Scandinavian Journal of Clinical & Laboratory Investigation最新文献

Introduction: There are important pharmacological differences between direct oral anticoagulants (DOAC) and a deeper knowledge of how they influence different aspects of hemostasis in patients on treatment is desirable.

Materials and methods: Blood samples from patients on dabigatran (n = 23), rivaroxaban (n = 26), or apixaban (n = 20) were analyzed with a fibrin network permeability assay, a turbidimetric clotting and lysis assay, the calibrated automated thrombogram (CAT), plasma levels of thrombin-antithrombin complex (TAT) and D-dimer, as well as DOAC concentrations, PT-INR and aPTT. As a comparison, we also analyzed samples from 27 patients on treatment with warfarin.

Results: Patients on dabigatran had a more permeable fibrin network, longer lag time (CAT and turbidimetric assay), and lower levels of D-dimer in plasma, compared with patients on rivaroxaban- and apixaban treatment, and a more permeable fibrin network than patients on warfarin. Clot lysis time was slightly longer in patients on dabigatran than in patients on rivaroxaban. Warfarin patients formed a more permeable fibrin network than patients on apixaban, had longer lag time than patients on rivaroxaban (CAT assay), and lower peak thrombin and ETP compared to patients on treatment with both FXa-inhibitors.

Conclusions: Results from this study indicate dabigatran treatment is a more potent anticoagulant than apixaban and rivaroxaban. However, as these results are not supported by clinical data, they are probably more related to the assays used and highlight the difficulty of measuring and comparing the effect of anticoagulants.

Internal quality control in clinical chemistry laboratories are based on analyzing samples of stable control materials among the patient samples. The control results are interpreted by using quality control rules that usually are designed to detect systematic errors. The best rules have a high probability of error detection (P_ed), i.e. to detect the maximal allowable (critical) systematic error and a low probability of false rejection (P_fr, false alarm). In this work we show that quality control rules can be represented by points on a ROC curve which appears when P_ed is plotted against P_fr and only the control limit is varied. Further, we introduce a new method for choosing the optimal control limit, analogous to choosing the optimal operating point on the ROC curve of a diagnostic test. This decision needs knowledge of the pretest probability of a critical systematic error, the benefit of detecting it when it occurs and the cost of false alarm. The ROC curve analysis showed that if rules based on N = 2 are used, mean rules outperform Westgard rules because the ROC curve of the mean rules was lying above the ROC curves of the Westgard rules. A mean rule also had a lower maximum expected increase in the number of unacceptable patient results reported during the presence of an out-of-control error condition (Max E(N_UF)) than comparable Westgard rules.

Neoadjuvant chemotherapy (NAC) is the preferred treatment option in locally advanced breast cancer (BC). The administration of NAC is associated with a wide range of adverse effects. This pilot observational prospective study examined the effect of NAC using anthracycline + cyclophosphamide (AC) followed by paclitaxel (PTx) on a portfolio of 22 plasma and urinary amino acids, plasma proteins (albumin, prealbumin, transferrin), and products of nitrogen metabolism (urea, creatinine, uric acid) in plasma and urine. Plasma and 24-h urine samples were obtained from ten patients with early breast cancer (N1-3 N0-2 M0), at the following time points: before the start of NAC and during the AC/PTx treatment period (a total of 8 measurements at three-weekly intervals). Amino acids were analyzed using ion exchange chromatography. There were no significant differences in the measured parameters in plasma and urine between pre-NAC and during AC- and PTx-treatment. No trend was detected. A significant difference in the portfolio of plasma and urinary amino acids was found only in the pre-treatment period compared to the control group. Levels of eight plasma amino acids (8/22) were significantly reduced and those of nine urine amino acids were increased (9/22). Nitrogenous catabolites in plasma and urine were not indicative of increased protein catabolism during the anthracycline and taxane treatment periods. A slightly positive nitrogen balance was accompanied by an average weight gain of 3.3 kg (range 0-6 kg). The AC/PTx treatment regimen did not cause significant changes in the monitored laboratory parameters.

