Background: The progression of periodontal diseases at national Portuguese level and its public awareness are of great interest, mainly due to the high burden of periodontitis. Objectives: To evaluate the prevalence progression of periodontal diseases in Portugal and correspondent public awareness, between 2004 and 2017, by using data from the Global Burden of Disease (GBD), Directorate-General of Health (DGH) and Google® Trends (GT). Methods: For the period 2004-2017, Portuguese national data of periodontal diseases prevalence were searched in the Institute for Health Metrics and Evaluation of GBD and DGH and for public awareness, GT comparison tool between Portuguese words for “Periodontitis”, “Gingivitis”, “Gums” and “Periodontal disease” trends was used. Results: For the period 2004-2017, the overall prevalence of periodontitis slightly increased from 11.3% to 11.7%. During that period the GT search term “Gums” (“Gengivas”) was the most relevant. It increased steadily over time while the search term “Periodontal disease” (“Doença periodontal”) decreased, being these search trends significantly correlated (

This study delves into the dynamic field of medical education research, emphasizing the integration of research training within medical curricula. It seeks to understand the impact of such integration on the competencies of future medical professionals. The primary aim is to systematically categorize and analyze the current trends and future directions in medical education research. This involves assessing the influence of research training on medical students' skills and the methodologies used in such research. Methods: The research employs an extensive bibliographic literature review across multiple databases. It classifies studies into categories like experiential or case studies, editorials, and original research articles. This classification is based on criteria such as geographical location, research objectives, theoretical frameworks, and methodologies. Results: Findings reveal a diverse landscape in medical education research, with a significant emphasis on research training. The research showcases varying methodologies and approaches used globally, highlighting the thematic focus and geographical distribution of these studies. Conclusion: Medical education research is a globally expansive and evolving field. It underscores the importance of continuous investigation, particularly focusing on integrating research elements at curricular levels and exploring innovative educational strategies. The study also points out potential gaps in research, especially in underrepresented regions, indicating directions for future research efforts.

Burden of diseases measured as disability-adjusted life years per 100,000 people can be mined from public domain data, when they are made available by population health surveillance systems. This can be analysed to allow insightful comparisons with the national average, and to understand differences in trends between the sexes, age groups, time periods, geographic regions and sub-regions. In this illustrative case study, we have analysed the Scottish burden of disease database to understand what ailed the population of the Grampian region before the COVID-19 pandemic. We have identified selected cancers, ischaemic heart disease, Alzheimer’s disease and other dementias amongst the highest contributors to the burden; that drug use disorders and colorectal cancer are showing worsening trends and require health promotion and disease prevention measures from ages 15 and 25 respectively, especially in Aberdeen City; and that males are more vulnerable to atrial fibrillation and flutter, diabetes mellitus and oesophageal cancer, while females are to cerebrovascular disease. We demonstrate the usefulness of our analysis and methodology for the wider health system, allowing targeted medical research investments and coordinated response from public health and health service delivery. We also show the need for up-to-date surveillance data, forecasts and evidence on the impact of interventions to be made available widely.

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.

Respiratory viral infections (RVI) are common reasons for healthcare consultations. The inpatient management of RVI consumes significant resources. From 2009-2014, we assessed the costs of RVI management in 4776 hospitalized chil-dren aged 0-18 years participating in a quality improvement program, where all ILI patients underwent virologic testing at the National Reference Centre followed by de-tailed recording of their clinical course. The direct (medical or non-medical) and indirect costs of inpatient management outside the ICU (“non-ICU”) versus management requiring ICU-care (“ICU”) added up to 2,767.14€ (non-ICU) vs. 29,941.71€ (ICU) for Influenza, 2,713.14€ (non-ICU) vs. 16,951.06€ (ICU) for RSV infections, and 2,767.33€ (non-ICU) vs. 14,394.02€ (ICU) for human rhinovirus (hRV) infections, respectively. Non-ICU inpatient costs were similar for all 8 RVI studied: Influenza, RSV, hRV, ade-novirus (hAdV), metapneumovirus (hMPV), parainfluenzavirus (hPIV), bocavirus (hBoV) and seasonal coronavirus (hCoV) infections. ICU-costs for Influenza however, ex-ceeded all other RVI. At the time of the study, Influenza was the only RVI with antivi-ral treatment options available for children, but only 9.8% of Influenza patients (non-ICU) and 1.5% of ICU-patients with Influenza received antivirals; only 2.9% were vac-cinated. Future studies should investigate the economic impact of treatment and pre-vention of Influenza-, COVID-19-, and RSV post vaccine introduction.

Our primary objectives were a) to determine the need for, and the availability of point-of-care testing (POCT) for infectious diseases and b) to recommend point-of-care testing strategies and spatial care paths (SCPs) that enhance public health preparedness in regional districts of Thua Thien Hue Province (TTHP), Central Vietnam, where we conducted field surveys. Medical professionals in 7 community health centers (CHCs), 7 district hospitals (DHs) and 1 provincial hospital (PH) participated. Survey questions (English and Vietnamese) determined the status of diagnostic testing capabilities for infectious diseases and other acute medical challenges in TTHP. Infectious disease testing was limited: 6 of 7 CHCs (86%) lacked infectious disease tests. One CHC (14%, 1/7) had two forms of diagnostic tests available for the detection of Malaria. All CHCs lacked adequate microbiology laboratories. District hospitals had few diagnostic tests for infectious diseases (Tuberculosis, Syphilis), blood culture (29%, 2/7), and pathogen culture (57%, 4/7) available. The PH had broader diagnostic testing capabilities but lacked preparedness for highly infectious disease threats (e.g., Ebola, MERS-CoV, SARS, Zika, and Monkeypox). All sites reported having COVID-19 rapid antigen tests; COVID-19 RT-PCR tests were limited to higher tier hospitals. We conclude that infectious disease diagnostic testing should be improved and POC tests must be supplied near patients’ homes and in primary care settings for the early detection of infected individuals and mitigation of the spread of new COVID-19 variants and other highly infectious diseases.

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 Work Ability Index (WAI) is the most widely used questionnaire for the self-assessment of working ability. Because of its different applications, shorter versions, and widespread use in healthcare activities, it is worthwhile assessing its characteristics. The WAI was distributed online among the workers of a healthcare company; the results were compared with data contained in the workers' personal health records and with absence registers. 340 out of 575 workers (59.1%) participated; 6.5% of them reported poor work ability. Exploratory factor analysis indicated that the one-factor version best described the characteristics of the WAI. The scores of the complete WAI, the shorter form without the list of diseases, and the minimal one-item version (WAS) had equal distribution and were significantly correlated. The WAI score was inversely related to age and significantly lower in women than in men, but it was higher in night workers than in colleagues due to the probable effect of selective factors. The WAI score was also correlated with absenteeism, but no differences were found between males and females in the average number of absences, suggesting that cultural or emotional factors influence the self-rating of the WAI. Workers tended to overreport illnesses in the online survey compared to data collected during occupational health checks. Musculoskeletal disorders were the most frequently reported illnesses (53%). Psychiatric illnesses affected 21% of workers and had the greatest impact on work ability. Multilevel ergonomic and human factor intervention seems to be needed to recover the working capacity of healthcare workers.

Background: The COVID-19 outbreak has accelerated the huge difference between medical care and disease prevention in Chinese medical institutions. This study aimed to investigated the relationship between the symbiotic units, environments, models, and effects of the integration of medical and disease prevention. Methods: This cross-sectional study involved 762 employees of public hospitals in 11 cities in Zhejiang Province by random stratified sampling. We analyzed the influence paths of elements in the mechanism of integration of medical and disease prevention and the mediating effect of symbiotic models among symbiotic units, symbiotic environments, and effects for on this integration. Results: The path coefficient of symbiotic unit on the symbiosis model was 0.46 (p<.001), the path coefficient of symbiotic environment on symbiosis model was 0.52 (p<.001). The path coefficient of the symbiotic unit and environment was 0.91 (p<.001). The symbiotic models exhibited a partial mediation effect between symbiotic units and the effect of this integration. Sobel test = 3.27, β = 0.152, and the mediating effect accounted for 34.6%. Conclusions: It is suggested that Health policy-makers and public hospital managers should provide sufficient symbiotic units, establish collaborative symbiotic models, and improve the effects of integration of medical and disease prevention in public hospitals.

Background: Media coverage of Lyme disease (LD) has led to an increase in consultations for presumed LD in Europe. However, LD is confirmed in only 10-20% of patients, with a significant number remaining in a diagnostic dead-end. Objectives: To reach a deeper understanding of how patients themselves contribute to the diagnostic process. To describe the genesis of the LD hypothesis in care pathways. Methods: In 2019, 30 patients from a prospective cohort consulting in the infectious diseases department at University Hospital in Marseille for presumed LD were recruited for semi-structured interviews. The inclusion criteria were : suffering from subjective symptoms for 6 months, no clinical or paraclinical argument suggesting current LD. The patients’ medical trajectories were collected using a biographical approach. Results: The diagnosis of Lyme disease was primarily triggered by identification with personal testimonies found on the internet. Most of patients were leading their own diagnostic investigation. The majority of participants were convinced they had LD despite the lack of medical evidence and the scepticism of their referring GP. Conclusion: GPs should first systematically explore patients’ etiologic representations in order to improve adherence to the diagnosis especially in the management of medically unexplained symptoms. Long COVID-19 syndrome challenge offers an opportunity to promote active patient involvement in diagnosis.

The patient's satisfaction level concerning hospitalization has certain particularities, related to the geographical area, medical/non-medical assistance, the age, incomes, morbidity and mortality of the population. The objective of this study is to emphasize the degree of patients' satisfaction, depending on the specialty of the hospitalization department: surgical, medical, oncological, psychiatry, and to evidence the factors influencing the reliability and accuracy of patients' answers, such as: the patient's health condition upon admission, the duration of the admission, the level of physical pain and the emotional state. Patients and methods: The research was conducted between April and December 2021 on patients hospitalized in two public hospitals from the north-west of Romania, both of them being independent Legal Entities: the Municipal Clinical Hospital of Oradea (MCHO) and the County Clinical Emergency Hospital of Oradea (CCEHO). Results: The lowest score of PSS recorded in these two analyzed public hospitals from the north-western of Romania was appointed for the Pharmaceutical availability of patients medical treatment (2.24), attitude of the staff (2.56) and the quality of nursing care offered (2.58). Conclusions: The hospital management’s focus has been set to improve the communication skills among medical staff, to evidence their compassion, politeness, and to ensure the availability of essential drugs.

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 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.

