Background: Necrotizing enterocolitis (NEC) is one of the leading causes of death in newborns, however, little is understood of which patients can be treated medically or require surgery. The purpose of our study is to analyze the associated factors of surgically treated patients compared to patients requiring only medical treatment. Methods: Patients diagnosed with necrotizing enterocolitis over a period of 14 years in a single children’s hospital were retrospectively enrolled. Demographics and clinical data patients were collected and analyzed. Results: A total of 189 patients with NEC were included. Surgically treated patients had a lower gestational age (P = .018), body weight at birth (P = .034), and percentage of exclusive breast milk feeding (P= .001). They had increased comorbidity with respiratory distress syndrome (RDS) (P = .005), number of days of antibiotic use (P = .014), and length of hospital stay (P = .000). In multivariate logistic analysis, a lower percentage of exclusive breast milk feeding (OR = 0.366, 95% CI: 0.164-0.817) and a longer hospital stay (OR = 1.010, 95% CI: 1.001- 1.019) was associated with surgical NEC. Conclusion: Comparing medical and surgical NEC, a significantly lower percentage of surgical NEC patients were exclusively fed breast milk and their hospital stays were longer.

Five years after the introduction of the Prescribing Safety Assessment (PSA) in the UK, the role pharmacists play to help prepare medical students for this challenge is uncertain. Our study explored pharmacists’ perceptions about their role in undergraduate medical training for the Prescribing Safety Assessment (PSA). Study participants were emailed a qualitative questionnaire aimed at ascertaining their current involvement in undergraduate medical education, particularly the preparation for PSA. Responses received were thematically-analysed. A total of 27 UK hospital pharmacists and 3 pharmacists from local education and training boards completed the questionnaire. Pharmacists were positive about their involvement in medical student training, recognising the added value they could provide in prescribing practice. However, respondents expressed concerns in relation to resource availability and the need for formal educational practice mentoring. This research highlights the potential value of pharmacists’ input into medical education and the need for a discussion on strategies to expand this role to maximise the benefit from pharmacist skill mix in teaching safe prescribing.

Background: In France, no previous studies had addressed the acquisition of multidrug resistant (MDR) bacteria and colistin resistance genes by medical students when undertaking internships abroad. Methods: Nasopharyngeal, rectal, and vaginal swabs samples were collected from 382 French medical students before and after travel to investigate the acquisition of MDR bacteria. The bacterial diversity in the samples was assessed by culture on selective media. We also genetically characterised the isolates of MDR bacteria including Extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-E), methicillin-resistant Staphylococcus aureus (MRSA), and Carbapenemase-producing Enterobacteriacae (CPE) using the real-time polymerase chain reaction method. The samples were collected from 293 students and were investigated for mcr colistin-resistance genes using RT-PCR directly on the samples, followed by conventional PCR and sequencing. Results: A proportion of 29.3% of the participants had acquired ESBL-E and 2.6% had acquired CPE. The most common species and ESBL-E encoding gene were Escherichia coli (98.4%) and bla_CTX-M-A (95.3%), respectively. A proportion of 6.8% of the participants had acquired mcr-1 genes, followed by mcr-3 (0.3%) and mcr-8 (0.3%). We found that taking part in humanitarian missions to orphanages, being in contact with children during travel, the primary destination of travel being Vietnam and north India, using antibiotics during travel, and studying in 2017 were associated with the acquisition of ESBL-E. When the primary destination of travel was Vietnam and the year of study was 2018, this was associated with acquisition of colistin resistance genes. Conclusion: Medical students are at a potential risk of acquiring ESBL-E, CPE and colistin resistance genes. A number of risk factors have been identified, which may be used to develop targeted preventive measures.

There are four categories of medical waste that cannot be mixed as this will cause serious problems such as environmental pollution or infection. In the past, the classification of medical waste often involved a lot of human and material resources to process, with workers at risk of exposure to infectious substances. Therefore, an augmented reality (AR) and artificial intelligence (AI) medical waste classification system and method were developed. This innovative medical waste classification system and method combines AR and AI identification technology to reduce the risk of manual judgment errors by clinical staff when handling medical waste.

Background: Role-playing is often used as a pedagogical method for learning communication in medical education. Therefore, medical play using the Teddy Bear Hospital (TBH) is a concept that can quickly familiarize children with health care and help them develop positive experiences in these areas. This review aims to assess the strengths of TBH, as a form of directed medical role play, in improving health outcomes and well-being in children, along with implanting an awareness of preventive health care in young children.Methods: For this scoping review, we examined the list of recommendations, including 11 studies from two databases, PubMed and Google Scholar. We incorporated pre/post quasi-experimental studies, ANOVA, qualitative research studies, systematic reviews, and control group studies that deliberately utilize the teddy bear hospital as an intervention.Results: The results of individual studies were further categorized into three sections. The first being upon the analysis of 11 studies, the Teddy Bear Hospital was mainly conducted in Europe and Asia. It is evident that regardless of the different approaches and strategies used to implement the Teddy Bear Hospital, they all ultimately share the same intent: to raise health care awareness and alleviate young children's anxiety over medical treatment while focusing on the promotion of positive healthy lifestyle. All studies portray the teddy bear hospital as an intervention of medical roleplay which analyzed the children's feelings, behaviors, and health awareness after visiting the Teddy Bear Hospital.Conclusion: The application of the teddy bear hospital has overwhelmingly positive results, with lower levels of anxiety and improved health knowledge. Its reported efficacy calls for future studies on aspects that lead to its efficacy and potential effectiveness.

Background: Since the advent of virtual reality (VR), it has been used in medical education for surgical training and anatomy teaching. Recently, other modalities of extended reality (XR) such as augmented reality (AR) and mixed reality (MR) has also made its way into medical education. Although there has been research validating XR’s use in medical education, there have been few studies on the research trends of the different XR modalities. The paper aims to compare the research trends of the XR modalities in general and in terms of the medical fields studied and outcomes measured. Methods: Web of Science was searched, and preliminary data was extracted to analyze the general trend. Inclusion and exclusion criteria were then applied, and finalized articles were analyzed and grouped based on the medical field studied and outcomes measured. Results: 31 articles on VR, eight on AR and one on MR were included in the final analysis. We found that there is increasing research in VR since 1990 and AR since 2008. The research in MR is constant. Most of the papers on VR studied endoscopic surgery and anatomy whereas AR studied mostly anatomy and endovascular procedures. Using Miller’s prism of clinical competence, the competency measured most for VR and AR is “show”. Discussion and conclusion: Advancement in computing, communication and display technologies since 1990 may contribute to the increase in research on VR whereas the ubiquity of smartphone since 2008 may explain the increase in research on AR. Although both VR and AR are used in surgical training and anatomy teaching, we found possible strengths of VR in counseling and AR in practical skills. The competency "show" was measured most as most of the papers were on surgery, and the XR simulators used can capture surgical parameters

This study examines demographic factors which may influence opinions concerning medical students’ self-care and substance use behaviors as a means of providing insights into how future doctors view these issues compared to Australian doctors and members of the public. We conducted national, multicenter, prospective, on-line cross-sectional surveys using hypothetical scenarios to three cohorts- Australian medical students, medical doctors, and the public. Participants’ responses were compared for the different contextual variables within the scenarios and the participants’ demographic characteristics. In total 2,602 medical students, 809 doctors and 503 members of the public participated. Compared with doctors and the public, medical students were least tolerant of alcohol intoxication, and most tolerant of using stimulants to assist with study, and cannabis for anxiety. Doctor respondents more often aligned with the public’s opinions on the acceptability of the medical students’ behaviors. Although opinions are not equivalent to behaviour, Australian students’ views on the acceptability for cannabis to help manage anxiety, and inappropriate use of prescription-only drugs are concerning; these future doctors will be responsible for prescribing drugs and managing patients with substance abuse problems. However, if current Australian medical student’s opinions on alcohol misuse persist, one of the commonest substance addictions amongst doctors may decrease in future.

The article reports on a patient who required a cranial protection system.Using additive manufacturing techniques and surgical planning with the help of bio-models, a patient-specific bone implant solution was proposed that allows aesthetic restoration of the affected area and provides an adequate level of protection. In addition, through a comparative analysis with finite elements, the mechanical response to external actions of the medical device, printed with two materials: polymethylmethacrylate (PMMA) and polyether-ether-ketone (PEEK), is simulated. The tested materials have recognized biocompatibility properties, but their costs on the market differ significantly. The results obtained demonstrate the similarities in the responses of both materials. It offers the possibility that low-income people can access these devices, guaranteeing adequate biomechanical safety, considering that PMMA is a much cheaper material than PEEK.

Thermal sterilization is generally avoided for 3-D printed components because of the relatively low deformation temperatures for common thermoplastics used for material extrusion-based additive manufacturing. 3-D printing materials required for high-temperature heat sterilizable components for COVID-19 and other applications demands 3-D printers with heated beds, hot ends that can reach higher temperatures than polytetrafluoroethylene (PTFE) hot ends and heated chambers to avoid part warping and delamination. There are several high temperature printers on the market, but their high costs make them inaccessible for full home-based distributed manufacturing required during pandemic lockdowns. To allow for all these requirements to be met for under $1,000, the Cerberus – an open source three-headed self-replicating rapid prototyper (RepRap) was designed and tested with the following capabilities: i) 200^oC-capable heated bed, ii) 500^oC-capabel hot end, iii) isolated heated chamber with 1kW space heater core and iv) mains voltage chamber and bed heating for rapid start. The Cereberus successfully prints polyetherketoneketone (PEKK) and polyetherimide (PEI, ULTEM) with tensile strengths of 77.5 and 80.5 MPa, respectively. As a case study, open source face masks were 3-D printed in PEKK and shown not to warp upon widely home-accessible oven-based sterilization.

Violence against paramedics has been described as a ‘serious public health problem’ but one that remains ‘vastly underreported’, owing to an organizational culture that stigmatizes reporting – hindering efforts at risk mitigation in addition to creating a gap in research. Leveraging a novel reporting process developed after extensive stakeholder consultation and embedded within the electronic patient care record, our objective was to provide a descriptive profile of violence against paramedics in a single paramedic service in Ontario, Canada. Between February 1, 2021, through January 31, 2023, a total of 374 paramedics in Peel Region (48% of the workforce) generated 941 violence reports, of which 40% documented physical (n=364) or sexual (n=19) assault. The violence was typically perpetrated by patients (78%) and primarily took place at the scene of the 9-1-1 call (47%); however, violent behavior frequently persisted or recurred while in transit to hospital and after arrival. Collectively, mental health, alcohol, or drug use were listed as contributing circumstances in 83% of violence reports. In all, 81 paramedics were physically harmed because of an assault. On average, our data correspond to a paramedic filing a violence report every 18 hours, being physically assaulted every 46 hours, and injured every 9 days.

COPD is currently the fourth leading cause of death in the world. Globally, due to continued exposure to COPD risk factors and an aging population, the burden of COPD is expected to increase in the coming decades. The BODE (body mass index, airflow obstruction, dyspnea, and exercise capacity) index is a practical and multidimensional predictor for prognosis of COPD, and better than FEV1.We used the database of Kaohsiung Chang Gung Memorial Hospital medical center, Taiwan to analyze the correlation between BODE index, healthcare resource utilization, and Charlson comorbidity index (CCI). This retrospective study to collect COPD patients with complete BODE index data who had undergone a 6-minute walk examination in our hospital from January 2015 to December 2016. The medical cost and comorbidities database were analyzed from January 1, 2015, to August 31, 2017. Of 396 patients, 382 (96.5%) were male, with an average age of 71.3 ± 8.4 years. There was a significant association between the BODE index and the CCI of COPD patients (p < 0.001). Healthcare resource utilization was positively correlated with the BODE index during the 32 months of retrospective clinical outcomes: positively correlated with the number of hospitalizations (p<0.001), hospitalization days (p<0.001), hospitalization expenses (p=0.005), and total medical expenses (p=0.024), respectively. Our findings provide the crucial information for clinician to predict medical burden and comorbidities in patients with COPD by using BODE index.

The health equipment are used to keep track of significant health indicators, automate health interventions, and analyze health indicators. People have begun using mobile applications to track health characteristics and medical demands because all devices are linked to high-speed internet and phones. Such a combination of smart devices, the internet, and mobile applications expands the usage of remote health monitoring through the Internet of Medical Things (IoMT). The accessibility and unpredictable aspects of IoMT create massive security and confidentiality threats in IoMT systems. In this proposed paper - Octopus, Physically Unclonable Functions (PUFs) have been used to provide privacy to the healthcare device by masking the data, and machine learning (ML) technique is used to retrieve the health data back and for reducing security breaches on networks. This technique has exhibited 99.45% accuracy, which proves that this technique could be used to secure health data with masking.

The contemporary landscape of eHealth is characterized by major concerns related to electronic medical records (EMRs). In an EMR, critical patient health information gets its own repository, which is the core of the eHealth system. Notably, the EMR not only retrieves health information generated in ambulatory clinical settings but also includes court-generated records. These overlapping records assume the role of a foundational data source for a comprehensive electronic health record (EHR). This scholarly review sheds light on recent trends in medical records and associated challenges, while at the same time providing insights into Saudi Arabia’s targeted approaches to healthcare delivery. Additionally, the talk expands to include a description of blockchain technology and its underlying conceptual framework. This demonstration positions blockchain technology as a promising approach that requires consideration for future use in the healthcare system.

