Background: Berberine, an isoquinoline alkaloid present in Berberis spp., Coptis chinensis and Hydrastis canadensis, is among the most widely consumed metabolic-health supplements, popularized as “nature’s Ozempic”. Concurrent, often undisclosed use with prescription drugs is common in older adults, yet berberine is far from inert. Objective: To synthesize the evidence on berberine as a perpetrator of supplement–drug interactions, propose a four-axis mechanistic taxonomy, with product quality treated separately as a modifier of exposure rather than as a mechanism, and derive a clinically actionable risk-stratification framework. Methods: Structured narrative review, prepared per the SANRA quality criteria; PubMed/MEDLINE, Scopus, Web of Science and Embase were searched up to May 2026. Results: Despite very low systemic exposure (oral bioavailability 0.68% in rats; low ng/mL plasma concentrations in humans), high luminal, enterocytic and hepatic concentrations generate interaction liability, documented in humans for a few pairs and mechanistic for most, along four mechanistic axes: inhibition, and transcriptional induction, of CYP3A4, with CYP2D6/CYP2C9 inhibition that is quasi-irreversible through a metabolite-intermediate complex; transporter modulation (P-glycoprotein, OCT1/OCT2, and MATE1); pharmacodynamic additivity (hypoglycemia, hypotension, and QT prolongation); and microbiome- and gut-barrier-mediated effects, the last of these being a candidate axis rather than a demonstrated one. Product-quality variability is treated separately, as a modifier of exposure. The clinical anchor is increased cyclosporine exposure in renal-transplant recipients (AUC +34.5%; trough 29.3% above control). These elements are integrated into a three-tier risk-stratification framework that combines perpetrator potency, victim-drug vulnerability, and patient vulnerability, with each tier being linked to a defined pharmacy action. Conclusions: In patients on multiple medications, and particularly when berberine is co-administered with drugs of narrow therapeutic index, it should be managed as an active pharmacological perpetrator rather than as an inert supplement. Unstandardized product quality and an unsettled European regulatory framework, under which national limits differ by more than an order of magnitude, further widen the uncertainty around the dose actually delivered. Berberine use should therefore be elicited routinely at medication reconciliation and stratified by mechanism, by victim-drug vulnerability, and by patient risk, with particular attention to metabolic self-medication in the GLP-1 era.

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.

Cardiovascular ultrasound is a cornerstone of noninvasive cardiac and vascular assessment, yet conventional interpretation remains operator-dependent, variable, and limited in sensitivity for subclinical disease. Artificial intelligence (AI), particularly machine learning (ML), deep learning (DL), and, most recently, vision–language and foundation models, offers tools to automate, standardize, and extend ultrasound analysis. This narrative review examines the role of AI-enhanced cardiovascular ultrasound in the transition from descriptive imaging toward predictive and personalized medicine. We conducted a structured literature search of PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar (January 2016–May 2026), combining Medical Subject Headings and free-text terms related to AI and cardiovascular ultrasound. Original studies, meta-analyses, reviews, consensus documents, and seminal works were considered. AI now spans the entire echocardiographic workflow, acquisition guidance, view classification, segmentation (Dice ≈ 0.92–0.94 on public datasets), and automated quantification of ejection fraction and global longitudinal strain, achieving expert-level accuracy and improved reproducibility. Across clinical domains, AI supports ischemia detection on stress echocardiography, heart-failure phenogrouping, Doppler-independent aortic stenosis detection, and carotid plaque characterization for stroke-risk stratification. Emerging vision–language and multitask foundation models (e.g., EchoCLIP, EchoPrime, and PanEcho) point toward general-purpose interpretation, and a growing number of tools (Caption Guidance, Us2.ai, and Ultromics EchoGo) have obtained FDA clearance and/or CE marking. Increasingly, AI-derived imaging biomarkers feed multimodal models that enable individualized risk prediction and therapy selection. AI-enhanced cardiovascular ultrasound is poised to become a central tool of precision cardiology. Realizing its potential will require prospective multicenter validation, cross-vendor standardization, attention to generalizability, interpretability, and reproducibility, and evolving regulatory and ethical frameworks.

