Only a few studies seem to address suicidality as an effect of the COVID-19 pandemic in persons previously affected by psychiatric disorders. The relationship between fear and stress caused by the COVID-19 pandemic and the level of social support and suicidality in patients diagnosed with affective and stress-induced psychiatric disorders prior to the onset of the COVID-19 pandemic were investigated. This study was observational and involved 100 participants. The examined period was from April 2020 to April 2022. The Fear of COVID-19 Scale (FCV-19S), the Oslo Social Support Scale 3 (OSSS-3) and general psychiatric interviews were used to obtain data. A statistically significant relationship between the impact of COVID-19-related distress on the occurrence of suicidality and the year of the pandemic χ²(2, N = 100) = 8.347, p = 0.015 was observed. No statistically significant correlation was found between suicidal behavior, stress intensity, fear and the score on the social support scale (p > 0.05). Fear related to the COVID-19 pandemic can only be seen as a contributor to suicidality. Overall, social support does not always act protectively. Previously stressful experiences such as wars, poverty and natural disasters seem to play a significant role in the resilience to each new public health crisis.

Background: There is a strong correlation between systemic inflammation intensity and clinical presentation, disease progression, and survival during liver cirrhosis decompensation. This study aimed to evaluate the prognostic performance of blood-based biomarkers as meta-inflammation markers, including NLR, PLR, LMR, INPR, MPR, ALBI, FIB4, and APRI, in predicting hospital mortality in patients with acute decompensation of alcohol-related liver cirrhosis. Methods: Data from 411 patients with their first onset of acute decompensation were analyzed, forming two groups: deceased and survived during hospitalization. Generalized partial least squares regression analysis was applied to explore the effects of surrogate indicators on mortality rates, using mortality rate as the dependent variable. Root Mean Square Error, Akaike’s, and Bayesian information criteria determined that four components accounted for most of the variance. Results: Variables with significant negative contributions to the outcome prediction (ranked by standardized regression coefficients) were encephalopathy grade, total bilirubin, Child–Turcotte–Pugh score, MELD, NLR, MPV, FIB4, INR, PLR, and ALT. Coefficient sizes ranged from −0.63 to −0.09, with p-values from 0 to 0.018. Conclusions: NLR, PLR, and FIB4 significantly contribute to hospital mortality prediction in patients with acute decompensation of alcohol-related liver cirrhosis. Conversely, some variables used to predict liver disease severity, including INPR, APRI, LMR, and ALBI score, did not significantly contribute to hospital mortality prediction in this patient population.

Background/Objectives: Most cases of colorectal cancer (CRC) arise from adenomatous polyps. Identifying risk factors for colorectal adenoma (CRA) is critical for CRC prevention. Emerging evidence suggests a link between metabolic syndrome (MetS) and an elevated risk of CRA and CRC, potentially mediated by visceral obesity and adiponectin (APN). We aimed to evaluate the association between different markers of visceral obesity, serum APN, MetS, and the presence of CRA. Methods: A cross-sectional study was conducted at the University Clinical Center of Vojvodina, involving 120 patients, aged 40–75 years, who underwent colonoscopy between January 2022 and January 2023. Sixty patients with CRA were compared to 60 controls with normal colonoscopy findings. Visceral fat thickness (VFT) was measured using ultrasound (US), and bioelectrical impedance analysis (BIA) was used to assess visceral fat area (VFA). Serum APN levels, anthropometric measures, and MetS components were also evaluated. Results: Patients with CRA had significantly higher VFT measured by US (p < 0.05), but no significant differences were found in VFA measured by BIA, waist circumference (WC), or waist-to-hip ratio (WHR). MetS was significantly more prevalent in the CRA group (55% vs. 31.6%, p < 0.05), and logistic regression confirmed MetS as a significant predictor of CRA presence (OR = 2.6). Serum APN levels were inversely correlated with visceral fat measurements and MetS (p < 0.01), but no significant difference in APN levels was observed between patients with and without CRA. Conclusions: This study highlights the importance of VFT measured by US and the presence of MetS as significant factors associated with CRA.