Background: Gender stereotypes and biases can influence perceptions of competence and suitability for certain medical specialties. Empathy is an important component of an optimal doctor-patient relationship. The scope of our study is to verify the correlation between “empathetic" behavioral style with attention and sensibility to the gender differences of patients of the medical students. Methods: An online survey was conducted using the Jefferson Scale for Empathy (JSE), to measure empathy in the context of health professions education and patient care; and the Nijmegen Gender Awareness in Medicine Scale (N-GAMS), which measures attitudes and assumptions about gender. A total of 234 students (52.1% M; mean age: 22.68±2.48) from Medicine and Surgery at the University of Salerno (Italy) participated, of whom n° 175 were third-year students and n° 59 were fifth-year students. Results: The JSE score shows that male students have higher scores (77.29±12.38) than females (75.91±10.39). Conversely, female students have higher perspective-taking (JSE Factor 1: Male= 51.26±11.84; Female= 52.72±11.88). In addition, third-year students are much more empathetic than their fifth-year colleagues (JSE Score: 3°ys= 77.35±11.46; 5°ys= 74.49±11.33). With reference to the GS, we found that male students have greater sensitivity than their female colleagues (GS: Male= 2.67±0.68; Female= 2.37±0.48); conversely, they have higher scores of gender stereotype towards patients (GRIP: Male= 2±0.88; Female= 1.59±0.61) and doctors (GRID: Male= 1.88±0.89; Female= 1.64±0.63). Also, the third-year students compared to their fifth-year colleagues are characterized by greater gender sensitivity (GS: 3°ys= 2.57±0.62; 5°ys= 2.42±0.57), less bias with respect to patients (GRIP: 3°ys= 1.77±0.79; 5°ys= 1.90±0.78) but, on the other hand, show more stereotypes and prejudices towards doctors (GRID: 3°ys= 1.77±0.81; 5°ys= 1.75±0.74). Conclusions: Humanistic attitudes, including empathy, should be instilled, and evaluated among trainees as an essential part of their postgraduate medical education.

Introduction: Due to the spread of SARS CoV-2 virus responsible for COVID-19 disease, there is an urgent need to analyse COVID-19 epidemic perception in Poland. This study aims to investigate social perception of coronavirus in the Internet media during the epidemic. It is a signal report highlighting the main issues in public perception and medical commutation in real time. Methods: We study the perception of COVID-19 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet on platforms: Google, Twitter, YouTube, Wikipedia and electronic media represented by Event Registry, from January 2020 to 29.04.2020 (before and after official introduction to Poland on 04.03.20). We present trend analysis with a support of natural language processing techniques. Results: We identified seven temporal major clusters of interest on the topic COVID-19: 1) Chinese, 2) Italian, 3) Waiting, 4) Mitigations, 5) Social distancing and Lockdown, 6) Anti-crisis shield, 7) Restrictions releasing. There was an exponential increase of interest when the Polish government “declared war against disease” around 11/12.03.20 with a massive mitigation program. Later on, there was a decay in interest with additional phases related to social distancing and an anti-crisis legislation act with local peaks. We have found that declarations of mitigation strategies by the Polish prime minister or the minister of health gathered the highest attention of Internet users. So enacted or in force events do not affect interest to such extent. Traditional news agencies were ahead of social media (mainly Twitter) in dissemination of information. We have observed very weak or even negative correlations between a colloquial searching term 'antiviral mask' in Google, encyclopaedic definition in Wikipedia “SARS-CoV-2” as well official incidence series, implying different mechanisms governing the search for knowledge, panic related behaviour and actual risk of acquiring infection. Conclusions: Traditional and social media do not only reflect reality, but also create it. Risk perception in Poland is unrelated to actual physical risk of acquiring COVID-19. As traditional media are ahead of social media in time, we advise to choose traditional news media for a quick dissemination of information, however for a greater impact, social media should be used. Otherwise public information campaigns might have less impact on society than expected.

At present, the health systems of many countries face complex challenges even if their priority objectives remain the same - to provide sustainable health systems at the current and the prognostic demographic changes and requirements in a health system. The quality and the efficiency of healthcare delivery and their mutual conformity have been brought to public attention. Similarly, the quality and the efficiency of an entire process depends on the instrumentation and its procurement that represents a significant economic and procedural issue in the healthcare systems for a long time. Many reports of the public procurement processes and research studies declare this fact. The primary aim of this study is to evaluate the public procurement efficiency in the health system by means of the valuation approach, or savings’ estimates that are achieved by the public procurement. The savings were defined as a percentage difference between the estimated and the final contract price. The secondary objective is to examine an influence of selected variables on a creation of savings in the public procurement process by means of a regression analysis. The researched variables are as follows: time, method, procurement, NUTS level of procurement, Common Procurement Vocabulary Code, number of offers. The analysis results showed interesting findings. The number of offers has a significantly positive impact on the savings. It means that if the number of offers increases by one unit, the savings will increase by 15.6%. Also, time variable (year) has a positive impact on the savings. Consequently, it may be assumed that the public procurement process is improving from a time perspective. It may be partially caused by the fact that a new public procurement legislative has been valid since 2015. The NUTS level has also an impact on the savings in relation to the public procurement. The public procurements which took place at the level of a state were more beneficial as the public procurements at the regional level. Also, the procurement method was statistically significant parameter of a regression analysis. The competition actions together with a negotiation process created higher savings in comparison to tenders. In case of the CPV codes, the most significant savings were achieved in the group of ‘various medicinal products’. The study’s results provide a valuable knowledge for the creators of policies and a realization of the national strategic plans within the health system. Also, these results support a creation of national and international benchmarks in this area and a networking of international partnerships in the area of a public procurement that focus on a development of methodologies and comparative platforms creation.

Background: With new challenges to the health system, many new competencies within the scope of teaching public health need to be addressed in medical schools’ curricula such as disaster risk management and health system science. The aims of this study were to identify the needs of public health competencies for medical doctors in Thailand and to assess the level of integration for technical collaboration in teaching public health. Method: A total of 17 out of 21 Thai medical schools participated in the national survey. Qualitative inquiries applied focus group interviews of community representatives from ten sample villages and in-depth interviews of representatives from stakeholder organizations particularly employers. The list of public health competencies framework recommended by WHO-SEARO was applied. Quantitative analysis applied descriptive analysis using STATA 15 and qualitative findings were validated by interrelating the meaning of themes from Word Clouds created in NVivo12. Data integration applied a mixed-method Quan-qual approach. Results: 17 medical schools returned the questionnaires (80.95 % yield). The most common regionally-defined public health competencies (in over 70% of schools) were shown to be: Biostatistics, Community Medicine, Epidemiology, Family Medicine, Medical Ethics and Professional Laws, Preventive Medicine, Health Promotion, Holistic Care, and Research. The curriculum in only one medical school lacked Health Economics, whilst Disaster Management was lacking in two other schools. Discipline-based subjects were found to be more prevalent than interdisciplinary competencies. A variety of methods were being applied for teaching public health. The majority of the schools applied lecture as the main teaching method and multiple-choice questions as the main assessment method. Thai communities expect the doctors to get in touch with the community more often, lead the primary health care team through training the health professionals and community health volunteers, and educate the community for better health. Conclusion: Human resource is the main challenge in addressing interdisciplinary competencies. It is necessary to establish a collaborating mechanism among the big and small medical schools and the faculties of public health to improve the teaching of public health to undergraduate students in medical schools. There is also a need to strengthen the health system science and leadership so that future MDs can lead health service delivery according to the needs of their employers such as the Ministry of Public Health and the Rural Doctors Association. The findings of this study may help to identify a national framework of public health core competencies for medical schools and create a common platform for interdisciplinary collaborations.

During the pandemic, educational digitization experienced a significant increase. In Mexico, social service is a crucial component of technical and professional training, a phase during which individuals apply the knowledge gained throughout their university education. The aim of this study is to standardize a digital model for the management of social service in the health care sector within health care units. This study employed an analytical, observational, retrospective, and longitudinal approach, involving two groups of trainees: Group A (n=133), utilizing a Non-Digital Model, and Group B (n=50), employing a Digital Model. In Stage I. the model design underwent validation through the Delphi method with a panel of three experts. The model was implemented on a Classroom® digital platform with the integration of the elements 1) a monthly rotation rubric 2) care services rubric 3) clinical cases or nursing process rubric, and 4) innovation project rubric. The validation of the model achieved 100% agreement (K=1). The variables measured for each group included the school of origin, career, unit of assignment, timely enrolment, and timely delivery of rubrics on the platform. The difference between the two groups was measured using Chi-Square. To measure the impact, the difference in the timeliness of the products was considered. From the University of Quintana Roo, the difference was 20.3 vs 34%. According to the Unit of Attachment the most frequent was HGR No. 17 with Group A at 22.5 vs 52%. According to the product the least delivered was Product 4, with 69% vs 81%. Timely enrollment was observed in Group A at 89% vs Group B at 80% p=0.001. Overall timely delivery in Group A was 81% vs Group B at 91% p=0.001 in the first 6 months post-implementation. Demonstrating that the implementation of the digital platform was effective, representing a significant advance in the adaptation of medical education to the circumstances imposed by the pandemic, highlighting the feasibility and effectiveness of digital teaching methods in the training of health professionals.

Background: Community-based medical education (CBME) is an essential component of medical education, where primary healthcare physicians (PHPs) play a crucial role. This study explores PHPs' awareness and engagement in CBME and investigates the factors influencing their participation. Methods: This mixed study was conducted in two phases. In the first phase, a qual-itative study was conducted using semi-structured interviews with PHPs, and thematic analysis related to their awareness and engagement in CBME. In the second phase, a quantitative survey was conducted among 72 PHPs pre- and post-training programs. Results: Primary healthcare physicians had a positive attitude toward community-based medical education. The participants have an acceptable level of awareness and engagement, which increased substantially (p-value = 0.03) and (p-value = 0.003), respectively. Logistic analysis indicated that non-Saudi physicians were likelier to participate in the CBME (p-value=0.001). Professions and academic experiences influence their willingness and engagement to participate in CBME (OR= 7.5, p-value=0.001) and (OR=0.21, p-value=0.001), respectively. Conclusion: The study findings highlighted the importance of increased awareness and the factors that enhance PHPs' engagement in CBME. This positive perspective of the PHPs helps build effective partnerships and facilitates the extension of the curriculum to apply CBME.

Background: The clinical impact of withdrawal of sodium-glucose cotransporter 2 inhibitor (SGLT2i) on the all-cause readmission in patients with heart failure remains unknown. Methods: Consecutive 212 patients who were hospitalized for heart failure and received SGLT2i during the index hospitalization between February 2016 and July 2022 were evaluated. Of these, 51 patients terminated SGLT2i during or after their index hospitalization. The primary outcome was defined as an all-cause readmission rates/times. Results: Over a median of 23.2 months, an all-cause readmission occurred in 38 of 51 patients (74.5%) withdrawn from SGLT2i and 93 of 161 patients (57.8%) with continuation of SGLT2i (p = 0.099). The total number of all-cause readmissions per year was 0.97 [0-1.50] in patients withdrawn from SGLT2i and 0.50 [0-1.03] in patients with continuation of SGLT2i (p = 0.030). There was no significant difference in total medical cost (62,906 [502-187,246] versus 29,236 [7,920-180,305] JPY per month, p = 0.866) between both patient groups. Conclusions: Termination of SGLT2i may be associated with incremental all-cause readmission and no benefit in reducing total medical costs.

