In our letter, we presented the challenges within medical biochemistry in a tertiary hospital in a measles outbreak. The letter somewhat shows the current situation in the first part. In the remaining part, the challenges in the work of the medical biochemical laboratory are listed and the significance of the most common biochemical and hematological analyzes for these patients is explained. This letter is an important clinical-epidemiological overview of the current situation that arose as a result of the measles outbreak.

Breast cancer is one of the most common types of cancer among women worldwide, therefore an early and precise process of diagnostics plays an important role in improving the prognosis and outcome of treatment. The application of artificial intelligence (AI) allows faster and more precise analysis of medical imaging, which contributes to the early detection of tumors and lowers the number of false-negative results. This review article analyzed 60 scientific papers and using the most recent findings about this topic, searched for AI implementation in breast cancer research and how AI may improve overall survival outcomes for breast cancer patients.

Introduction: Breast cancer (BC) is a malignant disease that predominantly affects women, with known genetic components such as mutations in tumor suppressor genes BRCA1 and BRCA2. Other risk factors include unhealthy lifestyles, lack of physical activity, and consumption of alcohol and cigarettes. Aging also plays a role in BC development, with hormonal influences such as estrogen and progesterone promoting cancer growth. Material and Methods: Research was conducted using data collection tools for risk factors and tumor markers from primary healthcare unit records. The sample comprised 200 women, divided into two groups based on BC diagnosis, with complete medical documentation. Male BC cases were excluded. Results: Statistical significance was found between genetic components, family history, aging, obesity, alcohol and cigarette consumption, longer hormone exposure, and female BC development using the Chi-Square test, confirmed by Fisher's Exact test. Tumor markers CA 15-3, CEA, CA 19-9, and CA 125 were useful for BC screening and metastasis detection, as determined by the One Sample T-test. In Sarajevo Canton, invasive ductal BC was the most common type among women, while lobular carcinoma in situ was the least common. Conclusion: Correlations between risk factors, including aging, unhealthy lifestyles, and hormone exposure, and increased BC risk were confirmed. Tumor markers CA 15-3, CEA, CA 19-9, and CA 125 were effective in diagnosis, screening, and metastasis detection in females, with sensitivity for regression detection at 81.8% and specificity at 100%.

Introduction: The diagnosis of coronavirus disease 2019 (COVID-19) disease is necessary for the further treatment of patients with the present symptoms, and molecular diagnostics is considered the gold standard. However, it is already known that patients with symptoms of the disease can have a negative test due to various factors. The purpose of this study is to evaluate the laboratory parameters in patients with symptoms of COVID-19 infection who have both positive and negative test results. Methods: The study included 101 samples from patients who tested positive for COVID-19 and 101 samples from patients who tested negative, both groups presenting symptoms of COVID-19. Data on the complete blood count, the absolute values of the differential blood count, and the D-dimer values were collected from the samples that were taken. Using blood count data, neutrophil-to-lymphocyte ratios, platelet-to-lymphocyte ratios, and systemic immune-inflammatory index (SII) were calculated. Results: Based on the examination and research, a significant increase and change in the values of inflammatory indices and D-dimer were determined. In addition to the increase of these values above the reference value, a positive correlation was confirmed between the inflammation index value and the D-dimer value. Conclusion: COVID-19-negative patients with characteristic symptoms of COVID-19 had higher values of lymphocytes and the determination of platelets and SII in these patients can be added to the diagnostic algorithm.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has caused a worldwide emergency. The disease is characterized primarily by symptoms of the respiratory system, but also by systemic inflammation. Since the onset of the disease, there has been a need for biomarkers to predict the severity of the clinical picture and the outcome of the disease. The aim of this study is to evaluate systemic inflammatory markers for predicting severity of COVID-19. Methods: The study was conducted at the Sarajevo Canton Health Center on a total of 170 adults suffering from COVID-19. 70 subjects had mild clinical picture, while the control group consisted of 100 subjects with moderate clinical picture. The results of complete and differential blood counts, C-reactive protein (CRP), and systemic inflammatory indexes (SII) (neutrophil/lymphocyte ratio [NLR], derived NLR [dNLR], platelet/lymphocyte ratio [PLR], and SII) were used to compare the groups. IBM SPSS Ver. 23 was used for statistical analysis and data processing. Results: The proportion of male patients in the group with a milder clinical picture was higher than the proportion of male patients with a moderate clinical picture, p = 0.016. The values of leukocytes and neutrophils were higher in patients with a moderate clinical picture (p = 0.006 and p < 0.001, respectively). The values of all inflammatory indexes (NLR, dNLR, PLR and SII) were higher in patients with a moderate clinical picture of COVID-19 than in patients with a mild clinical picture (p < 0.001 for NLR, dNLR, and SII; p = 0.023 for PLR). In the research, patient age showed no correlation and CRP showed no correlation with SII. Conclusion: SII show higher values in patients with a moderate compared with a mild clinical picture of COVID-19. These parameters can be cost-effective and useful indicators in patient classification, diagnosis, and probably in monitoring patients with COVID-19.

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Background: Psoriasis as an immune-mediated inflammatory skin disease. The basis of the pathogenesis of psoriasis is the dysregulation of immune cell function in genetically predisposed individuals. The characteristic dysfunction of the immune system in patients with psoriasis is manifested as a variation in the cellular phenotypic profile in accordance with the disease status. Objective: The aim of this study was to evaluate the immunophenotypic profile of lymphocytes obtained by flow cytometry as an auxiliary diagnostic tool in the objectivization of the PASI score. Methods: The study group included 40 patients with psoriasis, hospitalized and treated at Dermatology Clinic of Clinical center University of Sarajevo and 30 healthy individuals as controls. After venepunction, the blood samples for determining the immune profile were prepared following standard laboratory procedures using conjugated monoclonal antibodies and BD FACSCanto II flow cytometer. T-lymphocytes (CD3, CD4, CD8), B lymphocytes (CD19), Natural killer cells (NK), and activatet T-cells (CD3HLA) were determined for all patients. Based on the PASI score, the severity and area of the disease was assessed for all psoriasis patients by dermatology specialist. Results: Our data shows no significant difference in any of the lymphocyte subpopulations between psoriasis patients and healthy controls, except CD3HLA. CD3HLA has higher values in patients with psoriasis, p=0.015. Of all the parameters, only NK cells were significantly correlated to the PASI score (rho -0.279; p=0.048). ROC curve analysis revealed a statistically significant difference for the proportion of CD3 lymphocytes (AUC 0.799; p=0.004), CD8 lymphocytes (AUC 0.733; p= 0.023), NK cells (AUC 0.722; p=0.008) and CD3HLA activated T lymphocytes (AUC 0.347; p=0.034). Conclusion: Profile of major lymphocyte subsets in patients with psoriasis is similar to that of healthy controls. The values of CD3, CD8, NK, CD3HLA were defined as biomarkers capable of distinguishing psoriasis according to the severity of the disease. Immunophenotyping of peripheral blood lymphocytes can play an important role as an auxiliary diagnostic method in differentiating the clinical stages of psoriasis and objectifying the PASI score.