Clinical chemistry and laboratory medicine最新文献

Objectives: Clinical intent for laboratory testing ("indication") is rarely recorded in structured form, limiting contextual interpretation, auditability, and utilization stewardship. We developed a comprehensive, and clinically applicable framework that standardizes laboratory test indications and links them to indication-dependent utilization and interpretation.

Methods: A structured literature review on utilization, appropriateness, and request rationale informed an iterative, consensus-based process with a multidisciplinary expert panel to develop and operationalize an indication taxonomy and attribute schema. Structural coherence was assessed by comparing semantic distance hierarchies derived from indication labels alone with an enriched multi-layer ("layered prototype") representation incorporating these attributes. Use cases were applied to assess feasibility of indication-to-interpretation mapping.

Results: We defined 19 distinct indication types, grouped into five clusters across the clinical course: Initial Detection and Diagnostic Clarification, Disease Characterization and Prognosis, Therapy Guidance and Safety, Longitudinal Management and Reassessment, and Analytical and External Requirements. Each is specified with structured attributes and examples to support implementation. Semantic distance analyses supported a coherent hierarchy. Layered prototypes yielded more informative organization than labels alone, enabling context-dependent consolidation and guided deployment.

Conclusions: By providing explicit indication-to-interpretation mapping/logic, the framework closes a key gap in the total testing process between order entry and post-analytical interpretation. It supports context-specific decision limits, reporting logic, and stewardship analytics, and is amenable to formalization as a machine-readable ontology for interoperable implementation.

Objectives: This stability study aimed to evaluate the stability of 48 biochemical analytes in pooled serum samples derived from leftover sera over 14 days at room temperature (RT) and at 2-10 °C, and to assess the consistency of storage effects across independent pools. The goal was to determine the suitability of such materials for external quality assessment (EQA) schemes.

Methods: A total of 110 residual serum samples were derived from Greiner Bio-One Vacuette tubes (with or without separator gel) and randomly assigned to 10 pools. Aliquots were stored at RT or 2-10 °C and analysed on days 0, 1, 2, 3, 4, 7, and 14 using Roche Cobas and DiaSorin Liaison platforms. Percent deviations from baseline (PD%) were compared against maximum permissible differences (MPDs) derived from reference change values. Inter-pool variability was assessed by linear regression of standard deviations of PD%-values over storage time.

Results: Under refrigerated conditions, six analytes exceeded stability limits, with only alanine aminotransferase (ALAT), lactate dehydrogenase (LDH), and 1,25(OH)₂ vitamin D showing instability within seven days and the others not before day 14. At RT, 38/48 parameters remained stable for at least 4 days. Inter-pool variability increased significantly for only three parameters at 2-10 °C and nine at RT, with most slopes below 0.35 %/day, indicating largely matrix-independent degradation patterns.

Conclusions: The majority of analytes in pooled leftover sera demonstrated acceptable stability, particularly under refrigerated conditions. Storage effects occurred consistently across pools, supporting reproducibility. These findings indicate that pooled sera from diagnostic leftovers represent a practical resource for EQA when analysed within defined timeframes.

Objectives: Clinical laboratories play a vital role in healthcare but are also among the most resource-intensive hospital units. High energy and water consumption, extensive use of single-use plastics, and the generation of non-recyclable biomedical waste present major environmental challenges. This study aimed to quantify the environmental and economic burden associated with common and avoidable practices in clinical laboratory medicine, including: excessive blood collection, inappropriate test ordering, and unnecessary tube duplication in pre-analytical workflows.

Methods: Real-world data from the Clinical Biochemistry Laboratory of the AOU Maggiore della Carità (Novara, Italy) for the year 2024 were analysed to quantify the environmental and economic impact of inappropriate test ordering based on minimum retesting intervals, as well as pre-analytical practices, including redundant sample tube collection and excessive blood volumes relative to analytical requirements.

