Search Results (1,687)

Background/Objectives: The iBreast Exam (iBE) electronically palpates the breast to identify possible abnormalities. The purpose of this study was to assess iBE feasibility and compare it to Clinical Breast Exam (CBE) for breast lesion detection. Methods: Prospective evaluation of 300 asymptomatic women, ≥18 years old, with CBE, iBE, and mammography was performed. Sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV) of iBE and CBE for detecting suspicious breast lesions were calculated using breast imaging as the reference standard. For women with one year follow up, the sensitivity, specificity, PPV, and NPV for cancer detection were calculated. Results: 300 women (mean age 58.9 years) underwent CBE, iBE, and mammography. In 2/300 (0.7%), CBE was positive; in 1/300 (0.3%), iBE was positive; and in 24/300 (8%), screening mammograms were positive. Nine had suspicious imaging findings with biopsy (three malignant and six benign). Of three cancers, all visualized mammographically, CBE and iBE detected an ipsilateral breast abnormality in one woman and missed two cancers (<2 cm). Sensitivity, specificity, NPV, and PPV of iBE and CBE were similar, with no statistically significant difference in NPV or PPV for detection of suspicious breast findings or breast cancer (p > 0.05). Conclusions: Mammography detected all breast cancers in our cohort and remains the standard of care. iBE is feasible to perform. Our pilot data demonstrates iBE performed similarly to CBE by trained nurse practitioners. Given our small study population, further investigation is warranted into the potential use of iBE where trained healthcare practitioners are not readily available. Full article

The incorporation of Artificial Intelligence (AI) into medical services in Saudi Arabia offers a substantial opportunity. Despite the increasing integration of AI techniques such as machine learning, natural language processing, and predictive analytics, there persists an issue in the thorough comprehension of their applications, advantages, and issues within the Saudi healthcare framework. This study aims to perform a thorough systematic literature review (SLR) to assess the current status of AI in Saudi healthcare, determine its alignment with Vision 2030, and suggest practical recommendations for future research and policy. In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, 699 studies were initially obtained from electronic databases, with 24 studies selected after the application of established inclusion and exclusion criteria. The results indicated that AI has been effectively utilised in disease prediction, diagnosis, therapy optimisation, patient monitoring, and resource allocation, resulting in notable advancements in diagnostic accuracy, operational efficiency, and patient outcomes. Nonetheless, limitations to adoption, such as ethical issues, legislative complexities, data protection issues, and shortages in worker skills, were also recognised. This review emphasises the necessity for strong ethical frameworks, regulatory control, and capacity-building efforts to guarantee the responsible and fair implementation of AI in healthcare. Recommendations encompass the creation of national AI ethics and governance frameworks, investment in AI education and training initiatives, and the formulation of modular AI solutions to guarantee scalability and cost-effectiveness. This breakthrough enables Saudi Arabia to realise its Vision 2030 objectives, establishing the Kingdom as a global leader in AI-driven healthcare innovation. Full article

As new technologies, such as electronic medical records (EMRs), are introduced into healthcare services, we need to consider how they may be incorporated into simulated environments, so as to maintain and enhance authenticity and learning opportunities. While EMRs have revolutionised clinical practice, many education settings continue to rely on paper-based documentation in simulation, creating a widening gap between educational environments and real-world clinical workflows. This disconnect limits learners’ ability to engage authentically with the tools and resources that underpin contemporary healthcare, impeding the transfer of knowledge to the clinical environment. This practice-based commentary draws on institutional experience from a large, multi-disciplinary simulation-based education facility that explored approaches to integrating EMRs into simulation-based education. It describes the decision points and efforts made to integrate an EMR into simulation-based education and concludes that while genuine EMR systems increase fidelity, their technical rigidity and data governance constraints reduce authenticity. To overcome this, Adelaide Health Simulation adopted an academic EMR (AEMR), a purpose-built digital platform designed for education. The AEMR maintains the functional realism of clinical systems while offering the pedagogical flexibility required to control data, timelines, and learner interactions. Drawing on this experience, this commentary highlights how authenticity in simulation-based education is best achieved not through technological replication alone, but through deliberate use of technologies that align with clinical realities while supporting flexible, learner-centred design. Purpose-built AEMRs exemplify how digital tools can enhance both fidelity and authenticity, fostering higher-order thinking, clinical reasoning, and digital fluency essential for safe and effective contemporary healthcare practice. Here, we argue that advancing simulation-based education in parallel with health service innovations is required if we want to adequately prepare learners for contemporary clinical practice. Full article

