Snežana Jovičić

Introduction: Needlestick injuries (NSIs) remain a significant occupational hazard during specimen collection. This study aimed to evaluate whether safety-mechanism design is associated with differences in NSI rates in a real-world clinical setting.,Material and Methods: This retrospective observational study evaluated reported wing-set NSIs at a 600+ bed U.S. hospital over a 36 month period. NSI rates during exclusive use of a manually activated safety winged blood collection set (18 months) were compared with rates during exclusive use of the semi-automatic safety winged blood collection set (12 months), excluding a 6-month transition period. Injury rates were annualized and compared using Poisson tests. Analyses were stratified by occupational role and clinical setting.,Results: A total of 23 NSIs were recorded. Following implementation of the semi-automatic device, the overall NSI rate decreased by 77.5% compared with the manual-activation device (rate ratio 0.225; 95% CI 0-0.654; p=0.005). Statistically significant reductions were observed among phlebotomists and in inpatient settings. No needlestick injuries were reported among ER technicians or students during the period of semi‐automatic device use.,Conclusions: Implementation of a semi-automatic safety winged blood collection device was associated with a statistically significant reduction in reported wing-set NSIs. These findings suggest that safety-mechanism design, particularly reduced reliance on user-dependent activation, may play a role in reducing occupational injury risk during specimen collection.

The European Union Safe Hearts Plan provides an opportunity to strengthen cardiovascular prevention, early detection, treatment, and monitoring across Europe. This EFLM position paper argues that laboratory medicine must be recognized as a central component of its implementation. Reliable and harmonized laboratory data underpin cardiovascular risk assessment, diagnosis, therapeutic guidance, longitudinal monitoring, and evaluation of population outcomes. Beyond the minimum health-check dataset, tiered and personalized pathways should integrate established biomarkers, specialist testing, and validated emerging technologies. EFLM proposes five priorities: embedding laboratory expertise in governance; translating core testing into personalized pathways; expanding equitable access through quality-assured decentralized models; linking testing to clinical action and value-based financing; and accelerating responsible innovation while strengthening professional capability. By connecting screening with diagnosis, treatment, and measurable outcomes, laboratory medicine can provide the quality, interpretation, and data infrastructure required to transform the Safe Hearts Plan from policy ambition into equitable cardiovascular health gains across Europe.

Hospital-acquired anemia is highly prevalent and largely preventable complication of hospitalization, affecting up to 40–74 % of patients and up to 90 % of intensive care units patients. Excessive diagnostic blood loss from routine phlebotomy represents a significant and modifiable contributor, with cumulative blood collection volumes independently associated with increased risk of moderate to severe anemia and subsequent transfusion. This narrative review examines the magnitude, clinical consequences, and systemic drivers of diagnostic blood loss, and positions sample volume management (SVM) as a critical, laboratory-led component of patient blood management. Evidence demonstrates that diagnostic sampling frequently exceeds analytical requirements multiple-fold, resulting not only in avoidable patient harm but also in substantial environmental and economic burden. SVM is presented as a structured, system-level framework encompassing demand management, reduction of per-sample volume, workflow optimization, and improvement of preanalytical quality. Interventions such as reduced-volume blood collection tubes, closed sampling systems, capillary and microsampling techniques, and total laboratory automation have consistently been shown to reduce phlebotomy-related blood loss and transfusion requirements without compromising analytical quality or patient safety. Furthermore, strengthening preanalytical processes and leveraging automation can minimize errors and prevent unnecessary recollection. Despite strong evidence and clear alignment with international standards, implementation remains inconsistent. Immediate, coordinated action is therefore required to embed SVM into routine practice through multidisciplinary collaboration, standardized protocols, continuous monitoring, and sustained change management. Integrating SVM into clinical workflows represents a high-value strategy to improve patient outcomes, enhance sustainability, and advance value-based laboratory medicine.

Objectives: Preanalytical errors account for approximately 60–70 % of all laboratory errors, with sample misidentification among the most frequent causes of inaccurate and unreliable test results. Pre-barcoded tubes (PBTs) are collection tubes uniquely identified during manufacturing with machine-readable labels, eliminating the need for manual labeling or barcode printing. This study aimed to evaluate the impact of PBTs implementation on preanalytical workflow efficiency. Methods: An anonymous online survey comprising 25 questions was distributed to 58 laboratories using PBTs in routine practice. The questionnaire captured demographic data as well as information on workflow changes, including full-time equivalent (FTE) requirements, turnaround time (TAT), and challenges encountered before, during, and after implementation. Results: A total of 44 responses (75.9 %) were received within four weeks. More than half of respondents processed up to 5,000 PBTs daily. Implementation of PBTs was associated with reduced sample misidentification rates and shorter TAT in over 80 % of laboratories. These improvements were primarily attributed to the elimination of manual labeling steps, faster automated sample registration, and enhanced integration with digital workflows, resulting in estimated time savings of 1–3 h per day. Additional benefits included reduced FTE requirements and fewer laboratory errors. During implementation, 67 % of laboratories reported resistance, mainly related to adaptation to new processes (43 %) and digital solutions (27 %); however, more than half completed the transition within one month. Conclusions: From the user perspective, PBTs implementation improves labeling safety and operational efficiency, reduces error rates, and supports streamlined, digitalized preanalytical workflows.