Chimeric antigen receptor-T (CAR-T) cell therapy is currently the best-known type of immune effector cells therapy. For CAR T-cell therapy, the determination of CD3+ T cells is necessary for the quality control of fresh leukapheresis product as starting material. The aim was to validate analytical method for quantification of percentage and absolute count of T lymphocyte subtypes (CD3+, CD4+ and CD8+ cells) in fresh apheresis products using single-platform method on flow cytometer BD FACS Canto II. Validation study included determination of precision, trueness (bias), assessment of linearity, carryover, comparison of results obtained with two different protocols on flow cytometer for CD3+ cells determination and stability study. For between-run precision coefficients of variation (CVs) were <20%, as well as bias for all T-lymphocyte subtypes. For within-run precision, CVs were <10%, except for low CD8+ cell (percentage 10.51% and viable absolute count 12.37%). Comparison of results obtained with two different protocols for CD3+ cells determination shows no statistically significant difference. Statistically significant differences between results of the analysis of CD4+ cells in fresh samples and results obtained after storage at 4 °C (p = .004) and at room temperature (p = .018) were found. In conclusion, method for enumeration of T-lymphocyte subtypes can be used in routine work on BD FACS Canto II instrument for quality assessment of fresh cell products collected by leukapheresis procedure.

Background: Reduced activity of the sucrase-isomaltase (SI) enzyme can cause gastrointestinal symptoms. Biochemical measurement of SI activity in small intestinal biopsies is presently considered the gold standard for the diagnosis of SI deficiency, but this invasive test is not suitable as a routine diagnostic tool.

Aim: To evaluate a ¹³C-sucrose-breath test (¹³CSBT) as a diagnostic tool for SI deficiency in an adult population.

Methods: ¹³CSBT results were compared to sucrase activity measured in duodenal biopsies.

Results: Forty patients with gastrointestinal symptoms were included in the study, 4 of whom had celiac disease and the rest (n = 36) had normal histological findings. Nine patients (22.5%) had low sucrase activity measured using duodenal biopsies. No correlation was observed between enzymatic sucrase activity and the ¹³CSBT results. The ¹³CSBT-curves for the celiac patients versus patients with normal duodenal histology demonstrated that the patients with celiac disease were within the lower range of the distribution.

Conclusion: We observed a mismatch between the ¹³CSBT results and the biochemically measured sucrase activity, suggesting that SI activity is not uniformly distributed throughout the small intestines. This methodological discrepancy should be acknowledged when diagnosing SI deficiency.

Amyloidosis is a disease characterized by the deposition of protein fibrils. Cardiac involvement is a significant factor in determining prognosis. This study aimed to examine the clinical profile, outcomes, and long-term mortality rates in patients with transthyretin (ATTR) and amyloid light-chain (AL) amyloidosis. The retrospective cohort study included 94 patients with amyloidosis (69 with AL and 25 with ATTR amyloidosis) diagnosed between 2010 and 2022. The study involved multimodality imaging (ECG, echocardiography and cardiac magnetic resonance (CMR) data and survival analyses. Patients with ATTR amyloidosis were older and had a higher proportion of males compared to those with AL amyloidosis. Cardiac involvement was more prevalent in the ATTR group, including atrial fibrillation (AF), while pleural and pericardial effusion were more frequent in the AL group. Biomarkers such as NT-proBNP and troponin T were significantly elevated in both groups and were associated with all-cause mortality only in univariate analyses. CMR data, especially typical late gadolinium enhancement (LGE) was not associated with increased mortality, while pleural effusion and left atrial dilatation on echocardiography were identified as powerful predictors of mortality. In conclusion, both AL and ATTR amyloidosis exhibited poor outcomes. Cardiac involvement, particularly dilated left atrium and pleural effusion on echocardiography were associated with an increased risk of mortality, while typical LGE on CMR was not.

Aim: Measuring uncertainty (MU) is crucial to ensure the accuracy and precision of laboratory results. This study compares the ISO 20914 and Nordtest guidelines to analyze the MU values for 20 clinical chemistry analytes over six months.

