Annals of Laboratory Medicine最新文献

High-quality specimens are essential for accurate laboratory results. Preanalytical errors due to issues, such as hemolysis, microclotting, and insufficient specimen volume, account for 60%-70% of laboratory errors and frequently result from improper blood collection techniques or negligence during the collection process. Therefore, standardized blood collection guidelines and continuous education are required. In Korea, standardized venous blood collection procedures have not yet been fully established, highlighting the need for an evidence-based protocol tailored to local requirements. The venous blood collection guideline presented here was adapted from international standards to conform to globally recognized practices and address the Korean clinical context. The guideline, developed by the Korean Society for Laboratory Medicine, outlines the critical steps in venous blood collection, from patient identification and consent to post-collection handling. Practical recommendations are provided for medical students, doctors, nurses, and medical technologists. The guideline addresses specific considerations for pediatric and older patients, as well as individuals undergoing blood culture tests, with an emphasis on minimizing errors and promoting the safety of patients and medical staff. The guideline includes practical tools, such as checklists and detailed information on sampling devices, to facilitate implementation. This initiative would help standardize blood collection practices, improve specimen quality, and enhance patient care by ensuring accurate laboratory results in clinical settings.

Background: Measuring residual cells in blood products is legally required for monitoring the manufacturing process and ensuring recipient safety. We compared the accuracy and performance of the two methodologies.

Methods: Residual white blood cells (rWBCs), red blood cells (rRBCs), and platelets (rPLTs) were measured in RBC concentrates (rWBCs), fresh frozen plasma (rWBCs, rRBCs, and rPLTs), and PLT concentrates (rWBCs and rRBCs) using the Sysmex XN-1000 hematology analyzer (Sysmex, Kobe, Japan) equipped with Blood Bank mode and standard flow cytometry (fluorescence-activated cell sorting; FACS).

Results: rWBC counts in RBC concentrates and plasma were similar between XN-1000 and FACS. In pooled pathogen-inactivated PLT concentrates, XN-1000 yielded higher rWBC counts. Correlations between XN-1000 and FACS were moderate for rWBCs (0.42, 95% confidence interval: 0.15-0.69) in RBC inline-filtrated WBC-depleted RBC concentrates. In plasma, correlations were high for rWBC, rRBC, and rPLT counts, with Spearman correlation coefficients of 0.82-0.97. In pathogen-inactivated PLT concentrates, correlations were moderate for rWBCs (0.58, 0.33-0.84) and rRBCs (0.61, 0.35-0.87) in pooled samples but not significant in apheresis-derived samples. Median differences between FACS and XN-1000 were generally low, but XN-1000 overestimated residual cell counts in a subset of measurements. Residual cell cut-off values were surpassed in >90% of RBC concentrates, plasma, and apheresis pathogen-inactivated PLT concentrates using both methods. In pooled pathogen-inactivated PLT concentrates, 91.2% and 70.6% surpassed the cut-off using FACS and XN-1000, respectively.

Conclusions: Sysmex XN-1000 is suitable for residual cell measurements in RBC concentrates and plasma, with some limitations for PLT concentrates.

Background: Pancreatic cancer (PC)-screening methods have limited accuracy despite their high clinical demand. Differential diagnosis of chronic pancreatitis (CP) poses another challenge for PC diagnosis. Therefore, we aimed to identify blood protein biomarkers for PC diagnosis and differential diagnosis of CP using high-throughput multiplex proteomic analysis.

Methods: Two independent cohorts (N=88 and 80) were included, and residual serum samples were collected from all individuals (N=168). Each cohort consisted of four groups: healthy (H) individuals and those with CP, stage I/II PC (PC1), or stage III/IV PC (PC2). Protein expression in the first cohort was quantified using the Olink Immuno-Oncology and Oncology 3 proximity extension assay (PEA) panels and was analyzed using machine-learning (ML)-based analyses. Samples in the second cohort were utilized to verify candidate biomarkers in immunoassays.

Results: Both the PEA and immunoassay results confirmed that previously recognized biomarkers, such as the mucin-16 and interleukin-6 proteins, were more highly expressed in the PC (PC1 and PC2) groups than in the non-PC (CP and H) groups. Several novel biomarkers for PC diagnosis were identified via ML-based feature extraction, including C1QA and CDHR2, whereas pro-neuropeptide Y (NPY) appeared to be a promising biomarker for the differential diagnosis of CP. Applying XGBoost classification incorporating the selected features resulted in an area under the curve of 0.92 (0.85-0.98) for differentiating the PC group from the CP and H groups.

Conclusions: Promising blood biomarkers for PC diagnosis and differential diagnosis of CP were identified using a PEA platform and ML techniques.

Waldenström macroglobulinemia (WM) is a B-cell lymphoproliferative disease characterized by IgM monoclonal gammopathy and bone marrow (BM) infiltration caused by lymphoplasmacytic lymphoma. The MYD88 L265P variant is present in >90% of WM cases. We used droplet digital PCR (ddPCR) to detect MYD88 L265P in initial BM samples from 15 patients with WM and assessed the implication of variant burden as a tumor load and prognostic marker. MYD88 L265P burden correlated with clinical indicators, including peripheral blood and BM lymphocyte percentages (P <0.001 and P =0.003, respectively), serum lactate dehydrogenase level (P =0.045), and platelet count (P =0.003). Patients classified into intermediate and high groups according to the Revised International Prognostic Score System for WM had higher MYD88 L265P copies/μL than patients in very low and low groups (P =0.017), as had patients with minor response or stable disease after primary treatment than those with complete, partial, or very good partial response (P =0.034). MYD88 L265P burden correlates well with multiple clinical indicators and has prognostic relevance, making it a potential marker for assessing tumor burden and predicting prognosis in WM.