Aim: To investigate out-of-hospital cardiac arrest (OHCA) trend, provided advanced life support (ALS) measures, automated external defibrillator (AEDs) utilization and by-standers involvement in cardiopulmonary resuscitation (CPR) during OHCA incidents. Methods: This cross-sectional study encompassed data pertaining to all OHCA incidents attended to by the Emergency Medical Service of Canton Sarajevo, Bosnia and Herzegovina, covering the period from January 2018 to December 2022. Results: Among a total of 1131 OHCA events, 236 (20.8 %) patients achieved return of spontaneous circulation (ROSC); there were 175 (74.1%) males and 61 (25.9%) females. The OHCA incidence was 54/100.000 inhabitants per year. After a 30-day period post-ROSC, 146 (61.9%) patients fully recovered, while 90 (38.1%) did not survive during this timeframe. Younger age (p<0.05), initial rhythm of ventricular fibrillation (VF) or pulseless ventricular tachycardia (VT) (p<0.05) and faster emergency medical team (EMT) response time (p<0.05) were significantly associated with obtaining ROSC. Only 38 (3.3%) OHCA events were assisted by bystanders, who were mostly medical professionals, 25 (65.7%), followed by close family members, 13 (34.3%). There was no report of AED usage. Conclusion: This follow-up study showed less ROSC achievement, similar bystanders’ involvement, similar factors associated with achieving ROSC (age, EMT response time) and a decline in OHCA events (especially in year 2021 and 2022) comparing to our previous study (2015-2019). There was an extremely low rate of bystander engagement and no AEDs usage. Governments and health organizations must swiftly improve public awareness, promote better practice (basic life support), and actively encourage bystander participation.

Background: Lactate dehydrogenase (LDH) isoenzyme assay was used widely in the past to diagnose myocardial infarction (MI). Recent studies show that lactate dehydrogenase seems to be a promising biomarker of adverse left ventricular remodeling. Objectives: Higher levels of these biomarkers were associated with lower odds for favorable reverse remodeling in patients with MI. Methods: The study was performed on patients with the first occurrence of acute myocardial infarction (ST-elevation myocardial infarction (STEMI) or non-ST-elevation myocardial infarction (NSTEMI)), aged 34 to 80 years who underwent catheterization at the admission or during their hospital stay depending on indications. In this study, we compared peak levels of lactate dehydrogenase (LDH) and left ventricular ejection fraction (LVEF). Peak values of LDH were used from the second to the fourth day of hospitalization. Echocardiography has been done in the first 72 hours, which represents an early phase of cardiac remodeling. The ejection fraction was evaluated using the Simpson method. Results: Spearman's rank test showed a negative, statistically significant correlation between LDH and ejection fraction ρ(80)=−0.543, p<0.001. Weighted least squares regression model included LDH concentration, age, and type of myocardial infarction (STEMI/NSTEMI), and the slope coefficient for the LDH level was −0.010 (95% confidence interval (CI): −0.013 to −0.006). With each unit of LDH increase, there was a decrease of 0.01% in left ventricular ejection fraction when age and type of myocardial infarction were held constant. Conclusion: The increased LDH level could be a new predictor for early myocardial remodeling after the first occurrence of myocardial infarction independent of age and type of myocardial infarction.

This paper introduces a novel method that leverages artificial neural networks to estimate magnetic flux density in the proximity of overhead transmission lines. The proposed method utilizes an artificial neural network to estimate the parameters of a mathematical model that describes the magnetic flux density distribution along the lateral profile for various configurations of overhead transmission lines. The training target data is acquired using the particle swarm optimization algorithm. A performance comparison between the proposed method and the Biot-Savart law-based method is conducted using an extensive test dataset. The resulting coefficient of determination and mean square error values demonstrate the successful application of the proposed method for a range of different spatial arrangements of phase conductors. Furthermore, the performance of the proposed method is thoroughly assessed on multiple test cases. The practical relevance of the proposed method is highlighted by contrasting its results with the field measurements obtained in the proximity of a 400 kV overhead transmission line.

Key Clinical Message The diagnosis of extensive pulmonary tuberculosis, especially in young people, should take into account the possibility of an associated systemic autoimmune disease. Infections remain an important cause of morbidity and mortalityin systemic lupus erythematosus. This case illustrates the importance of recognizing the association of systemic autoimmune diseases and infections and the need for a multidisciplinary approach.

