Search Results (1,193)

Objectives: Clinical decision-support systems are computer-based tools to improve healthcare decision-making. However, their effectiveness depends on being positively perceived and well understood by healthcare professionals. Qualitative research is particularly valuable for exploring related behaviors and attitudes. This study aims to explore experiences of family physicians and nurses concerning the visualization, utility and understanding of the non-valvular atrial fibrillation clinical decision-support system (CDS-NVAF) tool in primary care in Catalonia, Spain. Methods: We performed a qualitative study, taking a pragmatic utilitarian approach, comprising focus groups with healthcare professionals from primary care centers in the intervention arm of the CDS-NVAF tool randomized clinical trial. A thematic content analysis was performed. Results: Thirty-three healthcare professionals participated in three focus groups. We identified three key themes: (1) barriers to tool adherence, encompassing problems related to understanding the CDS-NVAF tool, alert fatigue, and workload; (2) using the CDS-NVAF tool: differences in interpretations of Time in Therapeutic Range (TTR) assessments, and the value of TTR for assessing patient risk; (3) participants’ suggestions: improvements in workflow, technical aspects, and training in non-valvular atrial fibrillation management. Conclusions: Healthcare professionals endorsed a clinical decision-support system for managing oral anticoagulation in non-valvular atrial fibrillation patients in primary care. However, they emphasized the view that the CDS-NVAF requires technical changes related to its visualization and better integration in their workflow, as well as continuing training to reinforce their theoretical and practical knowledge for better TTR interpretation. Full article

The rapid expansion of mindfulness research has generated both enthusiasm and controversy regarding its actual clinical value. While meditation is often regarded as the central mechanism of mindfulness-based interventions, other components such as psychoeducation and informal practice may play an equally significant role in improving mental health outcomes. This critical review examines the relative contributions of these elements to the therapeutic impact of mindfulness and clarifies the extent to which its effects are comparable to established treatments, particularly Cognitive Behavioral Therapy (CBT). Evidence from meta-analyses and high-quality trials indicates that mindfulness programs achieve moderate efficacy in reducing symptoms of anxiety, depression, and stress, but effect sizes are frequently inflated by methodological limitations. Importantly, cognitive and emotional regulation skills, especially acceptance and non-judgment, appear to sustain long-term benefits more consistently than meditation alone. These findings highlight the need for rigorous longitudinal studies and component-focused designs to identify the mechanisms that drive clinical change. By distinguishing between evidence-based applications and overstated claims, this review contributes to a more balanced understanding of mindfulness and its appropriate integration into healthcare. Full article

Staphylococcus aureus biofilms represent a critical healthcare challenge, driving chronic infections and antimicrobial resistance. This study investigates the anti-staphylococcal efficacy of two Lactiplantibacillus strains isolated from traditional Bulgarian pickled vegetables (turshiya): L. plantarum IZITR_24 and L. paraplantarum IZITR_13. Combining whole genome sequencing (WGS) with functional assays, we established a robust genotype-to-phenotype framework to characterize their antimicrobial arsenal. Based on WGS, we identified conserved plantaricin (plnJK, plnEF) clusters in both isolates, with IZITR_13 additionally carrying genes for pediocin and enterolysin A—alongside the confirmed absence of virulence factors. Reconstituted lyophilized cell-free supernatants (LCFSs) were evaluated in dose–response microtiter assays to determine the minimum biofilm inhibitory concentration (MBIC) and minimum inhibitory concentration (MIC). Both strains demonstrated clear, dose-dependent inhibitory activity against the S. aureus growth and biofilm formation. Microscopy (SEM/CLSM) confirmed significant biofilm disruption and cell membrane permeabilization. The observed consistency between genome-inferred capacity and phenotypes highlights the strong predictive value of a genome-first screening approach for selecting bacteriocin-producing lactic acid bacteria (LAB). These findings position IZITR_24 and IZITR_13 as promising postbiotic producers with potent antibiofilm activity against S. aureus. By utilizing their stable postbiotic products rather than relying on live colonization, this study proposes a targeted, antibiotic-sparing strategy to combat persistent staphylococcal biofilms. Full article

