Search Results (6,003)

Background: Early surgical intervention is associated with improved outcomes in hip fracture care, yet in patients using Direct Oral Anticoagulants (DOACs), surgery is frequently delayed due to concerns about increased intraoperative bleeding. Despite the increasing prevalence of hip fracture patients on DOACs, no consensus exists on optimal surgical timing. This has led to substantial practice variation between hospitals, with some operating within 24 h of last DOAC intake and others delaying surgery beyond 24 h. This study hypothesizes that early surgery within 24 h results in a non-inferior blood transfusion risk compared to delayed surgery 24 h or more after last DOAC intake in hip fracture patients on DOACs. This protocol describes the design and methodological rationale of a natural experiment. Methods and analysis: A multicenter cohort study designed as a natural experiment will be conducted across seven Dutch level 2 trauma centers, using predefined and standardized prospectively collected variables from electronic health records. Centers will adhere to distinct local surgical timing protocols, forming two cohorts: early surgery within 24 h and delayed surgery 24 h or more after last DOAC intake. Patients presenting with an isolated hip fracture who are using a DOAC and have taken their last dose within 24 h before admission will be included. The primary endpoint is postoperative blood transfusion. Secondary endpoints include additional bleeding-related outcomes, thrombotic and postoperative complications, and hospital length of stay. The primary analysis will be conducted on a per-protocol basis, with an intention-to-treat analysis performed as a supplementary assessment. Non-inferiority will be established if the upper bound of the one-sided 95% confidence interval for the risk difference does not exceed the predefined margin of 5%. Ethics and dissemination: Ethical approval was obtained from the Medical Ethics Committee United, Utrecht, The Netherlands. As this is a cohort study without altering clinical care, individual informed consent is not required. All data will be pseudonymized, and findings will be disseminated through peer-reviewed journals and scientific conferences. Registration details: Medical Ethics Committee United, Utrecht, The Netherlands, registration number W25.034 Full article

The use of interpreter services is an important component of medical care. It is critical for medical students to practice this during training. It is known that simulation and role play provide important opportunities for students to practice skills. This scoping review maps the experience that medical students around the world have practicing with interpreter services in a simulated environment. We searched within three major databases (PubMed, ERIC, and SCOPUS) using a wide range of search terms for publications from the past 15 years. This scoping review was conducted according to PRISMA-ScR guidelines. Of the 1341 studies initially obtained from search terms, 22 were ultimately found to meet inclusion criteria. There is variability in curricula offered including when in medical school, what other specialties are involved, and how the education is conveyed. Most publications lacked longitudinal follow-up and assessment of learner competence was limited. Review articles, a prevalence study, and proof of concept studies also serve to demonstrate the breadth of publications on this subject. This is an area of important consideration within medical education today. Many studies highlight the relative scarcity of formal programs as well as a lack of consistency. Where programs do exist, the importance of including simulation is highlighted. Full article

Individuals across their lifespan may experience hearing loss from medications or chemicals, prompting concern about ototoxic environmental exposures. This study applies computational modeling as a screening-level hazard identification and chemical prioritization approach and is not intended to constitute a human health risk assessment or to estimate exposure- or dose-dependent ototoxic risk. We evaluated in silico drug-induced ototoxicity models on 80 environmental chemicals, excluding 4 with known ototoxicity, and analyzed 76 chemicals using fingerprinting, similarity assessment, and machine learning classification. We compared predicted environmental ototoxicants with ototoxic drugs, paired select polychlorinated biphenyls with the antineoplastic drug mitotane, and used PCB 177 as a case study to construct an ototoxicity pathway. A systems biology framework predicted and compared molecular targets of mitotane and PCB 177 to generate a network-level mechanism. The consensus model (accuracy 0.95 test; 0.90 validation) identified 18 of 76 chemicals as potential ototoxicants within acceptable confidence ranges. Mitotane and PCB 177 were both predicted to disrupt thyroid-stimulating hormone receptor signaling, suggesting thyroid-mediated pathways may contribute to auditory harm; additional targets included AhR, transthyretin, and PXR. Findings indicate overlapping mechanisms involving metabolic, cellular, and inflammatory processes. This work shows that integrated computational modeling can support virtual screening and prioritization for chemical and drug ototoxicity risk assessment. Full article