Vitamin D plays significant role in calcium metabolism and in bone and vascular calcifications. To investigate the association between vitamin D level, arterial hypertension, arterial stiffness and coronary calcifications detected by MSCT. Method: A 2 female case report comparative to each other investigated the correlation between vitamin D serum level, blood pressure, arterial stiffness and severity of the coronary calcification using MSCT diagnostic tool estimating the calcium score. The first case report showed that decreased level of vitamin D is correlated with increased blood pressure, increased arterial stiffness and with a severe coronary calcifications. The second case report showed normal blood pressure, normal vascular age and low calcium score in a no-defficient vitamin D female. Vitamin D has impact on blood pressure, arterial stiffness, coronary calcifications and coronary heart disease. The lower vitamin D, the higher arterial blood pressure, arterial stiffness and coronary calcium score.

The deployment of diverse data-generating technologies in livestock farming holds the promise of early disease detection and improved animal well-being. In this paper, we combine routinely collected dairy farm and herd data with weather and high frequency sensor data from 6 farms to predict new lameness events in various future periods, spanning from the following day to 3 weeks. A Random Forest classifier, using input features selected by the Boruta Algorithm, was used for the prediction task; effects of individual features were further assessed using partial dependence plots. We achieve precision scores of up to 93% when predicting lameness for the next 3 weeks and when using information from the last 3 weeks, combined with a balanced accuracy of 79%. Removing sensor data results have tendency to reduce the precision for predictions, especially when using information from the last one,2 or 3 weeks. Moving to a larger data set (without sensor data) of 44 farms keeps the similar balanced accuracy but reduces precision by more than 30%, revealing a substantial a trade-off in model quality between false positives (false lameness alerts) and false negatives (missed lameness events). Sensor data holds promise to further improve the precision of these models, but can be partially compensated by high resolution data from other systems, such as automated milking systems.

BACKGROUND Pharmacological treatment options for patients with dementia owing to Alzheimer's disease are limited to symptomatic therapy. Recently, the US Food and Drug Administration approved the monoclonal antibody lecanemab for the treatment of amyloid-positive patients with mild cognitive impairment (MCI) and early Alzheimer´s dementia. European approval is expected in 2024. Data on the applicability and eligibility for treatment with anti-amyloid monoclonal antibodies outside of a study population are lacking. AIMS This study examined eligibility criteria for lecanemab in a real-world memory clinic population between 1 January 2022 and 31 July 2023. METHOD We conducted a retrospective, single-centre study applying the clinical trial eligibility criteria for lecanemab to out-patients of a specialised psychiatric memory clinic. Eligibility for anti-amyloid treatment was assessed following the phase 3 inclusion and exclusion criteria and the published recommendations for lecanemab. RESULTS The study population consisted of 587 out-patients. Two-thirds were diagnosed with Alzheimer's disease (probable or possible Alzheimer's disease dementia in 43.6% of cases, n = 256) or MCI (23%, n = 135), and 33.4% (n = 196) were diagnosed with dementia or neurocognitive disorder owing to another aetiology. Applying all lecanemab eligibility criteria, 11 (4.3%) patients with dementia and two (1.5%) patients with MCI would have been eligible for treatment with this compound, whereas 13 dementia (5.1%) and 14 (10.4%) MCI patients met clinical inclusion criteria, but had no available amyloid status. CONCLUSIONS Even in a memory clinic with a good infrastructure and sufficient facilities for dementia diagnostics, most patients do not meet the eligibility criteria for treatment with lecanemab.

Although deep learning (DL) algorithms have been proved to be effective in diverse research domains, their application in developing models for tabular data remains limited. Models trained on tabular data demonstrate higher efficacy using traditional machine learning models than DL models, which are largely attributed to the size and structure of tabular datasets and the specific application contexts in which they are utilized. Thus, the primary objective of this paper is to propose a method to use the supremacy of Stacked Bidirectional LSTM (Long Short-Term Memory) deep learning algorithms in pattern discovery incorporating tabular data with customized 3D tensor modeling in feeding neural networks. Our findings are empirically validated using six diverse, publicly available datasets each varying in size and learning objectives. This paper proves that the proposed model based on time-sequence DL algorithms, which were generally described as inadequate when dealing with tabular data, yields satisfactory results and competes effectively with other algorithms specifically designed for tabular data. An additional benefit of this approach is its ability to preserve simplicity while ensuring fast model training also with large datasets. Even with extremely small datasets, models can be applied to achieve exceptional predictive results and fully utilize their capacity.