Background and Clinical Significance: Cerebral candidiasis (Candida albicans meningoencephalitis) is a rare but severe central nervous system (CNS) infection, usually associated with neurosurgical procedures or indwelling devices. Diagnosis is challenging due to frequent negativity of cerebrospinal fluid (CSF) cultures, and mortality remains high despite antifungal therapy. Case Presentation: We describe a 64-year-old woman who underwent retrosigmoid resection of a left vestibular schwannoma. The early postoperative course was complicated by fever, neurological deterioration, and hydrocephalus requiring external CSF drainage. Multiple lumbar punctures revealed inflammatory CSF profiles but persistently negative cultures. One month post-surgery, intraoperative samples from mastoid repair material grew Candida albicans, prompting antifungal therapy. Despite treatment, the patient experienced fluctuating neurological status and required multiple external ventricular drains. Three months after surgery, she clinically deteriorated and died. Autopsy showed diffuse meningeal thickening and purulent exudates at the brain base and posterior fossa. Histopathology confirmed chronic lympho-histiocytic meningitis with necrotizing foci containing Candida albicans. Conclusions: This case underscores the diagnostic and therapeutic challenges of post-neurosurgical Candida CNS infections. Repeatedly negative CSF cultures delayed diagnosis, emphasizing the value of ancillary tests such as β-d-glucan and molecular assays. Even with antifungal therapy, prognosis is poor. Autopsy remains essential for uncovering fatal healthcare-associated fungal infections and informing clinical vigilance and medico-legal assessment. Full article

Background/Objectives: Low back pain (LBP) is the leading cause of disability in Saudi Arabia and contributes substantially to healthcare utilisation, reduced quality of life, and lost productivity. This guideline provides nationally standardised, evidence-based recommendations for the assessment and management of non-specific LBP and sciatica in adults, adapted to the clinical and health-system context in Saudi Arabia. Methods: A multidisciplinary Task Force developed the guideline using the GRADE ADOLOPMENT approach, using NICE guideline NG59 as the primary evidence source. One additional clinical question was formulated to address pain neuroscience education, informed by a relevant systematic review. Update literature searches were conducted in PubMed, Embase, and the Cochrane Library (2016–2022). The evidence was appraised using GRADE, and recommendations were formulated through structured Evidence-to-Decision deliberations and consensus voting. Results: The Task Force addressed eleven clinical questions in this guideline. Strong recommendations were provided for the use of validated risk assessment tools (very low certainty of evidence) and stratified management (moderate certainty of evidence). Conditional recommendations were made for indications for imaging, pharmacological treatment for sciatica, psychological interventions, multidisciplinary return to work programmes, epidural injections, prognostic value of image-concordant pathology, spinal decompression, radiofrequency denervation, and pain neuroscience education, with certainty of evidence ranging from very low to low. Conclusions: The findings indicate that management of non-specific LBP and sciatica in Saudi Arabia should be guided by clinical assessment, with restricted use of imaging, careful selection of pharmacological treatments, and appropriate use of psychological, multidisciplinary, and procedural interventions. Full article

Background: The COVID-19 pandemic has put other infectious diseases, especially in children, into a new perspective. Our study focuses on two important viral infections: COVID-19 and influenza, which often present with similar clinical symptoms. Taking into consideration that the pathophysiology and systemic impact of the two viruses are distinct, which can lead to measurable differences in laboratory values, this study aimed to analyze laboratory features that differentiate between COVID-19 and influenza virus infections in pediatric patients. Methods: We statistically analyzed the routinely available laboratory data of 98 patients with influenza virus and 78 patients with COVID-19. Afterwards, the classification and regression tree (CART) method was performed to identify specific clinical scenarios, based on multilevel interactions of different features that could assist clinicians in evidence-based differentiation. Results: Significant differences between the two groups were observed in ALT, eosinophils, hemoglobin, and creatinine. Influenza-infected infants presented significantly higher leukocyte, neutrophil, and basophil counts compared to infants infected with COVID-19. Regarding children (over 12 months), significantly lower levels of ALT and eosinophil counts were observed in those with influenza compared to those with COVID-19. Furthermore, the CART decision tree model identified distinct profiles based on a combination of features such as age, leukocytes, lymphocytes, platelets, and neutrophils. Conclusions: After further refinement and application, such machine learning-based, evidence-driven models, considering the large scale of clinical and laboratory variables, might help to improve, support, and sustain healthcare practices. The differential decision tree may contribute to enhanced clinical risk assessment and decision making. Full article

