Electronic Journal of the International Federation of Clinical Chemistry and Laboratory Medicine最新文献

Thiopurine methyltransferase (TPMT) enzyme plays a key role in the metabolism of the thiopurine drugs that are used for the treatment of inflammatory diseases. Mutations in the TPMT gene cause abnormal metabolism, resulting in toxicity; therefore, TPMT genetic analysis has been recommended for effective dose management. We retrospectively analysed data to determine the distribution of TPMT genotypes in a western Indian population. TPMT genotyping test was performed on 1000 patients with different inflammatory conditions between January 2009 and October 2023. The common TPMT genotypes *2, *3A, *3B and *3C were detected by amplification refractory mutation system - polymerase chain reaction (ARMS-PCR) and polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) techniques. TPMT mutants were detected in 36 (3.6%) patients, of whom 14 (39%) had TPMT*1/*3A, 19 (53%) had TPMT*1/*3C, two (5.5%) had TPMT*1/*3B, and one (2.8%) had TPMT*3B/*3B alleles; mutant allele frequencies were 0.7% for *3A, 0.2% for *3B and 1.65% for *3C. A sub-group analysis explained thiopurine toxicity in only 33% patients by TPMT gene polymorphism whereas in 67% the toxicity remained unexplained. The low prevalence of TPMT mutants (3.6%) along with unexplained thiopurine toxicity suggest that TPMT genotyping solely might be clinically less relevant in patients of Indian origin, underscoring the role of other genetic factors that may be involved in thiopurine toxicity in these patients.

Background: The relationship between laboratory results and clinical decisions, including diagnoses, is not always clear. This study aims to determine the association between abnormal laboratory test results and diagnoses recorded by the clinicians within the electronic medical records in tertiary hospital settings.

Method: We conducted a retrospective observational study using anonymised linked hospital data of 223,789 adult admissions between January 2020 and December 2021 in two Local Health Districts in New South Wales, Australia. Data extracted from hospital information systems included patient demographics, recorded clinical diagnoses and laboratory test results. We analysed correlations between abnormal results from common laboratory tests (nasopharyngeal/oral swab SARS-CoV-2 PCR, serum/plasma total prostate-specific antigen (PSA) antigen [PSA], free thyroxine [free T4], thyroid stimulating hormone [TSH], cardiac troponin T, and cortisol) and their respective recorded diagnoses.

Results: We observed the following Spearman correlation coefficients between abnormal laboratory test results and their corresponding recorded clinical diagnoses: positive SARS-CoV-2 PCR and COVID-19 (ρ=1.00), total PSA >10 μg/L and prostate cancer (ρ=0.66), free T4 >25.0 pmol/L and hyperthyroidism (ρ=0.58), TSH >5.00 mIU/L and hypothyroidism (ρ=0.56), TSH <0.30 mIU/L and hyperthyroidism (ρ=0.55), cardiac troponin T >20 ng/L and acute coronary syndrome (ρ=0.51), free T4 <8.0 pmol/L and hypothyroidism (ρ=0.42), and cortisol <80 nmol/L and adrenal insufficiency (ρ=0.33).

Conclusions: This study demonstrates that abnormal laboratory results play an important but varied role in clinical diagnoses. The weaker associations highlight that laboratory tests may be utilised differently in different clinical pathways, underscoring the complex relationship between laboratory results and clinical diagnoses, and the importance of considering abnormal test results in the appropriate clinical context.

Introduction: Artificial intelligence (AI) is revolutionizing the healthcare sector via advanced tools to improve diagnostic accuracy, operational efficiency, and decision-making. In clinical laboratories (CLs), the integration of AI automates the processing and analysis of large volumes of data, enables the early detection of diseases, and supports personalized medicine. Determining how personnel involved in the use of AI in CLs conceptualize AI can enable the identification of challenges and difficulties impeding its implementation.

Methods: An observational, prospective, cross-sectional, and comparative study was performed using an online survey for CL or research professionals in public or private CL throughout Mexico. The survey had 36 questions aimed at obtaining sociodemographic information and conceptualization of different aspects of AI, namely, familiarity, use, concerns, limitations, and useful applications.