Chronic obstructive pulmonary disease (COPD) is a major health burden worldwide and in Taiwan, ranking as the third leading cause of death globally, and its prevalence in Taiwan continues to rise. Readmission within 14 days is a key indicator of disease instability and care efficiency, driven jointly by patient-level physiological vulnerability (such as reduced lung function and multiple comorbidities) and healthcare system-level deficiencies in transitional care. To mitigate the growing burden and improve quality of care, it is urgently necessary to develop an AI-based prediction model for 14-day readmission. Such a model could enable early identification of high-risk patients and trigger multidisciplinary interventions, such as pulmonary rehabilitation and remote monitoring, to effectively reduce avoidable early readmissions. However, medical data are commonly characterized by severe class imbalance, which limits the ability of conventional machine learning methods to identify minority-class cases. In this study, we used real-world clinical data from multiple hospitals in Kaohsiung City to construct a prediction framework that integrates data generation and ensemble learning to forecast readmission risk among patients with chronic obstructive pulmonary disease (COPD). CTGAN and kernel density estimation (KDE) were employed to augment the minority class, and the impact of these two generation approaches on model performance was compared across different augmentation ratios. We adopted a stacking architecture composed of six base models as the core framework and conducted systematic comparisons against the baseline models XGBoost, AdaBoost, Random Forest, and LightGBM across multiple recall thresholds, different feature configurations, and alternative data generation strategies. Overall, the results show that, under high-recall targets, KDE combined with stacking achieves the most stable and superior overall performance relative to the baseline models. We further performed ablation experiments by sequentially removing each base model to evaluate and analyze its contribution. The results indicate that removing KNN yields the greatest negative impact on the stacking classifier, particularly under high-recall settings where the declines in precision and F1-score are most pronounced, suggesting that KNN is most sensitive to the distributional changes introduced by KDE-generated data. This configuration simultaneously improves precision, F1-score, and specificity, and is therefore adopted as the final recommended model setting in this study. 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 and Objectives: Patients with Sjögren’s disease (SjD) do not experience any improvement in gastroesophageal reflux disease (GERD) symptoms after SjD treatment, and in some patients, reflux even worsens. It is important to note that GERD manifests itself through typical and atypical symptoms, the latter of which may include eye damage, as evidenced by a growing body of research. When SjD patients were prescribed medication to treat GERD, their condition improved at the same time. Therefore, we aim to investigate whether there is a link between ocular dryness and gastroesophageal reflux disease (GERD) in patients with Sjögren’s disease (SjD). Materials and Methods: Our study included 27 patients with SjD according to the 2016 American College of Rheumatology and the European League Against Rheumatism (ACR/EULAR) Sjögren’s syndrome Classification Criteria, and 28 patients with non-autoimmune sicca syndrome due to GERD (nonautoimmSicca). Results: The study involved 55 participants, 48 (87.3%) women and 7 (12.7%) men. The median age was 54 years (IQR 49–64). A total of 41 subjects (74.5%) had GERD, and 20 subjects (36.4%) tested positive for Helicobacter pylori: 13 (48.1%) and 1 (3.7%) in the SjD group, and 28 (100.0%) and 19 (67.9%) in the nonautoimmSicca group, respectively. A significant difference in asymmetric tear secretion (p < 0.001) was found between the nonautoimmSicca and SjD patients, with values of 5 (3–10) mm/5 min and 1 (0–2) mm/5 min, respectively. A low correlation was detected between sialometry results and tear secretion asymmetry (r = 0.48, p < 0.001). An increase of 1 mm/5 min in the tear secretion asymmetry between the eyes was associated with a 2.04-fold increase in the odds ratio for having GERD (95% CI 1.25–3.32, p = 0.004), and was associated with a 1.9-fold increase in the odds ratio for having GERD (95% CI 1.04–3.49, p = 0.038) in patients with SjD. The presence of Helicobacter pylori is associated with asymmetric tear secretion [95% CI 1.22 (1.05–1.41, p = 0.010)]. Conclusions: Asymmetric tear secretion between the eyes is associated with the odds of having GERD. Patients with non-autoimmune sicca syndrome due to GERD have significantly greater asymmetry in tear secretion compared to those diagnosed with Sjögren’s disease. Full article