Background: Inter-limb asymmetry has implications for both athletic performance and healthcare practice. High baseline inter-limb asymmetries have been associated with impaired mobility, increased fall risk, and musculoskeletal injuries across the lifespan. Exercise interventions able to stimulate the stretch–shortening cycle (e.g., plyometric training and jump training) have been shown to have a good impact on asymmetries. Among these, Mini-Trampoline Training (MTT) has recently emerged as potentially effective in reducing asymmetries. Objectives: The study aimed to evaluate the acute effects of a single MTT session on muscle power and inter-limb asymmetry in young adults. Methods: Twenty-eight recreationally active participants (25.6 ± 2.4 years) completed one MTT session. Before (PRE) and after (POST) the MTT session, single-leg 6 m Timed Hop (6MTH) and countermovement jump (CMJ) tests were administered. Additionally, 6MTH values of the dominant (DOM) and non-dominant (NODOM) limbs were used to stratify participants according to higher (HBIA) or lower (LBIA) baseline inter-limb asymmetry, based on a commonly adopted Normalized Symmetry Index (NSI) threshold (NSI ≥ 10%, n = 12; NSI < 10%, n = 16). Repeated-measures mixed models were used to evaluate the effects of the MTT session on 6MTH, NSI, and CMJ. Results: Regardless of group and limb, significant (p < 0.0001) improvements in 6MTH (PRE: 2.5 ± 0.06 s; POST: 2.3 ± 0.05 s) were found. Interestingly, the MTT session had a significant (p = 0.01) effect on both groups, with a significant (p = 0.003) interaction with NSI values, showing an improvement for HBIA (PRE = 15.4 ± 1.1%, POST = 11.3 ± 2.1%), whereas a decrement in LBIA was recorded (PRE = 5.1 ± 0.6%, POST = 9.6 ± 1.5%). CMJ did not show any changes in HBIA (PRE: 36.2 ± 0.9 cm; POST: 35.1 ± 0.7 cm), while a significant (p = 0.007) decrease was found in LBIA (PRE: 34.8 ± 1.2 cm; POST: 33.2 ± 1.3 cm). Conclusions: A single MTT session induced acute neuromuscular fatigue, reflected by reduced CMJ performance and improved (~8%) inter-limb control during hopping. The HBIA group preserved jump height (~36 cm) and demonstrated a significant reduction in asymmetry (NSI: −4.1%), suggesting more balanced lower-limb recruitment. Conversely, LBIA showed a significant decrease in CMJ and an increased NSI (+4.5%), possibly reflecting fatigue-related compensatory strategies. Overall, a single MTT elicited distinct responses according to baseline asymmetry, supporting its potential as an adaptable modality for enhancing neuromuscular function in HBIA. Full article