With recent focus on deep neural network architectures for development of algorithms for computer-aided diagnosis (CAD), we provide a review of studies within the last 3 years (2015-2017) reported in selected top journals and conferences. 29 studies that met our inclusion criteria were reviewed to identify trends in this field and to inform future development. Studies have focused mostly on cancer-related diseases within internal medicine while diseases within gender-/age-focused fields like gynaecology/pediatrics have not received much focus. All reviewed studies employed image datasets, mostly sourced from publicly available databases (55.2%) and few based on data from human subjects (31%) and non-medical datasets (13.8%), while CNN architecture was employed in most (70%) of the studies. Confirmation of the effect of data manipulation on quality of output and adoption of multi-class rather than binary classification also require more focus. Future studies should leverage collaborations with medical experts to aid future with actual clinical testing with reporting based on some generally applicable index to enable comparison. Our next steps on plans for CAD development for osteoarthritis (OA), with plans to consider multi-class classification and comparison across deep learning approaches and unsupervised architectures were also highlighted.

Objectives: To determine the effects of caffeine consumption on the sleep habits and lifestyle of medical students. Methods: A cross-sectional study was conducted at Jinnah Sindh Medical University (JSMU) and Hamdard College of Medicine. On 422 undergraduate students aged 18-25 years, through random sampling. The duration of the study was from January 2019 to June 2019. The data was collected through self-administered questionnaire which included data regarding sleep habits and lifestyle of medical students. Results: Majority (81.6%) of the students consumed caffeine while only (18.4%) did not. One third of the participants (31.8%) reported caffeine consumption increased their academic performance and (57.3%) reported that it does not. More than half of the participants (63.3%) who consumed caffeine slept during class, whereas (47.2%) never had difficulty in falling asleep during the night. Conclusion: This research concluded that caffeine does have some role on sleep habits of medical students as they tend to have less sleep hours, experience day time dysfunction, average quality of sleep, and falling asleep during class. It has been concluded that caffeine has no effect on eating habits of medical students however, it does increase the screening time, keeping them active.

Background: Health policy is a set of comprehensive principles and legislations that guide how healthcare should be effectively delivered in the community. Medical schools should prepare students to undertake managerial responsibilities by incorporating health policy in the curriculum to deal with the intricacies of healthcare systems and their clinical roles in their future professional careers. Objective: To examine medical students' perception at a Public University in Malaysia regarding teaching health policy and their participation in health policy roles. Material and Methods: A cross-sectional study using universal sampling was carried out among the medical students using a paper-based questionnaire to collect the data. Results: Most respondents opined their willingness to learn health policy (80.9%) and that teaching health policy (83.6%) should be compulsory for medical students. The respondents thought health policy should be introduced earlier in Year 1 or 2. The student scores on their knowledge regarding health policy and year of study were significantly associated with their involvement in the health policy roles in both the simple and multiple logistic regression. Both statistical tests reported higher participation in health policy roles with the higher year of study, though only Year 4 and 5 were significant in the simple logistic regression and only Year 5 in the multiple logistic regression compared to Year 1. On the other hand, age and type of admission show significant results only in the simple logistic regression, while the race was only significant at the multivariate level. Conclusion: This study demonstrated that most respondents showed their willingness to learn health policy, participate in the health policy programs, and recommend that health policy be considered an essential topic in the medical curriculum, which should be taught right from the first year of medical school. We recommend encouraging students’ participation in health policy activities.

Understanding the genetic architecture of a disease is crucial for development of valid diagnostic and therapeutic interventions. The analysis of genomic variations associated with pathological conditions is the starting point for uncovering disease-causing pathways (candidate processes). However, the complexity of intergenic and genetic-environmental interactions hinders the identification of pathogenic values of genomic changes. Furthermore, heredity, epigenetics and somatic mosaicism make the interpretation of genomic data even more sophisticated. To succeed, a variety of bioinformatic techniques are applied. Here, reviewing own and literature data, knowledge-based prioritization of genomic variations is described. Theoretical basis of the knowledge-based prioritization is given with a special regard to gene ontology, heuristics, hermeneutics (genomic hermeneutics) and analytics. Practical and methodological issues of prioritization using ontology- or pathway-based systems analysis are considered in the light of optimistic and realistic scenarios of cumulative phenotypic effects of the variome (the whole set of genomic variations in an individual or specific set of genomic variations for a phenotypic outcome). In the present communication, copy number variants (CNVs) in children with neurodevelopmental diseases are used as a practical foundation for the prioritization, inasmuch as these genome variations are systematically overlooked in the so-called NGS era. Nonetheless, it is highly likely that the prioritization is applicable to almost all types of genomic variations (e.g. chromosome abnormalities, gene mutations, functional synonymous variants etc.). The present methodology seems to be a valuable addition to current biomedical science widening the opportunities for medical genomics and genetics.

Alzheimer’s disease has become a major concern in the healthcare domain as it is growing rapidly. Many researches have been conducted to detect it from MRI images through various deep-learning approaches. However, the problem of the availability of medical data and the privacy of the patients still exists. To mitigate this issue in Alzheimer’s disease detection, we have implemented the federated approach which is found to be more efficient, robust, and consistent compared to the conventional approach. For this, we needed deep excavation on various orientations of MRI images and transfer learning architectures. Then, we utilized the publicly available two datasets (OASIS, and ADNI), and designed various cases to evaluate the performance of the federated approach. In almost all of them, the federated approach achieved better accuracy and sensitivity. In distinguishing between two classes equally, the capability of the models was better in the found model when trained with federated approach compared to the conventional approach. In this approach. MobileNet, which is a low-cost transfer learning architecture, achieved the highest 95.24%, 81.94%, and 83.97% accuracy in OASIS, ADNI, and merged (ADNI+OASIS) test set, which was way higher than the achieved performance in Conventional approach. Moreover, in this approach, only the weights of the model were shared which keeps the original MRI images in their respective hospital or institutions, mitigating the privacy concern in the healthcare domain.

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.

Chronic non-communicable diseases (NCDs) are major public health problems and a significant financial burden on public health systems. By 2030, mortality due to NCDs, such as cardiovascular diseases, cancer, respiratory diseases, and diabetes, is predicted to increase in Brazil. A peculiar aspect of NCDs involves their long-term and integrated care management. This paper proposes a chronic disease management platform based on artificial intelligence to deliver digital health services everywhere. The proposed platform is anchored and built with healthcare 4.0 technologies, such as wearable devices, the internet of medical things, and artificial intelligence cloud-based solutions that allow the deployment of a smart healthcare system. In addition, the paper presents the feasibility of the platform in a diabetes prediction study case. For the study case, an initial dataset was established with bio-impedance, oxygen concentration, pulse rate, skin impedance, and skin temperature attributes. A baseline was implemented with ten regression models to assess the prediction performance of the mean squared error, root mean squared error, and r-squared score to compare predictive findings with capillary blood glucose measurements. Results evidence that the decision tree regressor and three ensemble methods (bagging decision tree regressor, random forest regressor, and AdaBoost regressor) yielded improvement over the other models. Moreover, a comparison among those models revealed that the decision tree regressor outperforms them and presents promissory outcomes.

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.

Fractional flow reserve (FFR) is well recognized as a gold standard measure for the estimation of functional coronary stenosis. Technological progressions in image processing have empowered the reconstruction of three-dimensional models of the coronary arteries via both non-invasive imaging modalities, such as Coronary Computed Tomography Angiography (CCTA), and invasive coronary angiography or intravascular imaging. The application of computational fluid dynamics (CFD) techniques to coronary 3D anatomical models allows the virtual evaluation of the hemodynamic significance of a coronary lesion with high diagnostic accuracy in comparison to the invasive FFR using pressure wires. These opportunities providing hemodynamic information based on anatomy have given rise to a new era of functional angiography and coronary imaging. However, further validations are needed to overcome several scientific and computational challenges before these methods are applied in everyday clinical practice. This review aims to present all the data on the studies and methodologies that have been presented for the virtual estimation of FFR, and the diagnostic execution of the virtual tools for the hemodynamic assessment of coronary lesions compared to the invasive FFR.

This article presents a new input device for spastic patients and others with similar symptoms. The sensor consists of a disc used to determine positions and can replace standard joysticks in medical devices such as electric-powered wheelchairs. Using a standard joystick while operating a powered wheelchair can result in dangerous situations when spastic movements occur and extremities cramp making them uncontrollable. To avoid this, a disc was developed that can be controlled with any body part. By shifting weight (x- and y-axis) the disc can tilt in any direction creating a proportional output signal and can also be pushed down in the center (z-axis) to open a menu on a screen for example. When spasms occur it is impossible for users to get stuck on the input device because the disc is flat and can be mounted within a control panel. Body parts coming into contact with the disc would merely slide across the disc without triggering unintentional actions. The sensor presented here is also adaptive and can be adjusted to fit a user’s strength and range of motion. This proposal aims to develop an input device that enables spastic patients to operate sensitive systems safely.

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

Burnout represents a concern for all healthcare providers, particularly those specializing in emergency medical care for whom burnout outcomes have been well-documented. What remains unknown is the effect of burnout on redeployed medical specialists during the COVID-19 pandemic from an appointment-centered practice to emergency care directed by public health considerations. This research aims to identify and assess the burnout responses of fourteen medical specialties noted in searched returns of the four most cited articles published since 2020 about non-emergency physicians regarding their burnout brought on by the unanticipated need for them to provide emergency care during the recent pandemic. The hypothesis is that medical specialists accustomed to planning for emergency possibilities in their appointment-centered practice would demonstrate the least burnout regarding COVID-19-related emergencies. Considering coping as a process based on Lazarus's research, comparing and ranking the COVID-19 emergency responses across the various normally appointment-centered medical specialties in their employed coping strategies determines the outcome. With the hypothesis supported, suggested interventions for future pandemics—when these specialists are, again, redeployed to emergency care directed by public health considerations—are those coping strategies identified as most effective in reducing burnout while maintaining the viability of the medical specialty and excellent patient care.

Alzheimer's disease (AD) is a progressive and evolving neurodegenerative disease with an insidious onset that can lead to memory loss and cognitive impairment. There is no effective treatment for this disease. However, early diagnosis plays an important role in treatment planning to slow down its progression, as treatment has the greatest impact in the early stages of the disease. Neurological images obtained through different imaging techniques provide powerful information and help diagnose the disease. With the wide application of deep learning techniques in disease diagnosis, especially the prominence of Convolutional Neural Networks (CNNs) in computer vision and image processing, more and more studies are proposing the use of this algorithm for the diagnosis of AD. In this paper, we first systematically introduce the impact of AD on people, detailing the biomarkers, early clinical symptoms, and risk factors of this disease. Secondly, it goes on to detail the development of CNNs, their form, and methods to help diagnose AD. It is proposed that CNNs can help diagnose AD by analyzing medical imaging data, particularly structural brain scans such as magnetic resonance imaging (MRI) and functional scans such as positron emission tomography (PET). Finally, it is concluded that CNNs are of great importance for the diagnosis of AD and that they are likely to play an increasingly important role in the early detection of the disease, the understanding of disease mechanisms, and ultimately, in the development of effective AD therapies and interventions. CNNs are playing an increasingly important role in the Their potential impact on healthcare emphasizes the importance of continued research and innovation in neural networks and medical imaging.

