Introduction: Industrialization and urbanization led to a significant increase in the environment. Lead inhibits the activity of numerous enzymes, triggers oxidative stress, and causes protein biosynthesis dysregulation. Inhalation of lead particles is the most common route of intoxication associated with occupational exposure. This study aims to evaluate laboratory methods and biomarkers in the assessment of lead exposure. Methods: For non-experimental qualitative research, available scientific articles in English published in the relevant databases (MEDLINE and ScienceDirect) were used. The database search was performed using the keywords “Laboratory diagnostics”, “occupational exposure”, and “lead”. Results: Atomic absorption spectrometry (AAS) is the gold standard in laboratory monitoring of occupational lead exposure. Inductively coupled plasma with mass spectrometry is a commonly used method described as more sensitive than AAS due to its low detection limit. Lead concentrations can be determined in various samples, but blood and urine are the most commonly used in laboratory practice. The most important exposure biomarker is the enzyme δ-aminolevulinic acid dehydratase (ALAD) in the blood, which is characterized by progressive inactivation by lead and a negative correlation with its concentration. The concentration of urinary delta-aminolevulinic acid (δ-ALA-U) reflects the state of impaired enzyme function in heme biosynthesis. In addition, determining blood zinc protoporphyrin and urinary coproporphyrin levels significantly aids in assessing occupational lead exposure disorders. Conclusion: The availability of the laboratory methods used and the biomarker specificity and sensitivity play an important role in the adequacy of lead exposure monitoring. Accurate determination of ALAD and δ-ALA-U concentrations, along with other biomarkers, is critical for assessing individuals exposed to lead.

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Background: Coronavirus disease 2019 (COVID-19) can cause a wide clinical spectrum, ranging from asymptomatic to severe disease with a high mortality rate. In view of the current pandemic and the increasing influx of patients into healthcare facilities, there is a need to identify simple and reliable tools for stratifying patients. Objective: Study aimed to analyze whether hemogram-derived ratios (HDRs) can be used to identify patients with a risk of developing a severe clinical form and admission to hospital. Methods: This cross-sectional and observational study included 500 patients with a confirmed diagnosis of COVID-19. Data on clinical features and laboratory parameters were collected from medical records and 13 HDRs were calculated and analyzed. Descriptive and inferential statistics were included in the analysis. Results: Of the 500 patients, 43.8% had a severe form of the disease. Lymphocytopenia, monocytopenia, higher C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR) were found in severe patients (p < 0.05). Significantly higher neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), neutrophil-to-platelet ratio (NPR), neutrophil-to-lymphocyte-to-platelet ratio (NLPR) and CRP-to-lymphocyte ratio (CRP/Ly) values were found in severe patients (p < 0.001). In addition, they have statistically significant prognostic potential (p < 0.001). The area under the curve (AUC) for CRP/Ly, dNLR, NLPR, NLR, and NPR were 0.693, 0.619, 0.619, 0.616, and 0.603, respectively. The sensitivity and specificity were 65.7% and 65.6% for CRP/Ly, 51.6% and 70.8 for dNLR, 61.6% and 57.3% for NLPR, 40.6% and 80.4% for NLR, and 48.8% and 69.1% for NPR. Conclusion: The results of the study suggest that NLR, dNLR, CRP/Ly, NPR, and NLPR can be considered as potentially useful markers for stratifying patients with a severe form of the disease. HDRs derived from routine blood tests results should be included in common laboratory practice since they are readily available, easy to calculate, and inexpensive.

[This corrects the article DOI: 10.3389/fpubh.2022.795841.].

Background: Correct measuring of blood and urine creatinine level is necessary for identification and tracking of chronic kidney disease (CKD). Objective: The aim of this study is a comparison of Jaffe and enzymatic methods for measuring creatinine in serum and in urine, in order to determine whether there are any statistical significant differences between them, and whether they are reflected on creatinine clearance calculation and estimated glomerular filtration rate (eGFR). Methods: Creatinine in serum and urine was measured for the group of patients (N=60; female=34, male=26) from 24 to 69 years of age by using Jaffe’s method on Dimension RxL biochemical analyzer, and enzymatic method on integrated biochemical and immunochemical analyzer Architect ci8200, and obtained levels are used for creatinine clearance calculation and eGFR. Results: The methods correlate well, both in measuring serum creatinine (r 1 = 0.990) and in measuring urine creatinine (r 2 =0.974). There are no statistically significant differences between them (p=0.57). Measuring creatinine using different methods showed no statistically significant differences in the calculated clearances (p=0.93), they significantly correlate (r=0.9722). eGFR, using the MDRD and CKD-EPI formulas, were not statistically significantly different, regardless of the used method. Conclusion: Apart from significant correlations between the used methods, the results of using the Jaffe and enzymatic methods showed no significant differences at measuring serum creatinine level, or creatinine clearance and glomerular filtration rate.

Introduction: Laboratory personnel (LP) represent a high-risk group of healthcare workers for whom the primary laboratory environment and specific work activities are a major source of potential exposure to health hazards. This study aimed to evaluate the developed matrix and assess risk based on self-assessment. Methods: This multicenter, qualitative, and cross-sectional study was conducted on LP employed in biomedical laboratories. The respondents were divided into groups according to their territorial affiliation. The data collection tool used was a six-area questionnaire distributed online through a network of professional associations. For the risk assessment, a matrix was developed with scores ranging from 0 to 650, dividing the risk level into four categories. Descriptive and inferential statistical methods were used for the statistical analysis. Results: The developed model combined the classification of risk and risk factors with a certainty of p < 0.001. The regression analysis showed that working conditions had the greatest influence on overall risk, followed by physical, biological, and physical hazards. Of the 640 respondents, the medium risk category was the highest in European Union (EU) countries (81.2%). Comparing the values in the high-risk category between the Bosnians and Herzegovinians (BiH) group and the Republic of Serbia, Republic of Northern Macedonia, and Montenegro (SCM) group with the EU group, a doubling (16.6%: 36.7%) and tripling (16.6%: 52.1%) of the proportion was found, respectively (p < 0.001). Overall, 1.7% of the LPs from BiH fell into the high-risk category. Conclusions: The designed matrix provides a reliable basis for identifying risk predictors in the study population and can serve as a useful tool for conducting risk assessments in biomedical laboratories. The results of the risk assessment indicate significant differences between the studied groups and highlight the need for increased control of BiH workplaces through new regulatory requirements.