Marija Miloš

Evaluation of the Innovance D-DIMER analytical performance.

Abstract Background: Widespread use of D-dimer in recent years has led to the development of a number of new fully automated quantitative D-dimer assays. Methods: We evaluated the analytical performance of the particle-enhanced immunoturbidimetric assay Innovance D-DIMER (Siemens Medical Solutions) on the Behring Coagulation System (BCS) analyzer. Results: Within-run coefficients of variation (CVs) for samples with low, borderline, slightly, and extremely increased D-dimer concentrations were 2.1%–5.5%, whereas between-run CVs for control samples with low and extremely increased D-dimer were 5.5%–8.4%. The assay exhibited good linearity in the working range between 0.17 mg/L and 5.45 mg/L fibrinogen equivalent units (FEU), with the lower limit of detection of 0.099 mg/L FEU. The upper reference value determined in 40 plasma samples from healthy volunteers was 0.495 mg/L FEU. The results obtained in 457 fresh plasma samples were compared with results obtained with VIDAS D-Dimer Exclusion. Passing and Bablok regression analysis demonstrated highly significant correlation (y=1.370x–0.108, r=0.952, p<0.001). Bland and Altman difference plots demonstrated slightly higher results obtained with Innovance D-DIMER that was more pronounced with increasing values. Very good agreement between both assays was observed (κ=0.860; 95% confidence interval (CI), 0.811–0.908). Conclusions: This study demonstrates that Innovance D-DIMER fulfills all analytical requirements for daily routine use. Clin Chem Lab Med 2009;47:945–51.

Discrepancies between APTT results determined with different evaluation modes on automated coagulation analyzers

Modern photo‐optical coagulometers collect optical data in the form of reaction curves and offer a possibility to determine clotting times at different points of clot formation by using different evaluation modes. The objectives of this study were to determine the possible impact of an evaluation mode on activated partial thromboplastin time (APTT) results and to investigate potential benefits from visual inspection of obtained reaction curves. APTT was determined by using actin FS as reagent on two coagulometers (Siemens Medical Solutions) in 174 plasma samples with three different evaluation modes: fixed absorbance (FA), drifting baseline (DB), and point of inflexion (POI) on Behring coagulation timer (BCT), and with DB mode on Behring coagulation system (BCS). Statistically significant difference of APTT results applying the Friedman’s test (P < 0.0001) followed by Dunn’s multiple comparison test (P < 0.05) was obtained in all tested samples between POI mode and all other evaluation modes, independently of analyzer used. The differences obtained indicated that laboratory professionals must be aware of possible different evaluation modes on different analyzers, and establish evaluation mode‐specific reference intervals. Moreover, correctness of a reported result could be confirmed only by visual analysis of the reaction curve.

New quantitative aPTT waveform analysis and its application in laboratory management of haemophilia A patients

Diagnosis of haemophilia A is usually made by the measurement of factor VIII (FVIII) activity that allows categorization of the disease severity. However, tests that assess global haemostasis may better reflect clinical features and give additional clinically relevant information. The aim of this study was to develop a new quantitative activated partial thromboplastin time (aPTT) waveform analysis and compare it with FVIII activities to find out whether waveform parameters are superior determinants of clinical phenotype. A total of 81 haemophilia A patients divided into two groups (37 severe, 44 non‐severe) were included in the study. The control group comprised 101 healthy male volunteers. Quantitative aPTT waveform analysis was performed with Actin FS on BCS (Siemens Healthcare Diagnostics, Marburg, Germany) using three parameters (DELTA, RATIO‐1, RATIO‐2) obtained from a single aPTT measurement with two evaluation modes. FVIII activities were measured by one‐stage clotting and two‐stage chromogenic assay. Statistically significant difference (P < 0.001) between control group and all haemophilia A patients, as well as between severe and non‐severe haemophilia A patients was obtained for all quantitative waveform parameters. Our study revealed parameter DELTA as the best waveform parameter, showing significant correlation with FVIII activities and clinical parameters, and excellent performance for distinguishing between severe and non‐severe haemophilia A patients (ROC analysis: sensitivity 97.3%, specificity 93.2%). The results obtained by new quantitative aPTT waveform analysis were superior to those obtained by standard laboratory methods. The simplicity and cost‐benefit of the method make this approach a reasonable and promising tool for assessing coagulation in haemophilia A patients.

Autovalidation and automation of the postanalytical phase of routine hematology and coagulation analyses in a university hospital laboratory.

Abstract Background: The need to satisfy high-throughput demands for laboratory tests continues to be a challenge. Therefore, we aimed to automate postanalytical phase in hematology and coagulation laboratory by autovalidation of complete blood count (CBC) and routine coagulation test results (prothrombin time [PT], international normalized ratio [PT-INR], activated partial thromboplastin time [APTT], fibrinogen, antithrombin activity [AT] and thrombin time [TT]). Work efficacy and turnaround time (TAT) before and after implementation of automated solutions will be compared. Methods: Ordering panels tailored to specific patient populations were implemented. Rerun and reflex testing rules were set in the respective analyzers’ software (Coulter DxH Connectivity 1601, Beckman Coulter, FL, USA; AutoAssistant, Siemens Healthcare Diagnostics, Germany), and sample status information was transferred into the laboratory information system. To evaluate if the automation improved TAT and efficacy, data from manually verified results in September and October of 2015 were compared with the corresponding period in 2016 when autovalidation was implemented. Results: Autovalidation rates of 63% for CBC and 65% for routine coagulation test results were achieved. At the TAT of 120 min, the percentage of reported results increased substantially for all analyzed tests, being above 90% for CBC, PT, PT-INR and fibrinogen and 89% for APTT. This output was achieved with three laboratory technicians less compared with the period when the postanalytical phase was not automated. Conclusions: Automation allowed optimized laboratory workflow for specific patient populations, thereby ensuring standardized results reporting. Autovalidation of test results proved to be an efficient tool for improvement of laboratory work efficacy and TAT.

Serum carbohydrate sulfotransferase 7 in lung cancer and non-malignant pulmonary inflammations

Abstract Background: Carbohydrate sulfotransferases (CHST) were shown to be involved in carcinogenesis. The aim of the study was to assess the diagnostic value of serum CHST7 concentration in differentiation between lung cancer and non-malignant pulmonary inflammations. Methods: Clinical case-control study involving 125 participants was conducted: the control group containing cases of pneumonia and chronic obstructive pulmonary disease was compared to the lung cancer group composed of primary and metastatic cancers. Serum concentrations of CHST7 and routinely used markers including carcinoembryonic antigen (CEA), cytokeratin fragment 21-1 (CYFRA 21-1) and neuron-specific enolase (NSE) were determined for each participant using immunochemical methods. Statistical association, receiver operating characteristic (ROC) analysis and cross-validation were used for the evaluation of CHST7 either as a standalone biomarker or as a part of a biomarker panel. Results: In comparison to the control group, serum CHST7 was elevated in lung cancer (p<0.001), but no differences between the overall stages of primary cancers were detected (p=0.828). The differentiation performance in terms of ROC area under curve (AUC) was 0.848 making CHST7 superior biomarker to the NSE (p=0.031). In comparison to CEA and CYFRA 21-1, the performance differences were not detected. CHST7 was not correlated to other biomarkers, and its addition to the routine biomarker panel significantly improved the cross-validated accuracy (85.6% vs. 75.2%) and ROC AUC (p=0.004) of the differentiation using a machine learning approach. Conclusions: Serum CHST7 is a promising biomarker for the differentiation between lung cancer and non-malignant pulmonary inflammations.