Background: Evidence on how everyday walking and sleep relate to mood in health profession students from Central–Eastern Europe remains limited. Methods: We conducted a cross-sectional study among 277 Romanian medical students. Data were collected using validated instruments for physical activity (IPAQ-SF), sleep quality (PSQI), and depressive/anxiety symptoms (HADS). Associations were examined using bivariate and multivariable regression models, including sex-stratified analyses. Results: In bivariate analysis, total physical activity was inversely correlated with depressive symptoms (ρ = −0.19, p < 0.001). However, in the multivariable model, this effect was not statistically significant after controlling for other factors. Poor sleep quality emerged as the dominant independent predictor of both depression (β = 0.37, p < 0.001) and anxiety (β = 0.40, p < 0.001). Walking time and frequency were specifically protective against depressive symptoms. Sex-stratified analyses revealed distinct patterns: female students benefited more from walking, whereas male students showed stronger associations between overall physical activity and lower depressive symptoms. Conclusions: Within the constraints of a cross-sectional design, this study provides novel evidence from Eastern Europe that sleep quality and physical activity are central to student mental health. Psychological benefits of walking appear sex-specific, and the null mediation finding suggests benefits operate via direct or unmodelled pathways. Sleep is a critical independent target for tailored, lifestyle-based strategies.

The aim of this study was to assess the delays that can potentially occur in the emergency transfer of patients with ST-elevation myocardial infarction (STEMI) to percutaneous coronary intervention (PCI) centers. We conducted a retrospective study using the medical reports pertaining to 97 patients who presented to the Emergency Department of the Emergency County Hospital of Galati during the year of 2018 with the diagnosis of STEMI and meeting eligibility criteria for PCI, thus warranting transfer to a hospital with PCI facilities. The pick-up time of patients diagnosed with acute myocardial infarction from the emergency department by the transfer crew is significantly shorter (p < 0.05) than those transferred by air, regardless of the PCI center to which the transfer was performed, Iasi or Bucharest, when compared to the time required to process the patients transferred by land to the same PCI centers. The results of the study shows that the helicopter use for transferring acute myocardial infarction patients to a PCI center must be considered, given the distance between non-PCI and PCI centers is over 200 km.

Background/Objectives: Measles is a highly contagious viral disease that continues to have a profound effect on morbidity in Romania. Identifying temporal and spatial trends in how the disease spreads among the country’s counties and regions, both in the same disease generation as well as one generation apart (2-week case lag), aided by forecasting tools, could provide valuable insights into tailoring public health interventions. Methods: A big data analysis has been performed on notified measles cases from January 2020 to December 2024 using Python v3.13 grouping cases based on location (using the Nomenclature of territorial units for statistics) and time of the onset of the disease. Results: Feedback loops among both counties and macroregions have been identified (for example Centru-Brașov and București-Ilfov with a correlation factor of 0.77) while monthly forecasting for 2025 and 2026, explored using both the SARIMA and the Holt-Winters models (MAE 1616.74 and 1281.99, respectively), shows the measles might continue to be a burden, with the Holt–Winters models exhibiting slightly more reliable monthly forecast data nationwide, helping to define a solid basis for future predictions and decisions. Conclusions: The spatial feedback loops, both interregional or within the same region, coupled with the trend of lowering vaccination rates, contribute to the persistent emergence of new measles cases which might continue throughout 2025 and 2026 based on the forecasting, distinct from previous outbreaks which followed a specific cadence.