Results: Inappropriate retesting of selected biomarkers resulted in 2,931 unnecessary tubes, generating over 26.7 kg of avoidable waste. Redundant EDTA tubes for complete blood count, glycated haemoglobin, erythrocyte sedimentation rate, and haemoglobin electrophoresis led to 356.14 kg of excess waste, which could be eliminated through sample consolidation. In haematology, 264,834 CBC tests generated 2.62 tonnes of biological waste. For biochemistry, 3 million tests produced 36.98 tonnes of waste.

Conclusions: Excessive blood collection and unnecessary test repetition contribute to significant but avoidable environmental and financial burdens. Pre-analytical interventions, such as reducing tube volume and consolidating tests, could prevent over 40 tonnes of waste and save more than € 60,800 annually in a single laboratory.

Objectives: Despite growing interest in artificial intelligence (AI) and machine learning (ML), many laboratory professionals lack experience with developing in-house AI systems or implementing those supplied by external providers. The IFCC Committee on AI in Laboratory Medicine (C-AILM) conducted a survey to collect the status of AI/ML applications, challenges, and expert perspectives on key technical considerations.

Methods: An 20-item survey was distributed to laboratory professionals experienced in AI. It covered application status (in-house or provider-supplied, with or without regulatory approval); essential information to request from AI system providers; validation or verification practices; monitoring strategies; and perceived implementation challenges.

Results: Fifty complete responses from global experts were received. AI implementation in clinical laboratories was limited and heterogeneous. Most respondents agreed that AI systems provided externally, regardless of regulatory approval status, require local verification. Key information needed from providers included performance metrics from original and external datasets, and demographics of the training/test populations. For both approved and non-approved models, high-priority verification studies were local performance analysis, confirmation of intended-use alignment, and verification of privacy and security safeguards. Top monitoring strategies were regular accuracy checks and comparison against human decision-making. Leading challenges were insufficient IT infrastructure and lack of practical implementation guidelines.

Conclusions: Although many challenges remain, clinical laboratories demonstrate strong enthusiasm for AI, particularly with the growing prevalence of commercial AI products. The timely expert insights from our survey and C-AILM recommendations for both AI system providers and clinical laboratories on essential information, verification requirements, and monitoring strategies will inform standardized guideline development.

Objectives: Antiphosphatidylserine/prothrombin (aPS/PT) antibodies are promising non-criteria aPLs associated with antiphospholipid syndrome (APS) manifestations. Their influence on long-term outcomes and damage remains uncertain. To assess aPS/PT antibodies association with accrual damage and severe APS disease phenotypes, focusing on their potential for risk stratification.

Methods: This single-centre cohort study involved 163 patients who fulfilled the 2023 ACR/EULAR APS criteria. IgG/IgM aPS/PT, aCL, and anti-β2GPI antibodies were measured by commercial ELISA. Lupus anticoagulant (LA) was detected in accordance with the ISTH-SSC recommendation. Clinical data covered macrovascular, microvascular, obstetric, and hematologic manifestations. Damage was assessed using DIAPS.

Results: aPS/PT IgG and IgM were positive in 46.0 % and 65.6 %, respectively. aPS/PT IgG positivity was linked to microvascular involvement (58.7 % vs. 34.1 %, p=0.002), obstetric APS (57.4 % vs. 24.6 %, p<0.0001), valvular disease (17.3 % vs. 4.6 %, p=0.008), and thrombocytopenia (37.3 % vs. 12.5 %, p<0.0001). aPS/PT IgM positivity was also associated with microvascular APS (p=0.006), obstetric morbidity (p=0.02), and thrombocytopenia (p=0.01). In multivariable analysis, quadruple aPL positivity (LA + aCL + anti-β2GPI + aPS/PT) was independently linked to damage (OR 4.3, 95 % CI 1.3-14.5; p=0.02), with no other factors remaining significant.

Conclusions: Both IgG and IgM aPS/PT antibodies are associated with severe APS features, including microvascular and obstetric issues, as well as overall organ damage. Adding aPS/PT to standard aPL tests finds a subgroup of quadruple-positive APS patients at higher risk of damage. These results could help guide personalized APS management.