Multidisciplinary neurotechnology holds the promise of understanding and non-invasively treating neurodegenerative diseases. In this preclinical trial on Parkinson's disease (PD), we combined neuroscience together with the nascent field of medical virtual reality and generated several important observations. First, we established the Oculus Rift virtual reality system as a potent measurement device for parkinsonian involuntary hand tremors (IHT). Interestingly, we determined changes in rotation were the most sensitive marker of PD IHT. Secondly, we determined parkinsonian tremors can be abolished in VR with algorithms that remove tremors from patients' digital hands. We also found that PD patients were interested in and were readily able to use VR hardware and software. Together these data suggest PD patients can enter VR and be asymptotic of PD IHT. Importantly, VR is an open-medium where patients can perform actions, activities, and functions that positively impact their real lives - for instance, one can sign tax return documents in VR and have them printed on real paper or directly e-sign via internet to government tax agencies. Lastly, we generated a technical framework wherein movements in the real world can be measured side-by-side with those in virtual reality. With this framework, we observed anecdotal evidence of parkinsonian tremors being reduced in real life when our algorithms abolished digital hand tremors in VR.

Background: Handover is a critical process for ensuring quality and safety in healthcare. Considerable research suggests that poor handover results in significant morbidity, mortality, dissatisfaction, and excess financial costs. Despite this, little formal attention, education, and evaluation has been given to handover. There is also paucity of data on the opinions of practitioners on the safety of handover.Objectives: The aim of this study was to measure the perceived risk, degree of patient harm and the systems used to support handover, and to understand how this varied by care setting, type of clinical practice, location, or level of experience. Methods: An open, anonymous and confidential online questionnaire covering: (a) respondent characteristics; (b) peer-to-peer handover; (c) internal referrals; (d) discharges and transfers between organisations; and (e) leading and improving handover was conducted with healthcare practitioners and managers from various settings. Results: We gathered a total of 432 completed responses from 26 countries. The average reported performance of handover was rated as 3.9 out of 5.For each type of handover, 12 - 14% reported errors occurring more than weekly. Of those that knew the outcome of such errors, between 29% and 34% reported that they had witnessed moderate or severe harm. 12% and 17% of respondents believed that handover was high or very high risk (See table 4). These respondents were more likely to have witnessed moderate or severe harm, or to be more senior.A wide combination of handover systems was utilised by respondents. 28% - 32% relied exclusively on EPRs (with or without face-to-face contact). 21% used Office documents such as Word and Excel for peer-to-peer handover, and over 30% used hand-written or manual systems. Conclusions: This study suggests the need to do more — and go further — to improve communication and reduce risk during all types of handovers. Clinical leaders should find ways to train and support handover with effective systems, with less experienced staff being the primary focus. More research is needed to demonstrate the interventions that improve the safety of handover.

We evaluated the usefulness of the novel cholesterol-triglyceride subgroup (CTS) indices that potentially reflect the metabolic status regarding risk of coronary heart disease (CHD) using a retrospective longitudinal study of the Japanese general population. We recruited 12,373 individuals from the annual users of our healthcare center. Among them, the first onset of CHD was recorded in 131 individuals between April, 2014 and March, 2020. The multivariate Cox proportional hazards regression analyses for all normalized lipid indices revealed that the CTSqnt index showed a comparable hazard ratio for the CHD outcome to non-high-density lipoprotein cholesterol (nonHDL-c) and triglycerides. The HR of the CTSqlt index was significantly lower than for CTSqnt, but still comparable to that for low-density lipoprotein cholesterol (LDL-c). In comparison with the other indices, CTSqlt is more sensitive to risk increment while the index value increases. Linear regression analyses for the CTS indices and previously known lipid indices suggest that the CTSqnt and CTSqlt indices reflect the quantity of atherogenic lipoproteins and size of smaller and denser LDLs, respectively. Furthermore, the CTSqnt/HDL-c index can be used as a comprehensive risk indicator that may represent the status of lipid metabolism determined by the CTSqlt and CTSqnt indices and thus may be useful for screening. The CTS indices can be used to evaluate the metabolic status of individuals, which may increase the risk of future CHD.

In recent years, Parkinson's Disease (PD) as a progressive syndrome of the nervous system has become highly prevalent worldwide. In this study, a novel hybrid technique established by integrating a Multi-layer Perceptron Neural Network (MLP) with the Biogeography-based Optimization (BBO) to classify PD based on a series of biomedical voice measurements. BBO is employed to determine the optimal MLP parameters and boost prediction accuracy. The inputs comprised of 22 biomedical voice measurements. The proposed approach detects two PD statuses: 0– disease status and 1– reasonable control status. The performance of proposed methods compared with PSO, GA, ACO and ES method. The outcomes affirm that the MLP-BBO model exhibits higher precision and suitability for PD detection. The proposed diagnosis system as a type of speech algorithm detects early Parkinson’s symptoms, and consequently, it served as a promising new robust tool with excellent PD diagnosis performance.

This paper presents a new optical, multi-functional, high-resolution 3-axis sensor which serves to navigate and can, for example, replace standard joysticks in medical devices such as electric wheelchairs, surgical robots or medical diagnosis devices. A light source, e.g. a laser diode is affixed to a movable axis and projects a random geometric shape on an image sensor (CMOS or CCD). The software in the downstream microcontroller identifies the geometric shape’s center, distortion and size, then calculates X, Y, and Z coordinates. These coordinates can then be processed in attached devices. The 3-axis sensor is characterized by its very high resolution, precise reproducibility and plausibility of the coordinates produced. In addition, optical processing of the signal provides a high level of safety against electromagnetic and radio frequency interference. The sensor presented here is adaptive and can be adjusted to fit a user’s range of motion (stroke and force). This recommendation aims to optimize sensor systems such as joysticks in medical devices in terms of safety, ease of use, and adaptability.

Background: This study was conducted to investigate medical students' lifestyle habits, including sleep quality, eating and drinking pattern, physical activity, and social status. Method: This research project is part two of a multi-institutional cross-sectional observational study conducted among medical students from six medical colleges in Saudi Arabia between September and December 2019. Results: 675 medical students were enrolled electively into the lifestyle study. About half of this number were male students, and the majority aged 18-24 years. Most students (87.6%) slept between 4-8 hours a day, and over 44% were dissatisfied with their sleep. Only 28.1% had three meals a day; about 40% of them usually or always skipped breakfast. While 44% usually or always eat fast food, 44.7% drink 2 liters of water per day. Moreover, male students were significantly consuming fast foods than females, p<0.001. The majority (63.3%) revealed they usually or always drink black coffee daily. Females were significantly more inclined to regular coffee consumption than males, p<0.001. Only 4.3% exercising for 30 minutes or more daily. The majority (65%) of the students were introverted; they had few close friends. Yet, 81% were somewhat satisfied or satisfied with their social life. Male students were predicted to be significantly more satisfied with their social life than females, p=0.001. Only 4.6% smoked cigarettes daily. Whereas 7.1% smoke e-cigarette daily. In contrast, only 0.3% use shisha (hookah) daily. Male medical students were substantially more predicted to be inclined to e-cigarette use than females (p <0.001. The top five leisure activities of a medical student are surfing social media (75.9%), watching movies (61.3%), hanging out with friends (58.1%), spent time with their family (55.4%), and browsing the internet (53.6%). Female medical students were significantly more inclined to surfing social media than male medical students, p=0.022; also, watching movies was preferred for females compared to males, p=0.006. Conclusion: This study revealed that the majority of medical students in Saudi Arabia exhibited healthy lifestyles to some extent, and these health-promoting behaviors differed based on gender, especially concerning physical activity and eating patterns. The findings of this study provide relevant information for future actions that will be geared towards effectively decreasing the occurrence of chronic illnesses and improving future doctor’s well-being.

With the rapid increase in diabetes worldwide, the number of patients with diabetic kidney disease (DKD), a complication of diabetes mellitus, is also on the rise. DKD is a major cause of chronic kidney disease progressing to end-stage renal failure; however, current medical treatments for DKD do not achieve satisfactory outcomes. Molecular hydrogen (H2) is an antioxidant that selectively reduces hydroxyl radicals, a reactive oxygen species with a very potent oxidative capacity. H2 was recently shown to exert not only antioxidant, but also anti-inflammatory, cell lethality-regulating, and signal transduction-regulating effects, and is now being applied clinically. Many factors contribute to the onset and progression of DKD, with mitochondrial dysfunction, oxidative stress, and inflammation being strongly implicated. Recent preclinical and clinical trials reported that substances with antioxidant properties may slow the progression of DKD. Therefore, we conducted a literature review on animal models and human clinical trials in which H2 showed efficacy against various renal diseases. This literature review and our previous findings collectively suggest that H2 exerts therapeutic effects in patients with DKD by improving mitochondrial function. Future large-scale clinical studies are needed to confirm these findings.

Background: medical devices are designed, tested and placed on the market in a highly regulated environment. Wearable sensors are crucial components of various medical devices: design and validation of wearable sensors, if managed according to international standards, can foster innovation while respecting regulatory requirements. Material and methods: the purpose of this paper is to take into consideration the upcoming EU Medical Device Regulation 2017/245 and the current and future IEC and ISO standards that set methods for design and validation of medical devices, with a focus on wearable sensors. Risk classification according to the regulation is described. The international standards IEC 62304, IEC 60601, ISO 14971 and ISO 13485 are reviewed to define regulatory restrictions during design, pre-clinical validation and clinical validation of devices that include wearable sensors as crucial components. Results: current and future regulatory restrictions are described, and an integrated method for design planning, validation and clinical testing is described Discussion: application of this method to design wearable sensors should be evaluated in the future in order to assess its potentially positive impact to fostering innovation and to the time-to-market of the device.

Violence against paramedics is increasingly recognized as an important occupational health problem, but pervasive and institutionalized underreporting hinders efforts at risk mitigation. Earlier research has shown that the organizational culture within paramedicine may contribute to underreporting and researchers have recommended involving paramedics in the development of violence prevention policies, including reporting systems. Eighteen months after the launch of a new comprehensive violence reporting system in Peel Region, Ontario, Canada, we surveyed paramedics about their willingness to report violent encounters. A total of 204 (33% of eligible) paramedics chose to participate, of whom 67% (N=137) had experienced violence since the launch of the new reporting process, with 83% (N=114) reporting the incidents at least some of the time. In choosing to report, participants cited the accessibility of the new reporting process and the desire to promote accountability among perpetrators while contributing to a safer workplace as motivating factors. Their decisions to file a report, however, could be influenced by the perceived ‘volitionality’ and severity of the violent encounters, particularly in the context of (un)supportive co-workers and supervisors. Ultimately, the participants’ belief that the report would lead to meaningful change within the service was a key driver of reporting behavior.