Diffuse optical tomography (DOT) is an optical medical imaging method that can assess the structural properties of tissues and their functional characteristics, such as hemoglobin concentration, water content, as well as lipid concentration, via three-dimensional image reconstruction. This paper presents the theoretical basis and working principle of diffuse optical tomography. The paper explains how the optical properties of tissue can be imaged by photon migration techniques based on diffusion theory. The author presents the reasoning for near-infrared (NIR) imaging as the most effective technique in terms of quantitative recovery of spectroscopic optical parameters. This work also listed various advantages, applications, and challenges of DOT. The paper also briefly discusses current progress in near-infrared medical imaging and its future direction.

The disease COVID-19 is brought on by the acute respiratory syndrome coronavirus 2 (SARS-CoV-2) First appeared in China in December 2019 and quickly spread around the world after being declared a worldwide pandemic by the World Health Organization in March 2020. COVID-19, Medical Laboratory Professionals, SARS-COV-2, Diagnostic, Importance and difficulties for testing were the selected terms to search the databases of PubMed and Google Scholar for previously published material. Many diagnostic tests are applied in corona virus detection like Droplet Digital PCR (ddPCR), Multiplex PCR, Loop-mediated Isothermal Amplification (LAMP) and more. There is a lack of availability of molecular and serologic tests that have been clinically validated or authorized by national or international regulatory bodies. Clinical laboratory experts are tackling threats to our global defense and wellness, including infectious diseases. The opportunity to express gratitude to the unsung medical laboratory heroes and COVID0-19 pandemic allies is now greater than ever. Each year, Medical Laboratory Professionals Week should honors those who contribute key diagnostic data that help save lives. This review article explore overall summary on testing methods including Important and Difficult Tasks for Medical Laboratories which will provide good message for better public health matter.

IntroductionThe use of protective masks, especially medical masks, increased dramatically during the COVID-19 crisis. Medical masks are made of synthetic materials, mainly polypropylene, and a majority of them are produced in China and imported to the European market. The urgency of the need has so far prevailed over environmental considerations.ObjectiveAssess the environmental impact of different strategies for the use of facemaskMethod Different strategies for the use of medical and community masks are being investigated for their environmental impact in this study. 8 scenarios, differentiating the typologies of masks and the modes of reuse are compared using several environmental impact indicators, mainly the Global Warming Potential (GWP100), and the plastic leakage (PL). This study attempts to provide clear recommendations that consider both the environmental impact and the protective effectiveness of face masks used in the community.Results The environmental impact of single-use masks is the most unfavorable, with a GWP of 0.4 -1.3 kgCO₂ eq., depending on the transport scenario, and a PL of 1.8 g, for a one month protection against COVID-19. The use of home-made cotton masks and prolonged use of medical masks through wait-and-reuse are the scenarios with the lowest impact.ConclusionThe use of medical masks with a wait and reuse strategy seems to be the most appropriate when considering both environmental impact and effectiveness. Our results also highlight the need to develop procedures and the legal/operational framework to extend the use of protective equipment during a pandemic.

During the pandemic, nurses experienced anger that stemmed from a sense of threat, frustration or even a sense of injustice. The purpose of this study was to examine the relationship between vaccination hesitancy, anger, cynicism and medical mistrust among nurses, as there are no relevant studies in the literature. The study was conducted online by completing self-report questionnaires. The Dimensions of Anger Reactions-5, the 8-item "Cynical Distrust" scale and the Medical Mistrust Multiformat Scale were used. For vaccination hesitancy, two questions with a 5-point scale were used; one question examining hesitancy to get vaccinated with the COVID-19 vaccine, and another question examining hesitancy to get vaccinated with the influenza vaccine. 387 nurses (66 men and 321 women) participated in the study. Nurses showed statistically greater hesitancy for the COVID-19 vaccine compared to hesitancy for the influenza vaccine. The variation in Vaccine Hesitancy was explained by the scores in the Medical Mistrust Multiformat Scale, the Dimensions of Anger Reactions and the Cynical Distrust Scale. The Medical Mistrust Multiformat Scale mediated the relationship between Cynical Distrust Scale and Total Vaccine Hesitancy. The Dimensions of Anger Reactions Scale significantly moderated the indirect effect of Cynical Distrust Scale on Total Vaccine Hesitancy through the Medical Mistrust Multiformat Scale. In conclusion, it is highly likely that anger is involved in reported vaccine hesitancy both by activating schemas of distrust in others and by adopting antisystemic views of mistrust in the medical system.

This paper aims to implement histogram pyramids with marching cubes method for 3D medical volumetric rendering. The histogram pyramids are used for feature extraction by segmenting the image into the hierarchical order like the pyramid shape. The histogram pyramids can decrease the number of sparse matrixes that will occur during voxel manipulation. The important feature of the histogram pyramids is the direction of segments in the image. This feature will be then used for connecting pixels (2D) to form up voxel (3D) during marching cubes implementation. The proposed method is fast and easy to implement and it also produces a smooth result (compared to the traditional marching cubes technique). The experimental results show that time consuming for generating 3D model can be reduced by 15.59% in average. The paper also shows the comparison between the surface rendering using the traditional marching cubes and the marching cubes with histogram pyramids. Therefore, for the volumetric rendering such as 3D medical models and terrains where a large number of lookups in 3D grids are performed, this method is a particularly good choice for generating the smooth surface of 3D object.

Suboptimal knowledge of clinical pharmacology, therapeutics, and toxicology (CPT) and poor-quality prescribing are threats to patient safety. Our previous national survey of medical faculty identified limited confidence in medical student graduates’ ability to prescribe safely and an interest in a national prescribing competence assessment. Given the in-person challenges posed by the restrictions related to the COVID-19 pandemic, we aimed to re-evaluate opinions and gauge interest in e-learning resources and assessments. Using public sources, a sampling frame of medical school leaders from all 17 Canadian medical schools, including deans, vice-deans, and program directors for clerkship, residency, and e-learning, were invited to participate in a cross-sectional survey. Survey questions were finalized after several rounds of testing and analyses were descriptive.Of 1448 invitations, 411 (28.4%) individuals reviewed the survey, and among them, 278 (67.6%) completed at least one survey question with representation from all schools. While more than 90% of respondents agreed that medical students should meet a minimum standard of prescribing competence, only 17 (7.9%) could vouch for their school meeting objectives in CPT and many had significant concerns about their own or other schools’ recent graduate prescribing abilities. Given the lack of local CPT eCurricula resources, there was strong interest in a national online course and assessment in CPT. Our national survey results suggest an ongoing inadequacy of medical trainees’ prescribing competence and provide a strong endorsement for both a national online CPT course and assessment during medical school.

Introduction: At the end of 2019 the Covid-19 pandemic caused a huge amount of restrictions across the world which affected teaching around the world as it was not prepared to move from traditional face-to-face to an online conversion overnight, so the aim of this paper is to determine the changes in undergraduate anatomy teaching strategies post-pandemic compared to pre-pandemic. Methods: A systematic review was conducted based on the PRISMA statement. Data were retrieved from the searches conducted in the different databases, and the articles to be retrieved were selected with the help of the Rayyan platform. Using the OPMER and JBI tools, the quality of evidence was assessed for the selection of the articles included in the review. Results: The teaching of medicine, specifically anatomy, presented serious problems due to the fact that throughout history it has been taught in the classroom by means of cadaveric dissection and when this ceased to be available, new methods arose through the use of digital resources to try to make up for the needs of the lack of dissection laboratories which lost a great deal of content in this restructuring, which have been improving with the passing of the courses taught and the development of new material that has been better adapted to the needs of the students. Discussion: The authors agree that in the future the best way to teach anatomy will continue to be face-to-face dissection without neglecting the strategies developed during this pandemic and to be taken if necessary to restructure curricula in the future to improve teaching.

Spinal deformity refers to a range of disorders that are defined by anomalous curvature of the spine and may be classified as scoliosis, lordosis, or kyphosis. Among these, scoliosis stands out as the most common type of spinal deformity in human beings, and it can be distinguished by abnormal lateral spine curvature accompanied by axial rotation. Accurate identification of spinal deformity is crucial for a person's diagnosis, and numerous assessment methods have been developed by researchers. Therefore, the present study aims to systematically review recent works on spinal deformity as-assessment for scoliosis diagnosis, utilizing image processing techniques. To gather relevant studies, a search strategy was conducted on three electronic databases (Scopus, ScienceDirect, and PubMed) between 2012 and 2022, using specific keywords and focusing on scoliosis cases. A total of 17 papers fully satisfied the established criteria and were extensively evaluated. Despite variations in methodological designs across the studies, all reviewed articles obtained quality ratings higher than satisfactory. Various diagnostic approaches have been employed, including artificial intelligence mechanisms, image processing, and scoliosis diagnosis systems. These approaches have the potential to save time and, more significantly, can reduce the incidence of human error. While all assessment methods have potential in scoliosis diagnosis, they possess several limitations that can be ameliorated in forthcoming studies. Therefore, the findings of this study may serve as guidelines for the development of a more accurate spinal deformity assessment method that can aid medical personnel in the real diagnosis of scoliosis.

Fractures of the talar neck and body are associated with spine fractures and scoliosis deformity, which affect cosmetic appearance and cause difficulty in ambulation. The implant design for talus surgery is thriving as a functional alternative in case of severe talar destruction, focusing on segmentation and reconstruction of the talus’s shape. However, manual segmentation of the talus is time-consuming and subjective. In this study we exploited the automatic segmentation framework to efficiently train a deep learning-based model to accurately segment the talus based on computed tomography imaging. We developed three model configurations with nnU-Net and investigated their Dice similarity coefficients (DSC) and 95% Hausdorff distances (HD95) for talus segmentation on a CT image dataset. The three configurations performed well (DSC > 0.95, HD95 < 0.6). When tested on the same samples, one of the configurations was more efficient while ensuring higher accuracy. We propose to focus on talus anatomic variations with increasing age based on this framework and apply it to clinical trials at the next stage.

Introduction. Covid-19 faced the world with serious health and socioeconomic issues. At the very beginning of the pandemics, the vaccine was considered by health authorities and the medical community the only way to curb the spread of the virus. One of the measures that have been proposed to increase vaccinations was the mandatory policy. The purpose of this study was to compare determinants of voluntary and mandatory vaccination among students of Albanian University. Methodology: This cross-sectional study by means of an online survey, was conducted among students enrolled in the private University “Albanian University”, Tirana, Albania during the last week of winter semester 7-14 Feb 2022. Results: 878 students participated in this study, among them 612 (69.7%) were females, 266 (30%) were males. 506 (57%) of the participants were enrolled in Medical Sciences (MS), 372(42.3%) were Non-Medical Science (Non-MS) group. 773 (88%) was vaccinated against Covid-19, 105 (11.8%) were not vaccinated. 466 (53%) reported voluntary vaccination, 412 (46.9%) reported mandatory vaccination. Among students that vaccinated voluntary 266 (57%) were from MS group, 200(42.9%) from Non-MS group. 237(57.5%) of students in mandatory vaccination group were from MS group, 175 (42.4%) from Non-MS. Conlusion. Vaccine safety and efficacy were hindering factors of vaccination. Also, based on the results of this study, the students felt encouraged to vaccinate by the academic staff. This clearly demonstrates that the staff does not lack the skills to enhance stu-dents' knowledge about the risk of infectious diseases and the importance of vaccination. Therefore, to influence as much as possible students’ attitude toward vaccination, comprehensive educational programs including modification of existing curricula should be considered.

Innovation development in healthcare has paved the path towards the improvement in system efficiency, patient care and cost-effective healthcare services, increasing the overall efficiency of the healthcare system in a significant manner. Electronic medical record system has fostered interoperability and collaboration in healthcare departments by enabling different systems to exchange and use patient data. This trend has been accelerated dominantly by the pandemic, leading to increased use of telemedicine, referring specifically to the use of electronic communication to provide healthcare services remotely. Moreover, an increased prevalence towards the use of artificial intelligence and machine learning in healthcare has contributed effectively towards the rigorous and informed analysis of large amounts of data as well as to identify patterns or trends that may be useful for improving care delivery or identifying potential issues. A unified electronic medical record System that will generate competitive opportunities and success prospects with reference to enhanced interoperability in US healthcare departments, can contribute towards the improvement in the quality and efficiency of care by making it easier for healthcare providers to access and share patient information as well as reducing the risk of errors in effective patient care.

During the creation and integration of a health care system based on medical knowledge graphs, it is necessary to review and select the vocabularies and definitions that best fit the information requirements of the system being developed. This implies the reuse of medical knowledge graphs; however, full importation of knowledge graphs is not a tractable solution in terms of memory requirements. In this paper we present a modularization-based method for knowledge graph reuse. A case study of graph reuse is presented by transforming the original model into a lighter one.

Convolutional neural network architectures have become increasingly complex, which has improved the performance slowly on well-known benchmark datasets in the recent years. In this research, we have analyzed the true need for such complexity. We have introduced G-Net light, a lightweight modified GoogleNet with improved filter count per layer to reduce feature overlaps and complexity. Additionally, by limiting the amount of pooling layers in the proposed architecture, we have exploited the skip connections to minimize the spatial information loss. The investigations on the proposed architecture are evaluated on three retinal vessel segmentation publicly available datasets. The proposed G-Net light outperforms other vessel segmentation architectures by reducing the number of trainable parameters..

