International journal of laboratory hematology最新文献

Background: This study aims to evaluate the analytical performance of Sysmex and Mindray hematology analyzers for white blood cell (WBC), red blood cell (RBC), and platelet (PLT) counting. We calculated Z-scores and total allowable error (TEa) based on External Quality Assessment (EQA) data to provide references for laboratory quality improvement.

Methods: Sysmex and Mindray blood cell analysis systems are categorized into six groups based on instrument models, detection methods, or reagent properties: Sysmex (1), Sysmex (2), Sysmex (3) and Mindray (1), Mindray (2), Mindray (3). EQA data for WBC, RBC, and PLT from the National Center for Clinical Laboratories (NCCL) EQA programs (2020-2024) were collected. Robust means and standard deviations were calculated to determine Z-scores for each Sysmex and Mindray instrument group, assessing bias relative to assigned values. TEa for each instrument group of laboratories participating in the EQA activity (TEa-Lab) was calculated using bias and the robust coefficient of variation (CV). Subsequently, TEa-Lab was compared with the minimum, desirable, and optimal tiers of biological variation -based TEa (TEa-BV) to evaluate the performance specifications of participating laboratories.

Results: There were 10 instances where the absolute Z-score |Z| for WBC was greater than 2. These were distributed among the groups as follows: Sysmex (1): 0, Sysmex (2): 1, Sysmex (3): 0, Mindray (1): 3, Mindray (2): 3, Mindray (3): 3. For RBC, 22 instances had |Z| greater than 2, distributed as follows: Sysmex (1): 2, Sysmex (2): 3, Sysmex (3): 4, Mindray (1): 6, Mindray (2): 4, Mindray (3): 3. For PLT, 3 instances had |Z| greater than 2, with counts of Sysmex (2): 1, Sysmex (3): 1, Mindray (1): 1. Regarding the comparison TEa, for WBC, all groups, except Mindray (2), which met the desirable standard, achieved the optimal standard. For RBC, the Sysmex (3) group achieved the optimal standard; the Mindray (2) group met only the minimum standard, while the other groups met the desirable standard. For PLT, only the Sysmex (3) and Mindray (3) groups reached the minimum standard. The other peer groups did not meet the minimum standard.

Conclusions: Z-scores and TEa-Lab calculated from EQA data provide reliable insights into the performance of hematology analyzers. The performance of Sysmex and Mindray analyzers is stable and demonstrates advanced capabilities. This effectively supports the maintenance of laboratory quality systems and serves as a reference for mutual recognition of test results between laboratories.

Introduction: Platelet clumping is a pre-analytical artifact that leads to spurious thrombocytopenia, complicating laboratory interpretation and triggering unnecessary clinical interventions. Vortexing has been proposed as a corrective measure, yet the optimal duration, its applicability to transported samples, and its impact on WBC and RBC parameters remain poorly defined. This study aims to evaluate the efficacy and safety of vortexing across different durations to establish it as a standardized intervention in hematology laboratories.

Methods: A total of 730 EDTA-anticoagulated blood samples were analyzed. Samples were vortexed at 3200 rpm for 30 s, 1, or 2 min, using a fixed-speed vortex mixer. Platelet counts and interpretative messages were compared before and after vortexing using the Sysmex XN-10 platform. Stability of WBC and RBC parameters was also assessed.

Results: Vortexing significantly reduced platelet clumping flags, with 66% overall resolution and the highest effect in the 101-150 × 10⁹/L group (74%). Platelet counts improved across all durations, with 2 min yielding the highest median increase (+39.0 × 10⁹/L, p = 2.70 × 10^-12). The Kruskal-Wallis test confirmed statistically significant differences among vortexing durations (p = 1.24 × 10^-5). WBC and RBC parameters remained stable post-vortexing, supporting the method's safety.

Conclusion: Vortexing is a reliable, reproducible, and practical method for resolving platelet clumping in EDTA samples without compromising sample integrity. Its implementation can reduce redraws, minimize manual smear reviews, and streamline sample processing in high-volume hematology laboratories.

Purpose: The study aims to provide reference ranges of complete blood count (CBC) parameters in healthy children in Türkiye.