The German health authorities' guidelines for medical devices in 2012 highlighted the importance of cleaning ultrasound probes, emphasizing their validation and reliability. In addition to automated and validated options, alternative manual methods such as wipe disinfection have gained traction due to their independence from additional hardware. The study examines the effectiveness of manual disinfection methods, specifically the cleaning process, addressing concerns raised by the Robert Koch Institute regarding the lack of validation for wipe disinfection of semi-critical devices. The EQUINOS colored wipe disinfection kit identified wetting gaps in all cleanings across four probes tested. The results indicate significant challenges in ensuring complete surface wetting, particularly in complex body parts such as clip-on areas and shapes for additional biopsy attachments, suggesting that manual methods alone may not adequately mitigate the risk of infection transmission (p value .001). The study concludes that while manual disinfection methods are a viable alternative to automated reprocessing, there is a critical need for enhanced training and potentially the development of more effective manual disinfection techniques or colored wipes to ensure patient safety and compliance with healthcare hygiene standards.

Keywords: Marine Coasts; Protected Areas; Defense and Conservation; Asbestos Cement Materials; Wastes; Contamination; Human Health Risk; Medical Geology.

Background and Objectives: Mucilaginous substances from plant extracts are known to be able to support the lubricating effect of hyaluronic acid (HA) in dry eye disease (DED). In this pilot study, the combined lubricating effect of HA and mallow extract (Malva sylvestris L.) in patients with DED was assessed. Materials and Methods: 20 patients at 5 ophthalmological practices in Italy were treated with eye drops, containing HA and mallow extract on the one hand, and with eye drops containing HA only, on the other hand, in a two-period crossover design. As primary endpoints, the tear film breakup time (TBUT), the reduction of lissamine green staining of the ocular surface (Oxford Scheme, OS), and the safety and efficacy assessment by the ophthalmologists were evaluated. As secondary variables, the patient symptom score, the ocular surface index (OSDI), and the satisfaction, preference and efficacy judgement by the patients were evaluated. All data were analysed descriptively in addition to an exploratory analysis of the target variables. Results: Both products were well tolerated. There were no statistically significant differences, with regard to the TBUT, OS and OSDI, between both treatments. Anyway, the efficacy and safety assessments by the ophthalmologists and the patients showed results in favour of the combined product. Conclusion: The addition of mallow extract to HA containing eye drops enhances the treatment of DED at least with respect to subjective measurements. Further assessments will have to be done to prove and explain this observation in terms of measurable parameters, e.g. markers for inflammatory cytokines.

There are complex ethical dilemmas inherent in medicine teaching, particularly in clinical prac-tice involving actual patients. Questions must be raised on fulfilling medical students' training needs while still respecting patients' fundamental rights to autonomy and privacy. We aimed to assess patients' perspectives regarding medical students' involvement in their medical care. An observational, cross-sectional study was developed, and an interview-like questionnaire was ap-plied randomly to patients waiting for a consult/admitted to three distinct departments: General Surgery, Obstetrics/Gynaecology, and Infectious Diseases. Of the 77% interviewed patients who reported previous experiences with medical students, only 59% stated that they were asked for consent for their participation and 28% that students had adequately introduced themselves. Pa-tients from Gynaecology/Obstetrics were the ones who reported lower rates of these practices and were also the ones who were most bothered by students' presence, stating that they would refuse students' participation in the future. Male patients received more explanations than female pa-tients regarding the same matters. 35% of patients stated they would feel more comfortable without the medical students' presence. The study shows a need to pay closer attention to ful-filling patients' fundamental rights.

The Internet of Things (IoT) has a growing presence in society's daily lives. These lightweight devices can be easily deployed and maintained, enabling extensive adoption in different environments. Furthermore, one of the most promising areas for using IoT devices is healthcare, comprising devices referred to as the Internet of Medical Things (IoMT). Several examples of healthcare services are supported by IoMT devices, e.g., continuous health monitoring. Conversely, there is an increasing concern with the cybersecurity aspects of these devices, and several attacks against IoT infrastructures have been launched in the past few years. These cybersecurity concerns also apply to healthcare applications, where the tradeoff between the benefits and security of IoMT devices must be observed. Given the complexity and amount of data IoMT network traffic generates, advanced methods become especially useful in these environments. Although Machine Learning (ML) brings various techniques and solutions to improve cyberattack detection, prevention, and mitigation, essential features are not addressed in the current state-of-the-art benchmark dataset contributions. Thereupon, the main goal of this research is to propose a realistic benchmark dataset to enable the development and evaluation of IoMT security solutions. In order to accomplish this, 18 attacks were executed against an IoMT testbed composed of 40 IoMT devices (25 real devices and 15 simulated devices), considering the plurality of protocols used in healthcare (e.g., Wi-Fi, MQTT, and Bluetooth). These attacks are categorized into five classes: DDoS, DoS, Recon, MQTT, and spoofing. This effort aims to establish a baseline complementary to the state-of-the-art contributions. The outcome supports researchers in investigating and developing new solutions to make healthcare systems more secure using different mechanisms (e.g., machine learning - ML). This research goes beyond merely conducting attacks on IoMT devices. We also attempt to capture the lifecycle of these devices in different vital phases, from the moment they join the network until they leave, which is called profiling. Profiling allows the different classifiers to identify anomalies of each device individually in the healthcare network. The CICIoMT2024 dataset has been published on CIC's dataset page, making it available for other researchers to use.

.Abstract: Indonesia, one of the Asia Pacific LMICs, has suffered from a chronic medical workforce shortage. However, there are limited published studies describing the approaches implemented by the Indonesian government regarding the recruitment and retention of the medical workforce. This case study aimed to understand the current practices for recruitment and retention of the medical workforce in Indonesian rural and remote provinces. We conducted a case study of the Maluku Province of Indonesia with document analysis and key informant interviews with officials responsible for medical workforce recruitment and retention. We used the WHO’s guidelines as an analytical matrix to examine the recruitment and retention practices under four domains, i) educational, ii) regulatory, iii) financial, and iv) professional and personal development, and classified them into University/Medical School level and Government/Non-government level. Our findings suggest that Indonesia has implemented most of the WHO-recommended medical workforce recruitment and retention strategies. However, implementation is still problematic; hence, the aim of establishing an adequate, sustainable medical workforce has not been reached. Nationwide government intervention in educational aspects is important to magnify the impact of the regional medical school initiatives. Relevant programs must be re-evaluated and re-enforced concerning significance, comprehensiveness and effectiveness for sustainable rural and remote medical workforce.

In Thailand, the topic of medical ethics and laws related to medical professions has been one part of the national competency assessment criteria. The objective of this article was to design legal issues into the medical curriculum and to share experiences of creative legal study. Legal contents were inserted into 10 subjects and taught for year 1 to year 6 medical students. Students were divided into multi-groups or received individual tasks and then, shared their knowledge and idea for solving legal problems. The results showed they could interpret and create novel ideas for legal and ethical reconstruction, including the topic of the principle of laws, criminal laws, civil and commercial laws, public health laws, organ donation/transplantation, end of life decisions, and legal liability for the medical profession. Finally, the creative legal study can be used as a novel approach to support creativity among medical students.

Background: During anatomy (topographic) chair, we prepared an anatomic piece of an older female pelvis (unknown causa mortis). Here, we present an anatomic piece prepared by medical students that helped us to better understand hypertrophic bladder pathophysiology. Methods: A traditional corpse dissection guided by an assistant professor. Results: Corpse dissection enhanced our personal experience during the medical course. It also helped us to better visualize how big a hypertrophic urinary bladder can become as the etiologic cause is not taken care. Conclusions: Despite virtual and 3D anatomy lessons, we believe corpse dissection must remain as a teaching strategy that can help to build a new generation of surgeons as well as honor the History of Medicine.

Skilled academic/medical writing is critical to research communication. The fundamental sections of a scholarly manuscript are introduction, methods, results and discussion. The introduction of a medical manuscript is aimed at briefing readers on the clinical extent and public health context of the research problem. It must justify the essentialness of the research to the scientific community and reveal any underlying research novelty. Skillfully conceived, designed and performed research protocols that are unskillfully presented can lose scientific credibility and impact. Without research communication skills authors would not be able to display the usefulness of their research for the scientific community. Generally, research communication or medical writing training/skills is underrepresented in curricular systems of medical schools globally. This can challenge publication quality and quantity of early-career authors/researchers. The author presents the academic experience he accumulated through peer review and supervision of vast manuscripts and theses. This article aimed at presenting a comprehensive roadmap for academic writing of the introduction and at identifying its common pitfalls.

Peritoneal fluid is an ovarian exudate from the growing follicle or corpus luteum. Therefore, the free concentrations of estrogens and progesterone are always much higher than in plasma, especially after ovulation. The peritoneum is not vascularised, and peritoneal implants and the superficial portion of deep endometriosis are likely influenced mainly by peritoneal fluid. Follicular phase progesterone concentrations are as high as during the luteal phase in plasma. This explains that most peritoneal implants are rarely proliferative and out of phase with the endometrium. From some 5 mm of depth onwards, endometriosis is rather influenced by plasma hormone concentra-tions, and the deeper parts can be proliferative as the endometrium. Because of these progesterone concentrations, progesterone resistance has to be postulated, permitting endometriosis lesions to initiate and develop. This opens the discussion of whether endometriosis is similar to the basal endometrium. These peritoneal fluid concentrations are important to understand the natural history and medical therapy of endometriosis. Most medical therapies decrease ovarian function and affect peritoneal fluid steroid hormone concentrations. It is suggested that the efficacy of medical therapy for endometriosis-associated pain is a consequence of the decreased estrogen concentrations in the peritoneal cavity and that the local effect of progestins may not be determinant for pain relief. If this is true, a history of endometriosis should not be considered a contraindication for hormone re-placement therapy.

ABSTRACT:This paper presents arguments for why it is important to include disability in the undergraduate medical curriculum. I, the first author am currently involved with my doctoral thesis proposal titled "Proposing clinician competency guidelines for the inclusion of disability in the undergraduate medical curriculum of South Africa. An exploratory study.” As part of my research, I conducted a literature search and developed arguments to strengthen the reasons why the research I propose in my thesis is necessary. It is important that I position myself in this research. I am a South African, Caucasian, female medical doctor, with an interest in physical rehabilitation medicine and I am a person with a physical disability. Although this research study will be conducted in South Africa, I am hopeful that the findings will be transferable to medical schools across the world.

Diabetic retinopathy (DR) is the primary factor leading to vision impairment and blindness in diabetic people. Uncontrolled diabetes can damage the retinal blood vessels. Initial detection and prompt medical intervention are vital in preventing progressive vision impairment. Today's growing medical field poses more significant workload and diagnostic demands on medical professionals. In the proposed study, a convolutional neural network (CNN) is employed to detect the stages of DR. This research is crucial for studying DR because of its innovative methodology incorporating two different public datasets. This strategy enhances the model's capacity to generalize unseen DR images, as each dataset encompasses unique demographics and clinical circumstances. The network can learn and capture complicated hierarchical image features with asymmetric weights. Each image undergoes preprocessing using contrast-limited adaptive histogram equalization (CLAHE) and the discrete wavelet transform (DWT). The model is trained and validated using the combined datasets of Dataset for Diabetic Retinopathy (DDR) and the Asia Pacific Tele-Ophthalmology Society (APTOS). The CNN model is tuned with different learning rates and optimizers. The CNN model with Adam optimizer achieved 70% accuracy and an area under curve (AUC) score of 0.82. The recommended study results may reduce diabetes-related vision impairment by early DR severity identification.