Introduction. Annual and periodized training protocols significantly affect the muscle adaptation in rowers. Considering that the main goal of the training period is increasing specific muscle strength and of detraining period increasing general strength and active rest, the aim of this study was to compare the strength of different muscle groups between training and detraining periods. Material and Methods. The study was conducted at the Department of Physiology, Faculty of Medicine Novi Sad, and it included 34 male and female rowers, 15 to 18 years of age. The muscle strength was measured using a Concept 2 DYNO dynamometer. The strength of the arm extensors and flexors, as well as the leg extensors was measured twice, at the end of the competition season (peak of performance) and before the beginning of the preparation season (after detraining). Results. A statistically significant decrease was found in absolute and relative muscle strength, flexor and arm extensor contraction rate, as well as relative leg extensor strength and contraction rate during the training and detraining periods (p < 0.05). No difference was found in the absolute leg extensor power between the two measurements (p > 0.05). Conclusion. Periodization of the annual training program in rowers has a higher impact on differences in the upper limb muscle adaptation, compared to lower limb muscles in terms of absolute strength.

Introduction. Timely detection of insulin resistance is of great importance and a number of indices have been developed for its evaluation, among which the homeostasis model assessment of insulin resistance index is the most commonly used in clinical practice. However, it can be calculated via two different models - homeostasis model assessment 1 and homeostasis model assessment 2. Most studies determine the cut-off values of the study population using the homeostasis model assessment 1, while recently most physicians use homeostasis model assessment 2 in everyday clinical practice. The aim of our study was to examine whether there was a difference in the values of homeostasis model assessment of insulin resistance and homeostasis model assessment of panceratic beta cells function calculated using these two models. Material and Methods. Laboratory findings of 42 patients who were diagnosed with glycemia and insulinemia were used in this study. Fasting and postprandial glycemia and insulinemia were used to calculate homeostasis model assessment indices using homeostasis model assessment 1 and homeostasis model assessment 2. Results. When comparing the values of the homeostasis model assessment of insulin resistance and homeostasis model assessment B indices, calculated via homeostasis model assessment 1 and homeostasis model assessment 2, we found a statistically significant difference (p < 0.001) which was also obtained when comparing the values of the homeostasis model assessment B index. Linear correlation analysis showed a significant positive correlation between the measured values of the homeostasis model assessment of insulin resistance (calculated via both models) and postprandial insulinemia at 120 minutes (p < 0.005). Conclusion. The results indicate that homeostasis model assessment 2 yields significantly lower homeostasis model assessment of insulin resistance and homeostasis model assessment B index values than when calculated by the homeostasis model assessment, which may be a stumbling block in the use of homeostasis model assessment index. It is necessary to pay attention which homeostasis model assessment model was used to define the cut-off values of these indices, and to use the same model in the diagnosis of insulin resistance in each patient in everyday clinical practice.

Introduction: A sedentary lifestyle is one of the biggest health problems of the 21st century. The role of the trainer in motivating the sedentary individual is crucial. Also, there is a growing accessibility to gyms today, especially outdoor gyms, as a novel way to motivate people to train. Objective: The aim of the study was to evaluate the impact of regular combined indoor and outdoor physical activity on anthropometric and functional parameters and the adoption of a more active lifestyle. Methods: The study included 45 participants between 18 and 56 years of age. They underwent 12 weeks of resistance training, focusing on chest presses and leg presses. Height, weight, bioelectrical impedance, chest and leg press one-repetition maximums, push-up and curl-up counts, and sit and reach were measured both before and after the 12-week training program. Results: After 12 weeks of training, male participants showed a significant increase in the percentage of skeletal muscle mass (p<0.05) and a significant decrease in the fat mass percentage (p<0.05). Female participants experienced a significant reduction in the fat mass percentage (p<0.05). Both groups were able to significantly increase their one-repetition maximums for the chest press (p<0.05) and leg press (p<0.05). Push-up and curl-up counts increased significantly after 12 weeks of training in both sexes, as did flexibility in both sexes. A year after the study, 80% of all participants were still training with a combination of indoor and outdoor physical activities. Conclusions: After 12 weeks of training, the body composition of both female and male participants had changed significantly. Twelve weeks of resistance training significantly increased strength and flexibility in both male and female participants. A well-thought-out training plan seems to be the key factor in motivating a beginner trainee to adopt a more active lifestyle. Level of Evidence IV; Case series.