Background and Objectives: Healthcare-associated infections (HAIs) significantly increase morbidity and mortality in critically ill patients, and their burden became more pronounced during the COVID-19 pandemic. However, data describing the temporal evolution of HAIs, pathogen distribution, and associated risk factors across consecutive pandemic waves remain limited. This study aimed to characterize the epidemiology, microbiology, and outcomes of HAIs in COVID-19 intensive care units (ICU) patients and to identify clinical and laboratory predictors of mortality. Materials and Methods: This retrospective observational study included adult patients with RT-PCR–confirmed COVID-19 who developed at least one HAI ≥ 48 h after ICU admission between March 2020 and December 2020, encompassing the first three pandemic waves in Türkiye, in a tertiary-care ICU. Demographic, clinical, laboratory, and microbiological data were collected. Inflammatory markers and severity scores (SAPS-II, MCCI, and NLR) were analyzed. Receiver operating characteristic (ROC) curve analysis was used to determine optimal cut-off values for mortality prediction. Results: Among the 1656 ICU admissions, 145 patients (8.7%) developed HAIs; after exclusions, 136 patients were included in the final analysis. Bloodstream infections were the most frequent HAI (57%), followed by urinary tract infections (31%), ventilator-associated pneumonia (9%), and surgical site infections (1%). Klebsiella pneumoniae was the predominant pathogen, followed by Candida albicans and Acinetobacter baumannii. Multidrug-resistant organisms, including MRSA and VRE, showed variable distribution across pandemic periods. Overall in-hospital mortality was 74.3%. Non-survivors had significantly higher SAPS-II, MCCI, and NLR values. ROC analysis identified NLR > 38.8 and SAPS-II > 35.5 as mortality-predictive thresholds. Dynamic inflammatory marker patterns correlated with infection timing, and early peaks of CRP, WBC, and IL-6 were associated with worse outcomes. Conclusions: HAIs imposed a substantial clinical burden on critically ill COVID-19 patients, with high mortality driven predominantly by multidrug-resistant bloodstream infections. Severity indices and inflammation-based biomarkers demonstrated strong prognostic value. Temporal shifts in pathogen ecology across pandemic waves underscore the need for adaptive infection-prevention strategies, continuous microbiological surveillance, and strengthened antimicrobial stewardship in critical care settings. Full article

Background: As the overall prevalence of dietary supplements (DS) use in pediatric populations is high, these products should be strictly regulated. However, regulatory frameworks for DS in the European Union and Serbia share inconsistencies and ambiguities which may compromise pediatric DS safety. Objective: To identify and critically assess the regulatory and practical issues in defining, labeling, advertising, and use of pediatric dietary supplements in the EU and Serbia. Methods: This review focused on identifying and assessing inconsistencies, gaps, and other regulatory challenges, as well as marketing practices affecting consumer safety through the assessment of legal and policy frameworks of the European Union and Serbia, and peer-reviewed articles, pertaining to the definition, labeling, and advertising of pediatric dietary supplements, that were assessed for contextual evidence on related, evidence-based, and practice-based information. Results: The analysis identified five critical areas of concern within the current regulations for pediatric DS: (i) the absence of universal and clear product definition, (ii) the lack of uniform, age-appropriate composition standards, (iii) potential safety risks related to ambiguous composition standards, arbitrary age cut-offs, and lack of age-appropriate reference values specific to DS, (iv) misuse of labels and unfair advertising practices, and (v) practical aspects of pediatric DS use and the limited role of healthcare providers in it. Conclusions: Regulating pediatric DS is a complex task due to the diversity of the pediatric population. Regulatory systems must be ready to swiftly resolve all inconsistencies and adjust to new scientific developments and market changes in order to ensure our primary goal—children’s health and safety. Full article

Background: Healthcare quality is increasingly dependent on the patients’ perspective to ensure care aligns with patients’ needs and experiences, especially for those living with chronic conditions such as diabetes. The Swedish National Diabetes Register instrument (NDR) combines patient-reported experiences and outcomes to evaluate patient-centered diabetes care, but it has not yet been accessible in Arabic. This study aimed to assess the validity and reliability of the Arabic version of the Swedish National Diabetes Register questionnaire among patients with diabetes. Methods: A cross-sectional study was carried out from July to August 2023 at 47 primary healthcare centers in Saudi Arabia, involving 594 adult patients with diabetes. Reliability was measured with Cronbach’s alpha and composite reliability. Construct validity was tested using confirmatory factor analysis, and discriminant validity was assessed through the Heterotrait–Monotrait Ratio. Data analysis was performed using SPSS (version 28) and the lavaan package in R (version 4.3.2). Results: The Arabic version showed high internal consistency, with Cronbach’s α ranging from 0.716 to 0.886 and CR between 0.663 and 0.855. It also exhibited good model fit indices, including χ²/df of 2.72, RMSEA of 0.054, SRMR of 0.073, and a CFI above 0.90. All item loadings were statistically significant (p < 0.01). The HTMT values were below 0.85, confirming adequate discriminant validity. Conclusions: The Arabic version of the NDR instrument is a valid and reliable tool for measuring patient-reported experiences and outcomes among Arabic-speaking patients with diabetes, which supports its application in diabetic care across the Arab region. Health policymakers in the region are recommended to incorporate this validated Arabic tool into their national diabetes initiatives. Full article

