Scandinavian Journal of Clinical & Laboratory Investigation最新文献

Reference intervals, representing the normal range of values across age and gender groups, are essential for determining whether parameters from an individual are within physiological limits or not. Lysosomal glucocerebrosidase (GCase) activity has diagnostic relevance for Gaucher's disease (GD); it is also important in Parkinson's disease (PD) and other neurodegenerative disorders, particularly for assessing lysosomal functions. Although accurate laboratory tests are available for GCase, the absence of established reference intervals limits their application in clinical diagnostics and research. In this study, we measured GCase activity using leucocytes from healthy blood donors (n = 530) belonging to the 18-65 years age group. This study establishes a reference range for GCase activity in the healthy population, with a median of 2.29 nmol/10⁷cells/h (Inter-quartile range: 1.21-4.01; 95% reference interval of 0.093-8.945 nmol/10⁷cells/h). There was a slight decline in GCase activity beyond the age of 45 years. Females displayed higher GCase activity compared to males among all age groups. Haemoglobin, blood group and body weight showed no significant correlation with GCase activity. Our results increase the clinical and research utility of GCase assay, relevant to the screening of individuals with suspected lysosomal storage disorders and research in PD and other neurodegenerative conditions. The availability of reliable reference intervals may also facilitate a better understanding of lysosomal biology in health and disease.

Most clinical laboratories measure total magnesium (tMg) which includes both the ionized (iMg) and bound forms. Only the ionized component is biologically active, and it may be influenced by acid-base status, plasma protein concentrations and electrolyte disturbances, potentially altering how well tMg reflects iMg. This multicenter observational study evaluated the relationship between tMg and iMg using paired samples collected within a 2-hour window. Association was assessed with linear regression and Pearson's correlation coefficient, and agreement with Bland-Altman analysis. Ionized magnesium constituted 77.9% of tMg (95% CI 77.5%-78.4%). There was a strong correlation between iMg and tMg (r = 0.916, p < 0.0001). Bland-Altman analysis showed that tMg was, on average, 0.20 mmol/L higher than iMg (95% LoA 0.03-0.37 mmol/L). Proportional bias was observed (slope = 0.22, p < 0.001), with increasing discrepancies at higher concentrations. Stepwise multiple linear regression analysis including acid-base parameters, albumin and electrolytes, was used to identify variables independently associated with ionized and total magnesium concentrations. In this multivariable model, pH and ionized calcium were independently associated with both ionized and total magnesium. In conclusion, ionized and total magnesium were strongly correlated. However, proportional bias indicated that total magnesium increasingly deviates from the biologically active ionized fraction at higher concentrations. Therefore, derived equations to estimate one measure from the other are not reliable for clinical use.

Several methods are available to differentiate non-fibrosis from advanced liver fibrosis; however, data regarding intermediate stages remain limited. A total of 246 patients with chronic hepatitis B (CHB) were enrolled and classified into four groups according to fibrosis stage: non- or mild fibrosis (Group A), significant fibrosis (Group B), progressive fibrosis (Group C), and cirrhosis (Group D). The serum chitinase-3-like protein 1 (CHI3L1) levels in Groups A, B, C, and D were 40.33, 52.96, 92.28, and 153.63 μg/L, respectively. Significant differences were observed between Groups A and B (p = 0.040), Groups C and D (p < 0.0001), and Groups B and D (p < 0.0001). The percentage of regulatory T cells (Tregs) was 0.67 in the CHB-low fibrosis (CHB-L) group and 0.26 in the CHB-moderate to severe fibrosis (CHB-MS) group, representing a statistically significant difference (p = 0.039). The T helper 17 cells (Th17)/Treg ratio was 10.00 in the CHB-L group and 61.26 in the CHB-MS group, representing a statistically significant difference (p = 0.010). For predicting significant fibrosis, progressive fibrosis, and cirrhosis, the area under the curve (AUC) for the combined conventional markers - hyaluronic acid, laminin, type III procollagen N-terminal peptide, collagen type IV, and cholyglycine were 0.736, whereas those for CHI3L1 and Th17/Treg were 0.774 and 0.750, respectively. The combination of CHI3L1 and Th17/Treg cells yielded an AUC of 0.814, demonstrating the highest sensitivity (100%) and high specificity. These findings suggest that CHI3L1 combined with Th17/Treg cells may serve as a novel biomarker for staging hepatitis B virus-related liver fibrosis.

