International Journal of Laboratory Hematology最新文献

Introduction

It is recommended to use two chronometric assays of different principles for the diagnosis of lupus anticoagulant (LA), consisting in diluted Russell Viper Venom Time (dRVVT) and activated Partial Thromboplastin Time (aPTT). Yet, there are only a few integrated aPTT assays; this study aims to evaluate one of them: Cephen LS/Cephen (Hyphen Biomed).

Method

249 samples of patients were included in this study. Normal reference ranges were determined with platelet-poor plasma (PPP) from healthy blood donors. Performances were then evaluated by comparing Cephen LS/Cephen test results to the results of the laboratory's reference assay for the diagnosis of LA and to clinical data, both on non-anticoagulated and anticoagulated patients' samples (Unfractioned heparin (UFH), Low Molecular Weight Heparin (LMWH), Vitamin K Antagonists (VKA) and apixaban). Interference of UFH, LMWH and VKA were also evaluated thanks to spiking experiment of increasing heparin concentrations or factor deficiency.

Results

Cephen LS/Cephen test had 48.6% sensitivity towards LA. Although UFH and VKA seemed to interfere with this assay and were likely to cause false negative, LMWH and apixaban did not.

Finally, combination of Cephen LS/ Cephen with dRVVT had 89.0% sensitivity.

Conclusion

Cephen LS/Cephen seems relevant for LA diagnosis, in combination with dRVVT, and might be used in patients undergoing LMWH or apixaban therapy.

Introduction

Peripheral blood stem cells (PBSCs) are the most common source of stem cell transplantation, which depends on an adequate number of CD34+ cells. Although pre-apheresis CD34+ cell count is a standard guide for the collection, it is not always available. This study aimed to evaluate complete blood count parameters for predicting successful one-day autologous PBSC collection.

Methods

Data from the patients who underwent autologous PBSC collection at a tertiary care hospital were retrospectively reviewed.

Results

There were 123 patients (185 leukapheresis procedures). Successful PBSC collection (CD34+ cells ≥4.0 × 10⁶ cells/kg) was obtained in 85 patients (69.1%), of which 55 (44.7%) were successfully obtained on the first day. The median CD34+ collection efficiency was 44.1%. The mean platelet loss during apheresis was 39.9%. The adverse event rate was 18.9%. Patients in whom PBSCs were collected within one day were less likely to experience adverse effects related to leukapheresis. Pre-apheresis CD34+ cells ≥10 cells/μLand combined white blood cell (WBC) counts ≥5 × 10⁹/L and/or monocyte ≥10% were independently associated with the successful one-day PBSC collection (adjusted odds ratio 24.06, 95% confidence interval [CI] 5.30–109.10, p < 0.001; and 6.94, 95% CI 1.35–35.79, p = 0.021, respectively). Only pre-apheresis CD34+ cells had a strong correlation with the total stem cell yield.

Conclusions

To reduce the complication of leukapheresis, the combined pre-apheresis WBC ≥5 × 10⁹/L and/or monocyte ≥10% is a practical parameter to initiate a successfully one-day PBSC collection with or without pre-apheresis CD34+ cell results.

Introduction

Numerous AI-based systems are being developed to evaluate peripheral blood (PB) smears, but the feasibility of these systems on different smear preparation methods has not been fully understood. In this study, we assessed the impact of different smear preparation methods on the robustness of the deep learning system (DLS).

Methods

We collected 193 PB samples from patients, preparing a pair of smears for each sample using two systems: (1) SP50 smears, prepared by the DLS recommended fully automated slide preparation with double fan drying and staining (May–Grunwald Giemsa, M–G) system using SP50 (Sysmex) and (2) SP1000i smears, prepared by automated smear preparation with single fan drying by SP1000i (Sysmex) and manually stained with M–G. Digital images of PB cells were captured using DI-60 (Sysmex), and the DLS performed cell classification. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were used to evaluate the performance of the DLS.

Results

The specificity and NPV for all cell types were 97.4%–100% in both smear sets. The average sensitivity and PPV were 88.9% and 90.1% on SP50 smears, and 87.0% and 83.2% on SP1000i smears, respectively. The lower performance on SP1000i smears was attributed to the intra-lineage misclassification of neutrophil precursors and inter-lineage misclassification of lymphocytes.

Conclusion

The DLS demonstrated consistent performance in specificity and NPV for smears prepared by a system different from the recommended method. Our results suggest that applying an automated smear preparation system optimized for the DLS system may be important.