The success of total hip arthroplasty depends on the experience of the surgeon, and one of the ways the surgeon currently determines the final implant insertion depth is to listen to the change in audible pitch of the hammering sound. We investigated the use of acoustic vibration emissions as a novel method for insertion quality assessment. A non-invasive contact microphone-based measurement system for insertion depth estimation, fixation and fracture detection was developed using a simplified in vitro bone/implant (n=5). 2583 audio recordings were analysed in vitro to obtain energy spectral density functions. Out of the four main resonant peaks under in vitro conditions, broach insertion depth statistically correlates to increasing 3rd and 4th peak frequencies. Degree of fixation was also observed as higher goodness of fit (0.26-0.78 vs. 0.12-0.51 between two broach sizes, the latter undersized). Finally, however, the moment of fracture could not be predicted. A cadaver in situ pilot study suggests comparable resonant frequencies in the same order of magnitudes with the bone model. Further understanding of the signal patterns are needed for an early warning system diagnostic system for imminent fractures, bone damage, improving accuracy and quality of future procedures.

CVDs are a leading cause of death globally. In CVDs, the heart is unable to deliver enough blood to other body regions. Since effective and accurate diagnosis of CVDs is essential for CVD prevention and treatment, machine learning (ML) techniques can be effectively and reliably used to discern patients suffering from a CVD from those who do not suffer from any heart condition. Namely, machine learning algorithms (MLAs) play a key role in the diagnosis of CVDs through predictive models that allow us to identify the main risks factors influencing CVD development. In this study, we analyze the performance of ten MLAs on two datasets for CVD prediction and two for CVD diagnosis. Algorithm performance is analyzed on top-two and top-four dataset attributes/features with respect to five performance metrics –accuracy, precision, recall, f1-score, and roc-auc – using the train-test split technique and k-fold cross-validation. Our study identifies the top two and four attributes from each CVD diagnosis/prediction dataset. As our main findings, the ten MLAs exhibited appropriate diagnosis and predictive performance; hence, they can be successfully implemented for improving current CVD diagnosis efforts and help patients around the world, especially in regions where medical staff is lacking.

Introduction: Travel-based continuing medical education (CME) has become a popular format for physicians looking to combine education with travel. Emergency Medicine Update Europe is a biennial accredited CME program combining high quality Emergency Medicine education with structured group activities including cycling, hiking and social activities. This unique design incorporates innovative educational practices but as a whole has not yet been evaluated. Methods: This was a participant observation-based, ethnographic-style case study of the Emergency Medicine Update Europe conference in Provence, France in 2015. Participant interviews and embedded observation methods were used to collect data. Data was then analyzed using thematic content analysis techniques. Results: We describe three phenomena from the data that we feel are highly influential in the success of the program and impact on learning. These include “social engagement and a sense of community”; “the value of a stimulating escape” and “the ‘flat’ faculty-learner relationships”. Discussion: These unique features, prioritized by participants, seem to be key to the apparent success of this model over more traditional CME approaches. To our knowledge this is the first empirical research in this area and improves our understanding of how to leverage these more sociologic components for more effective continuing medical education.

For decades, sepsis research has been motivated by the idea of a dangerous overreaction of the immune system in sepsis. But is it true that the response to sepsis is dysregulated? This review surveys the history of sepsis trials and found that evidence for dysregulation does not exist in many of the physiologic mechanisms of sepsis. It is time to consider the alternative hypothesis, that sepsis traits are often functional, and do more harm than good. This review discusses the implications of this perspective for the future of sepsis research

In the last decades bioresorbable and biodegradable polymers have gained a very good reputation both in research and in industry thanks to their unique characteristics. They are, indeed, able to ensure high performances and biocompatibility, at the same time avoiding post-healing surgical interventions for devices removal. In the medical device industrial use of such biopolymers, it is widely known that product formulation and manufacturing need to follow specific procedures in order to ensure both proper mechanical properties and desired degradation profile. Moreover, also the sterilization method is crucial and its impact on physical properties is generally underestimated. In this work we focused our attention on the effect of different terminal sterilization methods on two commercially available poly(L-lactide-co-ε-caprolactone) with equivalent chemical composition (70% PLA and 30% PCL) and relatively similar initial molecular weight, but different chains arrangement and crystallinity. Results obtained show that crystallinity plays a key role, helping in preserving the narrow distribution of chains and, as a consequence, defined physical properties. These statements can be used as guidelines for a better choice of the most adequate biodegradable polymers in the production of resorbable medical devices.

Machine learning (ML) offers potential opportunities to enhance the learning, teaching and assessments within veterinary medical education including but not limited to assisting with admissions processes as well as student progress evaluations. The purpose of this primer is to assist veterinary educators in appraising and potentially adopting these rapid upcoming advances in data science and technology. In the first section, we introduce ML concepts and highlight similarities/differences between ML and classical statistics. In the second section, we provide a step-by-step worked example using simulated veterinary student data to answer a hypothesis driven question. Python syntax with explanations is provided within the text to create a random forest ML prediction model and within each step, specific considerations such as how to manage incomplete student records are highlighted when applying ML algorithms within the veterinary education field. The results from the simulated data demonstrate how decisions by the veterinary educator during ML model creation may impact the most important features contributing to the model. These results highlight the need for the veterinary educator to be fully transparent during the creation of ML models and future research is needed to establish guidelines for handling data not missing at random in medical education, and preferred methods for model evaluation.

In this paper we introduce the concept of Nano Beta Closure, Nano Beta Interior and study the relationship between them also study some of their properties. Based on these notions we introduced the topological Approach to Decision Making and Its Application in the Medical Field" which describes the use of topological methods in decision-making, specifically through the utilization of nano beta closure and nano beta interior. These mathematical tools are applied in the medical field to improve diagnostic accuracy and aid in treatment planning. The authors demonstrate the effectiveness of this approach through a case study on the diagnosis of Chronic Kidney. The results show that the topological approach using nano beta closure and nano beta interior provides a reliable and accurate method for medical decision-making. Finally, we introduce a medical application for disease groups patients of with chronic kidney. To identify the main causative agent of kidney disease. where using this approach, the medical team can identify the specific areas of the kidney that are affected by the infection, as well as the extent of damage and any potential complications. This information is used to create an individualized treatment strategy that is customized to meet the specific requirements of the patient. and medical history. We write an algorithm that can be a helpful tool for doctors to utilize in diagnosing infection disease Chronic Kidney infections. By utilizing this approach, clinicians can provide accurate diagnoses, develop effective treatment plans, and ultimately improve patient outcomes. finally, we show that fractals hold significant importance in future nano topological generation of the human factor. Their unique properties and self-similar patterns offer insights into the complex organization of biological systems and provide a foundation for designing advanced Nanosystems.

Cross-institutional secondary use of medical data benefits from structured semantic annotation, which, ideally, enables matching and merging semantically related data items from different sources and sites. While numerous medical terminologies and ontologies, as well as some tooling, exist to support such annotation, cross-institutional data usage based on independently annotated datasets is challenging for multiple reasons: the annotation process is resource intensive and requires a combination of medical and technical expertise since it often requires judgment calls to resolve ambiguities resulting from non-uniqueness of potential mappings to various levels of ontological hierarchies and relational and representational systems. Divergent resolution of such ambiguities can inhibit joint cross-institutional data usage based on semantic annotation since data items with related content from different sites will not be identifiable based on their respective annotations if different choices were made without further steps such as ontological inference, which is still an active area of research. We hypothesize that a collaborative approach to semantic annotation of medical data can contribute to more resource efficient and high-quality annotation by utilizing prior annotational choices of others to inform the annotation process, thus both speeding up the annotation itself and fostering a consensus approach to resolving annotational ambiguities by enabling annotators to discover and follow pre-existing annotational choices. Therefore, we have implemented a prototypical Collaborative Annotation Tool (CoAT), evaluated its usability, and present first inter-institutional experiences with this novel approach to promoting practically relevant interoperability driven by use of standardized ontologies.

Background: Serious games are conceptualized as a broad topic and overlap segments of more modern forms of education: e-learning, edutainment, game-based learning, and digital game-based learning. Serious Games aligns with digitalization and the modern era and creates novel opportunities for learning and assessment in medical education. Escape rooms, a type of serious games, merge mental and physical aspects to reinforce critical skills useful in daily life. It challenges logic and reasoning and demands careful analysis of situations to correlate and solve different stages of the escape room under pressurized, timed conditions. Furthermore, it serves as an adequate environment to build problem-solving skills, communication skills, and leadership skills through the collaboration of people to achieve a common goal. The aim of this study was to investigate the applications of escape rooms in Medical Education. Method: This study investigated the applications of escape rooms in medical education. Serious games are expanding in education and have attained great relevance due to their intriguing and intrinsically motivating attributes. Within serious games, we focused on escape rooms in which participants are locked in a room, faced with puzzles that must be solved to ‘escape the room’. Compiling the data from the first 100 hits of medical application of escape rooms, we found 72 cases and categorized them by year, specialty, participants structure, simulation experience, and design. Results: We reported on escape rooms in medical education by the year in which they were reported, the medical specialty, the participant structure, grouped or individual, the experience design; real, hybrid, or digital, and the modality of the delivery. 72% of the escape rooms focused on four main areas: nursing education (25.0%), emergency medicine (22.2%), pharmacy (12.5%), and interprofessional education (12.5%). Most of the escape rooms had a group-based physical design and little attention was given to provide a detailed description of the design considerations, such as the pathway type (linear, semi-linear, open). Conclusion: Escape rooms are applied in a wide range of medical education areas. In Medical Education, group-based on-site escape rooms with a focus on nursing, emergency medicine, pharmacy and interprofessional education dominates the implementation landscape. To further advance the field, stronger emphasis on making explicit the design considerations will advance the research and inform implementations.

Historically, admission of hematological patients in the ICU shortly after the start of a critical illness is associated with better survival rates. Early intensive interventions administered by MET could have a role in the management of hematological critically ill patients, eventually reducing ICU admission rate. In this retrospective and monocentric study, we evaluate the safety and effectiveness of intensive treatments administered by the MET in a medical ward frame. The administered interventions were mainly helmet CPAP and pharmacological cardiovascular support. Frequent reassessment by the MET at least every 8 to 12 hours was guaranteed. We analyze data from 133 hematological patients that required MET intervention. In hospital mortality was 38%; mortality doesn’t increase in patients not immediately transferred to the ICU. Only 3 patients died without a former admission in ICU; in these cases, mortality was not related to the acute illness. Moreover, 37% of patients overcame the critical episode in the hematological ward. Higher SOFA and MEWS scores were associated with a worst survival rate, while neutropenia and pharmacological immunosuppression were not. The MET approach seems to be safe and effective. SOFA and MEWS confirmed to be effective tools for prognostication.

The emergence of Internet of Things (IoT) devices is revolutionizing healthcare. This dynamic healthcare environment relies on Internet of Healthcare Things (IoHT) and Internet of Medical Things (IoMT) technologies. Economic, social, and technological opportunities from the IoHT are transforming healthcare systems. This article covers the history, present condition, and future prospects of IoHT, as well as its topologies, platforms, services, applications, market trends, and solution types. It examines security issues, requirements, and a threat taxonomy, studying smart healthcare privacy and security. It explores future research and the challenges IoHT-based solutions face. International health rules and regulations based on the IoT and their social and economic effects on long-term development are also examined. Integrating IoMT into healthcare infrastructures enhances scalability, efficiency, reliability, and accuracy. Through communication networks and data-processing algorithms, IoMT creates smart hardware and software platforms that enhance decision-making. IoMT devices' low resources raise privacy and security concerns. Security and privacy issues are organised by healthcare IoMT adoption in this study. We give an extensive attack taxonomy against the IoMT infrastructure, encompassing devices, security mechanisms, and their pros and cons. Furthermore, it describes the privacy and security requirements for any unique security solutions against IoMT's multiple attack vectors. This article explains the complicated difficulties, security concerns, and future research pathways needed to safeguard and ensure the long-term expansion of these game-changing technologies in the healthcare ecosystem.

Background: The effect of the COVID-19 pandemic has transformed medical education and is likely to have long-lasting effects on student learning, mental well-being, and eating behaviour. This study aimed to examine the learning behaviors of medical students at the American University of Integrative Sciences (AUIS), Barbados, during the COVID-19 pandemic. Methods: A cross-sectional web-based online survey was administered to medical students at AUIS from July until November 2021. The data collecting instrument recorded students’ demographic and learning behaviour information (Meo et al. 2020), and eating disorders (SCOFF questionnaire). Results: The overall response rate was 55% (n=120). In relation to learning behaviour, students agreed with the following statements: ‘deterioration in work performance and studying’ (48.4%), ‘remember subject’s contents appropriately’ (40.4%), ‘concentration on the studies’ (40.3%), ‘difficulty in performing two tasks simultaneously’ (38.7%), ‘difficulty in performing mental calculations’ (33.9%), ‘difficulty in recalling recent information’ (32.3%), and ‘difficulty in recalling old information’ (38.7%). Among the 8 dimensions of learning behaviors, deterioration in work performance or studying, and difficulties in recalling recent information were found to be significantly associated with the gender of the students. For SCOFF questionnaire, approximately 24.2% screened positive for eating disorders. Screening with the SCOFF test demonstrated that female, older (>25 years), overweight + obese, Clinical Sciences + PreMed, and non-USA-based students were at more risk of eating disorders. Conclusions: The results indicate that during the COVID-19 pandemic AUIS students have developed learning difficulties, and are likely to have eating disorders. University policymakers should take appropriate measures to support a healthy learning environment and improve students' mental well-being and eating behaviours.

