Scandinavian Journal of Clinical & Laboratory Investigation最新文献

The concentration of chromogranin A in serum (s-CgA) is a general marker of neuroendocrine neoplasms. Unfortunately, s-CgA is increased in several other clinical conditions, including renal failure. The physician who assesses s-CgA values must consider the patients' renal function. How this should be done is not clear. We developed an adjustment formula from the association between median s-CgA and the estimated glomerular filtration rate (eGFR) in 2708 patients where s-CgA was measured by the CgA II KRYPTOR method. We used multivariable fractional polynomial quantile regression with the model ln(s-CgA) = c₀ + c₁ × sex + c₂ × age + c₃ × eGFR, thus accounting for sex and age. The final adjustment formula could be simplified to s-CgA₁₀₀ = (eGFR / 100) × s-CgA, where s-CgA₁₀₀ is an indication of what s-CgA would be if eGFR in the same patient was 100 mL/minute/1.73 m². In patients with eGFR > 100 mL/minute/1.73 m² no adjustment was done. We tested the formula on another patient population (n = 1563), where s-CgA was measured by a RIA method. S-CgA₁₀₀ proved to be independent of eGFR in that population. The clinical validity of s-CgA₁₀₀ must await further investigations.

Large language models (LLMs) have demonstrated high performance across various fields due to their ability to understand, generate, and manipulate human language. However, their potential in specialized medical domains, such as clinical chemistry and laboratory management, remains underexplored. This study evaluated the performance of nine LLMs using zero-shot prompting on 109 clinical problem-based quizzes from peer-reviewed journal articles in the Laboratory Medicine Online (LMO) database. These quizzes covered topics in clinical chemistry, toxicology, and laboratory management. The models, including GPT-4o, Claude 3 Opus, and Gemini 1.5 Pro, along with their earlier or smaller versions, were assigned roles as clinical chemists or laboratory managers to simulate real-world decision-making scenarios. Among the evaluated models, GPT-4o achieved the highest overall accuracy, correctly answering 81.7% of the quizzes, followed by GPT-4 Turbo (76.1%), Claude 3 Opus (74.3%), and Gemini 1.5 Pro (69.7%), while the lowest performance was observed with Gemini 1.0 Pro (51.4%). GPT-4o performed exceptionally well across all quiz types, including single-select, open-ended, and multiple-select questions, and demonstrated particular strength in quizzes involving figures, tables, or calculations. These findings highlight the ability of LLMs to effectively apply their pre-existing knowledge base to specialized clinical chemistry inquiries without additional fine-tuning. Among the evaluated models, GPT-4o exhibited superior performance across different quiz types, underscoring its potential utility in assisting healthcare professionals in clinical decision-making.

Creatinine is a widely used clinical biomarker in adult and pediatric patients to estimate kidney function and glomerular filtration rate. There are however few recent studies that have addressed method performance in the creatinine range relevant for children. This study aimed to describe measurement performance in the pediatric concentration range by comparing commonly used enzymatic methods on four platforms: Abbott Alinity, Radiometer ABL800, Roche Cobas and Siemens Atellica, to the reference method isotope dilution mass spectrometry (IDMS). A secondary aim was to compare the Roche enzymatic methods by using dilutions of control sera issued by the Nordic Association of Clinical Chemistry. We found varying accuracy of the creatinine methods in the low concentration range. The relative difference between platforms, in an investigated range below 75 µmol/L, decreased as creatinine concentration increased. Using an absolute factor to correct for method bias as recommended by one of the manufacturers could hamper measurement trueness in the low concentration range. The in vitro diagnostic industry and stakeholders should strive towards creatinine measurement agreeability. Attention to the pediatric concentration range is needed when correcting for method bias.

