11237 research outputs found
Sort by
Quantifying the impact of immortal time bias: empirical evidence from meta-analyses
No full textNo description supplied</p
Understanding Hearing Aid Use and Non-Use in Adult Hearing Aid Recipients: A Qualitative Content Analysis
No full textNo description supplied</p
Novel Federated Graph Contrastive Learning for IoMT Security: Protecting Data Poisoning and Inference Attacks
No full textMalware evolution presents growing security threats for resource-constrained Internet of Medical Things (IoMT) devices. Conventional federated learning (FL) often suffers from slow convergence, high communication overhead, and fairness issues in dynamic IoMT environments. In this paper, we propose FedGCL, a secure and efficient FL framework integrating contrastive graph representation learning for enhanced feature discrimination, a Jain-index-based fairness-aware aggregation mechanism, an adaptive synchronization scheduler to optimize communication rounds, and secure aggregation via homomorphic encryption within a Trusted Execution Environment. We evaluate FedGCL on four benchmark malware datasets (Drebin, Malgenome, Kronodroid, and TUANDROMD) using 5 to 15 graph neural network clients over 20 communication rounds. Our experiments demonstrate that FedGCL achieves 96.3% global accuracy within three rounds and converges to 98.9% by round twenty—reducing required training rounds by 45% compared to FedAvg—while incurring only approximately 10% additional computational overhead. By preserving patient data privacy at the edge, FedGCL enhances system resilience without sacrificing model performance. These results indicate FedGCL’s promise as a secure, efficient, and fair federated malware detection solution for IoMT ecosystems.</p
RescQ: early findings from a feasibility pilot of a structured support platform for bystanders of out-of-hospital cardiac arrest
No full textNo description supplied</p
Editorial: impact of technology on human behaviors in medical professions education
No full textThe Research Topic focuses on the impact of technology on human behaviors in medical sciences teaching and learning. It also explores the effect of social, psychological, and other factors on the use of technology in medical education. In so doing, the Research Topic focuses on the integration of technology and the role of human behaviors in improving the teaching and learning process of medical education. Technology has revolutionized education by allowing teachers and students to establish new ways of teaching and learning. It has transformed the delivery of knowledge and the behaviors and attitudes of educators and learners. Integrating advanced tools, such as virtual reality (VR), artificial intelligence (AI), and online learning platforms, has improved how medical students and professionals acquire skills, interact with patients, and engage with peers. Interactive technologies like simulation-based learning and VR allow students to engage in realistic scenarios without risk to real patients. Digital tools such as shared virtual workspaces and cloud-based platforms enable students to collaborate on projects regardless of their geographical location. Digital platforms such as Massive Open Online Courses (MOOCs) and online medical databases provide professionals with instant access to the latest research and clinical guidelines. This accessibility promotes continuous learning habits among medical practitioners, encouraging them to stay updated and adapt to evolving practices.</p
Assessing the impact of sewage and wastewater on antimicrobial resistance in nearshore Antarctic biofilms and sediments
No full textBackground: Despite being recognised as a global problem, our understanding of human-mediated antimicrobial resistance (AMR) spread to remote regions of the world is limited. Antarctica, often referred to as “the last great wilderness”, is experiencing increasing levels of human visitation through tourism and expansion of national scientific operations. Therefore, it is critical to assess the impact that these itinerant visitors have on the natural environment. This includes monitoring human-mediated AMR, particularly around population concentrations such as visitor sites and Antarctic research stations. This study takes a sequencing discovery-led approach to investigate levels and extent of AMR around the Rothera Research Station (operated by the UK) on the Antarctic Peninsula.Results: Amplicon sequencing of biofilms and sediments from the vicinity of Rothera Research Station revealed highly variable and diverse microbial communities. Analysis of AMR genes generated from long-reads Nanopore MinION sequencing showed