Introduction

This study aims to assess the performance of the platelet count estimation using artificial intelligence technology on the MC-80 digital morphology analyzer.

Methods

Digital morphology analyzer uses two different computational principles for platelet count estimation: based on PLT/RBC ratio (PLT-M1) and estimate factor (PLT-M2). 977 samples with various platelet counts (low, median, and high) were collected. Out of these, 271 samples were immunoassayed using CD61 and CD41 antibodies. The platelet counts obtained from the hematology analyzer (PLT-I and PLT-O), digital morphology analyzer (PLT-M1 and PLT-M2), and flow cytometry (PLT-IRM) were compared.

Results

There was no significant deviation observed before and after verification for both PLT-M1 and PLT-M2 across the analysis range (average bias: −0.845/−0.682, 95% limit of agreement (LOA): −28.675–26.985/−29.420–28.056). When platelet alarms appeared, PLT-M1/PLT-M2 showed the strongest correlation with PLT-IRM than PLT-I with PLT-IRM (r: 0.9814/0.9796 > 0.9601). The correlation between PLT-M1/PLT-M2 and PLT-IRM was strong for samples with interference, such as large platelets or RBC fragments, but relatively weak in small RBCs. The deviation between PLT-M1 and PLT-M2 is related to the number of RBCs. Compared with PLT-I, PLT-M1/PLT-M2 showed higher accuracy for platelet transfusion decisions, especially for samples with low-value PLT.

Conclusion

The novel platelet count estimation on the MC-80 digital morphology analyzer provides high accuracy, especially the reviewed result, which can effectively confirm suspicious platelet count.

Introduction

Specific assays of plasma rivaroxaban level are not always readily available with short turnaround time, which hamper the management of urgent clinical situations. In this study, we aimed to build a predictive formula of plasma rivaroxaban levels from international normalized ratio (INR) value and validated in real world clinical situations.

Methods

Ninety-four patients who were taking rivaroxaban participated in the study. Patients were randomized into testing cohort and validation cohorts. The prediction formula was built from the testing cohort and then validated in validation cohort. The predictive performance was further validated on real-world clinical requests.

Results

The root mean square error (RMSE) of the predictive formula for the testing and validation cohorts were 61.81 and 69.32 ng/mL, respectively. The sensitivity and specificity for the formula to predict the threshold plasma rivaroxaban level of 75 ng/mL were 95% (95% CI: 85.4%–100%) and 87.5% (95% CI: 71.3%–100%), respectively, in real-world clinical situations.

Conclusion

Plasma rivaroxaban level of threshold level of 75 ng/mL can be calculated from prediction formula by INR value with satisfactory accuracy and it can be used to guide the decision for reversal.

Introduction

Aplastic anemia (AA) and hypoplastic myelodysplastic syndrome (MDS-h) are bone marrow failure disease and difficult to distinguish merely by morphological analysis. In this study, we investigated the value of flow cytometry (FCM) in the differential diagnosis of AA and MDS-h.

Methods

We included 822 patients (626 control, 69 AA, 22 MDS-h and 105 dilution patients) from January 2017 to December 2022 for a retrospective study. Bone marrow myeloid progenitor (MP) cell and mature lymphocytes proportions were analyzed by FCM. The ratio of MP cell proportion and mature lymphocytes proportion, MPLR, was calculated. Data were compared by Kruskal–Wallis test. Differential diagnostic efficacy was evaluated by receiver operating characteristic (ROC) curve. Cutoff value was determined by the maximum Youden index.

Results

Bone marrow MP cell proportion and MPLR of MDS-h patients were higher than AA patients. Mature lymphocytes proportion of MDS-h patients was lower than AA patients. Area under ROC curve (AUC of ROC) of MP cell proportion, MPLR and mature lymphocytes proportion to distinguish AA from MDS-h were 0.992, 0.988, and 0.850, respectively. Moreover, MPLR of dilution patients was higher than AA patients but lower than MDS-h patients. The AUC of ROC curves of MPLR to distinguish MDS-h and AA from dilution were 0.854 and 0.871, respectively.

Conclusion

Bone marrow MP cell proportion and MPLR can effectively discriminate AA from MDS-h with similar differential efficacy, which is higher than mature lymphocytes proportion. Moreover, MPLR can evaluate the quality of bone marrow aspirates, which would interfere with the differential diagnosis.