Computer vision and deep learning are essential in diverse fields such as autonomous driving, medical imaging, face recognition, and object detection. However, enhancing low-light remote sensing images remains challenging for both research and real-world applications. Low illumination degrades image quality due to sensor limitations and environmental factors, weakening visual fidelity and reducing performance in vision tasks. Common issues such as insufficient lighting, backlighting, and limited exposure create low contrast, heavy shadows, and poor visibility, particularly at night. We propose QWR-Dec-Net, a quaternion-based Retinex decomposition network tailored for low-light image enhancement. QWR-Dec-Net consists of two key modules: a decomposition module that separates illumination and reflectance, and a denoising module that fuses a quaternion holistic color representation with wavelet multi-frequency information. This structure jointly improves color constancy and noise suppression. Experiments on low-light remote sensing datasets (LSCIDMR and UCMerced) show that QWR-Dec-Net outperforms current methods in PSNR, SSIM, LPIPS, and classification accuracy. The model’s accurate illumination estimation and stable reflectance make it well-suited for remote sensing tasks such as object detection, video surveillance, precision agriculture, and autonomous navigation. Full article

Even though environmental health and climate change are rapidly intensifying the severity of determinants of disease and inequity, training for health professionals in these areas remains fragmented across Europe. To address this gap, the European Medical Association (EMA), in collaboration with the European Network on Climate and Health Education (ENCHE), the International Network on Public Health and Environment Tracking (INPHET) and University College London, convened a one-day hybrid roundtable in London on 17 September 2025, focused on “Preparing Health Professionals for Environmental Health and Climate Change: A Challenge for Europe”. The programme combined keynote presentations on global and European policy, health economics and curriculum design with three disease-focused roundtables (respiratory, cardiovascular and neurological conditions), each examining the following topics: (A) climate and environment as preventable causes of disease; (B) healthcare as a source of environmental harm; and (C) capacity building through education and training. Contributors highlighted how environmental epidemiology, community-based prevention programmes and sustainable clinical practice can be integrated into teaching, illustrating models from respiratory, cardiovascular, surgical and neurological care. EU-level speakers outlined the policy framework (European Green Deal, Zero Pollution Action Plan and forthcoming global health programme) and tools through which professional and scientific societies can both inform and benefit from European action on environment and health. Discussions converged on persistent obstacles, including patchy national commitments to decarbonising healthcare, isolated innovations that are not scaled and curricula that do not yet embed sustainability in examinable clinical competencies. The conference concluded with proposals to develop an operational education package on environmental and climate health; map and harmonise core competencies across undergraduate, postgraduate and Continuing -professional-development pathways; and establish a permanent EMA-led working group to co-produce a broader position paper with professional and scientific societies. This conference report summarises the main messages and is intended as a bridge between practice-based experience and a formal EMA position on environmental-health training in Europe. Full article

