Orthotopic liver transplantation can be associated with haemorrhage, particularly in patients with severe liver dysfunction. We assessed the value of rotation thromboelastometry (ROTEM®) to monitor coagulation in the operating theatre, its correlation with routine laboratory findings, and its ability to guide platelet (Plt) and fibrinogen (Fg) transfusion. Twenty-three patients were included in this prospective observational study. Laboratory tests and ROTEM® tests (EXTEM, INTEM, FIBTEM, and APTEM) were performed six times during the procedure. Correlations between laboratory findings and ROTEM® parameters were sought. Thresholds for ROTEM® parameters were determined with receiver-operating characteristic (ROC) curve analysis according to Plt count and Fg levels. Clot amplitude at 10 min (A10) of EXTEM was well correlated with Plt count and Fg levels (R2=0.46 and 0.52, respectively, P<0.0001). FIBTEM A10 was correlated with Fg (R2=0.55, P<0.0001). ROC analysis showed that EXTEM A10 with a threshold of 29 mm predicted thrombocytopenia with a sensitivity of 79% and a specificity of 60%, and a threshold of 26 mm predicted hypofibrinogenaemia with a sensitivity of 83% and a specificity of 75%. ROTEM® is useful for the global assessment of coagulation in the operating theatre. EXTEM was the most informative for assessing the whole coagulation process and A10 showed value in guiding Plt and Fg transfusion.
The goal of this study was to compare stroke volume variation (SVV) assessed from a peripheral artery with the Vigileo/FloTrac system (SVV-FloTrac) with SVV derived close to the heart by aortic Doppler (SVV-Doppler). Thirty patients undergoing liver transplantation underwent simultaneous SVV-FloTrac and SVV-Doppler measurements before and after intravascular volume expansion. SVV-FloTrac and SVV-Doppler comparison before intravascular volume expansion showed a mean bias of 0.7%, and 95% limits of agreement of -4.2% to 5.5%. The areas under the receiver operating characteristic curves generated to discriminate responders and nonresponders to intravascular volume expansion were not different for SVV-FloTrac and SVV-Doppler. SVV-FloTrac and SVV-Doppler measurements show acceptable bias and limits of agreement, and similar performance in terms of fluid responsiveness in patients undergoing liver transplantation.
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.
Respiratory-induced pulse pressure variations obtained with an arterial line (ΔPP(ART)) indicate fluid responsiveness in mechanically ventilated patients. The Infinity® CNAP™ SmartPod® (Dräger Medical AG & Co. KG, Lübeck, Germany) provides noninvasive continuous beat-to-beat arterial blood pressure measurements and a near real-time pressure waveform. We hypothesized that respiratory-induced pulse pressure variations obtained with the CNAP system (ΔPP(CNAP)) predict fluid responsiveness as well as ΔPP(ART) predicts fluid responsiveness in mechanically ventilated patients during general anesthesia. Thirty-five patients undergoing vascular surgery were studied after induction of general anesthesia. Stroke volume (SV) measured with the Vigileo™/FloTrac™ (Edwards Lifesciences, Irvine, CA), ΔPP(ART), and ΔPP(CNAP) were recorded before and after intravascular volume expansion (VE) (500 mL of 6% hydroxyethyl starch 130/0.4). Subjects were defined as responders if SV increased by ≥15% after VE. Twenty patients responded to VE and 15 did not. The correlation coefficient between ΔPP(ART) and ΔPP(CNAP) before VE was r = 0.90 (95% confidence interval [CI] = 0.84-0.96; P < 0.0001). Before VE, ΔPP(ART) and ΔPP(CNAP) were significantly higher in responders than in nonresponders (P < 0.0001). The values of ΔPP(ART) and ΔPP(CNAP) before VE were significantly correlated with the percent increase in SV induced by VE (respectively, r(2) = 0.50; P < 0.0001 and r(2) = 0.57; P < 0.0001). Before VE, a ΔPP(ART) >10% discriminated between responders and nonresponders with a sensitivity of 90% (95% CI = 69%-99%) and a specificity of 87% (95% CI = 60%-98%). The area under the receiver operating characteristic (ROC) curve was 0.957 ± 0.035 for ΔPP(ART). Before VE, a ΔPP(CNAP) >11% discriminated between responders and nonresponders with a sensitivity of 85% (95% CI = 62%-97%) and a specificity of 100% (95% CI = 78%-100%). The area under the ROC curve was 0.942 ± 0.040 for ΔPP(CNAP). There was no significant difference between the area under the ROC curve for ΔPP(ART) and ΔPP(CNAP). A value of ΔPP(CNAP) >11% has a sensitivity of at least 62% in predicting preload-dependent responders to VE in mechanically ventilated patients during general anesthesia.