events. So-called functional fibrinogen assessed by VETs showed a variable correlation with Clauss fibrinogen. Abnormal VET pattern, often evidenced despite standard prophylactic anticoagulation, tended to normalize after increased dosing. VET studies reported heterogeneity, and small sample sizes do not support an association between the poorly defined prothrombotic phenotype of COVID-19 and thrombotic events

The risk of COVID-19 death is much greater and age dependent with type I IFN autoantibodies

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection fatality rate (IFR) doubles with every 5 y of age from childhood onward. Circulating autoantibodies neutralizing IFN-α, IFN-ω, and/or IFN-β are found in ∼20% of deceased patients across age groups, and in ∼1% of individuals aged 4% of those >70 y old in the general population. With a sample of 1,261 unvaccinated deceased patients and 34,159 individuals of the general population sampled before the pandemic, we estimated both IFR and relative risk of death (RRD) across age groups for individuals carrying autoantibodies neutralizing type I IFNs, relative to noncarriers. The RRD associated with any combination of autoantibodies was higher in subjects under 70 y old. For autoantibodies neutralizing IFN-α2 or IFN-ω, the RRDs were 17.0 (95% CI: 11.7 to 24.7) and 5.8 (4.5 to 7.4) for individuals <70 y and ≥70 y old, respectively, whereas, for autoantibodies neutralizing both molecules, the RRDs were 188.3 (44.8 to 774.4) and 7.2 (5.0 to 10.3), respectively. In contrast, IFRs increased with age, ranging from 0.17% (0.12 to 0.31) for individuals <40 y old to 26.7% (20.3 to 35.2) for those ≥80 y old for autoantibodies neutralizing IFN-α2 or IFN-ω, and from 0.84% (0.31 to 8.28) to 40.5% (27.82 to 61.20) for autoantibodies neutralizing both. Autoantibodies against type I IFNs increase IFRs, and are associated with high RRDs, especially when neutralizing both IFN-α2 and IFN-ω. Remarkably, IFRs increase with age, whereas RRDs decrease with age. Autoimmunity to type I IFNs is a strong and common predictor of COVID-19 death.The Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute; The Rockefeller University; the St. Giles Foundation; the NIH (Grants R01AI088364 and R01AI163029); the National Center for Advancing Translational Sciences; NIH Clinical and Translational Science Awards program (Grant UL1 TR001866); a Fast Grant from Emergent Ventures; Mercatus Center at George Mason University; the Yale Center for Mendelian Genomics and the Genome Sequencing Program Coordinating Center funded by the National Human Genome Research Institute (Grants UM1HG006504 and U24HG008956); the Yale High Performance Computing Center (Grant S10OD018521); the Fisher Center for Alzheimer’s Research Foundation; the Meyer Foundation; the JPB Foundation; the French National Research Agency (ANR) under the “Investments for the Future” program (Grant ANR-10-IAHU-01); the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (Grant ANR-10-LABX-62-IBEID); the French Foundation for Medical Research (FRM) (Grant EQU201903007798); the French Agency for Research on AIDS and Viral hepatitis (ANRS) Nord-Sud (Grant ANRS-COV05); the ANR GENVIR (Grant ANR-20-CE93-003), AABIFNCOV (Grant ANR-20-CO11-0001), CNSVIRGEN (Grant ANR-19-CE15-0009-01), and GenMIS-C (Grant ANR-21-COVR-0039) projects; the Square Foundation; Grandir–Fonds de solidarité pour l’Enfance; the Fondation du Souffle; the SCOR Corporate Foundation for Science; The French Ministry of Higher Education, Research, and Innovation (Grant MESRI-COVID-19); Institut National de la Santé et de la Recherche Médicale (INSERM), REACTing-INSERM; and the University Paris Cité. P. Bastard was supported by the FRM (Award EA20170638020). P. Bastard., J.R., and T.L.V. were supported by the MD-PhD program of the Imagine Institute (with the support of Fondation Bettencourt Schueller). Work at the Neurometabolic Disease lab received funding from Centre for Biomedical Research on Rare Diseases (CIBERER) (Grant ACCI20-767) and the European Union's Horizon 2020 research and innovation program under grant agreement 824110 (EASI Genomics). Work in the Laboratory of Virology and Infectious Disease was supported by the NIH (Grants P01AI138398-S1, 2U19AI111825, and R01AI091707-10S1), a George Mason University Fast Grant, and the G. Harold and Leila Y. Mathers Charitable Foundation. The Infanta Leonor University Hospital supported the research of the Department of Internal Medicine and Allergology. The French COVID Cohort study group was sponsored by INSERM and supported by the REACTing consortium and by a grant from the French Ministry of Health (Grant PHRC 20-0424). The Cov-Contact Cohort was supported by the REACTing consortium, the French Ministry of Health, and the European Commission (Grant RECOVER WP 6). This work was also partly supported by the Intramural Research Program of the National Institute of Allergy and Infectious Diseases and the National Institute of Dental and Craniofacial Research, NIH (Grants ZIA AI001270 to L.D.N. and 1ZIAAI001265 to H.C.S.). This program is supported by the Agence Nationale de la Recherche (Grant ANR-10-LABX-69-01). K.K.’s group was supported by the Estonian Research Council, through Grants PRG117 and PRG377. R.H. was supported by an Al Jalila Foundation Seed Grant (Grant AJF202019), Dubai, United Arab Emirates, and a COVID-19 research grant (Grant CoV19-0307) from the University of Sharjah, United Arab Emirates. S.G.T. is supported by Investigator and Program Grants awarded by the National Health and Medical Research Council of Australia and a University of New South Wales COVID Rapid Response Initiative Grant. L.I. reports funding from Regione Lombardia, Italy (project “Risposta immune in pazienti con COVID-19 e co-morbidità”). This research was partially supported by the Instituto de Salud Carlos III (Grant COV20/0968). J.R.H. reports funding from Biomedical Advanced Research and Development Authority (Grant HHSO10201600031C). S.O. reports funding from Research Program on Emerging and Re-emerging Infectious Diseases from Japan Agency for Medical Research and Development (Grant JP20fk0108531). G.G. was supported by the ANR Flash COVID-19 program and SARS-CoV-2 Program of the Faculty of Medicine from Sorbonne University iCOVID programs. The 3C Study was conducted under a partnership agreement between INSERM, Victor Segalen Bordeaux 2 University, and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study was also supported by the Caisse Nationale d’Assurance Maladie des Travailleurs Salariés, Direction générale de la Santé, Mutuelle Générale de l’Education Nationale, Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France, and Ministry of Research–INSERM Program “Cohortes et collections de données biologiques.” S. Debette was supported by the University of Bordeaux Initiative of Excellence. P.K.G. reports funding from the National Cancer Institute, NIH, under Contract 75N91019D00024, Task Order 75N91021F00001. J.W. is supported by a Research Foundation - Flanders (FWO) Fundamental Clinical Mandate (Grant 1833317N). Sample processing at IrsiCaixa was possible thanks to the crowdfunding initiative YoMeCorono. Work at Vall d’Hebron was also partly supported by research funding from Instituto de Salud Carlos III Grant PI17/00660 cofinanced by the European Regional Development Fund (ERDF/FEDER). C.R.-G. and colleagues from the Canarian Health System Sequencing Hub were supported by the Instituto de Salud Carlos III (Grants COV20_01333 and COV20_01334), the Spanish Ministry for Science and Innovation (RTC-2017-6471-1; AEI/FEDER, European Union), Fundación DISA (Grants OA18/017 and OA20/024), and Cabildo Insular de Tenerife (Grants CGIEU0000219140 and “Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19”). T.H.M. was supported by grants from the Novo Nordisk Foundation (Grants NNF20OC0064890 and NNF21OC0067157). C.M.B. is supported by a Michael Smith Foundation for Health Research Health Professional-Investigator Award. P.Q.H. and L. Hammarström were funded by the European Union’s Horizon 2020 research and innovation program (Antibody Therapy Against Coronavirus consortium, Grant 101003650). Work at Y.-L.L.’s laboratory in the University of Hong Kong (HKU) was supported by the Society for the Relief of Disabled Children. MBBS/PhD study of D.L. in HKU was supported by the Croucher Foundation. J.L.F. was supported in part by the Evaluation-Orientation de la Coopération Scientifique (ECOS) Nord - Coopération Scientifique France-Colombie (ECOS-Nord/Columbian Administrative department of Science, Technology and Innovation [COLCIENCIAS]/Colombian Ministry of National Education [MEN]/Colombian Institute of Educational Credit and Technical Studies Abroad [ICETEX, Grant 806-2018] and Colciencias Contract 713-2016 [Code 111574455633]). A. Klocperk was, in part, supported by Grants NU20-05-00282 and NV18-05-00162 issued by the Czech Health Research Council and Ministry of Health, Czech Republic. L.P. was funded by Program Project COVID-19 OSR-UniSR and Ministero della Salute (Grant COVID-2020-12371617). I.M. is a Senior Clinical Investigator at the Research Foundation–Flanders and is supported by the CSL Behring Chair of Primary Immunodeficiencies (PID); by the Katholieke Universiteit Leuven C1 Grant C16/18/007; by a Flanders Institute for Biotechnology-Grand Challenges - PID grant; by the FWO Grants G0C8517N, G0B5120N, and G0E8420N; and by the Jeffrey Modell Foundation. I.M. has received funding under the European Union’s Horizon 2020 research and innovation program (Grant Agreement 948959). E.A. received funding from the Hellenic Foundation for Research and Innovation (Grant INTERFLU 1574). M. Vidigal received funding from the São Paulo Research Foundation (Grant 2020/09702-1) and JBS SA (Grant 69004). The NH-COVAIR study group consortium was supported by a grant from the Meath Foundation.Peer reviewe

Are antiphospholipid antibodies associated with thrombotic complications in critically ill COVID-19 patients?

