Seheult, Jansen N.

AbstractVon Willebrand factor (VWF) is a multimeric glycoprotein with essential roles in primary hemostasis. Patients with von Willebrand disease (VWD), due to quantitative and/or qualitative defects of VWF usually experience mucocutaneous bleeding. Based on the laboratory results of VWF antigen, various VWF activities, factor VIII activity, and VWF multimer patterns, VWD can be categorized as type 1, 2, and 3 VWD. VWF multimer analysis by either manual or semi-automated electrophoresis and immunoblotting is a critical part of the laboratory testing to differentiate type 1, type 2 VWD, and subtypes of type 1 or 2 VWD. The multimer distribution patterns can also help to understand the underlying molecular mechanism of VWF synthesis, multimerization, and clearance defects in VWD. This review will cover VWF synthesis, multimerization, secretion, VWF multimer analysis, and VWF multimer interpretation of various types and subtypes of VWD.

AbstractBackgroundWhole blood (WB) is carried by special operations forces as part of a remote damage control resuscitation strategy. The effects of an underwater mission on the quality and coagulation profile of WB were simulated by exposure to hyperbaric pressures in a chamber.MethodsWB units collected in CPDA‐1 were exposed to three different combinations of hyperbaric pressure and duration of exposure: Group A 153.52 kPa (15.24 msw; 1.52 atm) for 4 h; n = 9, Group B 506.63 kPa (50.29 msw; 5.00 atm) for 1 h; n = 9, Group C 153.52 kPa (15.24 msw; 1.52 atm) for 1 h; n = 7. The following parameters were measured on each unit: prothrombin time/international normalized ratio, activated partial thromboplastin time, thromboelastography and concentration determinations of platelets, lactate, fibrinogen, and lactate dehydrogenase. Each sample underwent baseline, prepressurization, immediate postpressurization, and 6 h postpressurization laboratory testing.ResultsSix hours following hyperbaric exposure, the lactate concentration in group C was higher than prepressurization measurement and the platelet concentration in Group A was lower than prepressurization measurement. There were no changes in any of the other analyzed biochemical, coagulation and thromboelastogram parameters following exposure to hyperbaric stress.DiscussionThese data suggest that pressurization of WB up to 5 atm did not impact parameters tested. Changes observed in lactate and platelet count need further study, as well as complementary testing of red blood cell integrity. Further investigation of the hyperbaric extremes is necessary to determine if there is a damage inducing pressure to which WB should not be exposed.

Flow cytometric (FC) immunophenotyping is critical but time-consuming in diagnosing minimal residual disease (MRD). We evaluated whether human-in-the-loop artificial intelligence (AI) could improve the efficiency of clinical laboratories in detecting MRD in chronic lymphocytic leukemia (CLL). We developed deep neural networks (DNN) that were trained on a 10-color CLL MRD panel from treated CLL patients, including DNN trained on the full cohort of 202 patients (F-DNN) and DNN trained on 138 patients with low-event cases (MRD < 1000 events) (L-DNN). A hybrid DNN approach was utilized, with F-DNN and L-DNN applied sequentially to cases. “Ground truth” classification of CLL MRD was confirmed by expert analysis. The hybrid DNN approach demonstrated an overall accuracy of 97.1% (95% CI: 84.7–99.9%) in an independent cohort of 34 unknown samples. When CLL cells were reported as a percentage of total white blood cells, there was excellent correlation between the DNN and expert analysis [r > 0.999; Passing–Bablok slope = 0.997 (95% CI: 0.988–0.999) and intercept = 0.001 (95% CI: 0.000–0.001)]. Gating time was dramatically reduced to 12 s/case by DNN from 15 min/case by the manual process. The proposed DNN demonstrated high accuracy in CLL MRD detection and significantly improved workflow efficiency. Additional clinical validation is needed before it can be fully integrated into the existing clinical laboratory practice.

AbstractIntroductionHemolysis, icterus, and lipemia (HIL) are common pre‐analytical variables in the clinical laboratory. Understanding their effects on coagulation laboratory results is essential.MethodsHIL effects on the prothrombin time (PT), activated partial thromboplastin time (APTT), dilute Russell's viper venom time (DRVVT), thrombin time (TT), and protein C chromogenic activity (CFx) were evaluated on the ACL TOP 750 optical analyzer and STA‐R Evolution mechanical analyzer (PT and APTT only) by spiking normal donor, patient, and commercial control samples with varying concentrations of hemolysate, bilirubin, or a lipid emulsion. The relative difference or bias compared to the original results was determined.ResultsHemolysis (H) indices up to 900 mg/dL did not affect the APTT, PT, DRVVT Confirm, TT, and CFx; however, H indices above approximately 200 mg/dL resulted in a false‐negative DRVVT screen and screen/confirm ratio in samples with a lupus anticoagulant. There was an artifactual prolongation of the PT and APTT when conjugated bilirubin was dissolved in aqueous solvents and not when it was dissolved in dimethyl sulfoxide. Icterus (I) indices up to 45 mg/dL did not result in significant (>15%) bias for all assays evaluated. The PT and APTT assays failed to produce a robust clot curve when the lipemia (L) index exceeded 6000 milliabsorbance units (mAbs), and the TT and DRVVT assays failed when the L index exceeded 3000 mAbs; the CFx assay was unaffected by lipemia.ConclusionsVerification of the manufacturer's recommended interference thresholds is important since it may avoid inappropriate instrument flagging and/ or sample rejection.

Abstract Objectives Despite more than 40 years of experience performing the Bethesda assay (BA), poor intra- and interlaboratory precision remains the biggest laboratory challenge to date. Methods The BA procedure was modeled using stochastic simulation techniques to determine the precision of the BA up to dilutions of 1:4,096, to estimate the minimum significant relative change at various inhibitor titers, and to understand the laboratory procedural variables that could significantly affect the performance of the BA at high dilutions. Results Selecting the lowest dilution tube with a residual activity closest to 25% for calculating the reported Bethesda titer (BT), using a factor activity assay with a coefficient of variation less than or equal to 7.5% in the range of 15% to 50% factor activity level, performing the factor activity measurement in replicates, and minimizing pipette volumetric error resulted in the lowest imprecision in the reported BT. The factor neutralization kinetics of the inhibitor appear to have little impact on the precision of the assay if the incubation time is greater than 90 minutes. Conclusions This in silico model will assist future laboratory efforts in standardizing the quantification of specific coagulation factor inhibitors and improving the precision of the reported results.