similar site variability in both drug class and resistance mechanism. Thus, no site sampled was more or less diverse than the other, either in the biofilm or sediment samples. Levels of enteric bacteria in biofilm and sediment samples were low at all sites, even in biofilm samples taken from the station sewage treatment plant (STP). It would appear that incorporation of released enteric bacteria in wastewater into more established biofilms or associations with sediment was poor. This was likely due to the inactivation and vulnerability of these bacteria to the extreme environmental conditions in Antarctica.Conclusions: Our results suggest minimal effect of a strong feeder source (i.e. sewage effluent) on biofilm and sediment microbial community composition, with each site developing its unique niche community. The factors producing these niche communities need elucidation, alongside studies evaluating Antarctic microbial physiologies. Our data from cultivated bacteria show that they are highly resilient to different environmental conditions and are likely to thrive in a warmer world. Our data show that AMR in the Antarctic marine environment is far more complex than previously thought. Thus, more work is required to understand the true extent of the Antarctic microbiota biodiversity, their associated resistomes and the impact that human activities have on the Antarctic environment.</p
Sedation, temperature and pressure after cardiac arrest and resuscitation—the STEPCARE trial: a statistical analysis plan
No full textBackground: Basic management for patients who have suffered a cardiac arrest and are admitted to an intensive care unit (ICU) after resuscitation includes setting targets for blood pressure and managing sedation and temperature. However, optimal targets and management are unknown.Methods: The STEPCARE (Sedation, Temperature and Pressure after Cardiac Arrest and Resuscitation) trial is a multicenter, parallel‐group, randomized, factorial, superiority trial in which sedation, temperature, and blood pressure strategies will be studied in three separate comparisons (SED‐CARE, TEMP‐CARE, and MAP‐CARE). The trial population will be adults admitted to intensive care who are comatose after resuscitation from out‐of‐hospital cardiac arrest. The primary outcome will be all‐cause mortality, and the secondary outcomes will be poor functional outcome (modified Rankin Scale 4–6), Health‐Related Quality of Life using EQ‐VAS, and specific serious adverse events in the intensive care unit predefined for each trial. All outcomes will be assessed at 6 months after randomization. The prognosticators, outcome assessors, statisticians, data managers, steering group, and manuscript writers will be blinded to treatment allocation. This statistical analysis plan includes a comprehensive description of the statistical analyses, handling of missing data, and assessments of underlying statistical assumptions. Analyses will be conducted according to the intention‐to‐treat principle, that is, all randomized participants with available data will be included. The analyses will be performed independently by two statisticians following the present plan.Conclusion: This statistical analysis plan describes the statistical analyses for the STEPCARE trial in detail. The aim of this predefined statistical analysis plan is to minimize the risk of analysis bias.</p
Reactive hypoglycaemia at glucose tolerance test—another presentation of gestational diabetes: a multicentre retrospective study
No full textObjective: To assess obstetric outcomes in pregnant women with ‘reactive hypoglycaemia’ (RH) during an oral glucose tolerance test (OGTT), defined as a 2‐h blood glucose level lower than the fasting value.Design: Retrospective observational study. Setting: Two tertiary maternity units in the United Kingdom.Population: A total of 1498 women with singleton pregnancies attending for an OGTT between April 2019 and July 2020.Methods: Maternal and neonatal outcomes were compared between three groups: gestational diabetes, reactive hypoglycaemia and normal OGTT. Both logistic and linear regression models were used, which adjusted for maternal age at booking, ethnicity, parity and BMI.Main Outcome Measures: Abdominal circumference > 95th centile, polyhydramnios, gestational age at delivery, preterm birth, birthweight, neonatal hypoglycaemia, admission to neonatal unit, perinatal mortality.Results: Of the 1498 women, 26.7% (n = 400) had reactive hypoglycaemia, 27.8% (n = 417) GDM and 45.4% (n = 681) normal GTT. The reactive hypoglycaemia group were twice as likely to develop polyhydramnios compared with both the GDM (OR 2.77, 95% CI 1.40–5.50) and control groups (OR 2.47, 95% CI 1.31–4.65). Relative to those with GDM, women with reactive hypoglycaemia had a similar mean birthweight (mean difference 59.4 g, p = 0.06) but were less likely to experience neonatal hypoglycaemia (OR 0.30, 95% CI 0.001–0.15) or preterm birth (OR 0.33, 95% CI 0.18–0.60). No differences were found in maternal hypertensive disorders, abdominal circumference > 95th centile, shoulder dystocia, Apgar Conclusion: Women with reactive hypoglycaemia in this sample were at risk of adverse outcomes frequently associated with diabetes, including polyhydramnios.</p