Results: Overall, 125 men and 237 women (aged 19-81 years) participated in this study. The survey results showed that CL or research professionals were familiar with AI in general. They preferred to use AI to reduce pre-analytical errors (67%) and save time (65%). Lack of knowledge and training (74%) and fear of being replaced (66%) were identified as major AI-related concerns; the ethical aspects of AI were also a main concern. Only 4.7% of respondents had received formal AI training, but 84.8% were willing to take AI courses.

Conclusion: The findings highlight opportunities and priorities to promote AI-related public and educational policies, regulate AI adoption in CLs, develop optimal training strategies, as well as foster ethics, avoiding the exclusion of particular social groups.

Background: Rheumatoid Arthritis (RA) is a chronic, inflammatory autoimmune disease that mainly affects small joints and progresses to larger joints. It impacts approximately 1% of the global population, with women being three times more likely to develop it than men, typically between ages 40 and 50. Genetic and environmental factors, including vitamin D deficiency, contribute to RA development. The vitamin D receptor (VDR) gene plays a crucial role in regulating metabolism and inflammation, making it a key candidate in RA.

Aims: This study determines the relationship between VDR FokI (rs10735810) and VDR BsmI (rs1544410) gene polymorphisms in RA patients and healthy controls.

Methods: A total of 400 participants were included in the study, consisting of 200 RA patients and 200 healthy controls. Genetic varations of VDR genes was performed using the PCR-RFLP technique.

Result: Among 200 RA patients, 42 (21%) were male and 158 (79%) were female, while in the control group, 40 (20%) were male and 160 (80%) were female. The average age of RA patients was 43±17 years and a mean disease onset at age 30.3±19.3 years. The Ff and ff genotypes of the FokI polymorphism were significantly more frequent in RA patients (OR=1.8, p=0.011 and OR=2.8, p=0.004, respectively). For the BsmI polymorphism, the Bb genotype showed a significant association with RA (OR=1.5, p=0.049), while the bb genotype did not (OR=1.4, p=0.241). Gender-based analysis revealed higher frequencies of the Ff, ff, and bb genotypes in females, with significant associations for Ff (OR=3.0, p=0.009), ff (OR=4.5, p=0.002) for Bsml genotype only bb (OR=3.9, p=0.006) was significantly increase the risk of RA.

Conclusions: This study concluded that the VDR FokI (rs10735810) gene polymorphism was associated with RA, while the VDR BsmI (rs1544410) polymorphism did not appear to have a significant association with the disease.

Background: Diabetic nephropathy (DN) is a prevalent and severe complication of type 2 diabetes mellitus (T2DM), contributing to kidney disease and cardiovascular risks. Oxidative stress and inflammation play crucial roles in DN pathogenesis. This study investigates the association of inflammatory cytokines, oxidative stress markers, and cortisol with albuminuria in T2DM patients.

Methods: A cross-sectional study was conducted on 150 T2DM patients categorized into normoalbuminuria, microalbuminuria, and macroalbuminuria groups. Blood samples were analyzed for total antioxidant capacity (T-AOC), pro-inflammatory cytokines (TNF-α, IL-1, IL-6, IL-8), high-sensitivity C-reactive protein (hsCRP), and cortisol levels. Statistical analyses included ANOVA and logistic regression.

Results: T2DM patients with albuminuria exhibited significantly lower T-AOC (P=0.027) and elevated TNF-α (P=0.006), IL-1 (P<0.001), IL-6 (P<0.001), IL-8 (P<0.001), hsCRP (P<0.001), and cortisol (P<0.001). High tertiles of TNF-α, IL-6, and hsCRP were strongly associated with increased albuminuria risk, particularly in overweight and hypertensive patients.

Conclusion: The findings highlight the interplay of oxidative stress, inflammation, and metabolic dysregulation in DN progression. Elevated inflammatory markers and cortisol levels correlate with albuminuria severity, emphasizing their potential as biomarkers for early DN detection. Targeting inflammatory pathways may offer therapeutic strategies to mitigate DN progression in T2DM patients.

Hematological disorders are frequently encountered at the doctor's office and in the emergency room. Sideroblastic anemia, a rare hematological malady, is characterized by ring sideroblasts in the red blood cells due to accumulation of poorly transported and underutilized iron. Unlike primary sideroblastic anemia which can be conclusively diagnosed through genetic testing, the more common secondary form of the disease requires intricate cascading of several preliminary and confirmatory laboratory testing to determine the accurate etiology and provide the appropriate management regimen. The scope of laboratory medicine is broadening; clinical chemists and other laboratorians are tasked with directing broader clinical pathology sections, including Core lab hematology. Understanding the testing dynamics, diagnostic criteria and management of hematological diseases is fundamental to attaining success in consulting with providers to manage diseases such as sideroblastic anemia. Via a relevant case study, we explore the etiology, workup, symptoms, and treatment of myelodysplastic syndrome-induced sideroblastic anemia.