ProGRP (Progastrin-releasing peptide), SCC (Squamous Cell Carcinoma Antigen), and HE4 (Human epididymis protein 4) are serum tumor markers (STMs) frequently used in clinical practice, particularly for detection and monitoring of ovarian and lung neoplasms. In clinical laboratories, their quantification is commonly performed using automated immunoassays. Nevertheless, variations in results obtained by different immunoassays can impact diagnostic accuracy and effectiveness of patient monitoring. Our aim is to assess differences in STMs concentrations between two automated immunoassays: the Elecsys (Roche) and the Architect (Abbott), which are integrated into the Cobas e402 and Architect i2000SR systems respectively. We included 401 serum samples from patients with different clinical conditions: patients with cancer (n = 170), benign diseases (n = 100) and a control group (n = 131). ProGRP, SCC, and HE4 concentrations were quantified in parallel by both analyzers. To evaluate the clinical impact of changing these methodologies, overall concordance, the kappa index and ROC (Receiver Operating Characteristic) curves were calculated. While some discrepancies were noted in specific cases, overall, we obtained a good correlation for three STMs, with a Pearson coefficient for proGRP (r = 0.99), SCC (r = 0.95) and HE4 (r = 0.973). We also obtained a similar performance in the differential diagnosis of cancer, according to the results of the ROC analyses for Cobas and Archictect assays respectively: proGRP (AUC = 0.92; 0.91), SCC (AUC = 0.90; 0.92) and HE4 (AUC = 0.92; 0.93).

Our study aimed to compare the quality of patient self-collected capillary samples with venous blood samples. Additionally, we assessed whether patients with rheumatic disease are both capable of and willing to perform capillary self-sampling through subjective and objective assessments. This research explores the future potential of at-home self-sampling. Patients with rheumatic diseases were asked to perform up to four supervised self-collected capillary blood samples, followed by a standard venous sample performed by study personnel. Anti-rheumatic drug treatment monitoring parameters, including biochemistry and hematology, were analyzed using Cobas 8000 and Sysmex XN-9000, respectively. The agreement was evaluated by Bland-Altman plots and compared to critical difference limits. Study personnel and patients answered a survey questionnaire after every visit to evaluate feasibility. In total, 21 patients completed 53 paired capillary and venous samples from November 2019 to December 2020. We found a strong correlation (r > 0.87) and good agreement for most parameters; platelets showed the poorest agreement. Patients experienced little pain, found self-sampling easy and reported no serious complications. Hemolysis affected 12/53 capillary biochemistry samples, and 5/53 capillary hematology samples coagulated. The good agreement for most parameters and excellent feasibility encourages the potential for capillary self-sampling of DMARD monitoring parameters, relevant limitations were hemolysis and aggregating platelets.

This study assessed the reliability of Roche Accu-Chek Inform II glucometers in a real-world setting. A retrospective analysis was conducted on 6,695 paired results. Capillary samples were tested using Roche Accu-Chek Inform II glucometers, while venous samples were analyzed using Roche Cobas c503/702 analyzers. Compliance was assessed using modified criteria based on the ISO 15197 guideline and the CLSI EP09-A3 guideline using Passing-Bablok regression analysis, Bland-Altman plots, and Surveillance Error Grid (SEG) analysis. The overall compliance of glucometer results within ±15% or 0.83 mmol/L (15 mg/dL) of the reference method was 81.5%, below the acceptance criterion of 94.6%. SEG analysis showed that 90.3% of the paired results fell within the No-risk zone, with less than 0.001% in the moderate/lower-risk zone. The Emergency Department results indicated 87.8% overall compliance and 92.2% of pairs falling in the No-risk zone. Based on the regression analysis, the glucometer results showed a positive constant bias of nearly 0.33 mmol/L (6 mg/dL). The Bland-Altman plots showed a positive mean difference of 0.43 mmol/L for results ≤5.55 mmol/L (≤100 mg/dL) and a positive mean percentage difference of 3.77% for results >5.55 mmol/L (>100 mg/dL), within the permissible deviation. The compliance values ranged from 76.0% to 90.3% for clinical concentration groups, with the highest compliance found between >16.65-22.20 mmol/L (>300-400 mg/dL). The Accu-Chek Inform II glucometers demonstrated in real-world reliability, with most results falling within acceptable risk categories. However, compliance still needs improvement, so manufacturers should assess opportunities for advancement.