The HI-MOM project investigated the potential of metabolic biomarkers to improve the prediction and understanding of pregnancy complications, with a particular focus on the high-density lipoprotein metabolome (HDL-ome). While HDL-cholesterol levels are traditionally considered protective during pregnancy, HDL functionality depends on its complex lipid and protein composition, which remains insufficiently explored. Using HPLC/MS-MS, qPCR, immunoassays, electrophoresis, and spectrophotometry, we characterized longitudinal changes in the HDL-ome during physiological pregnancy and cardiometabolic pregnancy complications. Our findings revealed significant alterations in HDL particle size, cholesterol synthesis and absorption markers, sphingolipids, and phospholipid transfer protein gene expression during cardiometabolic complications of pregnancy. These changes were accompanied by impaired anti-inflammatory and antioxidative functions of HDL, indicating substantial HDL remodeling in adverse pregnancy outcomes. A major objective of the project was the identification of novel metabolic biomarkers for early risk assessment. Multimarker prediction models demonstrated the highest diagnostic accuracy when traditional clinical and demographic risk factors were combined with specific HDL-ome components, particularly sphingosine-1-phosphate, and the inflammatory marker resistin. These findings highlight the added value of integrating conventional and metabolomic biomarkers in pregnancy risk stratification. The project also demonstrated associations between maternal lipid metabolism and neonatal outcomes, suggesting that gestational lipid adaptations are influenced by pre-pregnancy nutritional status and may affect newborn health. Overall, the HI-MOM project supports the future development of personalized approaches for pregnancy monitoring, risk prediction, and outcome evaluation

Anaemia in pregnancy is common and is most frequently attributable to iron deficiency. However, physiological hemodilution, inflammation, hemoglobinopathies, folate or vitamin B12 deficiency, and chronic disease may contribute to reduced haemoglobin concentration. Current clinical practice remains largely centred on haemoglobin, red cell indices, and serum ferritin. Yet, ferritin interpretation in pregnancy is complicated by gestational changes, inflammation, obesity, infection, and the absence of universally accepted trimester-specific thresholds. This narrative systematic review summarises evidence for laboratory parameters beyond ferritin, including reticulocyte count, immature reticulocyte fraction, reticulocyte haemoglobin content, soluble transferrin receptor, soluble transferrin receptor-ferritin indices, mean reticulocyte volume, and percentage of hypochromic erythrocytes. Available data suggest that reticulocyte haemoglobin content and soluble transferrin receptor-based indices are the most clinically promising adjuncts for identifying iron-restricted erythropoiesis in pregnancy, whereas immature reticulocyte fraction and hypochromic erythrocytes remain insufficiently validated in pregnancy-specific diagnostic pathways. Diagnostic algorithms should integrate haemoglobin, red cell indices, inflammation assessment, ferritin, and functional biomarkers, while accounting for trimester, analytical platform, and local assay standardisation.

Background: Preanalytical errors are the most common laboratory errors and are often related to manual steps in blood sample collection and handling. Blood collection devices, particularly tube materials and separator gels, are important sources of preanalytical variability. VACUETTE® CAT serum separator tubes (SSTs) and LH lithium heparin plasma separator tubes (PSTs) recently transitioned from one separator gel formulation (Reference Gel B) to the other (Gel 2.0). To understand whether and how this change affects the analytical performance of routine clinical chemistry and immunochemistry testing, we have compared the performance of tubes containing Gel 2.0 with that of tubes containing Reference Gel B. Methods: This bicentric, retrospective study was conducted at two clinical laboratories during two observation periods: one using VACUETTE® CAT SSTs and LH PSTs with Reference Gel B, and a subsequent period using tubes with Gel 2.0. Centrifugation conditions routinely applied in participating laboratories were not aligned with the manufacturer’s Instructions for Use (IFU), which are considered binding. This deviation was locally validated and accepted for scientific purposes, reflecting routine practices in a real-world laboratory environment. Routine testing on the Siemens Atellica® Solution clinical chemistry and immunoassay system was evaluated. Equivalence was assessed using the nonparametric Hodges–Lehmann estimate of the median difference. Haemolysis index (H-index) categories were compared using Chi-squared testing. Stable patient populations and sufficient sample sizes were assumed. Results: A total of 253261 serum and 161486 plasma esults: results were analysed. No significant differences were observed between gel types for any analyte, confirming analytical equivalence. Haemolysis frequencies in 24025 serum and 10807 plasma samples were comparable between periods, with no significant differences detected. Conclusion: Gel 2.0 demonstrated equivalent analytical onclusion: performance and preanalytical quality to Reference Gel B. Its implementation did not result in analyte drift or increased haemolysis, supporting its safe use in routine laboratory testing.