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

The landscape of medical education has witnessed significant transformations over the past decades, particularly with the advent of active teaching methodologies. However, despite these advancements, the traditional theoretical assessment methods have remained largely unchanged. This lack of evolution in assessment systems poses a challenge, as it is crucial for assessment methods to evolve in tandem with teaching approaches to ensure a comprehensive and effective learning process in medical education. This paper reviews the integration and effectiveness of open-book examinations (OBEs) in medical education, reflecting their growing significance. An integrative review of the literature was conducted, drawing from a range of relevant publications over the last decade, sourced from databases such as PubMed, Web of Science, Scopus, and ERIC. The inclusion criteria focused on full-text articles in English, with search terms including "medicine," "assessment," "open book examination," "open book exam," and "open book assessment," combined using Boolean operators. Thirteen publications were selected and critically appraised using The Critical Appraisal Skills Program checklist. The analysis identified three primary thematic categories: ' Teaching Strategy for Pandemic and Challenging Conditions,” Tool of Learning & Educational Impact” and “Operational Challenges & Future Directions”. These themes were explored to understand the role and impact of OBEs in medical education. The findings indicate that open-book examinations are a crucial component in the evolving landscape of medical education. While certain reservations remain, OBEs have shown significant potential in fostering critical thinking, argumentation skills, and lifelong learning among medical students. They reflect the ongoing evolution of knowledge in the medical field and contribute to the development of professionals’ adept at navigating and applying complex information. Further research is recommended to solidify these findings and to expand the understanding of OBEs in medical education.

Violence against paramedics is widely recognized as a serious, but underreported, problem. While injurious physical attacks on paramedics are generally reported, non-physical violence is less likely to be documented. Verbal abuse can be very distressing, particularly if the harassment targets personal or cultural identities, such as race, ethnicity, gender, or sexual orientation. Leveraging a novel, point-of-event reporting process, our objective was to estimate the prevalence of harassment on identity grounds against paramedics in a single paramedic service in Ontario, Canada, and assess its potentially differential impact on emotional distress. In an analysis of 502 reports filed between February 1, 2021, through February 28, 2022, two paramedic-supervisors independently coded the free-text narrative descriptions of violent encounters for themes suggestive of sexism, racism, and homophobia. We achieved high interrater agreement across the dimensions (k=0.73-0.83), and after resolving discrepant cases, we found that 1 in 4 violent reports documented abuse on at least one of the identity grounds. In these cases, paramedics were 60% more likely to indicate being emotionally distressed than for other forms of violence. Our findings offer unique insight into the type of vitriol paramedics experience in the course of their work and its potential for psychological harm.

Accurate medical image segmentation is paramount for precise diagnosis and treatment in modern healthcare. This research presents a comprehensive study on the efficacy of Particle Swarm Optimization (PSO) combined with Histogram Equalization (HE) preprocessing for medical image segmentation, focusing on Lung CT-Scan and Chest X-ray datasets. Best Cost values reveal the PSO algorithm’s performance, with HE preprocessing demonstrating significant stabilization and enhanced convergence, particularly in complex Lung CT-Scan images. Evaluation metrics, including Accuracy, Precision, Recall, F-Score, Specificity, Dice, and Jaccard, show substantial improvements with HE preprocessing, emphasizing its impact on segmentation accuracy. Comparative analyses against alternative methods, such as Otsu, Watershed, and K-means, confirm the competitiveness of the PSO-HE approach, especially in Chest X-ray images. The study also underscores the positive influence of preprocessing on image clarity and precision. These findings highlight the promise of the PSO-HE approach in advancing the accuracy and reliability of medical image segmentation, paving the way for further research and method integration to enhance this critical healthcare application.

Image registration (IR) is a process that deforms images to align them with respect to a reference space, making it easier for medical practitioners to examine various medical images in a standardized reference frame, such as having the same rotation and scale. This document introduces image registration using a simple numeric example. It provides a definition of image registration along with a space-oriented symbolic representation. This review covers various aspects of image transformations, including affine, deformable, invertible, and bidirectional transformations, as well as medical image registration algorithms such as Voxelmorph, Demons, SyN, Iterative Closest Point, and SynthMorph. It also explores atlas-based registration and multistage image registration techniques, including coarse-fine and pyramid approaches. Furthermore, this survey paper discusses medical image registration taxonomies, datasets, evaluation measures, such as correlation-based metrics, segmentation-based metrics, processing time, and model size. It also explores applications in image-guided surgery, motion tracking, and tumor diagnosis. Finally, the document addresses future research directions, including the further development of transformers.

A medical entity (hospital, nursing home, rest home, revalidation center, etc.) usually includes a multitude of information systems that allow for quick decision-making close to the medical sensors. The Internet of Medical Things (IoMT) is an area of IoT that generates a lot of data of different natures (radio, CT scan, medical reports, medical sensor data). However, these systems need to share and exchange medical information in a seamless, timely, and efficient manner with systems that are either located within the same entity or located in other healthcare entities. The lack of inter and intra entity interoperability causes major problems in the analysis of patient records and leads to additional financial costs (e.g., redone examinations). In order to develop a medical data interoperability architecture model that will allow providers and different actors in the medical community to exchange patient summary information with other caregivers and partners in order to improve the quality of care, the level of data security, and the efficiency of care, we take stock of the state of knowledge.

After conducting a detailed survey among the villagers of Pallissery and Karukutty, it was observed that in most of the villages the native people have to travel long distances for their basic health needs. Also most of the villagers lack knowledge regarding live health updates. At times, these problems have even resulted in death of many people including pregnant women and children. The objective of our research is to propose an integrated and easy to use Medical Kiosk that can be installed at various locations in rural areas. The Kiosk will provide an integrated environment for all medical related activities and would perform numerous functions like sending notifications regarding medical camps, mobile medical help, important dates for vaccinations, child care, insurance policies and provide other live medical updates to the villagers. It would also support the basic facilities for measurement of body parameters like height, weight, BMI, blood pressure, and heartbeat and also facilitate live consultation facilities with specialized doctors through video and voice chats.

The Smart Angel connected medical device allows ambulatory surgery patients to monitor their health by taking their own blood pressure and oxygen levels and by answering a health questionnaire from home. This preventive device must necessarily be "usable" by patients with different profiles. The objective of this article is, therefore, to better understand the links between certain characteristics of potential patients and usability. We conducted an experimental study involving thirty-six participants, investigating the effects of four patient characteristics (i.e. age, education, technophilia and health literacy) on usability measured in terms of effectiveness, efficiency, and satisfaction. The results show a moderate correlation between age, health literacy and usability. However, there is a weak correlation between technophilia and usability and no relationship between the level of education and usability. This study provides theoretical insights into the effects of user characteristics by means of personas in usability (ISO 9241-11).

In February 2004, the Food and Drug Administration (FDA) was the first to approve the combination of cisplatin (CDDP) and pemetrexed (PEM) as standard first-line chemotherapy for untreated, unresectable malignant pleural mesothelioma (MPM). However, after that approval, no progress was made in the standard first-line treatment of MPM for almost 15 years. Positive results from a phase 3 study (Mesothelioma Avastin Cisplatin Pemetrexed Study: MAPS) verifying the effect of bevacizumab, an anti-angiogenesis agent added to CDDP/PEM for unresectable MPM, were published in The Lancet in December 2015; however, this did not lead to approval by national drug regulatory agencies. Furthermore, no second-line treatment was established for cases refractory to CDDP/PEM. In August 2018, the Pharmaceuticals and Medical Devices Agency of Japan was the first in the world to approve monotherapy with nivolumab, an immune checkpoint inhibitor (ICI), for previously unresectable, advanced, or recurrent MPM. Following Japan, in October 2020, the FDA approved the combination of nivolumab and ipilimumab for the treatment of previously untreated, unresectable MPM. In this article, we review the transition of drug treatment for MPM, in light of the historical background, focusing on the benefits of ICIs.

The Medi-test system we developed was motivated by the large number of resources available for the medical domain, as well as the number of tests needed in this field (during and after the medical school) for evaluation, promotion, certification, etc. Generating questions to support learning and user interactivity has been an interesting and dynamic topic in NLP since the availability of e-book curricula and e-learning platforms. Current e-learning platforms offer increased support for student evaluation, with an emphasis in exploiting automation in both test generation and evaluation. In this context, our system is able to evaluate a student’s academic performance for the medical domain. Using as input medical reference texts and supported by a specially designed medical ontology, Medi-test generates different types of questionnaires for Romanian language. The evaluation includes 4 types of questions (multiple-choice, fill in the blanks, true/false and match), can have customizable length and difficulty and can be automatically graded. A recent extension of our system also allows for the generation of tests which include images. We evaluated our system with a local testing team, but also with a set of medicine students, and user satisfaction questionnaires showed that the system can be used to enhance learning.

Diagnostics is believed to drive about 70% of medical interventions, but this may not be true for all demographics. With more than 30% of the African population living in extreme poverty ($1.9 per day - 2022); and healthcare costs competing unfavorably against unbridled access to antibiotics and herbal concoctions, especially in Sub-Saharan Africa, how do you convince such a people to choose diagnostics first? More importantly, how do you design a medical device targeted at meeting the diagnostic needs of this demographic? In developing diagnostic devices for such a market, what is worth sacrificing? How dire is the need for advanced technologies in devices developed for such a demographic? These are questions that remain unaddressed by the technological breakthroughs and current research in medical device development, especially for infectious disease diagnostics. The objective of this paper is to underscore critical concerns which must be considered in the bid to successfully design medical diagnostic devices for Africa and perhaps, other limited-resource settings. It is also written as a suggestive guidance document for researchers whose interest is in the development of infectious disease diagnostic platforms for rural Africa and similar limited-resource environments.

The COVID19 pandemic had a major impact on emergency medical communication centres (EMCC). A live video facility was made available to second-line physicians in an EMCC with a first-line paramedic to receive emergency calls. The objective of this study was to measure the contribution of live video to remote medical triage. The single-centre retrospective study included all telephone assessments of patients with suspected COVID19 symptoms from 01.04.2020 to 30.04.2021 in Geneva, Switzerland. The organisation of the EMCC and the characteristics of patients who called the two emergency lines (official emergency number and COVID19 number) with suspected COVID19 symptoms were described. A prospective web-based survey of physicians was conducted during the same period to measure the indications, limitations and impact of live video on their decisions. 8,957 patients were included. 2,157 (48.0%) of the 4,493 patients assessed on the official emergency number had dyspnoea. 4,045 (90.6%) of 4,464 patients assessed on the COVID19 number had flu-like symptoms. 1,798 (20.1%) patients were reassessed remotely by a physician, including 405 (22.5%) with live video, successfully in 315 (77.8%) attempts. The web-based survey (107 forms) showed that physicians used live video to assess mainly the breathing (81.3%) and general condition (78.5%) of patients. They felt that their decision was modified in 75.7% (n=81) of cases, and caught 7 (7.7%) patients in life-threatening emergency. Medical triage decisions for suspected COVID19 patients are strongly influenced by the use of live video.