The possibility of using additive manufacturing (AM) in the medicine area has created a new opportunities in health care. This has contributed to a sharp increase in demand for 3D printers, their systems and materials that are adapted to strict medical requirements. We described herein a medical-grade thermoplastic polyurethane (S-TPU), which was developed and then formed into a filament for Fused Deposition Modeling (FDM) 3D printers during a melt-extrusion process. S-TPU consisting of aliphatic hexamethylene 1,6-diisocyanate (HDI), amorphous α,ω-dihydroxy(ethylene-butylene adipate) (PEBA) and 1,4 butandiol (BDO) as a chain extender, was synthesized without the use of a catalyst. The filament properties were characterized by rheological, mechanical, physico-chemical and in vitro biological properties. The tests showed biocompatibility of the obtained filament as well as revealed no significant effect of the filament formation process on its properties. This study may contribute to expanding the range of medical-grade flexible filaments for standard low-budget FDM printers.

The universal health insurance system in Taiwan was formed with good intentions to help vulnerable groups. However, the possibility of bankrupting the system due to wasted medical resources. In this study, using the medical expenditures of the Taiwanese Government and gross domestic product (GDP) as variables, the wavelet analysis method was used to empirically study the correlations and leading-lagging relationships in quarterly data in the period from 1996 to 2016. In addition, the dependent population of the insured was used as the control variable. This population had no income and had high medical demands. Results: After the dependent population was included as a control variable, there was a period of low-frequency (one to four years short-term) linkage correlation, as well as a period of high-frequency (four to eight years long-term) linkage correlation. In addition, for more than eight years, there was also a high degree of linkage correlation, indicating that the linkage between medical expenditures and GDP occurred over the long term. Moreover, since medical expenditures positively affected GDP, one-way causality was observed. However, after 2008, regardless of whether a long or short term was examined, there was almost no linkage correlation. Before 2008, the medical expenditures of the government were positively correlated with economic growth; i.e., they enhanced economic growth. But, after 2008, this effect had already disappeared. The universal health insurance system has long been denounced as a waste of medical resources, and the waste must be immediately stopped. The government urgently needs to find a new solution.

The objective of this study was to identify the key elements used by prehospital emergency physicians (EP) to decide whether or not to attempt advanced life support (ALS) in asystolic out-of-hospital cardiac arrest (OHCA). From 01.01.2009 to 01.01.2017, all adult victims of asystolic OHCA in Geneva, Switzerland, were retrospectively included. Patients with signs of "obvious death" or with a Do-Not-Attempt-Resuscitation order were excluded. Patients were categorized as having received ALS if this was mentioned in the medical record, or, failing that, if at least one dose of adrenaline had been administered during cardio-pulmonary resuscitation (CPR). Prognostic factors known at the time of EP's decision were included in a multivariable logistic regression model. 784 patients were included. Factors favourably influencing the decision to provide ALS were witnessed OHCA (OR=2.14, 95%CI1.43–3.20) and bystander CPR (OR=4.10, 95%CI2.28–7.39). Traumatic aetiology (OR=0.04, 95%CI0.02–0.08), age >80 years (OR=0.14, 95%CI0.09–0.24) and a Charlson comorbidity index greater than 5 (OR=0.12, 95%CI0.06–0.27) were the factors most strongly associated with the decision not to attempt ALS. Factors influencing the EP’s decision to attempt ALS in asystolic OHCA are the relatively young age of the patients, few comorbidities, presumed medical aetiology, witnessed OHCA and bystander CPR.

The advance of the medical field in the 21st century has influenced the development of many innovations, including in medical education. PBL (problem-based learning) is one of the pedagogical approaches that has been studying and implementing worldwide to attract medical students’ attention with their learning style and learning environment. China is the most significant “receiver” country of foreign students in Asia, and clinical medicine is one of the most chosen majors for undergraduate. In China, PBL has been implementing in some schools, but mostly with the local students and only a few implementations to the international students. International medical students in China faced a variety of challenges during their studies. In this review paper, we give the solution to adapt to the challenges by focusing on the implementation the integrated organ/system curriculum/syllabus with the PBL method to the school system with the support of the school stakeholders and students’ role.

Unexpected preoperative surgery cancellations are one of the important problems in daily anesthesia practice. It's an even bigger problem if these cancellations happen in the operating room. Our aim was to draw attention to this issue and reveal the reasons. This prospective, cross-sectional study aimed to assess the prevalence and causes of elective surgery cancellations once patients are in the operating room. The study sample consisted of 7482 adult patients scheduled for elective surgeries and taken to the operating room. Sixty-seven patients whose surgeries were canceled were grouped into Group 1, while the remaining 7415 whose surgeries were completed were in Group 2. Patients were divided into two groups based on whether their surgeries were completed or canceled. Factors such as age, American Society of Anesthesiologists physical status, and surgical department were analyzed. Metrics involved comparisons between the two groups regarding age, American Society of Anesthesiologists physical status classification, surgical department, and timing of the surgery. The prevalence of elective surgery cancellations after patients were in the operating room was 0.9%. Group 1 was significantly older than Group 2 (p&lt;0.001). The proportion of patients classified as American Society of Anesthesiologists physical status III was higher in Group 1 (p&lt;0.001). The department with the highest cancellation rate was ophthalmology(2.5%), followed by general surgery(2.1%), urology(1.5%), and ear, nose, and throat(1.4%). Approximately 59.7% of cancellations were deemed potentially avoidable. The study suggests that many of these cancellations are potentially avoidable, underscoring the need for optimized surgical scheduling and patient assessment protocols.

Previous research showed that intersex people face specific challenges in their sexual development, including uncertainties or confusion about their gender, a negative genital self-image, and hesitance to engage in romantic and sexual relationships. However, in-depth knowledge of a central period of this development, adolescence, is missing. In our qualitative study, we explore which factors influence the relational and sexual development of intersex youth and what elements contribute to a positive development. We interviewed eighteen intersex persons aged 18-38. We identified three main themes: (1) intersex experiences, (2) the described sexual and relational life course, and (3) factors influencing a positive development. Our findings show that intersex youth face many obstacles to their relational and sexual development, many of which related to healthcare. However, their life stories also illuminate how healthcare professionals but also parents, friends, partners, teachers and others can make a substantial difference in intersex lives by breaking normative, binary thinking on sex and gender.

Early treatment is the mainstay of sepsis therapy. We suspected that early recognition of sepsis by prehospital healthcare providers may shorten time to antibiotic administration in the Emergency Department. We retrospectively evaluated all patients above 18 years of age that were diagnosed with sepsis or severe infection in our Emergency Department between 2018 and 2020. We recorded the suspected diagnosis at time of presentation, type of referring healthcare provider and time until initiation of antibiotic treatment. Differences between groups were calculated using Kruskal-Wallis rank sum test. Of the 277 patients that were diagnosed with severe infection or sepsis in the emergency department, an infection was suspected in 124 (44.8%) patients and sepsis was suspected in 31 (11.2%) patients by referring healthcare providers. Time to initiation of antibiotic treatment was shorter in patients where sepsis or infection had been suspected prior to arrival for both patients with severe infections (p = 0.022) and sepsis (p = 0.004). Given the well described outcome benefits to early sepsis therapy, recognition of sepsis needs to be improved. Appropriate scores should be used as part of routine patient assessment to reduce time to antibiotic administration and improve patient outcomes.

Laser therapy devices (LTDs) operating with near-infrared laser light are increasingly being used in sports medicine. For several reasons the users cannot evaluate whether or not such devices emit laser beams according to the specifications provided by the manufacturer and the settings of the device. In this study the laser beams from two different LTDs that can be used in sports medicine were thoroughly characterized by measuring the emitted power, pulse shapes and lengths, and spatial intensity distributions using professional, high-fidelity laser measurement technology. This was repeated for three units of each LDT independently to distinguish problems of individual units from potential intrinsic instrument design errors. The laser beams from the units of one LTD agreed with the settings at the device, with the measured average power for these units being within 3.3% of the set power. In contrast, the laser beams from the units of the other LTD showed large deviations between the settings and the actual emitted light. This device came with three laser diodes that could be used independently and simultaneously. The average power differed greatly between the units as well as between the laser diodes within each unit. Some laser diodes emitted essentially no light, which could lead to a lack of treatment of patients. Other laser diodes emitted much more power than set at the device (up to 230%) that could result in skin irritations or burnings of patients. These findings indicate a need for better standardization and consistency of therapeutic laser light sources.

To evaluate the impact of a new Substance Use Disorder (SUD) education program on medical students' representations, we selected the Substance Abuse Attitude Survey (SAAS) questionnaire, which we adapted to our curriculum and cultural context. To validate this adapted version, we conducted an exploratory factor analysis following the administration of our 29-items bSAAS questionnaire to 657 medical students in Belgium (response rate: 71,1%). 23 items correlated to 3 factors namely "Stereotypes and moralism", "Treatment optimism" and "Specialised treatment" were retained (70% of total variance explained, Cronbach's alpha= 0.80) and constituted the new questionnaire called beSAAS. The factor "Specialised treatment", stood out from previous studies which could be explained by our target population and the impact of the formal, informal, and hidden curriculum in medical education. This study highlighted certain factors influencing stereotypical representations such as age, gender, origin, and personal or professional experience with substance use. Our study allowed us to retain the beSAAS as a good questionnaire to evaluate SUD stigma and highlighted interesting findings to improve SUD training in medicine. Further studies are needed to complete its validity and reliability.

Breast cancer (BC) is a heterogeneous disease representing a substantial economic burden. In order to develop policies that successfully decrease this burden, the factors affecting costs need to be fully understood. Evidence suggests that early detection in Stage I has a lower cost than late detection. We aim to provide conservative estimates of BC's stage-wise medical costs from German healthcare and the payer's perspective. To this end, we conducted a literature review of articles evaluating stage-wise costs of BC in Germany through PubMed, Web of Science, and Econ Lit databases supplemented by Google Scholar. We developed a decision tree model to estimate BC related medical costs in Germany using available treatment and cost information. The review generated seven studies; none estimated the stage-wise costs of BC. The studies were classified into two groups: (1) case scenarios (five studies) and two studies based on administrative data. The first sickness funds data study (Gruber, Stock, et al. 2012) used 1999 information to approach BC attributable cost; their results suggest a range between €3,929 and €11,787 depending on age. The second study (Kreis, Plöthner, et al. 2020) used 2011-2014 data and suggested an initial phase incremental cost of €21,499, an intermediate phase cost of €2,620, and a terminal phase cost of €34,513 per incident case. Our decision tree model based BC stage-wise cost estimates were €21,523 for Stage I, €25,679 for Stage II, €30,156 for Stage III, €42,086 for Stage IV. Alternatively, the modeled cost estimates are €20,284 for the initial phase of care, €851 for the intermediate phase of care, and €34,963 for the terminal phase of care. Our estimates for phases of care are consistent with recent German estimates provided by Kreis and Plöthner et al. Furthermore, the data collected by sickness funds are collected primarily for reimbursement purposes, where the German ICD-10 classification system defines a cancer diagnosis. As a result, claims data lack the clinical information necessary to understand stage-wise BC costs. Our model-based estimates fill the gap and inform future economic evaluations of BC interventions.

A quality marine ecosystem if it is free from GTP contaminants. Accuracy and caution are needed in the exploitation of marine resources as marine tourism destinations so that in the future, there will be no ecological hazards that cause chain effects, not only on aquatic ecosystems but also on humans. This article identifies exposure to GTP (MP, PAH, PR, HM, MW) in marine ecosystems in the MTA area and BCI waters. The combination of qualitative and quantitative analysis methods uses a combination of analytical instruments and mathematical formulas. The search results show the average total abundance of MP in seawater and fish samples (5.47 units/m3) and (7.03 units/m3), respectively, while in sediment and sponge samples (8.18 units/m3) and (8.32 units/m3). Based on the analysis of the polymer structure, it was identified that the dominant light group MP (PE, PP and PS), followed by PA and PC. Several PAH pollutants were identified in the samples, especially NL types found in all samples, followed by PN and AZ. BCI sea waters are suspected to be exposed to MW and PR. Pollutants of Pb+2 and Cu+2 around BCI were successfully calculated with average concentrations in seawater 0.164 mg/L and 0.294 mg/L, respectively, while in fish, 1.8110 µg/g and 2,452 µg/g, respectively. Based on these findings, the BCI area is not recommended as a marine tourism destination.

The US opioid overdose epidemic has risen to an all-time high. Prescription opioids often serve as a gateway to illicit opioids which have appreciable overdose potential. Recent investigations have highlighted the efficacy and safety of marijuana-based products for pain management. Providing alternative pain treatment options may help mitigate the opioid epidemic. The distribution of codeine, fentanyl, hydrocodone, morphine, and oxycodone per 100K people and by 3-digit zip codes and overdose rates from 2014 to 2018 in California, which legalized recreational marijuana in 2016, were compared to Texas, where marijuana is functionally prohibited. Drug weights were obtained from the Automation of Reports and Consolidated Orders System and converted to oral morphine milligram equivalents. Overdose data was retrieved from the Centers for Disease Control’s WONDER database. California (-43.7%) and Texas (-27.3%) showed significant reductions in cumulative opioid distribution from 2014 to 2018. Opioid distribution per 100K people decreased -38.9% in California relative to -26.4% in Texas. Opioid and heroin overdoses increased between 1999 and 2019 by +11.6% in California but +272.7% in Texas. This evidence supports marijuana legalization as a mitigating factor to the opioid epidemic and opioid misuse.