Wearable devices as part of postoperative early warning score systems: a scoping review
No full textPostoperative deterioration is often preceded by abnormalities in vital parameters, but limited resources prevent their continuous monitoring in patients with no indication to ICU admission. The development of new technologies allowed the introduction of wearable devices (WDs), enabling the possibility of postoperative monitoring in surgical wards. We performed a Scoping Review to determine the current use of wearable devices as part of Continuous Remote Early Warning Score (CREWS) systems and their efficiency during postoperative period. This Scoping Review was conducted according to PRISMA-ScR guidelines. PICO framework was used before the search to define the review protocol. Systematic literature research has been performed on PubMed, MeSH, MEDLINE and Embase, considering a period between 2018 and February 2024. Prospective and retrospective studies involving patients undergoing cardiac and non-cardiac surgery are included. A total of 10 articles were included in the review. 11 different CE/FDA approved wearable devices were used in the studies analyzed. In all studies the WDs were applied the day of the surgery. The use of WDs as part of CREWS systems is feasible and safe. Furthermore, with the aid of other technologies (LoRa and Artificial Intelligence), they shorten Length of Stay (LOS) and reduce the number of ICU admissions with a reduction in healthcare costs. Continuous monitoring in surgical departments can facilitate the correct and timely identification of postoperative complications. This article is a starting point for the development of new protocols and for the application of these monitoring systems in clinical practice.</p
Nationwide trends in screen time and associated risk factors by family structures among adolescents, 2008-2022: nationwide cross-sectional study
No full textBackground: Although understanding long-term trends in adolescent screen time and the influence of family structure is essential, there is a lack of research addressing these issues comprehensively. Objective This study aimed to conduct comprehensive investigations into adolescent screen time before and during the COVID-19 pandemic, with a particular focus on family structures. Methods: This study used nationwide, large-scale data from the Korea Youth Risk Behavior Web-Based Survey from South Korea. We aimed to indicate the changes in adolescent screen time over 15 years from 2008 to 2022. Weighted linear regression was used to analyze annual trends in screen time before and during the pandemic, and stratified analyses were conducted to examine associated risk factors across different family structures. Results: This study used data from a total of 836,972 individuals (n=403,456, 48.2% women), with an age range of 12-18 years. The analysis revealed an overall increase in screen time prepandemic (β=8.06, 95% CI 7.74-8.39), with a notable increase observed at the onset of the pandemic (β=162.06, 95% CI 159.49-164.64). Among diverse family structures, the orphanage group showed the most substantial increase in screen time during the pandemic (βdiff=221.90, 95% CI 159.62-284.17). Risk factors associated with screen time during the pandemic varied by family structure. Notably, the nuclear family group presented distinct screen time–related risk factors, including grade, region of residence, physical activity frequency, sadness and despair, and the highest education level of parents. Conclusions: There has been a notable increase in average screen time among adolescents since the onset of the pandemic, with the orphanage group exhibiting a pronounced trend. The risk factors associated with screen time during the pandemic varied for each family structure. Findings from this study suggest that the implementation of individualized measures tailored to each family structure should be adopted to effectively address the increased issue of adolescent screen time since the pandemic.</p
Data sources:
Access Repository Dashboard
Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