The integration of artificial intelligence (AI) into medical imaging has guided in an era of transformation in healthcare. This literature review explores the latest innovations and applications of AI in the field, highlighting its profound impact on medical diagnosis and patient care. The innovation segment explores into cutting-edge developments in AI, such as deep learning algorithms, convolutional neural networks, and generative adversarial networks, which have significantly improved the accuracy and efficiency of medical image analysis. These innovations have enabled rapid and accurate detection of abnormalities, from identifying tumors during radiological examinations to detecting early signs of eye disease in retinal images. The article also highlights various applications of AI in medical imaging, including radiology, pathology, cardiology, and more. AI-based diagnostic tools not only speed up the interpretation of complex images but also improve early detection of disease, ultimately delivering better outcomes for patients. Additionally, AI-based image processing facilitates personalized treatment plans, thereby optimizing healthcare delivery. This literature review highlights the paradigm shift that AI has brought to medical imaging, highlighting its role in revolutionizing diagnosis and patient care. By combining cutting-edge AI techniques and their practical applications, it is clear that AI will continue shaping the future of healthcare in profound and positive ways.

This review explores the integration of Virtual and Mixed Reality in medical training. The advent of immersive technologies has revolutionized traditional methodologies, offering immersive, interactive, and flexible learning environments. This study aims to assess the impact, efficacy, and potential of Extended Reality (XR) in medical education. Methods included a comprehensive analysis of current Metaverse’s applications in various medical fields, including surgery, diagnostics, and patient care. Results indicate a significant enhancement in learning outcomes, practical skills, and student engagement. Conclusions suggest that Virtual Reality is a valuable tool for medical training, providing realistic simulations and improving both theoretical knowledge and practical skills. The intersection of virtual reality and cognitive neuroscience presents an exciting frontier for understanding the human brain's response to immersive environments. This review explores how VR impacts learning, with a particular focus on the activation and engagement of the prefrontal cortex during immersive experiences. It delves into various studies that highlight the transformative potential of VR in educational settings and therapeutic applications, demonstrating how VR can facilitate deeper and more effective learning experiences. The review will present a dedicated section on the current methodologies used to analyze the brain's response while immersed in a virtual environment.

In 2020, students of Pakistan had to adapt to the online environment for the very first time. This study aims to analyze the perceptions of medical, dental, and allied health students about online education in Pakistan. A descriptive, cross-sectional study was done to assess the level of acceptance of undergraduate students. A pre-validated questionnaire regarding demographics, past-experience of e-learning, advantages disadvantages of e-learning, and general perception of students towards e-learning was distributed. Descriptive statistics were computed for demographics, Mann-Witney-U test was used to compare the differences of perceptions between pre-clinical year and clinical years students. Kruskal-Wallis test was applied to compare the results of three specialties of students. Chi-square was used to compare overall category-wise positive and negative responses of students. 1200 students participated in the study. The major advantage identified by all students was the ‘comfortable environment’ in which they studied online. The major disadvantage selected by preclinical year students was ‘anxiety due to social isolation’ and that chosen by clinical year students was ‘lack of patient interaction’. Overall, 72% of students had a negative perception of e-learning. Student-teacher training, student counselling sessions, and innovative techniques need to be introduced to enhance student engagement and reduce pandemic stress.

Aim: The purpose of this examination is determining predictors to oral health behaviors predict in Iranian students in district 1 Tehran based on the health belief model with added commitment to plan construct. Methods: This cross-sectional study were randomly selected conducted on 351 eligible four grade female students in the first district of Tehran, Iran in 2017. The random Multi‑stage random cluster sampling method was used to recruit students. The inclusion criteria were being graded, four female students (aged 9-11 years), or education at the fourth grade of one of the elementary schools studied in the first district of Tehran and, The health of the student from a physical and psychological of view. Logistic regression analysis was used to identify the variables that predict oral health behaviors. To assess the predictors of oral health behaviors, all the expanded Health Belief Model constructs with the construct of “Commitment to Plan of Action” from “Health Promotion Model were examined as risk factors to see if they influence on the probability of brushing behavior and dental floss behavior occurrence and were interpreted through odds ratio (OR). SPSS version 19 was used to analyze the data. Results: Totally 308 four grade female students with mean age of 9.32 ± 0.81 years old took part in the study. The total 31.8% of the students reported that they were brushing behavior less than twice a day and 55.2% students claimed, use of dental floss behavior once a week or less than once a day. The results indicated that perceived self-efficacy (OR=1.46, 95% CI=0.57-3.78, P<0.001), Commitment to plan (OR=1.13, 95% CI=1.04-1.23, P<0.001) and Cues to action (OR=1.42, 95% CI=1.14–1.76, P=0.002) were the significant predicting variables which is the key factor of brushing twice a day, and use of dental floss once a day or more (OR=1.02, 95% CI=0.23-3.53, P=0.003). Conclusion: This study has shown the effectiveness of the health belief model with added commitment to plan construct to predict oral health behavior in female students. So, it seems that the model as a framework for designing training programs to improve students to improve oral health behavior can be used.

Medical image analysis is an important branch in the field of medicine, which mainly uses image processing and analysis techniques to interpret and diagnose medical image data. Medical image data helps doctors to effectively observe and diagnose patients' body structures, tissues and lesions. Medical image analysis has been an important research area in the medical field, and it is important for disease diagnosis, treatment planning, and condition monitoring. In recent years, the rapid development of deep learning and computer vision technologies has contributed greatly to the automation, multimodal data fusion, real-time application, and accuracy improvement of medical image analysis. In addition, the development of deep learning has given rise to some new research areas in medical image analysis, such as Generative Adversarial Networks (GANs) for synthetic medical images, self-supervised learning for unsupervised feature learning, and neural network interpretability. In this paper, we will introduce some optimisation methods for medical images which are effective in improving the accuracy, efficiency and reliability of medical image analysis.

The aim of this review was to summarize the available literature regarding resident and medical student education utilizing the spaced repetition program Anki. This review enables current residents and medical students to recognize and utilize evidence-proven study techniques to increase learning efficacy. A systemic review of papers across all medical journals available on Pubmed was conducted to identify studies published without time constraints. The search was for (Anki) and (spaced repetition residency). Available outcome data was collected and discussed independently for students and residents. Many studies showed a statistically significant increase in exam performance associated with Anki use and high levels of satisfaction among residents and medical students. Further research is warranted to provide high-quality evidence of Anki’s applications and there is a need for exploration in additional residency specialties. Anki use has steadily increased with both medical students and residents. The application demonstrated consistent improvement on exam-based performance and was regarded highly by users. As burnout and time constrictions threaten educational workflow, Anki may serve as a powerful tool to improve the quality of learning. Further data needs to be collected and analyzed in specialties where Anki use may already exist.

COVID-19 greatly challenges human beings in the health sector and leaves behind a large amount of medical waste that poses many potential threats to the environment. In this paper, we compiled relevant data released by official agencies and the media, and conducted data supplementation based on previous studies to calculate the net value of medical waste production in Hubei Province during COVID-19 with the help of a neural network model. Then, we reviewed the data related to the environmental impact of medical waste per unit and designed four scenarios to estimate the environmental impact of new medical waste generated during the epidemic. The results showed that at a medical waste generation rate of\ 0.\ 5\ kg/(\ bed\ \cdot\ d) COVID-19 resulted in a net increase in medical waste volume of about 3366.99 tons in Hubei Province. In the four scenario assumptions, if the medical waste brought by COVID-19 is completely incinerated, it will have a large impact on the air quality. If it is disposed by distillation sterilization, it will produce a large amount of wastewater and waste residue. Based on the results of the study, three policy recommendations are proposed in this paper: strict control of medical wastewater discharge, reduction and transformation of the emitted acidic gases, and attention to the emission of metallic nickel in exhaust gas and chloride in soil. These policy recommendations provide a scientific basis for controlling medical waste pollution.

This research employs a spatial optimization approach customized for addressing equitable emergency medical facility location problems, through the p-dispersed-median problem (p-DIME). The p-DIME integrates two conflicting classes of spatial optimization problems, dispersion, and median problems, aiming to identify the optimal locations for emergency medical facilities to achieve a balanced spatial distribution of emergency medical services (EMS) while effectively serving demands. To demonstrate the utility of the p-DIME model, we selected Gyeongsangbuk-do in South Korea, recognized as one of the most challenging areas for providing EMS to the elderly population (aged 65 and over). This challenge arises from the significant spatial disparity in the distribution of emergency medical facilities. The results of the model assessment gauge the spatial disparity of EMS, provide significantly enhanced solutions for a more equitable EMS distribution in terms of service coverage, and offer policy implications for future EMS location planning. In addition, to address the computational challenges posed by p-DIME's inherent complexity, involving mixed-integer programming, this study introduces a solution technique through constraint formulations aimed at tightening the lower bounds of the problem's solution space. The computational results confirm the effectiveness of this approach in ensuring reliable computational performance, with significant reductions in solution times, while still producing optimal solutions.

Artificial intelligence-powered generative language models (GLMs), such as ChatGPT and Google Bard, have the potential to provide personalized learning, unlimited practice opportunities, and interactive engagement 24/7, with immediate feedback. However, to fully utilize GLMs, properly formulated instructions are essential. Prompt engineering is a systematic approach to effectively communicating with GLMs to achieve the desired results. Well-crafted prompts yield good responses from the GLM, while poorly constructed prompts will lead to unsatisfactory responses. Besides the challenges of prompt engineering, significant concerns are associated with using GLMs in medical education, including ensuring accuracy, mitigating bias, maintaining privacy, and avoiding excessive reliance on technology. Future directions involve developing more sophisticated prompt engineering techniques, integrating GLMs with other technologies, creating personalized learning pathways, and researching the effectiveness of GLMs in medical education.

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.

Cosmetic surgery is the subfield of plastic surgery that enhances appearance mainly for aesthetic reasons. Currently, cosmetic surgery interventions are highly considered appealing and popular all around the world. Several factors have contributed in this rapidly evolving field such as scientific and economic development, breaking down barriers and cultural norms, globalization, social media and mental disorders. Nowadays, the morality of cosmetic surgery is facing many dilemmas due to its benefits and drawbacks. It is proven that the advantages of cosmetic surgery include improved body confidence, mental health, and function. Additionally, aesthetic corrections can upscale the quality of life and create career opportunities for special targeted groups. Also, cosmetic surgery has a major impact in gender affirmation procedures. Although, herein we also describe the disadvantages of this widely developing field such as minor and major medical complications, potential postoperative risks and addiction in plastic surgeries associated with damaging economic issues. Lack in self-confidence, altered mental health status and ethical crisis consist another negative aspects of aesthetic surgery’s impact.

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.

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.

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.