Transitioning from theoretical learning to practical application remains a significant challenge for students in medical and veterinary science education, particularly in the context of medical imaging and ultrasound interpretation. Traditional lecture-based methods offer limited support for developing the spatial reasoning and technical skills required for ultrasound pregnancy diagnosis. This study evaluates the effectiveness of an interactive mixed reality (MR) training tool, Ewe Scan, delivered through the Apple Vision Pro, compared to traditional lecture-based instruction. Forty-two undergraduate students were randomly assigned to either a lecture-trained or MR-trained group and assessed immediately after training and again after six weeks. Results showed that MR-trained students significantly outperformed their lecture-trained peers in both immediate comprehension and retention over time, particularly in ultrasound interpretation skills. The MR-trained group also reported higher levels of engagement, confidence, and satisfaction with their training experience. These findings suggest that MR-based learning enhances educational outcomes by improving spatial understanding, increasing active engagement, and supporting knowledge retention. Integrating MR simulations into ultrasound education offers a scalable, ethical, and effective alternative to traditional training methods, contributing to advancements in medical imagery education. Full article

The closure of rural maternity units in hospitals across the United States contributes to health inequities; however, little is known about the effects of reopening maternity services in this context. We conducted a mixed-methods study to characterize labor and delivery outcomes and patient experiences associated with the reopening of a rural Level 1 Maternity Care Center (MCC) at a critical access hospital. We compared clinical outcomes and distance to care for patients who gave birth at the rural MCC in the three years after its opening with outcomes from a similar low-risk and geographically located sample who gave birth at a large suburban academic medical center in the same hospital system in the three years before the MCC reopened. We also conducted in-depth interviews with patients who gave birth at the MCC. Labor and delivery outcomes were similar across both groups, with significantly more care provided by family physicians and midwives and lower neonatal intensive care unit use at the MCC. The opening of the MCC halved the distance patients traveled to give birth, and patients reported high rates of satisfaction. Rural maternity care centers can improve access to quality care closer to home using a resource-appropriate model. 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

Medical students experience fluctuations in their motivation, influenced by various factors, including curricular rigor, mental health, and institutional factors. Based on Self-Determination Theory (SDT) and the Four Pillars of Academic Engagement (HPEE), this study, conducted at a private Mexican university, examined motivational variation according to academic year, curricular impact, gender differences, and its relationship with mental health. Methods: A quantitative, cross-sectional, descriptive study was conducted using qualitative tools for contextualization (n = 1326). Mann–Whitney U tests, Kruskal–Wallis tests, logistic regression, and psychological network analysis were performed. Results: Motivation showed cross-sectional variation: high in preclinical years 1 and 2, decreasing in clinical years 3 and 4 (p < 0.001), and rebounding in year 6. The reformed curriculum (elective subjects, student-centered active learning) resulted in greater motivation (OR = 10.68, p < 0.001). Women tended to have slightly higher motivation (p = 0.050), higher grade point averages (p < 0.001), but also greater stress (p < 0.001). Network analysis revealed that intrinsic achievement (centrality = 1.11) and curiosity about knowledge (predictability = 84.5%) are the main drivers, while demotivation was linked to the later years. The qualitative part of the study showed altruism/curiosity as the main motivators; mistreatment/workload (demotivators). Conclusions: Motivation is context-sensitive, peaks in the preclinical stage, and recovers with autonomy but is vulnerable during clinical immersion. Autonomy in course selection, active student-centered pedagogies, and gender-sensitive support foster sustained participation. The centrality of intrinsic factors in the network highlights that achievement motivation and knowledge are general and independent motivators. Qualitative data reveal systemic barriers. Stage-specific interventions, such as mentoring, student support programs, and reporting mistreatment, can be crucial for strengthening resilience and performance. Longitudinal and multi-institutional studies are needed to validate the causality and generalizability of this study. Full article

