Scandinavian Journal of Clinical & Laboratory Investigation最新文献

This study aimed to describe differences in prevalence and the long-term presence of nucleocapsid antibodies (N-antibodies) elicited by SARS-CoV-2 infection in a Swedish blood donor population not subjected to lockdown. We tested 20,651 blood donor samples for nucleocapsid antibodies from the beginning of March 2020 and 27 months onwards using the Roche Elecsys Anti-SARS-CoV-2 assay. The proportion of positive SARS-CoV-2 antibody samples was determined each week. After the exclusions of one-time donors and subjects with incomplete data, 19,726 samples from 4003 donors remained. Differences in antibody prevalences stratified for age, sex, and blood groups (ABO and RhD) were determined, as well as antibody loss and recovery. Lower antibody prevalence was seen for older donors, blood group AB, and RhD-negative subjects. A significant decrease in antibody titer between the first and the second antibody-positive donation was seen for the whole study group, females, older subjects, blood group O, AB, and RhD-positive subjects. The titer waned below the detection limit in 60 (3.0%) of 1983 N-antibody-positive donors, and for 18 of these donors, a second episode with antibodies was detected. We showed that N-antibodies persist for months or years and that surprisingly few antibody-positive donors lost their antibodies. We also conclude that antibody prevalence in a Swedish population never subject to lockdown did not apparently differ from populations that were subject to stricter regulations.

Introduction: Major Thalassemia patients suffer from iron overload and organ damage, especially heart and liver damage. Early diagnosis and treatment with a chelator can reduce the complications and mortality of iron overload. Therefore, we aimed to investigate the biochemical and hematological predictors as an alternative and indirect indicator of iron deposition in heart and liver cells in comparison with the MRI T2* method as the gold standard.

Material and method: MRI T2* was evaluated in the heart and liver tissues of 62 major beta-thalassemia patients undergoing regular transfusion and chelator therapy. Biochemical and hematological factors were also measured, including serum ferritin, serum electrolytes, liver enzymes, hemoglobin, blood glucose, and serum magnesium. The correlation between these factors was assessed using statistical evaluations.

Result: Serum ferritin had a positive and significant correlation with liver siderosis based on MRI T2* (p-value = .015), and no significant association was observed with cardiac siderosis (p-value = .79). However, there was a significant positive correlation between cardiac iron deposition and fasting blood sugar level (p-value = -.049), and plasma level of liver enzymes (alanine aminotransferase (ALT) (p-value = .001), aspartate aminotransferase (AST ((p-value = .01)). Moreover, there was a significant negative correlation between cardiac iron overload and plasma magnesium level (p-value = .014). According to MRI T2*, there was no significant correlation between cardiac and hepatic iron overload (p value = .36).

Conclusion: An increase in blood sugar or liver enzymes and a decrease in serum magnesium was associated with an increase in cardiac iron overload based on MRI T2*. Liver iron overload based on MRI T2* had a significant correlation with serum ferritin.

Neuron-specific enolase (NSE) derived from neurons and peripheral neuroendocrine cells is a biomarker for neuroendocrine tumors and for prognostication in comatose cardiac arrest survivors. However, as platelets and erythrocytes contain NSE, hemolysis causes falsely elevated NSE. We used native serum and hemolysate derived from the same patients to make serial dilutions, and subsequently measured NSE (mNSE) and hemolytic index (HI) in each dilution. An algorithm suitable for the laboratory information system was developed based on the mNSE, HI and the estimated gradient of hemolytic interference from 30 patients. We estimated the associated uncertainty of the corrected NSE (cNSE) results based on the observed range of the gradient and derived an equation for cNSE for samples with limited hemolysis (i.e. 5 < HI ≤ 30): cNSE = mNSE - HI × (0.34 ± 0.23) µg/L. By semi-quantitatively grading the contribution from limited hemolysis, a texted result noting the hemolysis-associated degree of uncertainty can accompany the cNSE result. The major challenge of hemolysis when using serum NSE as a biomarker can be managed using an automated algorithm for correction of NSE results based on degree of hemolysis. However, laboratorians and clinicians should be aware of the limitations associated with in vivo hemolysis.

