The Choice between Plasma-Based Common Coagulation Tests and Cell-Based Viscoelastic Tests in Monitoring Hemostatic Competence: Not an either-or Proposition.

There has been a significant interest in the last decade in the use of viscoelastic tests (VETs) to determine the hemostatic competence of bleeding patients. Previously, common coagulation tests (CCTs) such as the prothrombin time (PT) and partial thromboplastin time (PTT) were used to assist in the guidance of blood component and hemostatic adjunctive therapy for these patients. However, the experience of decades of VET use in liver failure with transplantation, cardiac surgery, and trauma has now spread to obstetrical hemorrhage and congenital and acquired coagulopathies. Since CCTs measure only 5 to 10% of the lifespan of a clot, these assays have been found to be of limited use for acute surgical and medical conditions, whereby rapid results are required. However, there are medical indications for the PT/PTT that cannot be supplanted by VETs. Therefore, the choice of whether to use a CCT or a VET to guide blood component therapy or hemostatic adjunctive therapy may often require consideration of both methodologies. In this review, we provide examples of the relative indications for CCTs and VETs in monitoring hemostatic competence of bleeding patients.

COVID-associated non-vasculitic thrombotic retiform purpura of the face and extremities: A case report.

SARS-CoV-2 infection can manifest many rashes. However, thrombotic retiform purpura rarely occurs during COVID-19 illness. Aggressive anti-COVID-19 therapy with a high-dose steroid regimen led to rapid recovery. This immunothrombotic phenomenon likely represents a poor type 1 interferon response and complement activation on the endothelial surface in response to acute infection.

Relative Hypercoagulopathy of the SARS-CoV-2 Beta and Delta Variants when Compared to the Less Severe Omicron Variants Is Related to TEG Parameters, the Extent of Fibrin Amyloid Microclots, and the Severity of Clinical Illness.

Earlier variants of SARS-CoV-2 have been associated with hypercoagulability and an extensive formation of fibrin amyloid microclots, which are considered to contribute to the pathology of the coronavirus 2019 disease (COVID-19). The newer omicron variants appear to be far more transmissible, but less virulent, even when taking immunity acquired from previous infections or vaccination into account. We here show that while the clotting parameters associated with omicron variants are significantly raised over those of healthy, matched controls, they are raised to levels significantly lower than those seen with more severe variants such as beta and delta. We also observed that individuals infected with omicron variants manifested less extensive microclot formation in platelet-poor plasma compared with those harboring the more virulent variants. The measurement of clotting effects between the different variants acts as a kind of "internal control" that demonstrates the relationship between the extent of coagulopathies and the virulence of the variant of interest. This adds to the evidence that microclots may play an important role in reflecting the severity of symptoms observed in COVID-19.

A Comparison of Univariate and Multivariate Forecasting Models Predicting Emergency Department Patient Arrivals during the COVID-19 Pandemic.

The COVID-19 pandemic has heightened the existing concern about the uncertainty surrounding patient arrival and the overutilization of resources in emergency departments (EDs). The prediction of variations in patient arrivals is vital for managing limited healthcare resources and facilitating data-driven resource planning. The objective of this study was to forecast ED patient arrivals during a pandemic over different time horizons. A secondary objective was to compare the performance of different forecasting models in predicting ED patient arrivals. We included all ED patient encounters at an urban teaching hospital between January 2019 and December 2020. We divided the data into training and testing datasets and applied univariate and multivariable forecasting models to predict daily ED visits. The influence of COVID-19 lockdown and climatic factors were included in the multivariable models. The model evaluation consisted of the root mean square error (RMSE) and mean absolute error (MAE) over different forecasting horizons. Our exploratory analysis illustrated that monthly and weekly patterns impact daily demand for care. The Holt-Winters approach outperformed all other univariate and multivariable forecasting models for short-term predictions, while the Long Short-Term Memory approach performed best in extended predictions. The developed forecasting models are able to accurately predict ED patient arrivals and peaks during a surge when tested on two years of data from a high-volume urban ED. These short- and long-term prediction models can potentially enhance ED and hospital resource planning.

Preventing Thrombohemorrhagic Complications of Heparinized COVID-19 Patients Using Adjunctive Thromboelastography: A Retrospective Study.

BACKGROUND: The treatment of COVID-19 patients with heparin is not always effective in preventing thrombotic complications, but can also be associated with bleeding complications, suggesting a balanced approach to anticoagulation is needed. A prior pilot study supported that thromboelastography and conventional coagulation tests could predict hemorrhage in COVID-19 in patients treated with unfractionated heparin or enoxaparin, but did not evaluate the risk of thrombosis. METHODS: This single-center, retrospective study included 79 severely ill COVID-19 patients anticoagulated with intermediate or therapeutic dose unfractionated heparin. Two stepwise logistic regression models were performed with bleeding or thrombosis as the dependent variable, and thromboelastography parameters and conventional coagulation tests as the independent variables. RESULTS: Among all 79 patients, 12 (15.2%) had bleeding events, and 20 (25.3%) had thrombosis. Multivariate logistic regression analysis identified a prediction model for bleeding (adjusted R2 = 0.787, p < 0.001) comprised of increased reaction time (p = 0.016), decreased fibrinogen (p = 0.006), decreased D-dimer (p = 0.063), and increased activated partial thromboplastin time (p = 0.084). Multivariate analysis of thrombosis identified a weak prediction model (adjusted R2 = 0.348, p < 0.001) comprised of increased D-dimer (p < 0.001), decreased reaction time (p = 0.002), increased maximum amplitude (p < 0.001), and decreased alpha angle (p = 0.014). Adjunctive thromboelastography decreased the use of packed red cells (p = 0.031) and fresh frozen plasma (p < 0.001). CONCLUSIONS: Significantly, this study demonstrates the need for a precision-based titration strategy of anticoagulation for hospitalized COVID-19 patients. Since severely ill COVID-19 patients may switch between thrombotic or hemorrhagic phenotypes or express both simultaneously, institutions may reduce these complications by developing their own titration strategy using daily conventional coagulation tests with adjunctive thromboelastography.