Background: Digitalization and artificial intelligence-supported clinical decision support systems (AI-DSS), defined here as tools that generate patient-specific alerts, risk estimates, prioritization prompts, documentation suggestions, or related recommendation outputs intended to support rather than replace professional nursing judgment, can improve clinical decision-making, yet they may also amplify technostress and burnout, with downstream effects on missed nursing care and implementation readiness. Methods: We surveyed 239 registered nurses from a tertiary-care hospital in Timișoara, Romania (January–March 2025), including critical care (n = 60) and general wards (n = 179). Measures included a 15-item technostress scale, eHEALS, Maslach Burnout Inventory–Human Services Survey (MBI-HSS), Safety Attitudes Questionnaire (SAQ) teamwork and safety climate subscales, a 10-item missed nursing care inventory, and a six-item AI-DSS acceptance scale reflecting perceived usefulness, trust, and stated willingness to use such tools if available as an attitudinal readiness outcome rather than as routine observed use. Multivariable regression, exploratory mediation models, cluster analysis, and exploratory ROC analysis were performed. Results: Higher technostress was associated with higher emotional exhaustion (r = 0.52) and more missed care (r = 0.41), whereas eHealth literacy correlated with higher AI-DSS acceptance (r = 0.35) and lower technostress (r = −0.34). In adjusted models, technostress (per 10 points) was associated with higher missed care (β = 0.28, p < 0.001) (equivalent to 0.14 points per 5-point increase) and higher odds of low AI-DSS acceptance (OR = 1.38, p = 0.001), while eHealth literacy was associated with lower odds of low acceptance (OR = 0.71 per 5 points, p < 0.001). Burnout and the safety climate statistically accounted for approximately 35% of the technostress–missed care association. Three workflow phenotypes were identified, with the high-strain/low-literacy cluster showing the most missed care (3.5 ± 1.8) and the lowest AI acceptance (19.7 ± 5.2). An exploratory in-sample ROC model for intention to leave achieved an AUC of 0.82. Conclusions: Higher technostress clustered with worse nurse well-being, more care omissions, and lower AI-DSS acceptance, whereas eHealth literacy appeared protective. Interventions combining digital skills support, usability-focused redesign, and a stronger safety climate may reduce missed care and support safer AI implementation.

Background: Limited data exist on primary palatine tonsil Non-Hodgkin lymphoma (NHL) from regions with constrained healthcare access. This study investigated this malignancy in Western and South-Western Romania, comparing lower-stage (Ann-Arbor I-III) and advanced-stage (IV) disease. Methods: A retrospective cohort study (2010–2019) at a tertiary referral hospital included 59 patients with primary palatine tonsil NHL. Data on demographics, clinical presentation, comorbidities (including viral hepatitis B/C), histology, International Prognostic Index (IPI) score, treatment, and outcomes were collected. Statistical comparisons between lower-stage (n = 26) and advanced-stage (n = 33) groups were performed. Results: A high proportion presented with advanced-stage disease (55.9%). The advanced-stage group had significantly more B symptoms (90.9% vs. 69.2%, p = 0.038) and elevated LDH levels (93.9% vs. 57.7%, p = 0.013). Viral hepatitis B and/or C infection was more frequent in advanced-stage disease (30.3% vs. 15.4%, p = 0.44). Combined chemoradiotherapy was more commonly used in lower-stage disease (38.46% vs. 12.12%, p = 0.019). There was no statistically significant difference in relapse rates between the groups. Conclusions: This study highlights the substantial burden of advanced-stage primary palatine tonsil NHL in Western Romania, suggesting a need for improved early detection. The association between viral hepatitis and advanced-stage, although not statistically significant, warrants further investigation. These findings may inform tailored management approaches in resource-constrained settings.