Background: Glaucoma is an age-related optic neuropathy frequently accompanied by systemic comorbidities. Vitamin D deficiency (VDD) has been associated with cardiovascular and renal diseases in the general population, yet its relationship with long-term systemic outcomes in glaucoma remains unclear. This study evaluated the association between baseline vitamin D status and subsequent mortality and cardiorenal events in patients with primary glaucoma. Methods: We conducted a retrospective cohort study using deidentified electronic health records from the TriNetX U.S. Collaborative Network, a federated network of participating healthcare organizations. Adults (≥18 years) with incident primary glaucoma (2005–2020) and a serum 25-hydroxyvitamin D (25(OH)D) test within 12 months prior to diagnosis were categorized as VDD (<30 ng/mL) or vitamin D adequacy (VDA; ≥30 ng/mL). After 1:1 propensity score matching across 47 demographic, clinical, medication, and laboratory variables, 11,855 patients per group were followed for up to 5 years. Outcomes included all-cause mortality, major adverse cardiovascular events (MACE), acute kidney injury (AKI), and renal function decline (eGFR < 60 mL/min/1.73 m²). Analyses incorporated Kaplan–Meier curves, Cox models, landmark tests, sensitivity analyses, and competing risk methods. Results: Among the 35,100 eligible patients, the matched cohorts demonstrated higher 5-year risks associated with VDD for all-cause mortality (HR 1.104; 95% CI 1.001–1.217), MACE (HR 1.151; 95% CI 1.078–1.229), and AKI (HR 1.154; 95% CI 1.056–1.261), whereas the risks of renal function decline did not differ (HR 0.972; 95% CI 0.907–1.042). Risk divergence emerged within the first year of follow-up and persisted through the 5-year observation period. Conclusions: In patients with primary glaucoma, vitamin D deficiency was associated with higher long-term risks of mortality and cardiorenal complications, but not renal function decline. Taken together, the results are consistent with vitamin D status serving as a marker of broader systemic vulnerability in glaucoma and highlight the need for prospective studies to further clarify its prognostic significance. Full article

Background/Objectives: Healthcare-associated infections (HAIs), particularly those caused by multidrug-resistant (MDR) bacteria, remain a major challenge for Romanian hospitals. This study aimed to evaluate the epidemiological burden of MDR-related HAIs and to characterize the distribution of MDR bacterial isolates and their antimicrobial resistance patterns over four consecutive semesters in a Romanian tertiary care hospital. Methods: A retrospective study was conducted using data from the Electronic Registry of HAIs, clinical observation sheets, and microbiology laboratory records. An epidemiological analysis was performed on patients diagnosed with MDR-related HAIs, while a separate microbiological analysis included all MDR bacterial isolates identified during the study period. Descriptive and comparative statistical analyses were applied to assess temporal trends, pathogen distribution, and resistance profiles. Results: Of the 327 HAIs identified, 56 cases (17.13%) were caused by MDR bacteria. Most MDR-HAIs originated from the Intensive Care Unit (≈60%), with Acinetobacter baumannii and Klebsiella spp. as the predominant pathogens. Overall mortality among patients with MDR-HAIs was high (51.79%), particularly in infections caused by A. baumannii and K. pneumoniae. Microbiological analysis of MDR isolates (n = 406) revealed consistently high resistance rates to ciprofloxacin, cefepime, and ceftazidime, exceeding 95% in 2023–2024, while resistance to carbapenems surpassed 90% by the end of the study period. Temporal variability in MDR burden was observed across semesters, suggesting an influence of clinical and institutional factors. Conclusions: MDR-related HAIs represent a significant and persistent problem in Romanian acute-care hospitals, particularly in Intensive Care Units. The dominance of carbapenem-resistant A. baumannii and extended-spectrum beta-lactamase-producing and carbapenem-resistant Klebsiella spp. highlights the urgent need for strengthened antimicrobial stewardship, enhanced microbiological surveillance, and reinforced infection prevention strategies. Full article