Methods: The researchers calculated MU components, including within-laboratory reproducibility (Rw), laboratory analytical performance bias (u(bias)), and combined standard uncertainty (u_c), based on internal quality control and external quality assessment data. The final expanded uncertainty (U) values were determined by multiplying the combined uncertainty with a coverage factor (k = 2 for 95% Confidence Interval), following each guideline's respective procedures. Clinical chemistry analytes were analyzed on Roche Cobas 6000 c501 auto analyzer (Roche Diagnostics, Mannheim, Germany) and manufacturer's kits were used analysis.

Results: The results show that 11 out of 20 clinical chemistry analytes met the targeted maximum allowable measurement uncertainty (MAU) values when calculated according to ISO 20914 guideline. Also, 11 out of 20 clinical chemistry analytes' MU values met the MAU values with the Nordtest guideline's recommended calculations. However, some tests met the MAU in the ISO 20914 approach but not in the Nordtest guideline, and vice versa.

Conclusions: The study found that intermediate precision (u_Rw) in the ISO 20914 approach and performance bias (u(bias)) in the Nordtest approach significantly impacted MU values. The research highlights the importance of standardization in MU calculation approaches across clinical laboratories. These findings have implications for patient care and clinical decision-making, emphasizing the importance of selecting appropriate laboratory guidelines for routine use.

PsoP27 is an antigen expressed in psoriatic lesions. It plays an inflammatory role in psoriasis. This study objective was to characterize antibodies (Abs) against PsoP27 in patients with psoriatic arthritis (PsA) and rheumatoid arthritis (RA). Levels of Abs against native and citrullinated PsoP27 in PsA and RA patients' synovial fluid (SF) and sera were determined by ELISA. SF of osteoarthritis (OA) patients and sera of healthy donors were used as controls. Levels of Abs against PsoP27 were correlated with disease activity scores. Abs against native and citrullinated PsoP27 levels in SF of PsA (n = 48; 0.38 ± 0.03 and 0.44 ± 0.04, respectively) and RA (n = 22; 0.57 ± 0.1 and 0.62 ± 0.09, respectively) were significantly higher than in OA patients (n = 23; 0.14 ± 0.01 and 0.15 ± 0.01, respectively) (p < .0001). For both Abs, there were no significant differences between their level in PsA and RA patients. There was no difference in the level of Abs against citrullinated PsoP27 in SF of seronegative versus seropositive RA patients. Levels of Abs against both native and citrullinated PsoP27 in the SF and level of systemic C-reactive protein in PsA correlated positively, while in RA there were no significant correlations with disease activity scores. No differences in level of Abs against PsoP27 were found in the sera of all three study groups. Abs against native and citrullinated PsoP27 are present in PsA and RA SF but not in those of OA patients, suggesting a potential role of those Abs in inflammatory joint diseases.

Early and differential diagnosis of sepsis is essential to avoid unnecessary antibiotic use and further reduce patient morbidity and mortality. Here, we aimed to identify predictors of sepsis and advance a machine-learning strategy to predict sepsis-induced respiratory tract infection (RTI). Patients with sepsis and RTI were selected via retrospective analysis, and essential population characteristics and laboratory parameters were recorded. To improve the performance of the primary model and avoid over-fitting, a recursive feature elimination with cross-validation (RFECV) strategy was used to screen the optimal subset of biomarkers and construct nine machine-learning models based on this subset; the average accuracy, precision, recall, and F1-score were used for evaluation of the models. We identified 430 patients with sepsis and 686 patients with RTI. A total of 39 features were collected, with 23 features identified for initial model construction. Using the RFECV algorithm, we found that the XGBoost classifier, which only needed to include seven biomarkers, demonstrated the best performance among all prediction models, with an average accuracy of 89.24 ± 2.28, while the Ridge classifier, which included 11 biomarkers, had an average accuracy of only 83.87 ± 4.69. The remaining models had prediction accuracies greater than 88%. We developed nine models for predicting sepsis using a strategy that combined RFECV with machine learning. Among these models, the XGBoost classifier, which included seven biomarkers, showed the best performance and highest accuracy for predicting sepsis and may be a promising tool for the timely identification of sepsis.