Background and Objectives: Sexual function often fluctuates during pregnancy, yet the contributions of body image-related quality of life (BI-QoL)—operationalized via body image instruments such as the Body Exposure during Sexual Activities Questionnaire (BESAQ) and pregnancy-specific body image scales—and relationship satisfaction remain inconsistently quantified. This systematic review aimed to synthesize evidence on the associations between BI-QoL, relationship satisfaction, and female sexual function in pregnant women. Methods: Following PRISMA 2020, PubMed/MEDLINE, Scopus, and Web of Science were searched up to 23 August 2025. Eligible studies enrolled pregnant women and reported quantitative data on BI-QoL and/or relationship satisfaction alongside sexual outcomes. Risk-of-bias used design-appropriate tools; findings were narratively synthesized due to heterogeneity. Results: Thirteen studies met criteria (predominantly cross-sectional; sample sizes 107–472; one RCT; several couples/longitudinal cohorts). Female Sexual Function Index (FSFI) means clustered in the mid-20s; in a randomized trial, the intervention arm improved FSFI by +1.76 points (22.95 → 24.71; p = 0.002). Overall female sexual dysfunction reached 54.7% in the largest cross-sectional sample. Higher body exposure anxiety was associated with ~4.24-fold greater odds of dysfunction across trimesters. Marital satisfaction explained ≈36% of FSFI variance in multivariable models. Pregnancy context factors related to BI-QoL included planned pregnancy (β = −0.273) and third trimester (β = −0.280) indicating better BI-QoL, while more children predicted worse BI-QoL (β = +0.317). In one cohort, BI during sexual activity worsened postpartum versus pregnancy (p = 0.01). Conclusions: Across diverse settings, poorer BI-QoL and lower relationship satisfaction were consistently linked to reduced sexual function during pregnancy, with desire/arousal most affected. Routine screening and couple-sensitive counseling should be considered as promising, yet still under-tested, strategies that warrant further evaluation in intervention studies.

Background and Objectives: Sleep disruption and reduced physical activity are common in pregnancy and may impair sexual function through mood, body-image, and relational pathways. We prospectively examined whether sleep quality and physical activity predicted third-trimester sexual function in a Romanian antenatal cohort, and explored psychosocial correlates. Materials and Methods: In a single-center cohort, 102 pregnant adults were enrolled ≤ 20 weeks and followed to the third trimester. Sleep (Pittsburgh Sleep Quality Index, PSQI), sexual function (Female Sexual Function Index–Romanian version, FSFI-RO), physical activity (IPAQ-SF), depressive symptoms (PHQ-9), body-image avoidance (Body Exposure during Sexual Activities Questionnaire, BESAQ), and perceived social support (MSPSS) were assessed. Groups were defined by mid-/late-pregnancy sleep (good, PSQI ≤ 5; poor, PSQI > 5). Analyses used t-tests, Pearson correlations, multivariable linear regression for FSFI-Total, and logistic regression for FSFI-Total < 26.55. Results: Compared with good sleepers (n = 56), women with poor sleep (n = 46) had lower third-trimester FSFI-Total (24.4 ± 3.9 vs. 27.9 ± 4.3; p < 0.001) and higher odds of FSFI-defined dysfunction (adjusted OR 121.1; 95% CI 19.2–763.0; p < 0.001). FSFI-Total correlated with worse sleep (PSQI r = −0.42), depressive symptoms (PHQ-9 r = −0.36), social support (MSPSS r = 0.40), body-image avoidance (BESAQ r = −0.34) and physical activity (IPAQ-SF r = 0.24; all p ≤ 0.015). In adjusted models (R² = 0.42), higher MSPSS (β = 0.26; p = 0.004) was protective, whereas PSQI (β = −0.24; p = 0.008), ΔPHQ-9 (β = −0.19; p = 0.023), BESAQ (β = −0.17; p = 0.031), and higher BMI (β = −0.14; p = 0.049) predicted lower FSFI-Total. Conclusions: In this antenatal cohort, poor sleep was strongly and independently associated with lower sexual function, with meaningful contributions from social support, mood, body-image cognition, and physical activity, highlighting sleep as a clinically actionable target for preserving sexual well-being in pregnancy.