Background/Objectives: Acute sinusitis (AS) is a common infection of the upper respiratory tract that places considerable clinical and economic burden worldwide. Although frequently encountered in practice, the factors that predispose individuals to AS remain poorly understood. This study examined how different respiratory disorders and comorbidities influence the likelihood of developing AS, aiming to clarify its underlying risk profile. Methods: A longitudinal analysis was performed using electronic health records from the Clinical Center of the University of Debrecen Hospital. The study cohort (2007–2022) encompassed 37,164 observations. To evaluate the risk of AS progression, Log-Rank tests and Cox proportional hazards regressions were applied whilst adjusting for covariates. Results: The risk of developing AS was significantly higher among individuals with preceding respiratory conditions. Patients with common cold demonstrated a 2.3-fold increased risk of developing AS (95% CI [1.51–3.40]). Compared to those without such disorders, participants with acute bronchitis had a 2.5-fold higher hazard of AS (95% CI 1.90–3.26). The strongest association was observed for allergic rhinitis (HR = 4.04, 95% CI 3.18–5.13), followed by chronic sinusitis (HR = 3.10, 95% CI 2.13–4.51). Chronic obstructive pulmonary disease was also identified as a significant predictor for AS (HR = 1.62, 95% CI 1.04–2.52), whereas dental pathologies were associated with a modest protective effect (HR = 0.69, 95% CI 0.48–0.97). Conclusions: Patients with allergic rhinitis, chronic sinusitis, acute bronchitis, common cold, or chronic obstructive pulmonary disease have a markedly higher risk of developing AS. Clinicians should actively screen for these conditions when assessing patients with recurrent or severe sinus infections. Early recognition and management of underlying respiratory disorders may reduce AS episodes, promote symptom control, and lessen healthcare burdens. Future research should concentrate on precision medicine to leverage AS preventive and management strategies. Full article

Background/Objectives: Healthcare workers at the frontline of managing pandemics are at increased risk for adverse physical and mental health outcomes, which has been shown to result in burnout. The relationship between personal resilience and burnout among clinical and non-clinical healthcare staff working in an acute care setting was assessed at the start of the COVID-19 pandemic. Methods: A prospective cross-sectional survey design with electronic questionnaires was used to measure resilience (Connor-Davidson Resilience Scale,) and burnout (Maslach Burnout Inventory—Human Services Survey). Linear regression analyses were conducted to examine the relationship between resilience and emotional exhaustion, depersonalization, and personal accomplishment. Results: A significant inverse relationship between resilience and both emotional exhaustion and depersonalization, and a positive relationship between resilience and personal accomplishment were identified. Higher resilience scores were significantly associated with lower emotional exhaustion and depersonalization and higher personal accomplishment under pandemic conditions. Conclusions: Strategies to boost resilience organization-wide amongst healthcare staff providing patient care are critical for providing skills to reduce the onset of burnout and support employee mental health. From a pandemic preparedness lens, organizational-level emergency management should consider the importance of resilience-building among staff to proactively prevent burnout and its subsequent effects on patient-care and general hospital functioning. Full article