Often a measurement of an analyte is repeated in the same patient. Then the physician must interpret a pair of test results of the same analyte (x1, x2), measured in specimens collected hours to weeks apart. Physicians compare both test results against the univariate reference limits (RLs) and perhaps the difference x2 - x1 against reference change values (RCVs). We believe that it would be rational to compare a specific pair of (x1, x2) values against percentiles in the bivariate distribution of (x1, x2) from reference individuals. That has never been done, so we simulated (x1, x2) reference values using data on RLs, intraindividual biological variation in healthy individuals, and analytical variation. The bivariate percentiles corresponding to (x1, x2) observations were estimated from the Mahalanobis distances (MDs) in the bivariate distribution of (x1, x2) reference values. With a very few exceptions, the combination of 95% RLs and 95% RCVs did not enclose any (x1, x2) reference value with a bivariate percentile above 95. However, the combination enclosed only 92-93% of the (x1, x2) reference values below the bivariate 95 percentile. In conclusion, bivariate percentiles in the distribution of (x1, x2) reference values from a healthy reference population can be derived from available data, and used for reporting and interpreting the finding of a specific (x1, x2) observation in a patient.

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide, with acute exacerbations (AECOPD) significantly contributing to disease burden and healthcare costs. This study aimed to explore the predictive role of the hemoglobin, albumin, lymphocyte, and platelet (HALP) score in 30-day readmission risk in AECOPD patients. AECOPD patients were categorized into Rehospitalization and N-Rehospitalization groups based on 30-day COPD-related readmission. The HALP score on the day of ICU admission (acute phase) was calculated as (hemoglobin × albumin × lymphocyte count)/platelet count. Spearman correlation analysis was performed to evaluate associations of acute-phase HALP scores with acute-phase APACHE IV scores and stable-phase FEV₁/FVC. ROC curves were plotted to compare HALP and CRP in predicting 30-day readmission. COX regression was conducted to identify independent risk factors for readmission. The Rehospitalization group exhibited significantly lower HALP scores. Acute-phase HALP scores were negatively correlated with acute-phase APACHE IV and positively with stable-phase FEV₁/FVC. HALP scores declined progressively with higher GOLD grades. HALP scores demonstrated superior predictive accuracy for 30-day readmission compared to CRP. Multivariate analysis confirmed HALP as an independent predictor of 30-day readmission. Overall, HALP score reduction correlates with AECOPD severity and independently predicts 30-day readmission, serving as a valuable biomarker for short-term rehospitalization risk.

Haematologists are often consulted on the need for additional diagnostic workup in patients with blast cells in peripheral blood. However, cancer risk (including solid tumors) after detection of blast cells in peripheral blood is lacking. Therefore we evaluated the 1-year cancer risk following detection of blast cells in peripheral blood. We used population-based retrospective data from the Region of Southern Denmark (2014-2021), including 2,187 individuals aged ≥20 years with blast cells in blood samples, excluding those with prior cancer. Results from haematological parameters derived from the laboratory information system, while diagnoses and vital status were from administrative registers. Natural language processing assisted review of clinical notes for individuals without cancer codes. We estimated age-standardised cancer incidence rates and compared observed versus expected cancers using standardised incidence ratios (SIR). We found that the overall 1-year cancer risk was 23% [95% CI: 21-24], with 19% [95% CI: 18-21] for haematological cancers and 3% [95% CI: 2-3] for solid cancers, compared to 0.87% in the background population. The age-adjusted SIR was 22 [95% CI: 21-24] and was highest for haematological cancers at 199 [95% CI: 184-214]. Although 78% of individuals had no blast cells upon repeated testing, 27% still developed cancer within a year. In conclusion the presence of blast cells in peripheral blood may warrant consideration of further diagnostic evaluation, particularly in the presence of other haematological abnormalities.

