Assays to quantify fibrinolysis: strengths and limitations. Communication from the International Society on Thrombosis and Haemostasis Scientific and Standardization Committee on fibrinolysis.

Fibrinolysis is a series of enzymatic reactions that degrade insoluble fibrin. Plasminogen activators convert the zymogen plasminogen to the active serine protease plasmin, which cleaves and solubilizes crosslinked fibrin clots into fibrin degradation products. The quantity and quality of fibrinolytic enzymes, their respective inhibitors, and clot structure determine overall fibrinolysis. The quantity of protein can be measured by antigen-based assays, and both quantity and quality can be assessed using functional assays. Furthermore, variations of commonly used assays have been reported, which are tailored to address the role(s) of specific fibrinolytic factors and cellular elements (eg, platelets, neutrophils, and red blood cells). Although the concentration and/or activity of a protein can be quantified, how these individual components contribute to the overall fibrinolysis outcome can be challenging to determine. This difficulty is due to temporal changes within and around the thrombi during the clot breakdown, particularly the fibrin matrix structure, and composition. Furthermore, terms such as "fibrinolytic activity/potential," "plasminogen activation," and "plasmin activity" are often used interchangeably despite having different definitions. The purpose of this review is to 1) summarize the assays measuring fibrinolysis activity and potential, 2) facilitate the interpretation of data generated by these assays, and 3) summarize the strengths and limitations of these assays.

Comparison of three dosing intervals for the primary vaccination of the SARS-CoV-2 mRNA Vaccine (BNT162b2) on magnitude, neutralization capacity and durability of the humoral immune response in health care workers: A prospective cohort study.

OBJECTIVES: The dosing interval of a primary vaccination series can significantly impact on vaccine immunogenicity and efficacy. The current study compared 3 dosing intervals for the primary vaccination series of the BNT162b2 mRNA COVID-19 vaccine, on humoral immune response and durability against SARS-CoV-2 ancestral and Beta variants up to 9 months post immunization. METHODS: Three groups of age- and sex-matched healthcare workers (HCW) who received 2 primary doses of BNT162b2 separated by 35-days, 35-42 days or >42-days were enrolled. Vaccine induced antibody titers at 3 weeks, 3 and 6-9 months post-second dose were assessed. RESULTS: There were 309 age- and sex-matched HCW (mean age 43 [sd 13], 58% females) enrolled. Anti-SARS-CoV-2 binding (IgG, IgM, IgA) and neutralizing antibody titers showed significant waning in levels beyond 35 days post first dose. The second dose induced a significant rise in antibody titers, which peaked at 3 weeks and then declined at variable rates across groups. The magnitude, consistency and durability of response was greater for anti-Spike than anti-RBD antibodies; and for IgG than IgA or IgM. Compared to the shorter schedules, a longer interval of >42 days offered the highest binding and neutralizing antibody titers against SARS-CoV-2 ancestral and Beta (B1.351) variants beyond 3 months post-vaccination. CONCLUSIONS: This is the first comprehensive study to compare 3 dosing intervals for the primary vaccination of BNT162b2 mRNA COVID-19 vaccine implemented in the real world. These findings suggest that delaying the second dose beyond 42 days can potentiate and prolong the humoral response against ancestral and Beta variants of SARS-CoV-2 up to 9 months post-vaccination.

Cross-immunity against SARS-COV-2 variants of concern in naturally infected critically ill COVID-19 patients.

Critically ill patients infected with SARS-CoV-2 display adaptive immunity, but it is unknown if they develop cross-reactivity to variants of concern (VOCs). We profiled cross-immunity against SARS-CoV-2 VOCs in naturally infected, non-vaccinated, critically ill COVID-19 patients. Wave-1 patients (wild-type infection) were similar in demographics to Wave-3 patients (wild-type/alpha infection), but Wave-3 patients had higher illness severity. Wave-1 patients developed increasing neutralizing antibodies to all variants, as did patients during Wave-3. Wave-3 patients, when compared to Wave-1, developed more robust antibody responses, particularly for wild-type, alpha, beta and delta variants. Within Wave-3, neutralizing antibodies were significantly less to beta and gamma VOCs, as compared to wild-type, alpha and delta. Patients previously diagnosed with cancer or chronic obstructive pulmonary disease had significantly fewer neutralizing antibodies. Naturally infected ICU patients developed adaptive responses to all VOCs, with greater responses in those patients more likely to be infected with the alpha variant, versus wild-type.