Background/Objectives: Healthcare-associated infections (HAIs) are a major and preventable threat to patient safety, yet reported figures in Central and Eastern Europe are widely affected by under-reporting, which can distort both the apparent infection profile and the perceived burden of disease. Patient-level regional surveillance data were analysed to characterise the reported HAI profile, the determinants of in-hospital mortality, and between-hospital surveillance quality in post-pandemic Southeast Romania. Methods: This was a retrospective, cross-sectional analysis of 2878 HAI cases reported across a five-county, multicentre network of 32 hospitals during 2024. Infections were grouped as Clostridioides difficile infection (CDI) versus non-CDI. Logistic regression was applied for in-hospital mortality, Cox and competing-risks models for time to death, negative binomial regression for length of stay, and a Spiegelhalter funnel plot for between-hospital variation. Results:Clostridioides difficile infection accounted for 56.3% of reported cases, a markedly higher proportion than that described in European point-prevalence surveys, although differences in design and denominator preclude direct comparison. CDIs and non-CDIs formed distinct clinical phenotypes. In-hospital mortality was lower in CDI than in non-CDIs (14.9% versus 26.1%) and was independently associated with intensive care admission, age, and immunosuppression, while CDI remained associated with lower mortality. The reported CDI proportion ranged from approximately 1% to 93% between hospitals, with most institutions lying outside the funnel control limits. Conclusions: The predominance of CDI among reported HAIs is best interpreted as a signal of selective ascertainment rather than as direct evidence of a genuinely higher CDI burden. Because the dataset lacked admission or patient-day denominators, the CDI-to-total ratio should be regarded as a simple screening indicator of potential surveillance imbalance, useful for identifying hospitals where non-CDIs may be under-detected.

Background and objectives: During an outbreak, measles cases tend to aggregate into increasingly bigger clusters that show specific characteristics, different from the non-cluster cases. As the measles threat continues throughout Europe in 2025 with a high notification rate in Romania as well, exploring how clustering affects the disease propagation can provide additional insights into how to improve measles surveillance and control. Methods: National measles cases from 2020 to 2024 have been split into cluster (at least three related cases) and non-cluster-related cases and analyzed comparatively based on vaccination status, disease-related data (hospitalization) and patient-related data (age, location). Large outbreaks with at least 150 cases, allowing for more comprehensive R₀ analysis, have been described and the basic reproduction numbers computed for each of them. Results: There are statistically significant differences in vaccination status, age, and hospital stay between outbreak and non-outbreak cases. Large outbreaks (≥150 cases) show a high degree of variability, with R₀ values varying from as low to 1 to as high as 3.92, indicating limited measles transmission control. Conclusions: The findings in this research highlight the critical impact of clustering on measles transmission dynamics during outbreaks. Significant differences in vaccination status, age, and hospitalization rates between cluster and non-cluster cases underscore the importance of targeted surveillance and intervention strategies while the wide range of R₀ values observed in large outbreaks points to inconsistent control measures and emphasizes the need for strengthened vaccination campaigns and improved outbreak response protocols to better contain measles spread.

Background/Objectives: This study was conducted in an infectious disease clinic in southeastern Romania on a cohort of patients with chronic hepatitis C virus (HCV) infection. It aims to longitudinally evaluate biochemical parameters and the progression of liver fibrosis following treatment with direct-acting antivirals. Methods: One hundred eighty-one patients who experienced improvement in hepatic fibrosis 1–8 years after treatment (group A) were compared with eighty-six patients (except F0–F1) who had stable fibrosis or experienced worsening of hepatic fibrosis after antiviral treatment (group B). Results: The study demonstrated improvement and normalization of mean biochemical parameters in both groups, starting 4 weeks after initiation of therapy and remaining stable up to 5 years post-treatment. The only biochemical parameter that did not return to normal values was serum glucose, which showed elevated mean levels in both groups, with the highest values observed at 5 years post-treatment. Among all 267 patients, 181 (67.79%) showed improvement in hepatic fibrosis after DAA (direct-acting antivirals) therapy, 62 (23.22%) had stable fibrosis, and 24 (8.98%) experienced fibrosis worsening. Of those with improvement, 115 (63.53%) improved by one fibrosis stage, 49 (27.07%) by two stages, and 17 (9.39%) by three stages. Conclusions: This study highlights that more than half of Romanian HCV patients experienced regression of hepatic fibrosis and sustained normalization of most biochemical parameters up to 5 years after DAA treatment, confirming the long-term hepatic benefits of antiviral therapy.