Background/Objectives: Mortality among patients receiving maintenance hemodialysis remains high, and biomarkers that allow early risk stratification are needed. Serum albumin reflects nutritional status and systemic inflammation and has been associated with adverse outcomes; however, its long-term prognostic significance remains incompletely defined. This study examined the association between baseline serum albumin and long-term (up to 10-year) all-cause mortality in a large hemodialysis cohort. Methods: This retrospective cohort study included adult patients undergoing maintenance hemodialysis between 2015 and 2025 at a tertiary nephrology center. Individuals with at least three months of stable dialysis and available baseline serum albumin measurements were included. Patients were categorized into two groups according to baseline serum albumin levels (<3.5 g/dL and ≥3.5 g/dL). The primary outcome was long-term (up to 10-year) all-cause mortality, while secondary outcomes included emergency department visits, hospital admissions, cardiovascular events, and infection-related hospitalizations. Survival was assessed using Kaplan–Meier analysis, and predictors of mortality were evaluated using Cox proportional hazards regression. The median follow-up duration was 54 months (interquartile range: 28–92), with a maximum follow-up of 10 years. Results: A total of 412 patients were analyzed, of whom 40.8% had serum albumin levels < 3.5 g/dL. During follow-up, 233 deaths occurred. Lower albumin levels were associated with significantly higher mortality (76.2% vs. 43.4%, p < 0.001), increased healthcare utilization, and a greater incidence of cardiovascular and infectious complications. In multivariate analysis, albumin < 3.5 g/dL remained an independent predictor of mortality (hazard ratio 1.84, 95% confidence interval 1.42–2.38; p < 0.001). Receiver operating characteristic analysis identified 3.4 g/dL as the optimal cutoff for mortality prediction (area under the curve 0.72). Conclusions: Baseline serum albumin is an independent predictor of long-term (up to 10-year) mortality and adverse clinical outcomes in patients receiving maintenance hemodialysis. Although albumin is not a causal determinant, its association with survival likely reflects underlying nutritional and inflammatory burden. Prospective multicenter studies are warranted to validate albumin-based risk stratification and to evaluate the prognostic value of longitudinal changes in serum albumin over time. Full article

The Internet of Medical Things (IoMT) interconnects medical devices, software applications, and healthcare services through the internet to enable the transmission and analysis of health data. IoMT facilitates seamless patient care and supports real-time clinical decision-making. The IoMT faces substantial security threats due to limited device resources, high device interconnectivity, and a lack of standardization. In this paper, we present an Intrusion Detection System (IDS) called An Empirical Distribution Ranking-Based Fuzzy J48 Classifier for Multiclass Intrusion Detection in IoMT Networks (EDR-FJ48) to distinguish between regular traffic and multiple types of security threats. The proposed IDS is built upon the J48 decision tree algorithm and is designed to detect a wide range of attacks. To ensure the protection of medical devices and patient data, the system incorporates a fuzzy IF-THEN rule inference module. In our approach, fuzzy rules are formulated based on the fuzzified values of selected features, which capture the statistical behavior of the input observations. These rules enable interpretable and transparent decision-making and are applied before the final classification step. We thoroughly evaluated our methodology through extensive simulations using three publicly available datasets, such as WUSTL-EHMS-2020, CICIoMT2024, and ECU-IoHT. The results exhibit exceptional accuracy rates of 99.68%, 98.71%, and 99.43%, respectively. A comparative analysis against state-of-the-art models in the existing literature, based on metrics including accuracy, precision, recall, F1-score, and time complexity, reveals that our proposed method achieves superior results. This evidence suggests that our method constitutes a robust solution for mitigating security threats in IoMT networks. Full article