The theatre has a tremendous ability to influence public discourse and shape societal opinions. And medical conditions can provide writers with a rich scope for plot development and characters with challenges to overcome. In particular, the neurological condition epilepsy has many possibilities with historical beliefs that people were possessed by gods and devils and the sudden, disabling seizures characteristic of the condition. But used unsympathetically, it can promote misunderstanding within audiences, resulting in discrimination for people with the condition. This review looks back at how epilepsy has been portrayed throughout history. How the Greeks portrayed epilepsy as a punishment from the gods. Then later, how Shakespeare utilised epilepsy to suggest characters as uncontrollable. However, we finish on a message of hope as modern writers look to collaboration to ensure accurate and honest portrayals of epilepsy, improving public understanding and removing many of the stigmas that have dogged the condition.

Introduction: The SARS-CoV-2/COVID-19 pandemic has triggered the need for developing rapidly effective and safety vaccines to prevent infection, particularly in those at-risk populations such as medical personnel. The objective of this study was to assess perception of COVID-19 vaccination amongst Colombian physicians featuring two different sceneries of COVID-19 vaccination. Methods: A cross-sectional analytical study was carried out through an online survey, directed at medical staff in several cities in Colombia. The percentage of physicians who have a positive perception to be vaccinated and the associated factors that determine that decision were determined. A binomial regression analysis adjusted for age and sex was carried out, taking as a dependent variable the acceptance of free vaccination with an effectiveness of 60 and 80%. The most significant factors were determined in the non-acceptance of vaccination. Results: Between 77.1% and 90.8% of physicians in Colombia, accept COVID-19 vaccination, according to the scenario evaluated where the effectiveness of the vaccine was 60 or 80%, respectively. Medical specialty, have ever paid for a vaccine, recommend administrating the vaccine to their parents or people over 70 years and dispense the vaccine to their children were the factors to be vaccinated for free with an effectiveness of 60% and 80%. Conclusions: There is a high perception of the intention to vaccinate physicians in Colombia against COVID-19. But it is very similar to that of the general population, according to results reported in other studies.

Medical Trust-Network is one of the most promising fields of study in network science. Establishment of trust within medical entities ensures better treatment and increases better medical facilities. The word ‘Trust’ signifies a very important behavioral aspect between any human entities, especially among doctors and patients. To represent such relationships Trust Network Models are built to express the interactions between human entities within such networks. Though the idea of a Trust-Network has traditionally been one of the major areas of research, yet the concept of a medical trust network model is relatively a new domain. In this paper, we introduce an overall multilayered Trust Network to represent the entire healthcare architecture. More specifically our model is based on an evolutionary graph system with a discrete relationship between the three most important entities of any healthcare system, namely – Doctors, Departments, and Hospitals. Observations indicate that based on our model, the medical healthcare system is a multilayered model unlike a feed-forward model as indicated by previous studies.

With the rapidly growing pandemic of COVID-19 caused by the new and challenging to treat zoonotic SARS-CoV2 coronavirus, there is an urgent need for new therapies and prevention strategies that can help curtail disease spread and reduce mortality. Inhibition of viral entry and thereby spread constitute plausible therapeutic avenues. Similar to other respiratory pathogens, SARS-CoV2 is transmitted through respiratory droplets, with potential for aerosol and contact spread. It uses receptor-mediated entry into the human host via angiotensin-converting enzyme II (ACE2) that is expressed in lung tissue, as well as oral and nasal mucosa, kidney, testes, and the gastrointestinal tract. Modulation of ACE2 levels in these gateway tissues may prove a plausible strategy for decreasing disease susceptibility. Cannabis sativa, especially one high in the anti-inflammatory cannabinoid cannabidiol (CBD), has been proposed to modulate gene expression and inflammation and harbour anti-cancer and anti-inflammatory properties. Working under the Health Canada research license, we have developed over 800 new Cannabis sativa lines and extracts and hypothesized that high-CBD C. sativa extracts may be used to modulate ACE2 expression in COVID-19 target tissues. Screening C. sativa extracts using artificial human 3D models of oral, airway, and intestinal tissues, we identified 13 high CBD C. sativa extracts that modulate ACE2 gene expression and ACE2 protein levels. Our initial data suggest that some C. sativa extract down-regulate serine protease TMPRSS2, another critical protein required for SARS-CoV2 entry into host cells. While our most effective extracts require further large-scale validation, our study is crucial for the future analysis of the effects of medical cannabis on COVID-19. The extracts of our most successful and novel high CBD C. sativa lines, pending further investigation, may become a useful and safe addition to the treatment of COVID-19 as an adjunct therapy. They can be used to develop easy-to-use preventative treatments in the form of mouthwash and throat gargle products for both clinical and at-home use. Such products ought to be tested for their potential to decrease viral entry via the oral mucosa. Given the current dire and rapidly evolving epidemiological situation, every possible therapeutic opportunity and avenue must be considered.

The aim of performed studies was to fabricate an antibacterial and degradable scaffold that may be used in the field of skin regeneration. To reach the degradation criterion the biocompatible polyurethane (PUR), obtained by using amorphous macrodiol α,ω-dihydroxy(ethylene-butylene adipate) macrodiol (PEBA), was used and processed with so-called “fast-degradable” polymer polylactide (PLA) (5 wt% or 10 wt%). To meet the antibacterial requirement obtained hybrid PUR-PLA scaffolds (HPPS) were modified with ciprofloxacin (Cipro) (2 wt% or 5 wt%), the fluoroquinolone antibiotic inhibiting growth of bacteria such as Pseudomonas aeruginosa, Escherichia Coli and Staphylococcus aureus, which are main cause of wound infections. Obtained unmodified and Cipro-modified HPPS were studied towards their chemical composition to detect presence or absence of characteristic functional groups of PUR, PLA and Cipro, and as well to indicate the participation of hydrogen bonds in the HPPS structure in dependence on PLA addition and ciprofloxacin modification. Mechanical properties were studied to determine the possible application of HPPS as a skin tissue scaffold. Scanning electron microscopy (SEM) was used to study morphology of unmodified and Cipro-modified HPPS and to performed elementary analysis by using energy-dispersive x-ray spectroscopy (EDX) of obtained materials. Finally, the microbiological tests were performed to indicate the antibacterial effect of Cipro-modified HPPS on S.aureus growth. Performed studies showed that Cipro-modified HPPS, obtained by using 5 % of PLA, possess suitable mechanical characteristic, morphology, degradation rate and demanded antimicrobial properties to be further developed as a potential scaffolds for skin tissue engineering.

Software-based ultrasound imaging systems provide high flexibility that allows easy and fast adoption of newly developed algorithms. However, the extremely high data rate required for data transfer from sensors (e.g., transducers) to the ultrasound imaging systems is a major bottleneck in the software-based architecture, especially in the context of real-time imaging. To overcome this limitation, in this paper, we present a Binary cLuster (BL) code, which yields an improved compression ratio compared to the exponential Golomb code. Owing to the real-time encoding/decoding features without overheads, the universal code is a good solution to reduce the data transfer rate for software-based ultrasound imaging. The performance of the proposed method was evaluated using in vitro and in vivo data sets. It was demonstrated that the BL-beta code has a good stable lossless compression performance of 20 ~ 30% while requiring no auxiliary memory or storage.

This study evaluated the impact of didactic videos and service user testimonial videos on mental illness stigma among medical students. Two randomized controlled trials were conducted in Nepal. Study 1 examined stigma reduction for depression. Study 2 examined depression and psychosis. Participants were Nepali medical students (Study 1:n=94, Study 2:¬n=213) randomized to three conditions: a didactic video based on the mental health Gap Action Programme (mhGAP), a service user video about living with mental illness, or a control condition with no videos. In Study 1, videos only addressed depression. In Study 2, videos addressed depression and psychosis. In Study 1, both didactic and service user videos reduced stigma compared to the control (F2,91=6.37, p=0.003). In Study 2 (depression and psychosis), there were no differences among the three arms (F2,210=2.07, p=0.13). When comparing Study 1 and 2, there was greater stigma reduction in the service user video arm with only depression versus service user videos with depression and psychosis (t(31)=-3.04, p=0.005). In summary, didactic and service user videos were associated with decreased stigma when content addressed only depression. However, no stigma reduction was seen when including depression and psychosis. This calls for different strategies based on types of mental illnesses. ClinicalTrials.gov identifier: NCT03231761

The aim of study was to investigate epidemiology aspects of magnetic resonance imaging (MRI) during COVID-19 pandemic. The study comprised depersonalized residents of Tomsk and Tomsk Region (n = 1714). Invitations to take online survey were sent to 50,000 residents by target SMS with response rate of 1.2% (n = 727, Cohort 1). Cohort 2 comprised retrospective patients (n = 987) who underwent contrast-enhanced cardiac MRI (CMR) in 2019-2022. Referrals, clinical characteristics, diagnosis, gender, age, past COVID-19, MRI study protocols, and MRI data were analyzed. 29% of respondents in cohort 1 received MRI examination within past two years; 26% of respondents considered MRI the most informative imaging modality for detecting COVID-19 pneumonia; 12% of respondents reported MRI unavailable. Proportion of CMR among MRI studies increased during COVID-19 pandemic, and maximum incidence of cardiac diseases detected by MRI was in 2021. Incidence of myocardial fibrosis increased from ~67% in 2019 to ~84% in 2022. The rate of outpatient MRI studies significantly increased in 2020, but returned to pre-pandemic level in 2021. COVID-19 pandemic increased the need for MRI and CMR. Patients with history of COVID-19 had persistent and newly occurring symptoms of myocardial damage suggesting chronic cardiac involvement requiring continuous follow-up.

Background: Obesity is a global health crisis with a rapidly increasing prevalence among university students. Medical students are a unique population that may be at a higher risk of obesity due to the demanding nature of their studies and the associated stress. Objective: This study aimed to determine the prevalence of overweight, obesity, and the associated risk factors among medical students at Jazan University in Saudi Arabia. Methods: A cross-sectional study was conducted among 228 medical students from their 2nd to 6th academic years at the Faculty of Medicine, Jazan University. A self-administered questionnaire was used to collect data regarding sociodemographic characteristics, physical activity, dietary habits, comorbidities, medication use, family history, and lifestyle factors. Anthropometric measurements including height, weight, and waist circumference were recorded. Chi-square test and binary logistic regression were used to identify the risk factors associated with obesity. Results: The prevalence of overweight and obesity among the participants was 13.3% and 15% respectively. Hence, the combined prevalence of overweight and obesity is 28.3%. The mean weight was 63.39 ± 18.93 kilograms, and the mean height was 163.48 ± 9.78 centimeters. On the other hand, 17.3% of participants had underweight whereas 54.4% had normal BMI. Most of the participants (61%) did not engage in regular exercise. A high proportion consumed fruits (82.9%) and vegetables (58.8%) 3 or fewer days per week, and 84.2% consumed 3 or fewer meals per day. Fast food consumption more than 3 days per week was reported by 42.1% of participants. Obesity was not significantly associated with sociodemographic factors, physical activity, dietary habits, comorbidities, medication use, or family histories. However, those with a monthly family income of 15,000-24,999 riyals had significantly lower odds of obesity than those in the lowest income group (OR 0.230, p = 0.045). Conclusion: The prevalence of overweight and obesity among medical students at Jazan University is high. Although no significant associations were found between obesity and most risk factors, this study highlights the need for interventions that promote healthy lifestyles among medical students. Further research is needed to identify effective strategies for preventing and managing obesity in this population.

Dermal injections of hyaluronic acid gel for aesthetic skin rejuvenation are increasingly popular nowadays. Although these products are classified as medical devices, the regulations on their administration by licensed practitioners are still weak, whereas their manufacturers increasingly highlight and advertise the cellular effects that underpin the efficacy of these injections. In this re-view, we discuss all current knowledge on the mode of action of dermally injected hyaluronic acid and the potential toxicological implications especially from crosslinked gels in conjunction with the current global regulations. We conclude that dermal injections of hyaluronic acid have several therapeutic implications that warrant further research, and that strict regulations must be applied on their manufacture/quality control and the required qualifications of licensed aesthetic injectors.

This paper investigates the effects of Inter-generational co-residence on health care market, and labor market outcomes, to see whether or not living under the same roof with at least one parent matters in health care market, and labor market behaviors in post-Affordable-Care Act (ACA) USA. The adopted analytical strategy involves not only looking at the gender differences in co-residence, and its effects on outcomes in the two markets, but also accounting for co-residence endogeneity following the recent literature. Unlike the recent literature that relies on instrumental variables methods, this study adopts a switching regression approach, defining inter-generational co-residence as an endogenous selection process using a binary probit equation, and modeled jointly with the extensive margins and intensive margins in the two markets. This novel approach results in a recursive trivariate probit model for each market, and estimated using penalized maximum likelihood methods. The results suggest that ACA by reorganizing the US health care market, seems to have reduced significantly disparities in health care access among males and females based on race, region of residence, place of birth, and citizenship. However not only do we observe significant differences in inter-generational co-residence status between males and females, we also find significant inequalities in the effects of co-residence on health care market, and labor market outcomes. In fact, co-residence is found to increase health care expenditure by 56.7% among females, while this figure increases to 74.2% among males. In addition co-residing individuals, while spending 69.7% more on health care annually are 1.22 times more likely to access health care, but 31% less likely to use health care intensively during the year. In the labor market, co-residence is found to reduce significantly hours of weekly labor supplied by 41% for females, and 55.6% for males. Furthermore co-residing individuals, while not significantly different in their likelihood of labor force participation, are 1.52 times less likely to work full time once they decide to participate, and also spend about 55.4% less time working in the labor market in post-ACA USA.