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Pathophysiological Processes Underlying the High Prevalence of Deep Vein Thrombosis in Critically Ill COVID-19 Patients

International audienceCoronavirus disease 2019 (COVID-19) predisposes to deep vein thrombosis (DVT) and pulmonary embolism (PE) particularly in mechanically ventilated adults with severe pneumonia. The extremely high prevalence of DVT in the COVID-19 patients hospitalized in the intensive care unit (ICU) has been established between 25 and 84% based on studies including systematic duplex ultrasound of the lower limbs when prophylactic anticoagulation was systematically administrated. DVT prevalence has been shown to be markedly higher than in mechanically ventilated influenza patients (6–8%). Unusually high inflammatory and prothrombotic phenotype represents a striking feature of COVID-19 patients, as reflected by markedly elevated reactive protein C, fibrinogen, interleukin 6, von Willebrand factor, and factor VIII. Moreover, in critically ill patients, venous stasis has been associated with the prothrombotic phenotype attributed to COVID-19, which increases the risk of thrombosis. Venous stasis results among others from immobilization under muscular paralysis, mechanical ventilation with high positive end-expiratory pressure, and pulmonary microvascular network injuries or occlusions. Venous return to the heart is subsequently decreased with increase in central and peripheral venous pressures, marked proximal and distal veins dilation, and drops in venous blood flow velocities, leading to a spontaneous contrast “sludge pattern” in veins considered as prothrombotic. Together with endothelial lesions and hypercoagulability status, venous stasis completes the Virchow triad and considerably increases the prevalence of DVT and PE in critically ill COVID-19 patients, therefore raising questions regarding the optimal doses for thromboprophylaxis during ICU stay

High Prevalence of Deep Vein Thrombosis in Mechanically Ventilated COVID-19 Patients

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von Willebrand factor/ADAMTS13 axis and venous thromboembolism in moderate‐to‐severe COVID‐19 patients

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Contrast between Prevalence of HIT Antibodies and Confirmed HIT in Hospitalized COVID-19 Patients: A Prospective Study with Clinical Implications

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Case series of massive direct oral anticoagulant ingestion—Treatment and pharmacokinetics data

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Performance of diagnostic scores in thrombotic microangiopathy patients in the intensive care unit: a monocentric study

International audienceEarly thrombotic thrombocytopenic purpura (TTP) recognition is critical as this disease is almost always lethal if not treated promptly with therapeutic plasma exchanges. Currently, as ADAMTS13 (a disintegrin and metalloproteinase with a thrombospondin type 1 motif, member 13) activity is not widely available in emergency, scores have been developed to help differentiating TTP from other thrombotic microangiopathies (TMAs). The aim of this work was to study the accuracy of these diagnostic scores in the intensive care unit (ICU) setting. Performance of both Coppo and PLASMIC scores was studied in a cohort of adult TMA patients requiring admission to one university hospital ICU from 2006 to 2017. Receiver operating characteristic (ROC) curves were established, and confidence intervals of the area under the curve (AUC) were determined. Multivariate logistic regression analysis was performed to identify parameters specifically associated with TTP, to compare diagnostic scores and to elaborate more accurate diagnostic models. During the study period, 154 TMA patients required ICU admission, including 99 (64.2%) TTP and 55 (35.7%) non-TTP patients. AUC under the ROC curve in predicting TTP was 0.86 (95% confidence interval [CI]: 0.81-0.92) for the Coppo score, 0.67 (95% CI: 0.58-0.76) for the PLASMIC score, and 0.86 (95% CI: 0.81-0.92) for platelet count alone. Platelet count ≤20 G/L, determined as the best cut-off rate for thrombocytopenia, performed similarly to the Coppo score and better than the PLASMIC score to differentiate TTP from non-TTP patients, both using AUC ROC curve and logistic regression. In a monocentric cohort of TMA patients requiring ICU admission, the PLASMIC score had limited performance for the diagnosis of TTP. The performance of the Coppo score was good but similar to a single highly discriminant item: platelet count ≤20 G/L at admission

No VTE Recurrence After 1-Year Follow-Up of Hospitalized Patients With COVID-19 and a VTE Event

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