Background: In the wake of the global COVID-19 pandemic, understanding its prolonged impact on vulnerable populations has become a critical area of investigation. This study aimed to elucidate the distinctive post-acute sequelae of SARS-CoV-2 infection (PASC) and liver injury in Romania’s elderly population, hypothesizing unique demographic, clinical, and healthcare factors influencing the manifestation. Methods: A longitudinal design was employed, enrolling COVID-19 patients from the Victor Babes Hospital for Infectious Diseases and Pulmonology in Timisoara, Romania. Participants were stratified into three groups based on age and Long COVID status. The study focused on a variety of demographic, clinical, and biological parameters, including liver function tests, to assess the trajectory and severity of liver injury over six months post discharge. Results: Involving 238 participants, the study revealed a significant increase in the duration of hospitalization for those over 65 (15.8 ± 8.2 days) compared to younger groups (p < 0.001). Notably, elderly Long COVID patients exhibited a marked elevation in liver enzymes post discharge, with median ΔALT and ΔAST of 24.1 U/L and 30.2 U/L, respectively, suggesting ongoing liver injury (p < 0.001). Significant metabolic disruptions were observed, with the ΔFasting glucose showing a substantial median decrease of 21.1 mmol/L in the elderly group (p < 0.001). A pronounced reduction in ΔGGT (16.7 U/L) and ΔLDH (48.7 U/L) was noted, indicating a recovery in liver function and reduced tissue damage (p < 0.001). Coagulation profiles and liver fibrosis risk scores, particularly ΔFIB-4 and ΔAPRI, also significantly improved post discharge, indicating a reduced risk of ongoing liver complications. Conclusion: This study confirms the hypothesis of more severe PASC and liver injury among the elderly Romanian population. Significant improvements post discharge suggest a degree of recovery, yet the persistent alterations in liver enzymes, glucose metabolism, and fibrosis risk scores call for continued monitoring and tailored management strategies.

Background/Objectives: Post-stroke cognitive impairment (PSCI) affects ~40% of survivors. Diffusion Tensor Imaging Analysis Along the Perivascular Space (DTI-ALPS) is a fast, contrast-free surrogate of perivascular (glymphatic-aligned) diffusivity that may stratify PSCI risk. We systematically synthesized evidence on the diagnostic and prognostic performance of ALPS in ischemic stroke. Methods: Following PRISMA 2020, we searched PubMed/MEDLINE, Scopus, and Web of Science from inception to August 2025 for human ischemic stroke studies reporting ALPS and cognitive or functional outcomes. Eligible designs were cohort or case–control. Outcomes included group differences, associations with cognition (Montreal Cognitive Assessment [MoCA]/Mini-Mental State Examination [MMSE]), prognostic accuracy for PSCI/functional outcome, and longitudinal change. Risk of bias was appraised with QUADAS-2 (diagnostic) and QUIPS (prognostic). The protocol was registered on OSF. Heterogeneity among studies precluded a meta-analysis. Results: Five single-center cohorts (n per cohort 29–120) from Asia, Europe, and the USA used 3T DTI with ventricular-level ALPS ROIs. Across studies, ALPS was lower after stroke, with early ipsilesional depression and partial recovery over weeks to months. ALPS correlated with cognition (MoCA r ≈ 0.43–0.56) and discriminated early cognitive impairment (AUC 0.868; sensitivity 96%, specificity 66%). Follow-up ALPS predicted poor 6-month outcome (AUC 0.786). In lacunar stroke with small-vessel disease, higher baseline ALPS related to better cognitive trajectories and lower incident dementia risk (HR ≈ 0.33), though associations attenuated after adjustment for diffusion microstructural covariates (PSMD/MD). Reporting of acquisition parameters and ROI methods varied; overall risk of bias was moderate. Conclusions: DTI-ALPS shows consistent post-stroke reductions, recovery-sensitive trajectories, and promising—though context-dependent—prognostic value for PSCI and longer-term outcomes. Clinical translation will require standardized acquisition/analysis, multimodal adjustment, prespecified cut-offs, and prospective multicenter validation.

During the coronavirus diseases 2019 (COVID-19) pandemic, the safety and efficacy of vaccination during pregnancy, particularly regarding the risk of preterm birth, have been a subject of concern. This systematic review aims to evaluate the impact of COVID-19 vaccination on preterm birth risk and to inform clinical practice and public health policies. Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a database search included PubMed, Embase, and Scopus, conducted up until October 2023. Inclusion criteria focused on studies that examined COVID-19 vaccination during pregnancy and its correlation with preterm birth, defined as a birth before 37 weeks of gestation. Six studies met these criteria, encompassing 35,612 patients. A quality assessment was performed using the Newcastle–Ottawa Scale and the Cochrane Collaboration’s tool, with the risk of bias evaluated via a funnel plot analysis and an Egger’s regression test. The studies demonstrated geographical diversity, mainly from Israel, Romania, and the United States, with a blend of prospective and retrospective designs. The patient cohort’s mean age was 31.2 years, with common comorbidities such as gestational diabetes and obesity affecting 9.85% of the total population. The vaccination types varied across the studies, with BNT162b2 being the most used. The results indicated a low heterogeneity among the included studies, evidenced by a Cochran’s Q statistic of 2.10 and an I² statistic of 13%. The meta-analysis yielded a pooled odds ratio (OR) for a preterm birth risk post-vaccination of approximately 1.03 (95% CI: 0.82–1.30), suggesting no significant increase in preterm birth risk was associated with COVID-19 vaccination. Notable findings included a low preterm birth rate (as low as 0.6% and up to 6.1%) with minimal differences in neonatal outcomes, such as birth weight and APGAR (appearance, pulse, grimace, activity, and respiration) scores between vaccinated and unvaccinated groups. This study concludes that a COVID-19 vaccination during pregnancy does not significantly increase the risk of preterm birth. These findings are crucial for reassuring healthcare providers and pregnant women about the safety of COVID-19 vaccines and supporting their use in public health strategies during the pandemic.