Aim: During the pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), many countries reported a significant decrease in the prevalence of influenza virus cases. The study aimed to characterize the flu seasons from 2018 to 2023 in Sarajevo Canton, Bosnia and Herzegovina (B&amp;H), and to assess the possible impact of the SARS-CoV-2 pandemic on the influenza A and B virus circulation.&nbsp; Methods: The CDC Human Influenza Virus Real-Time RT-PCR Diagnostic Panels were used for the detection of influenza virus A and B, and subtyping of influenza virus A (H1pdm09 virus and H3). The data for this regis-try-based retrospective study were collected at the Clinical Centre of the University of Sarajevo, Unit for Clinical Microbiology (the laboratory that acts as a referral for the detection and characterization of influenza virus and SARS-CoV-2 in Federation B&amp;H). Results: In the 2018/2019 and 2019/2020, an equal percentage of positive cases was recorded (148/410; 36%, and 182/504; 36%, respectively). The absence of the influenza virus was observed in 2020/2021. During 2021/2022, influenza virus was detected among 19/104 (18%) patients and slightly increased in 2022/2023 (45/269; 17%). The switch of the influenza B virus lineage was observed. Conclusion: The SARS-CoV-2 virus had an impact on the prevalence of influenza virus infection among the population of the Sarajevo Canton, B&amp;H. Since the interactions between these two viruses are not entirely clear, awareness of a possible threat to public health is crucial.

<p><strong>Aim </strong>To determine the normative range of ultrasound dimensions for the liver, spleen and kidneys in healthy children according to gender, age, body measurements, body surface area (BSA), and the influence of ethnicity on organ size.<br /><strong>Methods </strong>The prospective study included children, ranging from full-term neonates to children aged 15, with normal ultrasonographic (US) findings of the liver, spleen and kidney and no clinical evidence of a disease. Gender, age, as well as body measurements and BSA, were determined for each child along with US measurements, and normative ranges were established.&nbsp;<br /><strong>Results </strong>US images of the liver and spleen from 372 children and 366 US images of kidneys of 366 children were included. US measurements of the liver, spleen and kidney correlated well with gender, age, body weight and height, and often differed to a greater or lesser extent from the normal range of measurements (5th to 95th percentile) reported in other studies.<br /><strong>Conclusion </strong>Our results differed slightly from other reports conducted in Europe, but larger differences compared to measurements performed on children on other continents were found. Thus, our study confirmed that ethnically appropriate and modern tables of normal ultra-sound dimensions for the liver, spleen and kidneys should be used, and that the national nomogram is justified.</p>

<p><strong>Aim </strong>To evaluate the clinical impact of corticosteroids (CS) overuse in inflammatory bowel disease (IBD) patients. Excessive use of CS could delay more efficacious treatment and may indicate poor quality of care.<br /><strong>Method </strong>This is a two-phase study that used Steroid Assessment Tool (SAT) to measure corticosteroid exposure in IBD patients. In the first phase data from 211 consecutive ambulatory patients with IBD (91 with ulcerative colitis, 115 with Crohn's disease, and five with unclassified inflammatory bowel disease) were analyzed by SAT. In the second phase, one year after data entry, clinical outcome of patients with cortico-steroids overuse was analysed.<br /><strong>Results </strong>Of the 211 IBD patients, 132 (62%) were not on corticosteroids, 45 (22%) were cortico-steroid-dependent and 34 (16%) used corticosteroids appropriately, according to the European Crohn's and Colitis Organization guidelines. In the group of patients with ulcerative colitis, 57 (63%) were not on cortico-steroids, 18 (20%) were corticosteroid-dependent, and 16 (16%) used cortico-steroids appropriate-ly; in the group of patients with Crohn's disease 70 (61%), 27 (23%) and 18 (16%), respectively. Overall, 24 (out of 45; 53%) patients with IBD could avoid the overuse of cortico-steroids if they had a timely change of the treatment, surgery or entered a clinical trial.<br /><strong>Conclusion </strong>An excessive corticosteroid use can be recognized on time using the SAT. We have proven that excessive corticosteroid use could be avoided in almost half of cases and thus the overuse of CS may indicate poor quality of care in those patients.</p>