Multiple sclerosis (MS) is a chronic autoimmune disease that affects the central nervous system. Recently, research has highlighted the significance of biochemical evaluation of metabolic pathways and circulating amino acids beyond their fundamental role as protein building blocks. They also function as key modulators of the immune system, neurotransmission, collagen synthesis, metabolic and regenerative pathways, which may influence disease progression. We hypothesized that a disturbed amino acid profile could be used as a biomarker for MS in pregnancy. Amino acid profiles of pregnant women diagnosed with MS and healthy pregnant women were evaluated. MS diagnosis is done according to the McDonald criteria. The Expanded Disability Status Scale (EDSS) was used to evaluate MS patients. The medications used by pregnant women with MS for their disease were recorded. During the pregnancy period, none of them used a drug regimen. Progressive MS forms and EDSS > 3,5 were excluded from the study. Amino acid levels of MS patients were found to be different from healthy pregnant women. Excitatory amino acid levels were found to increase in MS patients. Glutamine and threonine levels are found to be decreased in MS pregnant women. Also, amino acids that take part in collagen synthesis are found to be different. Glutamic acid, histidine, asparagine, aspartate, proline, serine, ornithine, threonine, and tryptophan levels and citrulline/ornithine ratios are found to be significantly different between groups. These findings suggest that amino acid profiles could be potential biomarkers for early detection and new therapeutic targets for MS.

Background and aims: Ectopic pregnancy (EP) is a leading cause of maternal morbidity and mortality in the first trimester, accounting for nearly 9% of pregnancy-related deaths. An accurate biochemical marker for early detection is still unavailable. The kynurenine pathway, the primary route of tryptophan metabolism, is involved in immune tolerance, oxidative stress, and placental development. This study aimed to evaluate kynurenine metabolites as potential biomarkers for EP.

Methods: In this prospective single-center study, 106 pregnant women were recruited between January and June 2025, including 53 women with confirmed EP and 53 healthy first-trimester controls. Serum levels of tryptophan and its metabolites [3-hydroxykynurenine (3-HK), 3-hydroxyanthranilic acid (3-HAA), kynurenine, quinolinic acid, and kynurenic acid] were quantified using LC-MS/MS. Group comparisons, correlation analyses, and ROC curve evaluations were conducted.

Results: No significant differences were found in tryptophan, kynurenine, quinolinic acid, or kynurenic acid between groups (p > 0.05). However, 3-HK and 3-HAA were significantly elevated in the EP group (p < 0.001). ROC analysis demonstrated good diagnostic accuracy for 3-HAA (AUC = 0.80, 95% CI: 0.71-0.88) and 3-HK (AUC = 0.77, 95% CI: 0.67-0.86). Combined use improved discrimination (AUC = 0.86; sensitivity = 0.85; specificity = 0.75). Additionally, 3-HK correlated negatively with gestational age (ρ=-0.42, p < 0.001) and positively with monocyte and leukocyte counts.

Conclusion: These findings suggest that elevated 3-HK and 3-HAA levels are associated with EP and may reflect immunometabolic dysregulation underlying abnormal implantation, rather than implying a causal relationship. Therefore, these metabolites may offer complementary biomarker potential in selected research settings.

Transferrin saturation in plasma (P-TSAT) is 100 × P-iron/P-total iron binding capacity (P-TIBC). It is still used to diagnose iron deficiency, although P-ferritin is considered to be a better test. Both tests are sensitive to inflammation: P-TSAT decreases and P-ferritin increases. Unbound iron binding capacity in plasma (P-UIBC), which is P-TIBC minus P-iron, has a better diagnostic accuracy for iron deficiency than P-TSAT. However, how P-UIBC reacts in inflammation is less well known. We used cross-sectional data from 21681 patients to study how P-UIBC, P-TSAT, and P-ferritin varied with P-CRP. In a subpopulation of 8928 patients without inflammation (P-CRP ≤ 1 mg/L), we compared the diagnostic accuracy of P-TSAT and P-UIBC, using P-ferritin less than 15, 20, and 30 µg/L as reference standards for iron deficiency. We also estimated which values of P-UIBC and P-TSAT corresponded to a P-ferritin of 15, 20, and 30 µg/L. P-UIBC varied much less with P-CRP than did P-TSAT and P-ferritin. P-UIBC had better diagnostic accuracy than P-TSAT. Using P-ferritin < 20 µg/L as a reference standard, the areas under the ROC curves were 0.894 (95% confidence interval 0.883-0.905) for P-UIBC and 0.850 (0.836-0.864) for P-TSAT. At various ages, the values corresponding to a P-ferritin of 20 µg/L varied around 60 µmol/L for P-UIBC and around 20% for P-TSAT. In conclusion, when diagnosing iron deficiency, calculating P-UIBC is a better way of using P-iron and P-TIBC than calculating P-TSAT.