Suicide Behavior Results From the U.S. Army's Suicide Prevention Leadership Tool Study: The Behavioral Health Readiness and Suicide Risk Reduction Review (R4).

INTRODUCTION: The U.S. Army developed a new tool called the Behavioral Health Readiness and Suicide Risk Reduction Review (R4) for suicide prevention. A 12-month evaluation study with the primary objective of testing the hypothesis (H1) that Army units receiving R4 would demonstrate improved outcomes in suicidal-behavior measures following the intervention, relative to control, was then conducted. The results of analyses to answer H1 are herein presented. MATERIALS AND METHODS: The R4 intervention (R4-tools/instructions/orientation) evaluation study, Institutional Review Board approved and conducted in May 2019-June 2020, drew samples from two U.S. Army divisions and employed a repeated measurement in pre-/post-quasi-experimental design, including a nonequivalent, but comparable, business-as-usual control. Intervention effectiveness was evaluated using self-report responses to suicide-related measures (Suicide Behaviors Questionnaire-Revised/total-suicide behaviors/ideations/plans/attempts/non-suicidal self-injuries) at 6-/12-month intervals. Analyses examined baseline to follow-up linked and cross-sectional cohorts, incidence/prevalence, and intervention higher-/lower-use R4 subanalyses. RESULTS: Both divisions demonstrated favorable in-study reductions in total-suicide burden, with relatively equivalent trends for total-suicide behaviors, total-suicide risk (Suicide Behaviors Questionnaire-Revised), suicidal ideations, and non-suicidal self-injuries. Although both demonstrated reductions in suicide plans, the control showed a more robust trend. Neither division demonstrated a significant reduction in suicide attempts, but subgroup analyses showed a significant reduction in pre-coronavirus disease 2019-attempt incidence among those with higher-use R4 relative to control. CONCLUSIONS: There is no evidence of harm associated with the R4 intervention. R4 effectiveness as a function of R4 itself requires confirmatory study. R4 is judged an improvement (no evidence of harm + weak evidence of effectiveness) over the status quo (no safety data or effectiveness studies) with regard to tool-based decision-making support for suicide prevention in the U.S. Army.

Immunothrombosis Biomarkers for Distinguishing Coronavirus Disease 2019 Patients From Noncoronavirus Disease Septic Patients With Pneumonia and for Predicting ICU Mortality.

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.

Biomarkers of coagulation, endothelial function, and fibrinolysis in critically ill patients with COVID-19: A single-center prospective longitudinal study.

BACKGROUND: Immunothrombosis and coagulopathy in the lung microvasculature may lead to lung injury and disease progression in coronavirus disease 2019 (COVID-19). We aim to identify biomarkers of coagulation, endothelial function, and fibrinolysis that are associated with disease severity and may have prognostic potential. METHODS: We performed a single-center prospective study of 14 adult COVID-19(+) intensive care unit patients who were age- and sex-matched to 14 COVID-19(-) intensive care unit patients, and healthy controls. Daily blood draws, clinical data, and patient characteristics were collected. Baseline values for 10 biomarkers of interest were compared between the three groups, and visualized using Fisher's linear discriminant function. Linear repeated-measures mixed models were used to screen biomarkers for associations with mortality. Selected biomarkers were further explored and entered into an unsupervised longitudinal clustering machine learning algorithm to identify trends and targets that may be used for future predictive modelling efforts. RESULTS: Elevated D-dimer was the strongest contributor in distinguishing COVID-19 status; however, D-dimer was not associated with survival. Variable selection identified clot lysis time, and antigen levels of soluble thrombomodulin (sTM), plasminogen activator inhibitor-1 (PAI-1), and plasminogen as biomarkers associated with death. Longitudinal multivariate k-means clustering on these biomarkers alone identified two clusters of COVID-19(+) patients: low (30%) and high (100%) mortality groups. Biomarker trajectories that characterized the high mortality cluster were higher clot lysis times (inhibited fibrinolysis), higher sTM and PAI-1 levels, and lower plasminogen levels. CONCLUSIONS: Longitudinal trajectories of clot lysis time, sTM, PAI-1, and plasminogen may have predictive ability for mortality in COVID-19.