Two of the most common activation functions (AF) in deep neural networks (DNN) training are Sigmoid and ReLU. Sigmoid was tend to be more popular the previous decades, but it was suffering with the common vanishing gradient problems. ReLU has resolved these problems by using zero gradient and not tiny values for negative weights and the value “1” for all positives. Although it significant resolves the vanishing of the gradients, it poses new issues with dying neurons of the zero values. Recent approaches for improvements are in a similar direction by just proposing variations of the AF, such as Leaky ReLU (LReLU), while maintaining the solution within the same unresolved gradient problems. In this paper, the combining of the Sigmoid and ReLU in one single function is proposed, as a way to take the advantages of the two. The experimental results demonstrate that by using the ReLU’s gradient solution on positive weights, and Sigmoid’s gradient solution on negatives, has a significant improvement on performance of training Neural Networks on image classification of diseases such as COVID-19, text and tabular data classification tasks on five different datasets.

Data sets for medical images are generally imbalanced and limited in sample size because of high data collection costs, time-consuming annotations, and patient privacy concerns. The training of deep neural network classification models on these data sets to improve the generalization ability does not produce the desired results for classifying the medical condition accurately and often overfit the data on the majority of class samples. To address the issue, we propose a framework for improving the classification performance metrics of deep neural network classification models using transfer learning: pre-trained models, such as Xception, InceptionResNet, DenseNet along with the Generative Adversarial Network (GAN) – based data augmentation. Then, we trained the network by combining traditional data augmentation techniques, such as randomly flipping the image left to right and GAN-based data augmentation, and then fine-tuned the hyper-parameters of the transfer learning models, such as the learning rate, batch size, and the number of epochs. With these configurations, the Xception model outperformed all other pre-trained models achieving a test accuracy of 98.7%, the precision of 99%, recall of 99.3%, f1-score of 99.1%, receiver operating characteristic (ROC) - area under the curve (AUC) of 98.2%.

Fermatean fuzzy sets (FFSs) are a versatile tool for handling uncertain problems and have shown great effectiveness in practical applications. However, many existing Fermatean fuzzy similarity measures exhibit counter-intuitive situations, making it challenging to accurately measure the similarity or difference between FFSs. To address this issue, several similarity and distance measures for FFSs are proposed, inspired by the Tanimoto similarity measure. The properties of the proposed measures are also explored, along with several comparative examples with existing measures for FFSs, which illustrate their superior performance in processing fuzzy information from FFSs. The proposed measures have effectively overcome the counter-intuitive challenges posed by many existing measures and significantly outperforms existing measures in differentiating different FFSs. Furthermore, we demonstrate the practical applicability of the proposed measures in solving pattern recognition, medical diagnosis and multiple-attribute decision-making problems.

The presented research faces the problem of early detection of sepsis for patients in the Intensive Care Unit. The PhysioNet/Computing in Cardiology Challenge 2019 facilitated the development of automated, open-source algorithms for the early detection of sepsis from clinical data. A labeled clinical records dataset for training and verification of the algorithms was provided by the challenge organizers. However, a relatively small number of records with sepsis, supported by Sepsis-3 clinical criteria, led to highly unbalanced dataset (only 2% records with sepsis label). A high number of unbalanced data records is a great challenge for machine learning model training and is not suitable for training classical classifiers. To address these issues, a number of various models were investigated. A solution including feature selection and data balancing techniques was proposed in this paper. In addition, several performance metrics were investigated. Results show, that for successful prediction, a particular model having few or more predictors based on the length of stay in the Intensive Care Unit should be applied.

Exoskeletons designed to assist patients with activities of daily living are becoming increasingly popular, but still are subject to research. In order to gather requirements for the design of such systems, long-term gait observation of the patients over the course of multiple days in an environment of daily living are required. In this paper a wearable all-in-one data acquisition system for collecting and storing biomechanical data in everyday life is proposed. The system is designed to be cost efficient and easy to use, using off-the-shelf components and a cloud server system for centralized data storage. The measurement accuracy of the system was verified, by measuring the angle of the human knee joint at walking speeds between 3 and 12 km/h in reference to an optical motion analysis system. The acquired data was uploaded to a cloud database via a smartphone application. Verification results showed that the proposed toolchain works as desired. The system reached an RMSE from 2.9° to 8°, which is below most of the comparable system. The system provides a powerful, scalable platform for collecting and processing biomechanical data, which can help to automize the generation of an extensive database for human kinematics.

Patients living with cancer often experience serious adverse events due to their condition or its treatments. Those events may lead to a critical care unit admission or even result in death. One of the most important but challenging part of care is to build a caring plan according to the patient’s wishes, meeting his goals and values. Advance directives (ADs) allow everyone to give their preferences in advance regarding life sustaining treatments, continuation, and withdrawal or withholding of treatments in case one is not able to speak his mind anymore. While the absence of ADs is associated with a greater probability of receiving unwanted intensive care around the end of his life, their existence correlates with the respect of the patient’s desires and his greater satisfaction. Although progress has been made to promote ADs’ completion, they are still scarcely used among cancer patients in many countries. Several limitations to their acceptation and use can be detected. Efforts should be made to provide tailored solutions for the identified hindrances. This narrative review aims to depict the situation of ADs in the oncology context, and to highlight the future areas of improvement.

Introduction: In an era of increasing public awareness regarding the pivotal role of nutrition in the onset and progression of chronic degenerative diseases, there is a growing demand for information and assistance pertaining to the intricate relationship between diet and disease. Nutritional practices, therefore, emerge as a fundamental element in the prevention and management of these maladies, necessitating a proactive response from healthcare professionals (HCP). This study sought to evaluate the impact of participation in a Culinary Medicine (CM) program on Mediterranean diet adherence, food management skills, culinary proficiency, and counseling confidence among HCP. Methods: A mixed-methods pilot implementation program (PIP) was meticulously designed and executed, engaging a cohort of 20 HCP recruited from Hospital Clinic Barcelona. The program unfolded at the Alícia Foundation kitchen-lab and encompassed a series of interactive, hands-on sessions that delved into the realms of gastronomy, food management, culinary skills, and culinary diet therapy, with a specific focus on prevalent diseases and their prevention, treatment, and care. Tailored questionnaires were administered to all participants both before and after the PIP. Results: Of the 20 participants, 14 successfully completed the study, comprising 86% women, 86% aged above 40, 71% nurses, and 7% medical doctors. Interestingly, 86% of the participants had previously received nutrition training, whereas only 14% had received culinary training. Following the completion of the program, there was a remarkable improvement in adherence to the Mediterranean diet (p < 0.01). However, no statistically significant improvements were observed in food management and culinary skills or counseling confidence (p > 0.5). Despite the absence of statistical significance, there was a noteworthy trend towards greater advocacy for dietary changes before resorting to medication, along with enhanced confidence in providing nutritional and culinary guidance to patients. Conclusion: The findings from this study underscore the potential of hands-on CM training as a vital component of nutrition education for HCP. While statistically significant improvements in certain domains were not observed, the program did demonstrate its ability to influence attitudes, knowledge, and behaviors related to healthy cooking and eating for both HCP themselves and their patients. Given these promising trends, future studies with a larger sample size must be performed to further elucidate the impact of CM training on HCP and its potential benefits for public health.

Not a lot is known about either death or the dying process. Politicians and many in the medical profession in the UK tend to shy away from interfering with it by not allowing euthanasia as an end of life option for the patient. This is the first paper in a series of two, comparing the situation in human medicine and veterinary medicine, in which euthanasia is well practiced for relieving suffering at the end of an animal’s life. This first part takes the form of a literature review including best practice around end of life care, its deficiencies and the need for assisted dying. Veterinary surgeons are well trained in the ethics of euthanasia and put it to good use in the best interest of their animal patients. In countries which have legalized physician assisted suicide for the terminally ill reporting indicates that it works well, without increases in involuntary euthanasia and most importantly without intimidation of the vulnerable. However, there is still an ever increasing tendency to overuse sedation and opioids at the end of life, which merits further investigation. With advances in medical science able to significantly prolong the dying process, patient autonomy demands a review of the law in the UK.

A substantial spike in the need for quality healthcare has resulted from people being more cognizant of health issues. With blockchain, healthcare providers may safely share patient information electronically, which is especially important given the sensitive nature of the data contained inside them. However, flaws in the current blockchain design have surfaced since the dawn of quantum computing systems. The study proposes a novel quantum inspired blockchain system (Qchain) and constructs a unique entangled quantum medical record (EQMR)system with an emphasis on privacy and security. This Qchain relies on entangled states to connect its blocks. Automated production of the chronology indicator reduces storage capacity requirements by connecting entangled BloQ (blocks with quantum properties) with controlled activities. One qubit is used to store the hash value of each block. A lot of information regarding quantum internet is included in the protocol for the entangled quantum medical record (EQMR). EQMR can be accessed in Medical Internet of Things (M-IoT) systems may be kept private and secure, and their where-abouts can be monitored in the event of an emergency. The protocol also uses quantum authentication in place of more conventional methods like encryption and digital signatures. Mathematical research shows that the quantum converged blockchain (QCB) is highly safe against attacks such as the External attack, Intercept-Measure-Repeat attack, and Entanglement-Measure attack. The reliability and auditability evaluations of the entangled BloQ, as well as the quantum circuit design for computing the hash value, are presented. There's also a comparison between the suggested approach and several other quantum blockchain designs.

Post-menopausal women are at risk of osteoporotic vertebral fractures (OVFs), which if undetected and untreated, can lead to significant pain and morbidity. However, OVFs are often not reported by radiologists on routine chest radiographs. Artificial Intelligence (AI) is increasingly used in medical applications with improvements in detection and diagnosis. This study aims to investigate the clinical value of a newly developed AI tool, Ofeye 1.0 for automated detection of OVFs on lateral chest radiographs in post-menopausal women (&gt;60 years) who were referred to undergo chest x-rays for other reasons. A total of 510 de-identified lateral chest radiographs from three clinical sites were retrieved and analysed by Ofeye1.0 tool. These images were then reviewed by a consultant radiologist to decide whether there is any fracture present or not with findings served as the reference standard for determining the diagnostic performance of the AI tool. The percentage of radiologist reports which included the OVF was analysed by comparing diagnostic reports with AI findings, while the accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive values (NPV) of the AI tool were calculated. Out of all the original radiologist reports, missed OVFs were found in 14% images but were detected by the AI tool. The AI tool demonstrated a relatively high specificity 92.8% (95% CI: 89.6, 95.2%), moderate accuracy 80.3% (95% CI: 76,3, 80.4%), PPV 73.7% (95% CI: 65.2, 80.8%) and NPV 81.5% (95%CI: 79, 83.8%), but low sensitivity 49% (95%CI: 40.7, 57.3%). The high false negative results were mainly due to mild OVFs with &lt;20% vertebral height loss. The new AI software tool has high specificity with a low false positive rate of 5.1%, showing that it can be used as a complimentary tool to the routine diagnostic reports for reduction of missed OVF in elderly women. The low sensitivity with high false negative rates indicate the necessity of radiologist’s in identifying and reporting early OVFs.

Exudative-pleural-effusion (ePE) is a common presentation in pulmonology clinics. Pleural biopsy is indicated for identifying the aetiology in undiagnosed ePE especially the ones with low adenosine-deaminase levels. The access to rigid and semi-rigid medical thoracoscopy is scarce and heterogeneous in a resource limited country like India. In such circumstances, using flexible bronchoscope via intercostal-chest-tube for visualization of parietal pleura and pleural biopsy offers a way out. Here, in this retrospective study, we have presented our experience of such practice on 25 cases. Mean age was 52.4±1 years. Adhesions were present in 40% of the subjects. Most common finding was presence of nodules. On an average 6.8 passes were taken with maximum of 10. In 32% cases only tiny tissue was obtained, hence requiring multiple passes. Large tissue could be obtained in 44% of the subjects. Mean duration of the procedure was 35.6±9.0 minutes. Tissue diagnosis was established in 80% with most common being malignancy (48%) followed by tuberculosis (20%). In 3 cases, the final diagnosis was made by exclusion. No major complications were recorded. In conclusion, medical thoracoscopy using flexible video bronchoscope via intercostal-chest-tube was a feasible alternative for the diagnosis of ePE effusion in resource limited settings.

One of the challenges in the healthcare sector is making accurate forecasts across insurance years for claims reserve. The state-of-the-art envisages various methods for estimating the claims reserve but without being applied to systems that do not present huge variability and heterogeneity, such as the healthcare sector. The methodology is based on generalized linear models using the Overdispersed Poisson distribution as shown in the state-of-the-art. In this context, we developed a method to estimate the parameters of the quasi-likelihood function using a Gauss-Newton algorithm optimized through a genetic algorithm. The genetic algorithm plays a crucial role in glimpsing the position of the global minimum to ensure a correct convergence of the Gauss-Newton method, where the choice of the initial guess is fundamental. The proposed methodology has been entirely developed using MATLAB and has been applied to estimate the claims reserve in the healthcare system of the Tuscany Region in Italy, as case study. The results obtained were validated by comparing them with the state-of-the-art by measuring the confidence intervals of the Overdispersed Poisson distribution parameters. Therefore local healthcare authorities could use the proposed and improved methodology to allocate the resources dedicated to healthcare and global management.