Background/Objectives: Effective nutritional care is a critical component of oncology treatment. Behaviour change techniques (BCTs) are key elements that drive individual behaviour change and are commonly identified within clinical interventions and implementation strategies. Despite their relevance, the application of BCTs in oncology nutrition has not been systematically examined. This systematic review aimed to identify and synthesise the use of BCTs in nutrition interventions and their implementation strategies within adult oncology care. Methods: A search across 10 electronic databases was conducted from inception up to December 2024. Data extraction focused on intervention characteristics, plus implementation barriers, strategies, and outcomes, which were coded using relevant established taxonomies, i.e., Theoretical Domains Framework, Behaviour Change Techniques, and Proctor’s outcomes framework. Study quality was assessed using the QuADS tool. Results: After screening 4055 abstracts and 165 full texts, 38 articles representing 31 unique studies were included. Nutrition interventions (n = 31) spanned across risk screening/assessment, care planning/pathways, nutritional monitoring, and support guidelines. Among the 19 interventions that incorporated BCTs targeting patients and/or healthcare professionals (HCPs), 20 unique BCTs were identified across 97 instances. Separately, implementation strategies reported in 25 of the 38 articles included 96 BCT instances (18 unique) targeting HCPs. BCTs were frequently observed alongside positive outcomes across patient, service, and implementation levels. Conclusions: Application of BCTs in oncology nutrition practice remains implicit and inconsistent. For clinical practice, more explicit specifications of BCTs may support better integration of nutrition care in routine oncology settings. Future research is warranted to test the effectiveness of specific BCTs and their combinations. This can be supported by standardised reporting of intervention content and implementation strategies which can enable identification of patterns of success and optimise replicability. Full article

In the context of the rapid growth of the Internet of Things and mobile health services, sensors and smart wearable devices are continuously collecting and uploading dynamic health data. Together with the long-term accumulated electronic medical records and multi-source heterogeneous clinical data from healthcare institutions, these data form the cornerstone of intelligent healthcare. In the context of medical data sharing, previous studies have mainly focused on privacy protection and secure data transmission, while relatively few have addressed the issue of incentive mechanisms. However, relying solely on technical means is insufficient to solve the problem of individuals’ willingness to share their data. To address this challenge, this paper proposes a three-party Stackelberg-game-based incentive mechanism for medical data sharing. The mechanism captures the hierarchical interactions among the intermediator, electronic device users, and data consumers. In this framework, the intermediator acts as the leader, setting the transaction fee; electronic device users serve as the first-level followers, determining the data price; and data consumers function as the second-level followers, deciding on the purchase volume. A social network externality is incorporated into the model to reflect the diffusion effect of data demand, and the optimal strategies and system equilibrium are derived through backward induction. Theoretical analysis and numerical experiments demonstrate that the proposed mechanism effectively enhances users’ willingness to share data and improves the overall system utility, achieving a balanced benefit among the cloud platform, electronic device users, and data consumers. This study not only enriches the game-theoretic modeling approaches to medical data sharing but also provides practical insights for designing incentive mechanisms in IoT-based healthcare systems. Full article

Background/Objectives: Population aging increases the healthcare burden of chronic diseases. We aimed to characterize the sociodemographic and clinical characteristics of Aged Madrid, a cohort comprising 98.6% of the population aged 75 years and older in Madrid, Spain. Methods: Observational study with a five-year retrospective baseline period (2015–2019) to assess baseline vascular and metabolic risk. Data were taken from primary care electronic medical records, hospital discharge summaries, and pharmacy records. Results: 587,603 individuals (mean age: 84 years ± 5.8 years, 61.3% women) were analysed. Obesity affected 31.3% (more frequent in women), while type 2 diabetes occurred in 23.8% (predominantly in men). Hypertension (52.8%), dyslipidaemia (61.6%), and chronic kidney disease (21.7%) were more frequent in women. Atrial fibrillation was the leading cardiovascular condition in women (15.1%), while acute myocardial infarction predominated in men (8.2%). The most prescribed drug classes were antihypertensives (53.8%), statins (44.2%), and oral antidiabetics (26.4%). Among antihypertensives, diuretics (53.9%), ACE inhibitors (27.4%), and ARBs (25.3%) were most used, often in combinations such as diuretics + ACE inhibitors (30.1%). Diabetes treatments favoured metformin and DPP-4 inhibitors; 5.2% received insulin. Conclusions: Sex-based differences emerged in biochemical, anthropometric, and lifestyle variables. Men showed a higher prevalence of cardiovascular diseases and several cardiometabolic risk factors, while women used fewer lipid-lowering and antidiabetic agents. Diuretics were the predominant antihypertensives, and antidiabetic therapy largely followed guideline recommendations. Although 60% of statin users had no prior cardiovascular disease, and their use was concentrated mainly among individuals with major cardiometabolic risk conditions and declined with advancing age, suggesting an age- and risk-sensitive prescribing pattern rather than indiscriminate use. Full article

