Background: Viscoelastic coagulation testing has been suggested to help manage coagulopathy in critically ill patients with COVID-19. However, results from different viscoelastic devices are not readily comparable. ClotPro® is a novel thromboelastometry analyzer offering a wider range of commercially available assays.Methods: We compared the results from ClotPro with results from the well-established ROTEM® Delta device and conventional coagulation tests in critically ill patients with COVID-19.Results: Viscoelastic parameters indicated the presence of a potentially hypercoagulable state in the majority of patients. In up to 95 paired measurements, we found strong correlations between several parameters routinely used in clinical practice: (i) EX test vs. EXTEM CT, A5, A10, MCF, (ii) IN test vs. INTEM A5, A10, MCF, and (iii) FIB test vs. FIBTEM A5, A10, MCF (all R > 0.7 and p < 0.001). In contrast, IN test CT vs. INTEM CT showed only a moderate correlation (R = 0.53 and p < 0.001). Clot strength parameters of both devices exhibited strong correlations with platelet counts and fibrinogen levels (all R > 0.7 and p < 0.001). Divergent correlations of intrinsically activated assays with aPTT and anti-factor Xa activity were visible. Regarding absolute differences of test results, considerable delta occurred in CT, CFT, and clot strength parameters (all p < 0.001) between both devices.Conclusions: Several parameters obtained by ClotPro show strong correlations with ROTEM Delta. Due to weak correlations of intrinsically activated clotting times and considerable absolute differences in a number of parameters, our findings underline the need for device-specific algorithms in this patient cohort.

BACKGROUND: Dynamic mechanical analysis of blood clots can be used to detect the coagulability of blood. OBJECTIVE: We investigated the kinetics of clot formation by changing several blood components, and we looked into the clot “signature” at its equilibrium state by using viscoelastic and dielectric protocols. METHODS: Oscillating shear rheometry, ROTEM, and a dielectro-rheological device was used. RESULTS: In fibrinogen- spiked samples we found the classical high clotting ability: shortened onset, faster rate of clotting, and higher plateau stiffness. Electron microscopy explained the gain of stiffness. Incorporated RBCs weakened the clots. Reduction of temperature during the clotting process supported the development of high moduli by providing more time for fiber assembly. But at low HCT, clot firmness could be increased by elevating the temperature from 32 to 37°C. In contrast, when the fibrinogen concentration was modified, acceleration of clotting via temperature always reduced clot stiffness, whatever the initial fibrinogen concentration. Electrical resistance increased continuously during clotting; loss tangent (D) (relaxation frequency 249 kHz) decreased when clots became denser: fewer dipoles contributed to the relaxation process. The relaxation peak (Dmax) shifted to lower frequencies at higher platelet count. CONCLUSION: Increasing temperature accelerates clot formation but weakens clots. Rheometry and ROTEM correlate well.

BackgroundAnti-factor Xa activity has been suggested as a surrogate parameter for judging the effectiveness of pharmacological thromboprophylaxis with low molecular weight heparins in critically ill patients. However, this practice is not supported by evidence associating low anti-factor Xa activity with venous thromboembolism.MethodsWe performed a retrospective observational study including 1,352 critically ill patients admitted to 6 intensive care units of the Medical University of Vienna, Austria between 01/2015 and 12/2018. Included patients received prophylactically dosed enoxaparin (≤100 IU/kg body weight per day). We analyzed median peak, 12-h trough and 24-h trough anti-factor Xa activity per patient and compared anti-factor Xa activity between patients without vs. with venous thromboembolic events.Results19 patients (1.4%) developed a total of 22 venous thromboembolic events. We did not observe a difference of median (IQR) anti-factor Xa activity between patients without venous thromboembolism [peak 0.22 IU/mL (0.14–0.32); 12-h trough 0.1 IU/mL (<0.1–0.17), 24-h trough < 0.1 IU/mL (<0.1– <0.1)] vs. patients with venous thromboembolism [peak 0.33 IU/mL (0.14–0.34); 12-h trough 0.12 IU/mL (<0.1–0.26); 24-h trough < 0.1 IU/mL (<0.1–<0.1)].ConclusionPatients who developed venous thromboembolism had anti-factor Xa activities comparable to those who did not suffer from venous thromboembolism.

Intraoperative hypothermia increases perioperative morbidity and identifying patients at risk preoperatively is challenging. The aim of this study was to develop and internally validate prediction models for intraoperative hypothermia occurring despite active warming and to implement the algorithm in an online risk estimation tool. The final dataset included 36,371 surgery cases between September 2013 and May 2019 at the Vienna General Hospital. The primary outcome was minimum temperature measured during surgery. Preoperative data, initial vital signs measured before induction of anesthesia, and known comorbidities recorded in the preanesthetic clinic (PAC) were available, and the final predictors were selected by forward selection and backward elimination. Three models with different levels of information were developed and their predictive performance for minimum temperature below 36 °C and 35.5 °C was assessed using discrimination and calibration. Moderate hypothermia (below 35.5 °C) was observed in 18.2% of cases. The algorithm to predict inadvertent intraoperative hypothermia performed well with concordance statistics of 0.71 (36 °C) and 0.70 (35.5 °C) for the model including data from the preanesthetic clinic. All models were well-calibrated for 36 °C and 35.5 °C. Finally, a web-based implementation of the algorithm was programmed to facilitate the calculation of the probabilistic prediction of a patient’s core temperature to fall below 35.5 °C during surgery. The results indicate that inadvertent intraoperative hypothermia still occurs frequently despite active warming. Additional thermoregulatory measures may be needed to increase the rate of perioperative normothermia. The developed prediction models can support clinical decision-makers in identifying the patients at risk for intraoperative hypothermia and help optimize allocation of additional thermoregulatory interventions.