Objectives: The objective of this study was to perform a method comparison between the CellaVision preclassification neutrophil count and the reclassification neutrophil count performed by trained laboratory technicians, and to evaluate the diagnostic performance of the preclassification neutrophil count at clinical decision levels.

Methods: We retrospectively identified patient samples through 2019-2022 in which the differential count was performed on Cellavision (n = 4,354). Data on sample characteristics and leukocyte- and differential counts was extracted from the electronic medical journal. For each sample, data containing the pre- and reclassification leukocyte classification, respectively, was extracted from the Cellavision software. Method comparison between the pre-and reclassification neutrophil count was performed using Bland Altman analysis. Diagnostic performance of the preclassification neutrophil count was evaluated according to four pre-specified categories of results with the reclassification as reference method.

Results: The median difference between the pre- and reclassification neutrophil count was 0.044 x 10⁹/L. The preclassification neutrophil count categorised 95.6% of all samples correctly according to the four categories. The sensitivity, specificity, positive predictive value and negative predictive value for detecting neutrophilia > 7.00 x 10⁹/L was 98.8%, 97.2%, 95.8%, and 99.2%, respectively. In samples with leukopenia (n = 543), the sensitivity, specificity, positive predictive value and negative predictive value for detecting severe neutropenia (< 0.50 x 10⁹/L) was 97.7%, 99.1%, 98.6%, and 98.5%, respectively.

Conclusion: The diagnostic performance of the CellaVision preclassification neutrophil count was satisfactory. The preclassification neutrophil count may be released to the electronic medical journal to improve turnaround time and benefit laboratory management.

It is internationally recognized to use clinical decision limits (CDL) when interpreting the lipid levels in both adults and children, even though the evidence for children is scarce. The purpose of this study is to describe how lipid levels progress in healthy Danish children ages 5 to 17 years. This study is based on the Childhood Health, Activity, and Motor Performance School Study Denmark (CHAMPS-study DK) consisting of 1456 observations of schoolchildren aged 5 to 17 years. Participants have been tested for blood levels of total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, and remnant cholesterol levels are calculated. Finally, sex-specific percentile reference curves are presented. Percentile reference curves stratified by sex were generated for all cholesterols and showed that the total cholesterol level peaks at 4.32 mmol/l in 10-year-old boys and 4.46 mmol/l in nine-year-old girls. HDL levels in boys peak at 1.72 mmol/l in nine-year-old boys. HDL levels in girls and LDL levels in both sexes are nearly constant. Triglycerides kept rising to the age of 17 years in both sexes and remnant cholesterol decreased from age 5 to 17 years in both sexes. BMI z-score adjustment revealed no significant association with total cholesterol in both sexes but a significant association between HDL, LDL, triglycerides, and remnant cholesterol. This study is the first to generate percentile reference curves for blood levels of total cholesterol, LDL, HDL, triglycerides, and remnant cholesterol in a cohort of healthy Danish children aged 5 to 17 years.

Cerebrospinal fluid hypocretin-1 is proven to be a precise diagnostic marker of narcolepsy Type 1 (NT1). However other characteristics of cerebrospinal fluid and blood parameters have not yet been described. The objective of this study was to evaluate the differences in routine blood and cerebrospinal fluid analyses between NT1 patients and patients suspected of hypersomnia. We collected retrospectively all measures of cerebrospinal fluid hypocretin-1 between 2019 and 2022. This yielded 612 patients out of which 146 were diagnosed with NT1 and the rest (466 patients) were used as a control group. We selected the most relevant routine samples from both blood, plasma and cerebrospinal fluid and compared the two groups. The only significantly different analytes were plasma lactate dehydrogenase and cerebrospinal fluid hypocretin-1. No other differences were found between the groups including thyroid markers, markers of neuroendocrine function, inflammatory markers in blood or cerebrospinal fluid, markers of permeability of the blood brain barrier or metabolic markers in blood samples. We found no significant differences in routine blood or cerebrospinal fluid components, neuroendocrine function, neuroinflammation and metabolic markers. The results reflect that the hypocretin system does not seem to play a chronic major role in regulation of these markers. None of the parameters routinely measured in blood in these patients could differentiate between NT1 and non-NT1 disorders besides CSF-hcrt-1.

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.

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.