Background and Objectives: Early bedside tools that flag non-response in hospitalized adults with lower urinary tract infection (UTI) could align clinical care with antimicrobial stewardship. We evaluated REACT-UTI, a 72 h composite combining C-reactive protein (CRP) clearance ≥35%, defervescence (temperature < 37.5 °C), and ≥2-point symptom improvement, to predict early non-response and hospital length of stay (LOS), and we assessed modifiable processes of care. Methods: We conducted a prospective observational study of adults with culture-confirmed lower UTI (n = 126) admitted to a tertiary hospital in Timișoara (December 2023–August 2025). The primary outcome was 72 h early clinical response (ECR) defined by REACT-UTI. Multivariable logistic regression examined associations of catheter-associated UTI (CAUTI), time-to-effective therapy, baseline CRP, diabetes, early catheter removal/exchange (≤48 h), and early intravenous-to-oral switch (≤72 h) with non-response. Results: Overall, 76/126 patients (60.3%) achieved ECR. Non-responders more often had CAUTI, higher baseline CRP, longer time-to-effective therapy, ESBL or fluoroquinolone-resistant Enterobacterales, and longer LOS (14.1 vs. 9.8 days; p < 0.001). Adjusted models showed that CAUTI, delayed active therapy, higher baseline CRP, and diabetes increased the odds of non-response, whereas early catheter removal (adjusted odds ratio [aOR] 0.5, 95% confidence interval [CI] 0.3–0.9) and early IV-to-oral switch (aOR 0.4, 0.2–0.8) were protective. Greater CRP clearance correlated with shorter LOS (ρ = −0.52; p < 0.001). Conclusions: In this single-center setting with a high burden of antimicrobial resistance, REACT-UTI at 72 h identified patients at risk of early non-response and prolonged hospitalization and highlighted actionable levers—timely active therapy, catheter management, and early oral step-down. External validation in diverse settings is needed before broader implementation.

Background and Objectives: Hospitals increasingly use AI tools that give nurses on-screen alerts and recommendations (AI-supported clinical decision support, AI-DSS). When nurses override these alerts too often, useful guidance can be lost; when they trust them blindly, errors can slip through. We examined which work and wellbeing factors are associated with nurses’ self-reported intention to override AI alerts, rather than observed override behavior. Methods: We surveyed 239 registered nurses (76.6% female; mean age 33.7 years) at a large hospital in Timișoara, Romania, from January to March 2025. Questionnaires measured alert fatigue, moral distress, mental workload, sleep problems, resilience, team psychological safety, and how strongly nurses intended to override AI alerts. Results: Nurses fell into three groups: those who tended to over-trust AI (26.8%), those with balanced trust (41.0%), and those who resisted it (32.2%). The resistant group had the strongest intention to override alerts and the weakest sense of psychological safety. Alert fatigue was the factor most strongly associated with override intention, and this association was partly accounted for by moral distress. The indirect association was weaker among nurses reporting higher team psychological safety. An exploratory model using these factors distinguished nurses with high self-reported override intention with acceptable accuracy. Because all variables were measured at a single time point, findings are associative and hypothesis-generating rather than causal. Conclusions: How nurses respond to AI alerts depends less on the technology than on their workload, ethical strain, and team climate. Cutting unnecessary alerts, easing moral distress, and building psychological safety may help nurses use AI more safely.

The incidence of Neonatal Systemic Inflammatory Response Syndrome (SIRS) is a critical concern in neonatal care. This study aimed to identify maternal laboratory parameters predictive of SIRS in newborns, focusing on the establishment of diagnostic cutoffs and evaluating the predictive power of these biomarkers. This prospective cohort study was conducted from January 2023 to January 2024 across several regional hospitals specializing in neonatal care. It included 207 mother-newborn pairs, divided into groups based on the neonatal development of SIRS (66 cases) or its absence (141 controls). Key maternal parameters measured included inflammatory markers and liver enzymes, analyzed using standard biochemical methods. The study applied receiver operating characteristic (ROC) analysis to establish optimal cutoff values and conducted multivariate logistic regression to determine hazard ratios (HRs) for SIRS prediction, with adjustments for potential confounders. The study identified significant ROC/AUC values for several biomarkers. The neutrophil-to-lymphocyte ratio (NLR) demonstrated an AUC of 0.926, with a cutoff value of 3.64, achieving 81.8% sensitivity and 90.9% specificity (p < 0.001). The systemic immune–inflammation index (SII) showed an AUC of 0.819 and a cutoff of 769.12, with 75.8% sensitivity and 81.8% specificity (p < 0.001). Multivariate regression analysis highlighted that neonates with maternal SII values above this cutoff were three times more likely to develop SIRS (HR 3.09, 95% CI 2.21–4.17, p < 0.0001). Other notable biomarkers included dNLR and ALRI, with respective HRs of 1.88 (p = 0.018) and 1.75 (p = 0.032). These findings confirm the significant predictive value of specific maternal inflammatory markers for neonatal SIRS. These findings support the utility of these biomarkers in prenatal screening to identify neonates at increased risk of SIRS, potentially guiding preemptive clinical interventions.