Background/objectives. Clostridioides difficile infection (CDI) remains a major cause of healthcare-associated infectious colitis, particularly among elderly and multimorbid patients. Disease severity and clinical evolution are influenced by the host’s systemic inflammatory response. This study aimed to evaluate the hematological and inflammatory profile of hospitalized CDI patients and to explore the prognostic value of routine laboratory parameters for prolonged hospitalization. Methods. A retrospective observational study was conducted on 50 adult patients hospitalized with laboratory-confirmed CDI (positive glutamate dehydrogenase, antigen and toxins A/B). Hematological parameters (WBC, hemoglobin, RDW) and inflammatory markers (CRP, fibrinogen) were analyzed at admission and discharge. Prolonged hospitalization was defined as length of stay (LOS) > 8 days (cohort median). Multivariable logistic regression was performed to assess admission predictors of prolonged hospitalization, and model discrimination was evaluated using leave-one-out cross-validation (LOOCV). Results. At admission, patients exhibited marked inflammatory activation accompanied by reduced hemoglobin and elevated RDW. Significant correlations were observed between inflammatory markers. All inflammatory and hematologic parameters improved at discharge. In multivariable analysis, lower admission hemoglobin and higher log-transformed CRP showed exploratory associations with prolonged hospitalization. The internally validated model demonstrated moderate discriminative performance (AUC = 0.65). Conclusions. CDI is associated with substantial systemic inflammatory activation and hematologic alterations. While no individual predictor reached statistical significance, the observed effect sizes provide hypothesis-generating estimates to inform future prospective validation studies.

Arterial hypertension in adolescents is increasingly a lifestyle-driven disorder, and a growing share of cardiovascular risk in this age group is hidden from conventional office measurement. Intensive nighttime screen use, together with the chronic sleep loss that accompanies it, may disrupt circadian control of the cardiovascular system, an effect we designate, as a proposed integrative concept, digital chronotoxicity. Through melatonin suppression, sustained sympathetic and neuroendocrine activation, oxidative stress, and metabolic dysregulation, this exposure is hypothesized to attenuate the physiological nocturnal fall in blood pressure and to contribute to the non-dipper phenotype, a predictor of early vascular aging that remains invisible to office readings. This narrative review traces the mechanistic pathway from screen exposure to the loss of nocturnal dipping and reframes the problem as a diagnostic one. Twenty-four-hour ambulatory blood pressure monitoring is positioned as the reference standard for detecting the at-risk phenotype and masked hypertension; the cardiac, vascular, renal, autonomic, and neurocognitive biomarkers of early hypertension-mediated organ damage are reviewed; and emerging wearable and artificial-intelligence tools for continuous, preventive screening are examined. An integrated screening pathway is proposed, on the premise that the evaluation of a hypertensive adolescent is incomplete without a digital and sleep history alongside ambulatory monitoring. Reframed in this way, pediatric hypertension becomes a detectable chronobiological disease.

Background/Objectives: Following the COVID-19 pandemic, pertussis resurged sharply across Europe, with 209,674 cases reported in the EU/EEA in 2024. This study characterises the epidemiology of the 2024 pertussis resurgence across five counties of southeastern Romania, with emphasis on vaccination status, clinical severity, and regional surveillance performance. Methods: A retrospective, population-based analysis was conducted on 452 cases notified between February 2024 and January 2025, extracted from the national surveillance database. A pre-specified reclassification of PCR-positive cases yielded 326 confirmed cases. Categorical, non-parametric, correlation, and multivariate logistic regression analyses were performed. Results: The epidemic peaked in September 2024, with 56.0% of cases occurring between August and October. Children under five years accounted for 63.2% of confirmed cases, and 72.1% were not vaccinated according to age-appropriate schedule, predominantly due to parental refusal (43.0%) and non-attendance (36.6%). Pneumonia affected 36.8% of confirmed cases, ranging from 81.0% in infants under two months to 0% in adolescents. Age-appropriate vaccination was independently protective against pneumonia (adjusted OR = 0.53, 95% CI 0.29 to 0.96, p = 0.035; population attributable risk 37.3%). Significant inter-county heterogeneity was identified in PCR implementation (72 to 100%) and reporting delays. Conclusions: Vaccination gaps were the principal modifiable driver of the resurgence, supporting targeted coverage improvement and the introduction of a national maternal Tdap programme.