Crystals in urinary sediment are commonly recognized structures, typically identified by a combination of crystal morphology and urine pH. In this paper, we present the first reported case of EDDP (2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidene) crystals, the primary metabolite of methadone, in a 67-year-old male with hepatorenal syndrome. Routine urinalysis revealed numerous needle-shaped crystals, which prompted further investigation. Advanced techniques, including Raman spectroscopy and mass spectrometry, confirmed the crystals to be EDDP. This case highlights the diagnostic challenge posed by drug-induced crystalluria, particularly in the context of complex comorbidities and chronic opioid therapy. Early recognition and identification of such crystals are crucial to preventing further kidney injury, emphasizing the importance of meticulous urine sediment analysis in clinical practice. This report broadens the spectrum of drugs known to induce crystal formation.

β-hydroxybutyrate (BHB) is recommended as a measure of ketosis and is often assessed by capillary samples on point-of-care (POC) meters. However, liquid chromatography tandem mass spectrometry (LC-MS/MS) is considered the gold standard for assessing venous samples. The POC device KetoSure^TM is recommended only for capillary samples from finger pricks. So far, KetoSure^TM has not been compared to LC-MS/MS just as it has not been evaluated if the sampling site influences the BHB concentration. Blood samples were collected from 16 healthy, fasting individuals before and after ingestion of ketone monoester. BHB concentrations were measured in capillary samples from the earlobe and fingertip, and in venous blood using KetoSure^TM. Venous plasma samples were collected for BHB quantification using LC-MS/MS. No sign of significant difference between values of BHB measured from the two capillary sampling sites were found. Interestingly, significantly higher values of BHB were measured in capillary samples compared to venous samples reflecting a systematic proportional relationship. No systematic difference was observed in the measured BHB concentrations when comparing KetoSure^TM and LC-MS/MS results: However, a significant mean bias of 32% reflects a skewness at very low BHB concentrations. In conclusion, capillary BHB concentration did not exhibit variation between the earlobe and fingertip. Conversely, a significant bias was observed between venous and capillary blood and between the POC and LC-MS/MS methods. It is recommended that caution be exercised if individual monitoring of BHB changes encompasses both capillary and venous sampling.

Obesity alters lipid and carbohydrate metabolism, which has an impact on micronutrient status. Zinc affects lipid and glucose metabolism while also acting as an anti-inflammatory and antioxidant in various physiological processes. It has a direct effect on the insulin-signaling system and acts as an insulin mimic. In this study we predicted that zinc deficiency in obese Serbian adults affects anthropometric parameters, lipid and glucose metabolic profiles, inflammation, and atherosclerotic markers. We conducted a case-control study with 31 adult obese individuals and 31 controls. Different methods were used to determine the values of anthropometric and biochemical parameters. Obese participants had significantly decreased serum zinc levels compared to controls (p < .01). In obese subjects, there is a significant negative correlation between zinc and body weight (ρ = -0.324, p < .05), body mass index (ρ = -0.351, p < .05), body fat mass (%) (ρ = -0.431, p = .006), and triglycerides (ρ = -0.317, p < .05), as well as a positive correlation between zinc and high-density lipoproteins (ρ = +0.453, p < .01) and lipoprotein (a) (ρ = +0.417, p < .01). Atherosclerotic index and lipoprotein (a) were significantly related to zinc (p = .0022 and p = .0016, respectively) independently of each other in obese subjects. Our results suggest that the determination of zinc levels in obese persons and their correlation with anthropometric and metabolic parameters could help in the identification of individuals at higher risk for cardiovascular disease.