Methods: Children aged 1 month to -18 years who were administered to the Well Child Outpatients Clinics of Department/Unit of Social Pediatrics in 10 centers in different regions of Türkiye were included in the study. Complete blood count measurements were collected from these centers.

Results: A total of 24 115 healthy infants and children (12 204 males and 11 911 females) aged 1 month-18 years old were enrolled. Mean and median values of the red blood cell, white blood cell, and platelet parameters according to the age groups are presented in this study. In addition, the nonparametrically determined CBC reference intervals (RIs) corresponding to the 2.5th to 97.5th percentile, stratified by age and sex were provided.

Conclusion: This is the first study that established RIs for hematological parameters in Turkish children younger than 18 years old. These data provide a more reliable basis for hematological evaluation across all pediatric healthcare disciplines in Türkiye.

Background: Splenic B-cell lymphoma/leukemia includes a group of indolent small B-cell lymphomas/leukemias that share overlapping morphological and immunophenotypic features, making accurate diagnosis challenging. Specific gene rearrangements have not been commonly associated with splenic B-cell lymphomas/leukemias, and the TCL1 gene rearrangement-characteristic of T-cell prolymphocytic leukemia-has not been previously reported in B-cell lymphomas/leukemias. Here, we report two unique cases of splenic B-cell lymphoma/leukemia harboring an IGH::TCL1 rearrangement.

Case presentation: Patient #1 was a 74-year-old man with a 25-year history of low-grade B-cell leukemia involving the peripheral blood, spleen, and bone marrow. Patent #2 was a 54-year-old woman who recently presented with lymphocytosis and low-level bone marrow involvement. Both patients were asymptomatic and incidentally found to have lymphocytosis. The neoplastic cells in both cases displayed polar villous cytoplasmic projections, were of B-cell lineage, and were negative for CD5 and CD10. Notably, an IGH::TCL1 fusion was identified in both cases.

Conclusions: The identification of IGH::TCL1 fusion in these two cases of splenic B-cell lymphoma/leukemia suggests that TCL1 gene rearrangements can occur in B-cell lymphoma/leukemia and should not be considered exclusive to T-cell prolymphocytic leukemia. Accurate diagnosis of splenic B-cell lymphoma/leukemia with TCL1 rearrangement requires evaluation of morphologic and immunophenotypic features and genetic assessment of TCL1.

Introduction: Sickle cell disorders (SCD) are among the commonest symptomatic hemoglobinopathies worldwide. Their diagnosis involves multiple tests, including complete blood count, cation-exchange high-pressure liquid chromatography (CE-HPLC), hemoglobin electrophoresis, sickling tests, and molecular assays. We evaluated the diagnostic utilities of various testing methods for precise classification of SCDs in a specialist hematology laboratory of a tertiary-care teaching hospital.

Methods: Clinical, demographic and laboratory data from all SCDs diagnosed between January 2009 and June 2020 using CE-HPLC, slide-based sickling test and cellulose acetate electrophoresis were analyzed. Cases with over 50% S-window peaks on CE-HPLC were considered for HbS and β-thalassemia mutation testing. Performance indices of CE-HPLC, sickling test and electrophoresis were determined in molecularly-proven SCDs.

Results: The 261 cases with HbS variant included 56% (n = 147) sickle cell traits (SCT), 21% (n = 55) Sβ-thalassemia (Sβ), 17% (n = 45) sickle cell anemia (SCA), and 5% (n = 14) HbSD-Punjab (HbSD^Punjab) cases. Molecular analysis of 71 cases revealed that HbA2 ≥ 4.0% discriminated most efficiently between SCA and Sβ, with 95.2% sensitivity, 96.5% specificity and positive/negative predictive values of 97.5%/93.3%. The commonest β-thalassemia mutation in Sβ-thalassemia was HBB:c.92 + 5G>C (58.4%). Alkaline pH electrophoresis and sickling test showed 100% sensitivity. A diagnostic pitfall occurred in PCR-RFLP due to loss of DdeI restriction site.

Conclusions: Most SCDs encountered in a hospital-setting are reliably characterized by HPLC and hemogram data, supplemented with the sickling test and, where necessary, parental HPLCs. Molecular analysis aids in accurate characterization of complex cases and in resolution of diagnostic discrepancies; however, their own pitfalls must be borne in mind.