Background: Phospholipid transfer protein (PLTP) regulates high-density lipoprotein (HDL) remodelling by transferring cholesterol and phospholipids and affecting particle size and function. Pregnancy alters lipid metabolism, but the adaptation of PLTP to pregnancy remains poorly understood. This study investigated longitudinal changes in PLTP gene expression and concentration during healthy pregnancy and pregnancy with cardiometabolic complications, and their associations with maternal lipid metabolism and inflammatory status. Methods: We followed 84 healthy and 20 pregnant women who developed gestational diabetes mellitus and hypertensive disorders during pregnancy. PLTP gene expression, PLTP concentration, advanced lipid profile parameters, and inflammatory status were analysed throughout the trimesters. Results: Comparable trajectories of changes in PLTP gene expression and PLTP concentrations were observed in both groups, but PLTP gene expression in the first trimester was significantly lower in the group with complications (p<0.05). Analysis of serum non-cholesterol sterols in HDL subfractions (NCSHDL) and plasma ceramides [ceramide C16:0 (Cer C16:0), ceramide C24:0 (Cer C24:0)] has revealed significantly lower desmosterolHDL (p<0.05), while significantly higher C24:0 (p<0.001). Conclusion: Our results showed altered PLTP gene expression, advanced lipid profile, and inflammatory status in the first trimester of pregnancy with cardiometabolic complications. Our findings emphasize the importance of a thorough investigation of lipid metabolism and inflammatory pathways in early pregnancy to improve the outcomes.

Medical laboratories require a great amount of energy, ranging from three to six times more than a standard office building. Also, they consume massive amounts of water and gases and produce diverse waste products, some of which are toxic. Their energy requirements are complex and when estimating the total carbon footprint of a medical laboratory, we need to keep in mind the different contributors present. First, laboratory instrumentation varies for various laboratory tests, requiring different amounts of electricity, gas, water, and consumables. Furthermore, according to some estimates, laboratory infrastructure of heating, ventilation, and air-conditioning (HVAC) system may account for 40-60% of energy consumption, depending on its complexity and different requirements for different buildings. A lighting/shading system may consume up to 15% of the total energy. Also, the computers and their supporting systems needed for laboratory data processing use electrical power and contribute to the carbon footprint of medical laboratories. The systematic approach to mitigate the environmental impact of the healthcare sector in general, and medical laboratories in particular, is the voluntary adoption of an Environmental Management System (EMS) according to the International Standards ISO 14001 or the European EMAS (Eco-Management and Audit Scheme). Focusing on managing energy efficiency, the ISO 50001 Energy Management Systems - Requirements with guidance for use, can help medical laboratories develop and implement an energy-saving strategy by establishing achievable energy usage goals, defining action plans to achieve them, and quantifying improvements. To prevent and manage the risks of uncontrolled energy consumption in medical laboratories, it is important to bear in mind the energy-intensive laboratory features, thus facilitating the implementation of strategies for energy conservation and sustainability. Additionally, laboratory buildings have a substantial embodied carbon that significantly affects their functional environmental impact. In recent years, many initiatives, tools, and methods that address the environmental sustainability of health research have been developed. Many of them are applicable and are used in clinical laboratory settings even though they are not developed specifically for it. Recently, the European Federation of Clinical Chemistry and Laboratory Medicine generated educational material that aims to both raise awareness of medical laboratories carbon footprint, and to guide them on how to decrease it. This review aims to give an overview of the current efforts to improve the sustainability of medical laboratories in the sense of energy conservation. We will present the extent of the environmental impact of healthcare structures and medical laboratories, identify the major contributors to their carbon footprint, focus on energy consumption, and finally, offer strategies that could mitigate it.

Catecholamines are adrenal hormones and neurotransmitters that follow a circadian rhythm, making a 24-hour urine collection the preferred sample. The HPLC method with electrochemical detection is the method of choice for their determination. Since sample stability is crucial for accurate metabolite measurement, this study examined the effects of storage duration and freeze-thaw cycles on catecholamine stability in urine. Stability testing was conducted on six 24-hour urine samples using HPLC (Alliance Waters e2695 Separations Module). Samples were divided into three groups: those stored at -20 °C, aliquots of eluates stored at +4 °C, and five samples subjected to six freeze-thaw cycles. Noradrenaline and adrenaline remained stable in eluates at +4 °C for 14 days, while dopamine levels significantly decreased within 7 days (p<0.05). At -20 °C, noradrenaline and adrenaline remained stable for 14 days, whereas dopamine concentrations were altered. Noradrenaline was stable for two freeze-thaw cycles, but adrenaline and dopamine changed after one. This study results suggest that samples should be processed immediately when possible. If not, they should be stored below -20 °C, avoiding repeated freeze-thaw cycles.