Biomedical antennas are essential components in modern healthcare systems, supporting wireless communication, physiological monitoring, diagnostic imaging, and therapeutic energy delivery. Their performance is strongly influenced by proximity to the human body, creating challenges such as impedance detuning, signal absorption, and size constraints that motivate new materials and fabrication approaches. This work reviews recent advances enabling next-generation wearable and implantable antennas, with emphasis on printed electronics, additive manufacturing, flexible hybrid integration, and metamaterial design. Methods discussed include 3D printing and inkjet, aerosol jet, and screen printing for fabricating conductive traces on textiles, elastomers, and biodegradable substrates, as well as multilayer Flexible Hybrid Electronics that co-integrate sensing, power management, and RF components into thin, body-conforming assemblies. Key results highlight how metamaterial and metasurface concepts provide artificial control over dispersion, radiation, and near-field interactions, enabling antenna miniaturization, enhanced gain and focusing, and improved isolation from lossy biological tissue. These approaches reduce SAR, stabilize impedance under deformation, and support more efficient communication and energy transfer. The review concludes that the convergence of novel materials, engineered electromagnetic structures, and AI-assisted optimization is enabling biomedical antennas that are compact, stretchable, personalized, and highly adaptive, supporting future developments in unobtrusive monitoring, wireless implants, point-of-care diagnostics, and continuous clinical interfacing. Full article

Background/Objectives: This study aimed to determine the prevalence of persistent symptoms and the radiological and laboratory evolution at 6 months and 5 years after discharge in patients hospitalized for SARS-CoV-2 pneumonia during the first wave of the pandemic in Spain and to estimate the healthcare impact of their follow-up. Methods: A retrospective longitudinal observational study was conducted at the “Hospital Central de la Defensa”. A total of 200 patients aged >18 years with a diagnosis of SARS-CoV-2 pneumonia were screened. Clinical, radiological, and laboratory data were collected from electronic medical records. Patients with symptoms or radiological abnormalities at discharge underwent in-person evaluations, while the remainder were assessed by telephone. Results: A total of 182 patients met the inclusion and exclusion criteria. Of these, 112 were assessed in the outpatient setting; 60.7% required in-person evaluations, with normal pulmonary auscultation in 93.6%, complete radiological resolution in 85%, and normalized laboratory parameters in almost all cases. At 6 months, 26.5% presented at least one residual symptom, whereas only three patients (4.5%) reported symptoms at 5 years. No risk factors associated with symptom persistence were identified. The estimated cumulative healthcare cost was EUR 21,627.50. Conclusions: Among patients hospitalized for SARS-CoV-2 pneumonia during the first wave of the pandemic, 26.7% and 4.46% presented at least one persistent symptom at 6 months and 5 years after discharge, respectively. Full article

