Scandinavian Journal of Clinical & Laboratory Investigation最新文献

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.

Tube manufacturers use different composition of gels and blood clot activator formulations in serum tube production. Our aim was to investigate the within-tube (repeatability) and between-tube variation, concordance between comparison results of BD and VacuSEL tubes. Blood samples were collected from control subjects (n = 20) and patients (n = 30) in accordance with the CLSI GP41-A6 and CLSI GP34-A guidelines. Twenty-three clinical chemistry parameters were analysed via Roche Cobas C702 Chemistry Analyzer on T0 (0 hour) and T24 (24 hour). Mean differences % were compared with Wilcoxon matched pair test. Clinical significance was evaluated based on desirable bias according to total allowable error (TEa). VacuSEL tubes demonstrated acceptable performance for the results of 20 parameters with regards to desirable bias % limits. Lactate dehydrogenase (LD) [mean difference % (%95 confidence intervals (CI) values of BD and VacuSEL tubes at T0 [6.41% (4.80-8.01%)]; sodium (Na) and total protein (TP) at T24 [-0.27% (-0.46 to -0.07%) and -1.39% (-1.87 to -0.91), respectively] were over the desirable bias limits (LD: 4.3%, Na: 0.23% and TP: 1.36%, respectively) but not exceeding total biological variation CV % [Na: 0.5 (0.0-1.0) % and TP: 2.6 (2.3-2.7) %). %95 confidence intervals (CI) of T0 LD values overlap with within-subject biological variation % (CI) limits (LD: 5.2 (4.9-5.4) %). The differences between two tubes were not medically significant and necessarily conclusive. VacuSEL serum tubes presented comparable performance with BD serum tubes.

Background: The Immature Platelet Fraction (IPF) is an indicator of thrombopoiesis which is a useful parameter in thrombocytopenia. It demonstrates compensatory mechanisms in production of platelets, but currently not implemented in routine clinical practice. The aim of this study was to establish the reproducibility and stability of IPF, for both percentage (%-IPF) and absolute (A-IPF) measurements.Material/methods: A total of 71 samples, of which 45 for reproducibility and 26 for stability analysis, were assayed for full blood count using the Sysmex XN-10 analyser at room temperature (RT:19-25 °C). For reproducibility analysis, IPF measurements were analysed 11 times by different appraisers using the same sample, while for stability analysis, IPF was measured over fourteen hourly-intervals up to 24 h (n = 21) and then separately extended beyond the point of stability to 72 h (n = 5).

Results: Reproducibility analysis of %-IPF and A-IPF (n = 45) showed very reliable results, with the range of mean CV% values between 1.25-8.90% and 1.70-9.96%, respectively. On the other hand, overall, stability analysis of %-IPF and A-IPF (n = 21) at RT over 24 h showed reliable results, with pooled mean CV% values of 1.32% and 1.43%, respectively, with no significant difference between %-IPF and A-IPF (p = 0.767 and p = 0.821). All %-IPF and A-IPF values had exceeded the set acceptance criterion of stability (CV% ≥ 10.0%) before 72 h.

Conclusions: Overall, %-IPF and A-IPF reproducibility and storage at RT for 24 h predominantly demonstrates the suitability of their usage for testing on the Sysmex XN-series analysers.

No definitive prognostic biomarkers for carbon monoxide (CO) poisoning have been proposed. The aim of this study is to investigate, through a systematic literature review and pooled analysis, whether red blood cell distribution width (RDW) can predict disease severity in CO-poisoned patients. We performed an electronic search in Scopus and PubMed using the keywords: 'red blood cell distribution width' OR 'RDW' AND 'carbon monoxide' AND 'poisoning,' with no time or language restrictions (i.e. through August 2023) to find clinical studies that examined the value of RDW in patients with varying severity of CO poisoning. The analysis was performed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 reporting checklist. We identified 29 articles, seven of which were included in our analysis, with a total of 1979 CO-poisoned patients, 25.9% of whom were severely ill. In all but one of the studies, the RWD mean or median value was higher in CO-poisoned patients with severe disease. The weighted mean difference (WMD) of RDW was 0.36 (95% confidence interval (CI), 0.26-0.47)%. In the three articles in which the severity of illness in CO-poisoned patients was defined as cardiac injury, the WMD of the RDW was 1.26 (95%CI, 1.02-1.50)%. These results suggest that monitoring RDW in CO-poisoned patients may help to determine the severity of disease, particularly cardiac injury.

Natural and semi-synthetic cannabinoid analogs are getting increasing media attention for their recreative use as an alternative to traditional cannabis, in Sweden as well as internationally. To investigate an increasing number of urine samples incoming to our clinical laboratory that were screening positive, using a CEDIA THC-COOH immunoassay from ThermoFisher Scientific, but then testing negative using GC-MS based verification analysis, we developed an LC-MS/MS-method for verification of hexahydrocannabinol (HHC) and Δ8-tetrahydrocannabinol. Assessment of HHC intake was based on identification of the following four metabolites: 11-nor-9(R)-carboxy-hexahydrocannabinol (R-HHC-COOH), 11-nor-9(S)-carboxy-hexahydrocannabinol (S-HHC-COOH), 11-hydroxy-9(R)-hexahydrocannabinol (R-HHC-OH) and 11-hydroxy-9(S)-hexahydrocannabinol (S-HHC-OH). Out of 46 urine samples analysed in this study, 44 showed presence of HHC-metabolites, which indicate HHC as the main explanation for an increased number of negative verifications for THC-COOH. In these samples, the HHC-OH metabolites occurred at a higher concentration than R-HHC-COOH while S-HHC-COOH was only detected in few samples at low concentrations. R-HHC-COOH and S-HHC-COOH can easily be added to a pre-existing verification method for THC-COOH, and still show acceptable results, while HHC-OH requires an enzyme capable of hydrolysing the ether glucuronide bond.

The aim of the present study was to define pediatric reference intervals for serum cobalamin and folate utilizing data generated from a population not exposed to food fortified with folic acid. Folate and cobalamin results analyzed by electrochemiluminescence immunoassay (Roche Cobas) were obtained from 2375 children (2 months to 17.99 years of age). The serum samples were collected between 2011 and 2015 as part of the LIFE (Leipzig Research Centre for Civilization Diseases) Child cohort study in Germany, where folic acid fortification of food is not mandated. These results were used to generate age- and gender-specific reference intervals presented as non-parametric 2.5 and 97.5 percentiles. Because of a subsequent restandardisation of the Roche folate assay in 2016, folate values were recalculated accordingly for adaptation to results obtained using the present calibration. In both genders, folate concentrations decreased continuously with age, whereas cobalamin concentrations peaked at five years of age and then declined. Teenage females had higher concentrations of cobalamin in the age group 12-17.99 years.