The impact of direct oral anticoagulants (DOACs) on laboratory assays used for thrombophilia testing (e.g., antithrombin, protein S, protein C, lupus anticoagulant and activated protein-C resistance) is a well-known issue and may cause false-positive and -negative results. Therefore, the correct interpretation of tests that are performed in patients taking DOACs is mandatory to prevent misclassification and the subsequent clinical consequences. We aimed at evaluating the efficiency of a new and simple procedure (DOAC-Stop®; Haematex Research, Hornsby, Australia) to overcome the effect of all DOACs in real-life settings and to assess the percentage of erroneous results due to the presence of DOACs on thrombophilia screening tests. For this purpose, 135 DOAC-treated patients (38 apixaban, 40 dabigatran, 15 edoxaban, and 42 rivaroxaban) and 20 control patients were enrolled. A significant drop in apixaban, dabigatran, edoxaban, and rivaroxaban plasma concentrations following the DOAC-Stop® treatment was observed (74.8–8.2 ng/mL [p < 0.0001], 95.9–4.7 ng/mL [p < 0.0001], 102.1–8.8 ng/mL [p = 0.001], and 111.3–7.0 ng/mL [p < 0.0001], respectively). The DOAC-Stop® treatment was mostly effective to overcome the effect of DOACs on PTT-LA, dilute Russell's viper venom time (dRVVT) screen, and dRVVT confirm tests. Using our procedures, false-positive results due to DOACs were observed only with lupus anticoagulant tests (up to 75%) and fell to zero after the DOAC-Stop® procedure, regardless of the DOAC considered. In conclusion, the DOAC-Stop® adsorbent procedure appeared to be an effective and simple way to overcome the interference of DOAC on coagulation tests and should facilitate the interpretation of thrombophilia screening tests in patients taking DOACs.

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Pseudothrombocytopenia (PTCP), a relative common finding in clinical laboratories, can lead to diagnostic errors, overtreatment, and further (even invasive) unnecessary testing. Clinical consequences with potential life-threatening events (e.g., unnecessary platelet transfusion, inappropriate treatment including splenectomy or corticosteroids) are still observed when PTCP is not readily detected. The phenomenon is even more complex when occurring with different anticoagulants. In this review we present a case of multi-anticoagulant PTCP, where we studied different parameters including temperature, amikacin supplementation, measurement methods, and type of anticoagulant. Prevalence, clinical risk factors, pre-analytical and analytical factors, along with clinical implications, will be discussed. The detection of an anticoagulant-dependent PTCP does not necessarily imply the presence of specific disorders. Conversely, the incidence of PTCP seems higher in patients receiving low molecular weight heparin, during hospitalization, or in men aged 50 years or older. New analytical technologies, such as fluorescence or optical platelet counting, will be soon overturning traditional algorithms and represent valuable diagnostic aids. A practical laboratory approach, based on current knowledge of PTCP, is finally proposed for overcoming spuriously low platelet counts.

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Preventing the cytokine storm observed in COVID-19 is a crucial goal for reducing the occurrence of severe acute respiratory failure and improving outcomes. Here, we identify Aldo-Keto Reductase 1B10 (AKR1B10) as a key enzyme involved in the expression of pro-inflammatory cytokines. The analysis of transcriptomic data from lung samples of patients who died from COVID-19 demonstrates an increased expression of the gene encoding AKR1B10. Measurements of the AKR1B10 protein in sera from hospitalised COVID-19 patients suggests a significant link between AKR1B10 levels and the severity of the disease. In macrophages and lung cells, the over-expression of AKR1B10 induces the expression of the pro-inflammatory cytokines Interleukin-6 (IL-6), Interleukin-1β (IL-1β) and Tumor Necrosis Factor a (TNFα), supporting the biological plausibility of an AKR1B10 involvement in the COVID-19-related cytokine storm. When macrophages were stressed by lipopolysaccharides (LPS) exposure and treated by Zopolrestat, an AKR1B10 inhibitor, the LPS-induced production of IL-6, IL-1β, and TNFα is significantly reduced, reinforcing the hypothesis that the pro-inflammatory expression of cytokines is AKR1B10-dependant. Finally, we also show that AKR1B10 can be secreted and transferred via extracellular vesicles between different cell types, suggesting that this protein may also contribute to the multi-organ systemic impact of COVID-19. These experiments highlight a relationship between AKR1B10 production and severe forms of COVID-19. Our data indicate that AKR1B10 participates in the activation of cytokines production and suggest that modulation of AKR1B10 activity might be an actionable pharmacological target in COVID-19 management.

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Continuous intravenous unfractionated heparin (UFH) is administered routinely in the intensive care unit (ICU) for the anticoagulation of patients, and monitoring is performed by the activated partial thromboplastin time (APTT) or anti-Xa activity. However, these strategies are associated with potentially large time intervals before dose adjustments, which could be detrimental to the patient. The aim of the study was to compare a point-of-care (POCT) version of the APTT to (i) laboratory-based APTT and (ii) measurements of anti-Xa activity in terms of correlation, agreement and turnaround time (TAT). Thirty-five ICU patients requiring UFH therapy were prospectively included and followed longitudinally for a maximum duration of 15 days. UFH was administered according to a local adaptation of Raschke and Amanzadeh’s aPTT nomograms. Simultaneous measurements of POCT-APTT (CoaguCheck® aPTT Test, Roche Diagnostics) on a drop of fresh whole blood, laboratory-based APTT (C.K. Prest®, Stago) and anti-Xa activity (STA®Liquid anti-Xa, Stago) were systematically performed two to six times a day. Antithrombin, C-reactive protein, fibrinogen, factor VIII and lupus anticoagulant were measured. The time tracking of sampling and analysis was recorded. The overall correlation between POCT-APTT and laboratory APTT (n = 795 pairs) was strongly positive (rs = 0.77, p < 0.0001), and between POCT-APTT and anti-Xa activity (n = 729 pairs) was weakly positive (rs = 0.46, p < 0.0001). Inter-method agreement (Cohen’s kappa (k)) between POCT and laboratory APTT was 0.27, and between POCT and anti-Xa activity was 0.30. The median TATs from sample collection to the lab delivery of results for lab-APTT and anti-Xa were 50.9 min (interquartile range (IQR), 38.4–69.1) and 66.3 min (IQR, 49.0–91.8), respectively, while the POCT delivered results in less than 5 min (p < 0.0001). Although the use of the POCT-APTT device significantly reduced the time to results, the results obtained were poorly consistent with those obtained by lab-APTT or anti-Xa activity, and therefore it should not be used with the nomograms developed for lab-APTT.