This study presents a comprehensive bibliographic and semantic analysis of 3957 scientific publications on artificial intelligence (AI) in government and public administration. Using an integrated text- and network-based approach, we identify the main thematic areas and conceptual orientations shaping this rapidly expanding field. The analysis reveals a research landscape that spans AI-driven administrative transformation, digital innovation, ethics and accountability, citizen trust, sustainability, and domain-specific applications such as healthcare and education. Across these themes, policy-oriented and conceptual contributions remain prominent, while empirical and technical studies are increasingly interwoven, reflecting growing interdisciplinarity and methodological consolidation. By clarifying how AI research aligns with governance values and institutional design, this study offers actionable insights for policymakers and public managers seeking to navigate responsible public-sector AI adoption. Overall, the findings indicate that AI-for-Government research is moving from fragmented debates toward a more integrated, implementation-relevant knowledge base centered on trustworthy and value-aligned digital-era governance. Full article

Precision medicine, which relies on genomic, multi-omic, phenotypic, and environmental data, has the potential to transform healthcare from population-focused heuristics to individualized prevention, diagnosis, and treatment. Moreover, recent advances in sequencing, molecular profiles, wearable sensors, and machine learning have created opportunities for rapid translational innovation: rapid genomic diagnosis in neonatal and paediatric rare diseases, targeted oncology, pharmacogenomic-based prescribing strategies, and individual sport performance. Nevertheless, the vast majority of innovations remain in centers of specialism or pilot programs, rather than routinely or equitably integrated into clinical or athletic practice. This narrative review synthesizes translational evidence across the life course—in pregnancy, paediatrics, adult medicine, geriatrics, and sportomics—to find reproducible clinical and performance examples which enable precision-based alternative approaches to management, outcome, or preparation; and to reshape those examples into pragmatic, scalable priorities which minimize inequity, and maximize benefit. We undertook a structured narrative synthesis of peer-reviewed literature, trials, clinician translation programs, implementation studies, and sportomics reports, prioritizing examples that demonstrate utility, reproducibility, and impact. Important findings suggest that multi-omics and rapid sequencing improve diagnostic yield and time to diagnosis. Molecular profiling and circulating tumor DNA help realize adaptive treatment selection. Integrated genomics, metabolomics, wearable physiology, and AI analytics facilitate individualized training, injury-risk stratification, and recovery optimization. But systematic value is limited by insufficient representative validation, dataset bias, poor interoperability, regulatory uncertainty, workforce preparedness, and inequities of access. Converting a promise into population- and performance-level value requires coordinated action across four fronts: representative validation; interoperable, privacy-preserving infrastructures; clinician- and coach-centered implementation; and templates for scalable, cost-sensitive deployment. Full article

Rehabilitation robots are a leading solution towards bridging the gap between the growing number of rehabilitation patients requiring therapy and the limited availability of healthcare professionals. However, existing robotic systems are often bulky and expensive, limiting their ability to provide widespread, repetitive, and intensive exercises. This paper presents the development of an impedance-based control strategy designed to provide safe and compliant upper-body passive and active exercises on the low-cost PlanAID robot, which is built using consumer-grade components. The system’s functionalities are evaluated using a high-precision force sensor. Results show that the PlanAID exhibits performance comparable to seminal devices such as the MIT-Manus, achieving a similar applicable reaction force target of 28 N and reflected inertia of 1.1 kg. Although the overall performance is comparable, the low-cost PlanAID prototype suffers from reduced coupled stability margins, limiting the maximum achievable virtual spring constant to 1100 N/m. Despite this limitation, the stiffness values required in practical applications remain low, suggesting that the PlanAID could potentially be a viable candidate for real-world rehabilitation. Initial user feedback was obtained through a preliminary qualitative trial involving healthy subjects. Full article