Background/Objectives: Refeeding syndrome (RFS) is challenging to prevent and manage in hospitalized patients receiving enteral nutrition (EN). Nebraska Medicine implemented an Electronic Medical Record (EMR) Refeeding Risk Order Set (RROS) to standardize prevention measures, including structured electrolyte monitoring, thiamine supplementation, and conservative EN initiation. This study evaluated whether RROS implementation reduced RFS occurrence or severity and assessed its operational impact. Methods: In this retrospective cohort study, adults receiving EN before and after RROS implementation were compared. Primary outcomes were RFS occurrence and severity; secondary outcomes included EN initiation and advancement rates, electrolyte trends, lab frequency, and electrolyte repletion. Results: RFS occurrence did not differ significantly between groups (92.3% vs. 91.3%, p = 0.694), nor did severity (p = 0.535). The post-RROS group received more electrolyte boluses on EN Day 0 (p = 0.027) and had a lower EN starting rate (15.7 vs. 18.3 mL/h, p = 0.045). Conclusions: Although the RROS did not reduce RFS occurrence or severity, integrating American Society for Parenteral and Enteral Nutrition (ASPEN)-based guidance into the EMR was highly feasible and adopted immediately. Automating electrolyte monitoring, micronutrient supplementation, and conservative feeding initiation reduces the risk of errors and promotes consistent care. These benefits improve workflow efficiency and support providers during high census periods, limited staffing, or when experience varies. Future research should explore combining EMR tools with predictive analytics to optimize early risk identification and individualized management. Full article

This paper explores recent advancements in end-of-life (EOL) care in Canada, focusing on palliative care (PC) in oncology, advance care planning (ACP), and medical assistance in dying (MAiD). Despite improvements in cancer treatment, cancer remains a leading cause of death in Canada, with patients facing significant physical, psychosocial, and emotional challenges throughout the illness trajectory. Over the past few decades, PC has evolved to address serious illness from diagnosis onward, enhancing symptom management, quality of life, and patient satisfaction, while reducing hospital admissions and unnecessary treatments. However, barriers such as misconceptions about PC, late PC referrals, and limited access to PC, particularly in rural and remote areas, still exist. This perspective paper draws on the authors’ collective clinical and research experience in oncology and PC, complemented by a focused review of key literature. Ongoing education for oncology nurses on EOL care, including on PC, ACP, and MAiD, as well as continued efforts to expand access to PC for all Canadians, are imperative in order to improve the EOL experience for people affected by cancer nationwide. Full article

Background/Objectives: Healthcare workers (HCW) in primary care settings play a significant role in recommending vaccines to patients. We aimed to describe COVID-19 vaccination knowledge, attitudes, perception, and practices (KAPP) of HCWs in Tunisia and identify associated factors. Methods: We conducted a national cross-sectional survey (29 January to 3 February 2024) among HCWs in primary public healthcare centers using purposive sampling. Factors associated with good knowledge, positive attitude, and good practice, measured through Likert scales using face-to-face questionnaires, were identified using binary logistic regression. Results: We included 906 HCWs (mean age = 41.87 ± 8.89 years). In total, 37.75% (342/906) of HCWs had good knowledge and perception, 4.30% (39/906) had a positive attitude, and 24.9% (226/906) had good practices related to COVID-19 vaccination. Working in urban compared to rural areas was associated with good knowledge (aOR = 1.57, 95%CI = 1.12–2.21) and positive attitude (aOR = 4.94, 95%CI = 1.19–20.44) to COVID-19 vaccination. Physicians had better KAPP scores than other medical professionals. HCWs working in departments with high-risk patients were more likely to have good knowledge (aOR = 1.28, 95%CI = 1.00–1.72). Positive attitude was also associated with being male (aOR = 2.97, 95%CI = 1.75–5.07) and having at least one non-communicable disease (aOR = 1.92, 95%CI = 1.14–3.23). Being male (aOR = 1.97, 95%CI = 1.35–2.88) and having more years of professional experience (aOR = 1.81, 95%CI = 1.29–2.52) were associated with good practice. Conclusions: Just over a third of HCWs in primary healthcare clinics had good knowledge of COVID-19 vaccination, while positive attitudes and good practices were low. Targeted interventions, particularly for HCWs with less professional experience working in rural settings, are needed to increase good practices and improve COVID-19 vaccination coverage in Tunisia. Full article