Recently, there has been remarkable progress in the development of smart textiles, especially knitted strain sensors, to achieve reliable sensor signals. Stable and reliable electro-mechanical properties of sensors are essential for using textile-based sensors in medical applications. How-ever, challenges associated with significant hysteresis and low gauge factor (GF) values remain for using strain sensors for motion capture. To evaluate these issues, a comprehensive investiga-tion of the cyclic electro-mechanical properties of weft-knitted strain sensors was conducted in the present study to develop a drift-free elastic strain sensor with a robust sensor signal for mo-tion capture for medical devices. Several variables were considered in the study, including the variation of the basic knit pattern, the incorporation of the electrically conductive yarn, and the size of the strain sensor. The effectiveness and feasibility of the developed knitted strain sensors are demonstrated through experimental evaluation, by determining the gauge factor, its non-linearity, hysteresis and drift. The developed knitted piezoresistive strain sensors have a GF of 2.4, a calculated drift of 50 %, 12,5 % hysteresis, and 0.3 % nonlinearity in parts.

This paper describes the design and development of an active device that was applied to shoulder rotation rehabilitation. It implements a force control in a similar way to the haptic devices that reflect a force on the user’s hand according to the rehabilitation parameters. This device was tested with patients, combining clinician manipulation and programmed exercises. The results were excellent, given that the range of movement of the shoulder increased in most of the pa-tients. The results of the Usability Scale questionnaire were also promising.

Medical tests' cost-effectiveness analysis reveals a strong correlation between their accuracy and analysis results. Theoretically, we provide two lower bounds that medical tests' accuracy must exceed to be considered cost-effective. Theoretically, we provide two lower bounds that the accuracy of medical tests meeting cost-effectiveness must exceed. First, medical tests' accuracy should surpass the lower bound of matching requirements for each patient to receive the most appropriate intervention based on their test results. Second, the overall lower limit should be exceeded for the medical testing to be cost-effective for the patients as a whole. Furthermore, the conclusions from this model also provide an economic explanation for the under-diagnosis of rare diseases and the challenges faced in implementing precision medicine for minority patients. A numerical simulation example validates the conclusions of this paper.

This study aimed at assessing the extent to which the Saudi general population has embraced digital health medical applications to meet their health-related needs so that the Saudi Ministry of Health and government can appropriately be guided on scaling up of digital health across the country. As such, this study was guided by the question of to what extent do the Saudi people use digital health mobile-based applications?. This was a cross-sectional study utilizing snowballing sampling approach. Frequencies, Chi-square, and Spearman rank correlation statistics were used to offer descriptive and inferential analysis of the variables. The majority of the participants were economically able to afford smart devices that have medical apps, had at least an app on such devices, and highly regarded the benefits of the apps. Unfortunately, their understanding of how to use such apps was limited and this posed a barrier to embracing digital health alongside difficulty downloading apps, and medical ethical concerns. Although there is a willingness, extra effort is needed from the Saudi Ministry of Health and government to promote the uptake of digital health in Saudi Arabia.

The National Occupational Competency Profile (NOCP) – the competency framework for paramedics in Canada – is presently undergoing revision. Since the NOCP was published in 2011, paramedic practice, healthcare and society have changed dramatically. To inform the revision, we sought to identify emerging concepts in the literature that would inform the development of competencies for paramedics. We conducted a restricted literature review and content analysis of all published and grey literature pertaining to or informing Canadian paramedicine from 2011 to 2022. Three authors performed a title and abstract, and full-text review to identify and label concepts informed by existing findings. A total of 302 articles were categorized into eleven emerging concepts related to competencies: Inclusion, Diversity, Equity, and Accessibility (IDEA) in paramedicine; Social responsiveness, justice, equity and access; Anti-racism; Healthy Professionals; Evidence Informed Practice and Systems; Complex Adaptive Systems; Learning Environment; Virtual Care; Clinical Reasoning; Adaptive Expertise; and Planetary Health. This review identified emerging concepts to inform the development of the 2023 National Occupational Standard for Paramedics (NOSP). These concepts will inform data analysis, development group discussions, and competency identification.

The optical properties and physiology of biological tissue, as well as how near-infrared (NIR) light interacts with the tissue, both play a significant role in interpreting the tissue probing optical measurements, and in solving the inverse problem of near-infrared spectroscopy (NIRS)-based medical imaging modalities such as diffuse optical tomography and functional near-infrared spectroscopy. This paper discusses the optical properties of tissue, specifically in the NIR wavelength range, which influence NIRS measurements in NIRS-based medical imaging. There is an easy-to-understand explanation given in this paper of the NIR light-tissue interaction phenomenon. The mathematical explanation, the processes involved in the interaction, and the rationale for a few approximations are described. Various types of chromophores present in the tissue, their composition in the tissue, and how these chromophores overall affect the scattering and absorption of NIR light are presented. The absorption spectra of these chromophores are shown. Finally, the paper concludes with the author’s perspective on two NIRS-based medical imaging modalities, diffuse optical tomography, and functional near-infrared spectroscopy.

During the COVID-19 pandemic, conducting face-to-face medical residency interviews was challenging due to infection prevention precautions, social distancing and travel restrictions. Virtual interviews were implemented by the Saudi Commission for Health Specialties (SCFHS) as an alternative process for residency matching while striving to maintain the same quality standards. This national survey was conducted to assess the satisfaction and perceptions of faculty members’ virtual interviews performance in the assessment for the medical training residency programs. Among the participating 173 faculty members (34.1%) did not have previous experience with video-conferencing. Zoom application was the most commonly used platform (65.9%). Most (89.6%) of the faculty perceived virtual interviews as “adequate” for the candidates to express themselves, while almost half of the faculty (53.8%) agreed that virtual interviews allowed them to accurately reach an impression about the candidates. Overall, 73.4% of faculty felt comfortable ranking the virtually interviewed candidates. We conclude that the acceptance of participating faculty members in the first Saudi medical residency training matching cycle virtual interviewing event was well perceived. This study provides evidence for future application and research of virtual interviews in residency candidates' assessment, especially after the pandemic crisis resolves.

Little is known about family medicine academic staff in Taiwan, and basic data about this workforce may aid healthcare decision makers. We analysed data on Taiwan’s 13 medical schools collected by the Taiwan Association of Family Medicine from June to September 2019. Items included medical school names and total staff, and the gender, age, degree, working title (part-time/full-time), academic level, and sub-specialty of each current family medicine faculty member. A total of 116 family medicine faculty members were reported; most were male (n= 85, 73.3%). Ages ranged between 30 and 69 years, with a mean (SD) age of 43.3 (8.09). Faculty members with a master’s degree were the largest group (n= 49, 42.2%), and most were academic lecturers (n=49, 42.2%). Additionally, only about one-fourth (n=26, 22.4%) of family medicine faculty in medical schools were full-time, while the other three-fourths (n=90, 77.6%) were part-time faculty; most were located in northern Taiwan (n=79, 68.1%) and specialized in gerontology and geriatrics (n=55, 47.4%) and hospice palliative care (n=53, 45.7%). Our research provides the most complete census of family medicine academic physicians in medical schools in Taiwan. The results inform efforts to improve the establishment and development of family medicine departments in Taiwan.

Despite the surge in the research of cannabis chemistry and its biological and medical activity, only a few cannabis-based pharmaceutical-grade drugs have been developed and marketed to date. Not many of these drugs are Food and Drug Administration (FDA)-approved and some are still going through regulation processes. Active compounds including cannabinergic compounds (i.e., molecules targeted to modulate the endocannabinoid system) or analogs of phytocannabinoids (cannabinoids produced by the plant) may be developed into single-molecule drugs. However, since in many cases treatment with whole plant extract is preferred over treatment with a single purified molecule, some more recently developed cannabis-derived drugs contain several molecules. Different combinations of active plant ingredients (API) from cannabis with proven synergy may be identified and developed as drugs to treat different medical conditions. However, possible negative effects between cannabis compounds should also be considered, as well as the effect of the cannabis treatment on the endocannabinoid system. FDA registration of single, few or multiple molecules as drugs is a challenging process and certain considerations that should be reviewed in this process, including issues of drug-drug interactions, are also discussed here.

Food handlers’ medical examinations are mandated by most countries as a way of safeguarding the health and safety of consumers. Food-borne diseases are an important cause of morbidity and mortality. In Zimbabwe, the use of chest radiographs and throat and rectal swab tests are a requirement during food handlers’ medical examinations. This study aimed at exploring the patterns and outcomes of physical medical examinations, chest radiographs, and other tests of food handlers. A cross-sectional review of retrospective occupational health records was carried out. The mean age for the study population was 37 years with an age range of 21 to 56 years. Males accounted for 73% of the study participants. All of the 157 rectal swabs were normal and did not culture any organism. Fifteen percent (24) of the throat swabs cultured one or more organisms. Ninety-seven percent of chest radiographs were normal. Ninety-seven percent of employees were certified as fit. Thirty-six percent of the food handlers were in the overweight and obese categories. Hypertension and high blood pressure were common conditions in the study sample. It can be concluded that routine radiological and laboratory testing of the food handlers in this study was of little value.

Keyhole neurosurgery implies reaching a target area inside the brain through an entry point specified by the neurosurgeon. In order to avoid complications, a risk assessment procedure must be done to establish the minimum risk trajectory from the entry point to the target area. The neurosurgeon establishes the risk values for the brain structure according to the type of intervention. The preset brain structure risk value is used to assess the risk value for each voxel of the brain. This paper proposes an improved risk assessment methodology based on the sum of N maximum risk values for each voxel. Then, risk assessment for a trajectory is done by adding the risk of all voxels that are part of the path. The safest trajectory is defined as the trajectory with the lower risk. Our proposed search trajectory methodology includes a Genetic Algorithm (GA) for finding the safest trajectories. The use of a GA drastically reduces the number of trajectories to analyze, speeding up the planning procedure. The achieved results were qualified by expert neurosurgeons as satisfactory. Our proposed method allows neurosurgeons to calibrate the surgical planning system by allowing them to establish the risk brain structure and the risk value for each structure.

This study was undertaken to investigate and analyze noise pollution in a large Chinese governmental hospital’s medical intensive care unit and compare to the WHO guidelines.This cross-sectional study was conducted in a MICU at a public governmental teaching hospital in Fujian province between July and August of 2017. A WENSN® WS1361 Integrated Sound Level Meter (China) was used for continuous every five seconds one week noise levels recording. After this measurement, the decibel meter was used for recording different location of isolation rooms and open bays, including occupied and unoccupied patient, and recording sound events occurs in the ICU to identify sources of noise. Peak and average noise levels were obtained from the meter, and data were downloaded from the WS1361 into a laptop computer. The measured mean equivalent sound pressure levels (L) and standard Aeq deviation over one week period were 66.64±7.57 dB(A), with acute spikes reaching 119.7 dB(A), the average sound level for a 24 hour period in a work day was 68.03±5.07 dB(A). These are higher than the current daytime environmental noise limit of 40-45 decibels in China and WHO. Mean work day noise was significantly louder than weekend time, there was a significant difference in work days and weekend (t=16.85;P=0.000).There was a statistical difference between the day time and night time shifts (t=34.67;P=0.000). The isolation rooms were significantly quieter than the open-bay rooms(t=46.15; p=0.00), sound levels in the occupied and unoccupied rooms also had significant difference(t=17.26; P=0.000).Two types of noise resources, including twenty kinds sources were identified and measured, mean noise levels ranged from of 61.33 to 79.21 dB(A). This study shows noise levels in intensive care units were exceeded the recommended. The study of the influence of noise on patient and staff is needed, and noise reduction strategies must be conduct in ICU.

This paper investigates existing mathematical morphology based techniques applied for performing malaria parasites detection and identification in both Giemsa and Leishman stained blood smears images. Malaria is an epidemic health disease and a rapid, accurate diagnosis is necessary for proper intervention. Generally, pathologists visually examine blood stained slides for malaria diagnosis; this kind of visual inspection is subjective, errorprone and time consuming. In order to cope with such issues, computer-aided methods have been increasingly evolved for abnormal erythrocyte and/or parasites detection, segmentation and semi/fully automated classification. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection.

Cancer is the second major cause of disease-related dead worldwide, and its accurate early diagnosis and therapeutic intervention are fundamental for saving the patient’s life. Cancer, as a complex and heterogeneous disorder, results from disruption and alteration of a wide variety of biological entities, including genes, proteins, mRNAs, miRNAs, and metabolites that eventually emerge as clinical symptoms. Traditionally, diagnosis is based on clinical examination, blood tests for biomarkers, histopathology of biopsy, and imaging (MRI, CT, PET, US). Additionally, omics biotechnologies help to further characterize the genome, metabolome, microbiome traits of the patient that could have an impact on the prognosis and patient’s response to the therapy. The integration of all these data relies on gathering of several experts and may require considerable time, and, unfortunately, it is not without the risk of error in the interpretation and therefore in the decision. Systems biology algorithms exploit Artificial Intelligence (AI) combined with omics technologies to perform a rapid and accurate analysis and integration of patient’s big data and support the physician in making diagnosis and tailoring the most appropriate therapeutic intervention. However, AI is not free from possible diagnostic and prognostic errors in the interpretation of images or biochemical-clinical data. Here, we first describe the methods used by systems biology for combining AI with omics and then discuss the potential, challenges, limitations, and critical issues in using AI in cancer research.

Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease. Technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of Things, nanotechnology etc. has led to the development of molecular approaches and computer aided diagnosis for the detection of COVID-19. This study provides a holistic approach on COVID-19 detection based on (1) molecular diagnosis which include RT-PCR, antigen-antibody and CRISPR-based biosensors and (2) computer aided detection based on AI-driven models which include Deep Learning and Transfer learning approach. The review also provide comparison between these 2 emerging technologies and open research issues for the development of smart-IoMT-enable platform for the detection of COVID-19.

Care coordination (CC) for children with special healthcare needs and medical complexity (CSHCN-CMC) is challenging, and medication management is especially difficult for providers, parents/caregivers, and patients alike. While numerous strategies for CC have been suggested and implemented, barriers to medication optimization remain. The report describes the creation of a pediatric clinical pharmacotherapy practice, related standard operating procedures to assure consistent application of screening tools and care provision through comprehensive medication management (CMM), and establishment of a collaborative practice agreement (CPA) to guide drug therapy delegation, monitoring, and modification. The methodology of a prospective case series is also presented to highlight drug therapy problems and their resolution in CSHCN-CMC. Future opportunities to expand the practice for engagement in population health management as well as prior authorization activities on behalf of physicians will be discussed.

This comprehensive review explores the advancements in Orthognathic and Oral Maxillofacial Surgery, focusing on the integration of 3D Printing and Virtual Surgical Planning (VSP). Traditional surgical methods, while effective, come with inherent risks and complications, and can lead to variability in outcomes due to the reliance on the surgeon's skill and experience. The shift towards patient-centric care necessitates personalized surgical methods, which can be achieved through advanced technology. The amalgamation of 3D printing and VSP revolutionizes surgical planning and implementation by providing tactile 3D models for visualization and planning, and accurately designed surgical guides for execution. This convergence of digital planning and physical modeling facilitates a more predictable, personalized, and precise surgical process. However, the adoption of these technologies presents challenges, including the need for extensive software training and the steep learning curve associated with computer-aided design programs. Despite these challenges, the integration of 3D printing and VSP paves the way for advanced patient care in orthognathic and oral maxillofacial surgery.

Best practices in global health training prioritize leadership and engagement from investigators from low- and middle-income countries (LMICs), along with more conscientious community consultation and research that benefits local participants and autochthonous communities. However, well into the 20th century, international research and clinical care were rife with paternalism, extractive practices, and racist ideation, with race presumed to explain both vulnerability or protection from various diseases despite scientific evidence for more precise mechanisms for infectious disease. We highlight experiences in global research on health and illness among indigenous populations in LMICs, seeking to clarify what is both scientifically essential and ethically desirable in research with human subjects; we apply a critical view towards race and racism as historically distorting elements that must be acknowledged and overcome.

Mechanical ventilation systems, which are used for breathing support when a person is not able to do it by their own, requires a device for measuring the air flow to the patient in order to monitoring and a assure the magnitude establish by a medical staff. Flow sensors are the conventional devices used for the air flow measuring; however, there were not available in Peru, because of the international demand during COVID-19 pandemic. In this sense, a novel air flow sensor based on orifice plate and an intelligent transducer stage were developed as an integrated design. Advanced methodologies in simulations and experiments using specially designed equipment for this application were carried out. The obtained data was used for a mathematical characterization and dimensions validation of the integrated design. The device was tested in its real working conditions, it was implemented in a breathing circuit connected to a low-cost mechanical ventilation system based on cams. Results indicate that the designed air flow sensor/transducer is a low-cost complete medical device for mechanical ventilators able to provide satisfactorily all the ventilation parameters air flow, pressure and volume over time by measuring the air flow and calculating the others. Furthermore, this device provides directly a filtered equivalent electrical signal for a display or a computer.

Mobile robots can perform tasks on the move, including exploring terrain, discovering landmark features or moving a load from one place to another. This group of robots is characterized by a certain level of intelligence allowing making decisions and responding to stimuli received from the environment. As part of Industry 5.0, such mobile robots and humans are expected to co-exist and work together in a shared environment to make human work less tiring, quicker, and safer. This can only be realized when clean, dense, and economical energy sources are available. The aim of the study is to analyze the state of the art and to identify the most important directions for future developments in robotic power systems based mainly on batteries. The efficiency and performance of the battery depends on the design using different materials. Work environments and performance requirements are considered in this systematic review to classify solutions that help developers choose the best suited power system for specific application. Indirectly, the aim of the work is to generate discussion within the scientific and engineering community. A narrative review of publications from six major bibliographic databases according to preset inclusion criteria was combined with a critical analysis of current and future technologies. The main findings of the review allow answering question what is the role of modern power source technologies, artificial intelligence and ground-breaking research work in global policies related to energy saving, green policies, and sustainable development. The main opportunities and threats are discussed, and a brief feasibility analysis is carried out. Novelty of the article relates not only to the analysis of technologies, but also to approaches and their use under conditions of limited resource availability, when resource usage must be minimized. The article provides an overview of batteries, their specifications, classifications, and their advantages and disadvantages. In addition, we propose: (1) an algorithm for selecting main energy source for robot application, and (2) an algorithm for selecting electrical system power supply. Current mobile robot batteries are, in most cases, their biggest limitation. Progress in batteries development is too slow to catch up with the demand for robot autonomy and range requirements, limiting the development of mobile robots. Further intensive research and implementation work is needed to avoid years of delay in this area.

The COVID-19 pandemic measures have negatively impacted education worldwide via travel restrictions, student visas, and physical attendanc,e among many other fac-tors. As one of the first places to impose strict pandemic measures and one of the last places to lift the measures, Mainland China provided a unique venue to investigate the effect of public health pandemic control policies on tertiary education. Considering the large portion of international students in medical schools and the higher susceptibility to the pandemic measures due to the natural synergy with teaching hospitals, medical schools can be an early forefront indicator of the impact of the pandemic on tertiary education. We surveyed 513 participants international medical students from Wen-zhou Medical University’s school of international studies in 2019 and 2022 about their satisfaction and demographic and cultural adaptation parameters. We found that the pandemic restrictions did not generally impact student satisfaction. Further analyzing the associated parameters, we found teaching satisfaction to be independent of age (P=.159), years in China (P=.896) and Chinese Level (P=.577) in the medical university. Teaching satisfaction is associated with the region of origin (P <0.001), acceptance of local social norms (P <0.001), satisfaction with the core values of Chinese culture (P <0.001), acclimatization to life in China (P <0.001), can easily make Chinese friends (P <0.001) among other factors. The findings of this study provide an understanding of the effects of pandemic measures on tertiary education satisfaction and other factors that can aid in international student satisfaction.

Background: Tele-emergency physicians (TEPs) take an increasingly important role in the need-oriented provision of emergency patient care. To improve emergency medicine in rural areas, we set up the project Land|Rettung (English: Rural|Rescue), which uses TEPs to restructure professional rescue services using information and communication technologies (ICTs) in order to reduce the therapy-free interval. Successful implementation of ICTs relies on user acceptance and knowledge sharing behavior. Methods and findings: We conducted a factorial design with active knowledge transfer and technology acceptance as a function of work satisfaction (high vs. low), workload (high vs. low) and point in time (prior to vs. after digitalization). Data were collected via machine readable questionnaires issued to 755 persons (411 pre, 344 post), of which 304 or 40.3% of these persons responded (194 pre, 115 post).Technology acceptance was higher after the implementation of TEP for nurses but not for other professional groups, and it was higher when the workload was high. Regarding active communication and knowledge sharing, employees with low work satisfaction are more likely to share their digital knowledge as compared to employees with high work satisfaction. Additional and more detailed analyses reveal that this is an effect of previous knowledge concerning digitalization. After implementing the new technology, work satisfaction increased for the more experienced employees, but not for the less experienced ones. Results are discussed considering the Dunning-Kruger effect. The Dunning-Kruger effect describes a cognitive bias. People with high expertise often underestimate their actual skill level. They have a more critical attitude towards their performance and feel the urgent need to fill possible knowledge gaps they notice. Conclusions: Our research illustrates that employees’ workload has an impact on the intention of using digital applications. The higher the workload, the more people are willing to use TEPs. Regarding active knowledge sharing, we see that employees with low work satisfaction are more likely to share their digital knowledge compared to employees with high work satisfaction. This might be attributed to the Dunning-Kruger effect. Highly knowledgeable employees initially feel uncertain about the change, which translates into temporarily lower work satisfaction. They feel the urge to fill even small knowledge gaps, which in return leads to higher work satisfaction. Those responsible need to acknowledge that digital change affects their employees’ workflow and work satisfaction. During such times, employees need time and support to gather information and knowledge in order to cope with digitally changed tasks.

While referral-level medicine is important in the veterinary curriculum, students also need a solid base knowledge of clinically relevant routine surgery and diagnostic skills. Veterinary hospitals must maintain a steady caseload that provides wellness cases and commonly encountered conditions. Shelter Medicine programs can create the opportunities to meet these challenges. Students can gain quantifiable surgical experience in spay/neuter with measured growth in surgical efficiency and competency while providing needed community service for animal shelters. Students can directly interact with shelter animals by performing examinations, diagnostic testing, and development of treatment protocols and recommendations for commonly encountered problems. Furthermore, students can obtain a working knowledge of biosecurity on a population level to minimize risk of infectious diseases spreading to healthy populations.

Chronic kidney disease (CKD) is a progressive condition that affects more than 10% of the world's population. Monitoring urine albumin and creatinine ratio (µACR) has become the gold standard for nephropathy diagnosis and control. The objective of the present study was to develop a simple, accurate, sensitive, and rapid point-of-care test (PoCT) device - MYμALBUMIN that community healthcare professionals can use in resource-limited facilities and by patients in their own homes for screening the risk and monitoring the progress of CKD. Albumin and creatinine concentrations in urine samples were determined using spectrophotometric dye (tetrabromophenol blue)-binding and colorimetric Jaffe’assay, respectively. Urine samples were diluted with distilled water (1:80) and mixed separately with albumin and creatinine reaction mixture. The creatinine reaction was incubated at room temperature (25oC) for 30 minutes before analysis. Optical density (OD) was measured at the wavelengths of 625 nm (albumin) and 515 nm (creatinine). All calibration curves (2-60 mg/L and 0.25-2 mg/dL for albumin and creatinine) yielded linear relationships with correlation coefficients (r2) of &gt; 0.999. Good accuracy (%DMV &lt; + 2.88%) and precision (%CV &lt; 3.0%) were observed from both the intra- or interday assays for the determination of albumin and creatinine by MYµALBUMIN. The limit of quantification (LOQ) of albumin and creatinine in urine samples determined by MYµALBUMIN and laboratory spectrophotometer were 2 mg/L and 0.1 mg/dL, respectively, using 37.5 μL urine samples. The device was well applied with clinical samples from 13 CKD patients. The median (range) of %DMV of the central (hospital) laboratory method (immune-based assay) was 3.18 (-10.11 to 14.12)%, with a high correlation coefficient (r2 &gt;0.99). In conclusion, MYμALBUMIN showed satisfactory test performance in terms of accuracy, reproducibility, sensitivity, and specificity. The device would have significant economic benefits besides obviously improving clinical decision-making processes.

Keywords: Energy harvesting, Hybrid, Medical Wearable Sensor Nodes, Health Monitoring, Power Management

Paramedics are increasingly being subjected to violence, creating the potential for significant physical and psychological harm. Where a patient has a history of violent behavior, hazard flags - applied either to the individual, their residential address, or phone number - can alert paramedics to the possibility of violence, potentially reducing the risk of injury. Leveraging a novel violence reporting process embedded in the electronic patient care record, we reviewed violence reports filed over a thirteen-month period since its inception in February 2021to assess the effectiveness of hazard flagging as a potential risk mitigation strategy. Upon reviewing a report, paramedic-supervisors can generate a hazard flag if recurrent violent behavior from the patient is anticipated. In all, 502 violence reports were filed, for which paramedic-supervisors generated hazard flags in 20% of cases (n=99). In general, cases were not flagged either because the incident occurred at a location not amenable to flagging, or because the supervisors felt that a hazard flag was not warranted based on the details in the report. Hazard flagging was associated with an increased risk of violence during subsequent paramedic attendance (Odds Ratio [OR] 6.21, p

This review summarizes available data on invasive procedures applied with questionable indications in Russia in the recent past: mastectomy with the removal of muscles, gastrectomy for peptic ulcers, spleno-renal anastomosis for diabetes mellitus, thoracic surgery for bronchial asthma, overuse of surgery in tuberculosis, excessive and compulsory treatments of alcohol-dependent patients, etc. Among factors contributing to the use of invasive procedures with unproven efficiency have been the partial isolation from international scientific community, insufficient consideration of the principles of professional autonomy, informed consent and scientific polemics, training of medical personnel. It is known that invasive procedures can exert a placebo effect, which might have contributed to reported efficiency of some methods discussed here. However, by definition, placebo must be free of risks.