Background/Objectives: Mobile health (mHealth) interventions can enhance chronic disease management, but their integration into public healthcare systems remains complex. DiabeText is the first SMS-based intervention in Spain delivering personalized diabetes self-management support using electronic health record data. This study explored perceived barriers and facilitators to the implementation of DiabeText in the Spanish public health context from the perspective of key stakeholders. Methods: A qualitative study was conducted using semi-structured interviews with 14 purposively selected stakeholders involved in digital health, diabetes care, data protection, and healthcare management across several Spanish regions. Interviews were thematically analyzed using Braun and Clarke’s approach and guided by the Implementation Research Logic Model. Results: Participants reported several barriers, including concerns regarding data protection, uncertainty about long-term sustainability, insufficient training and engagement of healthcare professionals and low digital literacy among certain patient groups. Facilitators included favorable institutional momentum for digital innovation, funding availability, perceived clinical utility and scalability of DiabeText, and growing patient familiarity with digital tools. Recommended strategies included integration into existing healthcare systems and workflows, professional training and use of familiar communication platforms. Conclusions: Effective implementation of DiabeText requires addressing regulatory, organizational, and equity-related barriers while leveraging institutional support and readiness for innovation. Early involvement of healthcare professionals, robust data governance, and investment in digital literacy are essential to ensure sustainable and equitable adoption. These findings provide actionable insights to support the integration of mHealth tools into chronic disease care in Spain and similar settings. Full article

Wearable multi-modal body fluid monitoring enables continuous, non-invasive, and context-aware assessment of human physiology. By integrating biochemical and physical information across multiple modalities, wearable systems overcome the limitations of single-marker sensing and provide a more holistic view of dynamic health states. This review offers a system-level overview of recent advances in multi-modal body fluid monitoring, structured into three hierarchical dimensions. We first examine sensing-combination strategies such as multi-marker analysis within single fluids, coupling biochemical signals with bioelectrical, mechanical, or thermal parameters, and emerging multi-fluid acquisition to improve analytical accuracy and physiological relevance. Next, we discuss platform-integration mechanisms based on biochemical, physical, and hybrid sensing principles, along with monolithic and modular architectures enabled by flexible electronics, microfluidics, microneedles, and smart textiles. Finally, the data-processing patterns are analyzed, involving cross-modal calibration, machine learning inference, and multi-level data fusion to enhance data reliability and support personalized and predictive healthcare. Beyond summarizing technical advances, this review establishes a comprehensive framework that moves beyond isolated signal acquisition or simple metric aggregation toward holistic physiological interpretation. It guides the development of next-generation wearable multi-modal body fluid monitoring systems that overcome the challenges of high integration, miniaturization, and personalized medical applications. Full article

Background/Objectives: Hyperglycemia in hospitalized patients is associated with an increased risk of complications, morbidity, mortality, and healthcare costs, regardless of a prior diagnosis of diabetes. The hospitalist system can improve various outcomes, including length of stay, medical costs, patient satisfaction, and mortality rates. However, the effects of hospitalist care on blood glucose control in hospitalized patients remain unclear. This study aimed to assess the specific effects of hospitalist services on blood glucose control in hospitalized patients, with a focus on hyperglycemia management and patient outcomes. Methods: This retrospective study reviewed the electronic medical records of patients diagnosed with diabetes at Yonsei Severance Hospital in Yongin, between March 2020 and February 2022. It included adults aged ≥20 years who were hospitalized and had undergone blood glucose measurements during hospitalization. Glycemic control was assessed using hemoglobin A1c, and the blood glucose levels were measured four times daily during hospitalization. Variability was quantified using the coefficient of variation and compared between hospitalist-led and traditional specialty care groups, over a 14-day hospitalization period. Results: Despite a higher baseline risk profile, patients receiving hospitalist-led care experienced significantly more stable glycemic variability over time (p = 0.002), suggesting better inpatient glucose management than those receiving traditional specialty care. Conclusions: Hospitalist-led care was associated with more stable glycemic variability over time in hospitalized patients with diabetes, despite a higher baseline burden of comorbidities and poorer glycemic control at admission. Full article