Recent advances in blood-based biomarkers for neurodegenerative diseases present promising opportunities for earlier diagnosis and more effective disease monitoring. However, challenges in standardizing sample collection, processing protocols, and data reporting continue to hinder reproducibility, limit cross-study comparability, and delay clinical adoption. As efforts toward harmonization progress (supported by technological innovation and integration into multimodal diagnostic strategies), blood biomarkers are expected to transition from research settings to routine clinical use, bringing precision medicine closer to individuals affected by these disorders.

Objectives: Diagnosing atypical IgG4-mediated anti-glomerular basement membrane (anti-GBM) disease is challenging because conventional serological assays poorly detect IgG4 antibodies. Here we study which commercial assays are affected and we describe proof-of-concept of improved IgG4 anti-GBM detection.

Methods: To investigate the scope of the diagnostic dilemma detecting IgG4 anti-GBM antibodies, serum from a patient with atypical IgG4-mediated anti-GBM was distributed to 36 laboratories participating in the Dutch External Quality Assessment (EQA) program. To improve IgG4 anti-GBM detection in the fluorescent enzyme immunoassay (FEIA), the standard anti-IgG conjugate was replaced with anti-IgG4 conjugate.

Results: We report the diagnostic delay of a patient with atypical anti-GBM disease who presented with an indolent disease course. Histopathology comprised hallmarks of classic anti-GBM disease including bright linear IgG deposits along the GBM but without the typical findings of diffuse crescentic and necrotizing glomerulonephritis. IgG anti-GBM test results were repeatedly negative. Histopathological subclass analysis demonstrated that the linear IgG deposits were predominantly IgG4. All 36 Dutch EQA-participants reported negative anti-GBM test results, demonstrating that the diagnostic challenge of detecting IgG4 anti-GBM is broadly applicable across multiple diagnostic assays. A minor modification to the manufacturer's standard protocol of the FEIA anti-GBM dramatically improved the assay's performance for measuring antibodies of the IgG4 isotype. Using the modified IgG4-GBM test, we were able to diagnose and monitor one more patient with atypical IgG4-mediated anti-GBM disease.

Conclusions: Here we demonstrate proof-of-concept of a modified IgG4 anti-GBM blood test allowing serological confirmation of atypical anti-GBM disease and sensitive monitoring of therapy response.

Objectives: Newborn screening for congenital hypothyroidism (CH) relies on thyroid-stimulating hormone (TSH) levels from dried blood spots (DBS). We investigated whether incorporating TSH variation across serial DBS could improve prediction of CH in term and preterm infants with complex risk profiles.

Methods: Among 207,895 newborns screened, 272 (0.13 %) were diagnosed with CH. TSH variations across 3 serial DBS were analyzed in 6,146 healthy infants (2.96 %). Predictive algorithms were developed using linear mixed-effects models in 1,968 term and 1,387 preterm infants with ≥2 and ≥3 DBS, respectively. Average DBS collection times were 58, 260, and 478 h for term and 63, 350, and 664 h for preterm infants. TSH was measured by GSP neonatal hTSH assay (Revvity).

Results: Daily TSH variation was influenced by the initial DBS1 value. For DBS1 >5.2 and <1.7 mUI/L, increase and decrease, respectively, in TSH level on DBS2 is detectable, and this particularly occurs in preterm infants. In preterms, CH could be excluded when TSH remained <5 mUI/L on DBS1, <6 mUI/L on DBS2, <4 mUI/L on DBS3, and with daily variation <12 % from DBS1 to DBS3 (sensitivity 100 %; specificity 77.85 %). Term infants with TSH <11 mUI/L on DBS1, <4.5 mUI/L on DBS2, and daily variation <13 % from DBS1 to DBS2 may be ruled out for CH (sensitivity 96.5 %; specificity 66.6 %).

Conclusions: Distinct predictive algorithms for term and preterm newborns, incorporating TSH variations as daily percentage changes, may improve CH rule out in children with complex risk profiles.