Background: Centrifugation of specimens is an important pre-analytical process that significantly impacts turnaround time, enabling clinicians to diagnose, treat, and monitor patients more effectively. In this study, we verified different combinations of tubes and identified optimal centrifugation settings for chemical and immunological assays.

Methods: We evaluated 40 leftover blood samples and collected them in 4-mL vacutainer and 2-mL vacuette lithium heparin tubes. All the tubes were centrifuged using an Abbott Automation GLP system. The first set of samples was centrifuged according to the manufacturer's guidelines. The second and third sets of samples were centrifuged at 2700×g for 7 and 5 min, respectively. All samples were analyzed through 30 chemical and 9 immunological assays on Alinity ci analyzers. The allowable total error, paired t-test, slope, intercept, and correlation coefficient (R) were used to determine the significance of differences in the first set of samples.

Results: Centrifugations for 7 and 5 min at 2700×g were within the acceptable range from the manufacturer's protocol after testing 39 assays in both vacutainer and vacuette lithium heparin tubes, except for LDH that was centrifuged for 5 min at 2700×g.

Conclusions: Shorter centrifugation times (7 min at 2700×g) can be used for different tube combinations. Centrifugation for 5 min at 2700×g affected LDH assays in vacutainer and vacuette lithium heparin tubes.

While current systems for continuous glucose monitoring (CGM) are safe and effective, there is a high degree of variability between readings within and across CGM systems. In current CGM performance studies, device readings are compared to glucose concentrations obtained with a comparator ("reference") measurement procedure (usually capillary or venous glucose). However, glucose concentrations from capillary and venous samples can systematically differ, often by as much as 5 to 10%. Different comparator methods have shown biases of up to 8%, and comparator devices of the same brand can systematically differ by more than 5%. To address these issues, the Working Group on CGM of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC WG-CGM) recommends standardizing study procedures and the comparator measurement process in CGM performance studies. The majority of IFCC WG-CGM members recommend the use of capillary samples as reference, mainly because CGM readings will then be aligned better with results from self-monitoring of blood glucose (SMBG). Even with factory-calibrated CGM systems, manufacturers require CGM users to perform SMBG in some situations, e.g., manual calibration, confirmation of extreme readings, discordance between CGM readings and symptoms of hyper- or hypoglycemia, or intermittent signal loss. Comparator devices should meet defined analytical performance specifications for bias and imprecision. Comparator bias can be reduced by retrospective correction of comparator values based on measurements with a method or materials of higher metrological order. Once manufacturers align CGM readings of their systems with comparator results using standardized procedures, variability across CGM systems will be reduced.

Background: Diabetes is an established risk factor for coronary artery disease (CAD), with substantial evidence linking it to a higher prevalence of multivessel disease and worse cardiovascular outcomes. This study aimed to explore the relationship between lipid profile and diabetes with severity of CAD by evaluating the degree of stenosis as assessed by Gensini Score (GS).

Methods: A total of 300 participants were included: 100 CAD patients with diabetes, 100 CAD patients without diabetes, and 100 healthy controls. Serum lipoproteins were quantified using standard colorimetric methods, while HbA1c levels were determined through HPLC. GS was assessed using angiographic data obtained from the catheterization laboratory.

Results: Significant differences in lipid profile, and HbA1c were observed between diabetic CAD patients, non-diabetic CAD patients, and healthy controls. The GS in patients with CAD was markedly elevated in the diabetic CAD cohort (32.97±22.47) in comparison to the non-diabetic CAD cohort (28.70±20.60). A positive correlation was found between HbA1c (r²=0.061), random blood sugar (r²=0.23), and TG (r²=0.00) with the GS. Conversely, HDL levels (r²= -0.074) exhibited a significant negative correlation with GS.

Conclusion: Our results suggest that lipoproteins and diabetic indicators have a considerable impact on the severity of CAD. This highlights the need for a more personalized approach in managing diabetes and CAD, incorporating regular monitoring of glucose and lipid levels to evaluate cardiovascular risk.