Evidence on hospitalised COVID-19 patients during the Omicron BA.5 wave from Eastern European, vaccine-heterogeneous cohorts remains limited. We conducted a retrospective single-centre cohort study of 395 consecutive adults admitted with laboratory-confirmed COVID-19 to a tertiary infectious-diseases unit in western Romania between 1 July and 31 October 2022. Median age was 72 years (IQR 65–81); 33.2% were unvaccinated, 42.8% had documented prior SARS-CoV-2 infection, and 41.3% were obese. Multivariable logistic regression identified independent predictors of in-hospital mortality and post-acute symptom burden. In-hospital mortality was 15.7% (62/395). Vaccination was independently associated with lower mortality (adjusted odds ratio [aOR] 0.55, 95% CI 0.30–0.99; p = 0.048), as was each 1% increase in admission SpO₂ (aOR 0.83, 95% CI 0.76–0.92; p < 0.001), whereas COPD independently increased mortality risk (aOR 2.42, 95% CI 1.15–5.10; p = 0.020). Interleukin-6 was the most discriminating admission biomarker for in-hospital mortality (AUROC 0.70). Bloodstream bacterial co-infection, detected in 22.5% of patients tested on clinical suspicion, was dominated by gut-derived organisms with case-fatality ≥30%. At discharge, 90.1% reported persistent symptoms, most commonly cognitive (24.6%). Prior SARS-CoV-2 infection independently predicted post-acute symptom burden (aOR 2.96, 95% CI 1.75–5.01; p < 0.001), with a specific cardiopulmonary signature. In this BA.5 cohort, vaccination remained protective; IL-6 was the most informative admission biomarker; bloodstream infections suggested gut translocation; and prior infection was an independent determinant of early post-acute symptom burden.

Background/Objectives: Orthodontic treatment induces controlled mechanical forces that alter the periodontal environment, including changes in oral microbiota composition and activation of local inflammatory pathways. Despite the widespread and growing use of orthodontic appliances across all age groups, the magnitude, timing, and multi-domain biological impact of these changes have not been comprehensively quantified in a single systematic synthesis. This systematic review and meta-analysis aimed to synthesize the available evidence on periodontal clinical parameters, oral microbiota composition, and local inflammatory biomarkers associated with orthodontic treatment using fixed appliances and clear aligners, and to provide a structured, GRADE-rated evidence base for clinical practice. Methods: A systematic review and meta-analysis was conducted in accordance with PRISMA 2020 guidelines. PubMed/MEDLINE, Scopus, and Web of Science were searched from inception to March 2026. Prospective cohort studies, longitudinal clinical studies, and randomized controlled trials evaluating periodontal parameters, oral microbiota, and inflammatory biomarkers during orthodontic treatment were included. Quantitative synthesis was performed using mean differences or standardized mean differences with 95% confidence intervals, primarily assessing within-group (pre–post) changes. Results: Eighteen studies (n = 812 patients; follow-up 3–12 months) met inclusion criteria. Fixed orthodontic appliances were consistently associated with transient increases in plaque index (MD 0.45, 95% CI 0.32–0.58; I² = 62%), gingival index (MD 0.38, 95% CI 0.25–0.51; I² = 55%), and bleeding on probing (MD 15.2%, 95% CI 10.1–20.3%; I² = 48%), particularly during early treatment phases. Microbiological analyses demonstrated within-group shifts toward increased prevalence of periodontopathogenic species (Streptococcus mutans OR 2.45, 95% CI 1.89–3.18; Porphyromonas spp. OR 2.14, 95% CI 1.67–2.75) in patients treated with fixed appliances. Local inflammatory responses were characterized by elevated IL-1β (MD 1.2, 95% CI 0.8–1.6) and IL-6 (MD 0.9, 95% CI 0.6–1.2) in gingival crevicular fluid. Certainty of evidence was rated moderate for plaque and gingival indices and low for microbiological and inflammatory outcomes (GRADE). Conclusions: Orthodontic treatment—particularly with fixed appliances—is associated with transient, reversible deterioration of periodontal indices, shifts toward a more dysbiotic oral microbiome, and elevation of local inflammatory mediators in gingival crevicular fluid during active treatment phases. These changes are manageable through structured preventive protocols and regular periodontal monitoring. Future prospective studies with concurrent control groups and standardized multi-domain outcome measures are needed to better define the magnitude and reversibility of these biological responses. PROSPERO: CRD420261336117.