In this paper we report on the use of an in-house developed solid-state hybrid microwave and radiofrequency generator operating at frequencies of 2.45 GHz and/or 480 kHz for cancer ablation in various tissues. The generator has demonstrated increased accuracy due to its custom-designed hardware, which incorporates the latest technologies and algorithms to control the emitted power versus temperature profile of the treated sample. In particular, the hybrid generator incorporates control systems based on impedance or reflected power measurements that allow controlled ablation without causing unwanted carbonisation and without including areas where tissue damage is not desired. Tests performed ex-vivo on chicken breast and bovine liver show that radiofrequency ablation (RFA) is very effective for performing controlled ablations with minimally invasive probes, such as cardiac pathologies, small lesions, tissues with particular composition, while microwave ablation (MWA) is optimal for performing large ablations in highly vascularised tissues, such as liver cancer, where it is necessary to achieve higher temperatures.

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.

Background and objectives: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome ME/CFS is a common complex multi-system disease with a significant impact on the quality of life of patients and their families, yet the majority of ME/CFS patients go unrecognised or undiagnosed. For two decades the medical education establishment in the UK has been challenged to remedy these failings, but little has changed. This study was designed to ascertain the current UK medical school education on ME/CFS and to identify challenges and opportunities to inform the future of medical education. Materials and methods: A questionnaire, developed under the guidance of the Medical Schools Council, was sent to all 34 UK Medical Schools to collect data for the academic year 2018-2019. Results: Responses were provided by 22 out of a total of 34 medical schools (65%). 59% of respondents taught ME/CFS, led by specialists drawn from 6 medical disciplines. Teaching delivery was usually by lecture; however, discussion case studies and e-learning were used. 7 schools included questions on ME/CFS in their examinations and 3 schools reported likely clinical exposure to ME/CFS patients. 64% of respondents were interested in receiving further teaching aids in ME/CFS. None of the schools shared details of their teaching syllabus so it was not possible to ascertain what students were being taught. Conclusions: UK medical school teaching in ME/CFS is shown to be inadequate. Several medical disciplines, with known differences about the disease, need to set these aside to give greater clarity in teaching undergraduates so they can more easily recognise and diagnose ME/CFS. Improvements are proposed in ME/CFS medical education consistent with the international paradigm shift in biomedical understanding of this disease. Many medical schools (64% of respondents) acknowledge this need by expressing a strong appetite for the development of further teaching aids and materials. The GMC and MSC are called upon to use their considerable influence to bring about the appropriate changes to medical school curricula so future doctors can recognise, diagnose and treat ME/CFS. The GMC should also consider creating a registered speciality encompassing ME/CFS, post viral fatigue and Long Covid.

The primary goal of picture compression is to reduce the amount of unused image data while still storing or transmitting it in a format that is appropriate. The compression of raw binary data is quite different from the compression of a picture, and these differences may be rather substantial. In light of this, compression is often regarded as an essential technique for the purposes of both data storage an d transmission in order to mitigate the excessive amounts of data that are generated by these images. In order to transmit enormous datasets, particularly for the purposes of telemedicine and teleradiology, one needs a significant amount of storage capacity as well as an expansive network. As a result, compression is an important aspect of medical imaging. In addition to the importance of compression, the quality of the photos themselves is also an essential factor in the success of analysis. In addition to this, the amount of time necessary to compress the photographs before sending them should be reduced.

Introduction: Like other public safety professions, paramedicine has historically been a male-dominated occupation, both in the demography of its workforce and in its organizational culture. Although women are increasingly choosing paramedicine as a career, participation in leadership roles remains limited. Drawing on data from a recent comprehensive mental health survey, we describe the proportion of women in leadership in a single, large, urban paramedic service in Ontario, Canada. Methods: We distributed an in-person, paper-based survey during the fall 2019 - winter 2020 Continuing Medical Education (CME) sessions. Participating paramedics completed a demographic questionnaire alongside a battery of mental health screening tools. We assessed the demography of the workforce and explored differences in employment classification, provider level (e.g., primary vs. advanced care), and participation in formal leadership roles along self-reported gender lines. Results: Out of 607 paramedics attending CME, we received 600 completed surveys, with 11 excluded for missing data, leaving 589 for analysis and a 97% response rate. Women comprised 40% of the active-duty paramedic workforce, with an average of 8 years of experience. Compared to men, women were more than twice as likely to have a university degree (Odds Ratio [OR] 2.02), but almost half as likely to practice at the Advanced Care Paramedic level (OR 0.61), and somewhat less likely to be employed full-time (OR 0.77). Women were nearly 70% less likely to hold a leadership role in the service compared to men (OR 0.36), occupying just 20% of leadership positions. Conclusion: Although paramedicine is witnessing an encouraging shift in the demography of its workforce with greater participation from women, there is still work to be done, particularly in leadership. Future research should focus on identifying and ameliorating barriers to career advancement among women and other historically underrepresented people.

The situation in the world of pandemics is rapidly changing, and the second wave of COVID-19 has put a lot of pressure on the government and private sector, which are primarily responsible for controlling the situation. COVID-19 positive cases have increased in recent months relative to last year, and the number of patients admitted to hospitals has also increased, despite the fact that few of them were denied admission due to shortage of beds. Normal people who experience any symptoms immediately isolate themselves and begin taking the COVID medications prescribed by medical personnel and their team. During these times, all domestic people tossed the wrappers and boxes of medicines into the regular trash can, and the waste was handed over to the waste collector, who treated it like any other domestic waste and disposed of it using open dumping or other methods. The goal of this perspective is to suggest the collections of these types of waste from domestics, and protect the natural resources like water, soil, and even living beings like animals from pollution (from the effect of SARS-CoV-2). The main challenge for environmental waste management agencies is determining who has COVID positive and which houses generate these types of waste; thus, proposed strategy may be beneficial to the long-term sustainability of natural resources and animals.

As medical schools cope with the consequences of the COVID-19 pandemic, a new cohort of students will be admitted in the fall. Administrators are again challenged to make unprecedented enrollment decisions without standardized exams. This challenge provides unique opportunities to support holistic admissions but also abruptly bypasses a process that has been employed since 1928. This article highlights key factors that are being considered during current medical school admission cycles, including limited opportunities to take standardized exams, heightened student anxiety, and potential exam alternatives. These factors are framed and discussed within the context of the medical college admission test (MCAT) exam.

High-quality chromosome-scale haplotype sequences— of diploid genomes, polyploid genomes and metagenomes — provide important insights into genetic variation associated with disease and biodiversity. However, whole-genome short read sequencing does not yield haplotype information that spans whole chromosomes directly. Computational assembly of shorter haplotype fragments is required for haplotype reconstruction, which can be challenging owing to limited fragment lengths and high haplotype and repeat variability across genomes. Recent advancements in long-read and chromosome-scale sequencing technologies, alongside computational innovations, are improving the reconstruction of haplotypes at the level of whole chromosomes. Here, we review recent methodological progress in these areas and discuss perspectives that could enable routine high-quality haplotype reconstruction in clinical and evolutionary studies.

On the 30^thanniversary of the Karolinska Institutet Summer Research School for High School students an evaluation was carried out of the school’s activities. The evaluation was performed by questionnaire sent to 533 former students and also by searching the KI course registration database for all former students who went on to register in under- or postgraduate education at KI. Approximately half of all former Summer School students performed their undergraduate studies at KI, predominantly in the medical program. Those were far more likely to choose a research-oriented education than their peers. KI Medical students who previously attended the Summer School were also more likely to later register for PhD education than their peers who did not attend the summer school.

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.

Advancements in deep learning and availability of medical imaging data have led to use of CNN based architectures in disease diagnostic assisted systems. In spite of the abundant use of reverse transcription-polymerase chain reaction (RT-PCR) based tests in COVID-19 diagnosis, CT images offer an applicable supplement with its high sensitivity rates. Here, we study classification of COVID-19 pneumonia (CP) and non-COVID-19 pneumonia (NCP) in chest CT scans using efficient deep learning methods to be readily implemented by any hospital. We report our deep network framework design that encompasses Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory (biLSTM) architectures. Our study achieved high specificity (CP: 98.3%, NCP: 96.2% Healthy: 89.3%) and high sensitivity (CP: 84.0%, NCP: 93.9% Healthy: 94.9%) in classifying COVID-19 pneumonia, non-COVID-19 pneumonia and healthy patients. Next, we provide visual explanations for the CNN predictions with gradient-weighted class activation mapping (Grad-CAM). The results provided a model explainability by showing that Ground Glass Opacities (GGO), indicators of COVID-19 pneumonia disease, were captured by our CNN network. Finally, we have implemented our approach in three hospitals proving its compatibility and efficiency.

Chronic non-cancer pain is a highly debilitating condition affecting approximately 20% of the global population. Chronic pain may lead to significant physical disability, emotional distress, social isolation and financial burden. Whilst^. pharmacological therapies remain the cornerstone of pain management in non-cancerous chronic pain, factors including the current opioid epidemic have led to non-pharmacological techniques becoming a more attractive proposition. We explored the prevalence of medical device use and their treatment efficacy in non-cancer pain management. A systematic methodology was developed, peer reviewed and published in PROSPERO (CRD42021235384). Key words of medical device, pain management devices, chronic pain, lower back pain, back pain, leg pain and chronic pelvic pain using Science direct, PubMed, Web of Science, PROSPERO, MEDLINE, EMBASE, PorQuest and ClinicalTrials.gov. All clinical trials, epidemiology and mixed methods studies that reported the use of medical devices for non-cancer chronic pain management published between the 1^st of January 1990 and the 30^th of April 2022 were included. 13 studies were included in systematic review, of these 6 were used in the meta-analysis with 173 participants. Our meta-analysis for pain reduction in each study showed that transcutaneous electrical nerve stimulation combined with instrument-assisted soft tissue mobilization treatment and pulsed electromagnetic therapy produced significant treatment on chronic lower back pain patients. Pooled evidence revealed the use of medical device related interventions resulted in 0.7 degree of pain reduction under a 0-10 scale. Significant improvement in disability scores, with a 7.44 degree reduction in disability level compared to a placebo using a 50 score range was also seen. The application of medical devices in patients with chronic pain has gained popularity due to increasingly cost effective techniques, minimally invasiveness and greater awareness of risks associated with pharmacological management. Our analysis has shown that the optimal use of medical devices in a sustainable manner requires further extensive research, needing larger cohort studies with greater gender parity, in a more diverse range of geographical locations.

Cheating during examination is now day serious problem spatially in Ethiopia where many students sit in one class to exam. When cheating occurs in medical schools, it has serious consequences for human life, social values, and the economy. Even though, cheating on exams has existed in any department, with unknown reason, prevalence of cheater among 2^nd year laboratory students were high. So that assessing factors and improving cheating behavior of the students are mandatory to create competitive graduated students. To identify factors and to improve cheating behavior action research study design was conducted among 2^nd year medical laboratory student. Criterion sampling technique was used to selects sixteen cheater students among 2^nd year laboratory students. To gather necessary data, we used focus group discussions, individual interview, open-ended questionnaire and observation and collected information by using hand writing notes. During exam different cheating methods used by students like using a system of signals, writing on hands, desks and copy the other students answer. While the compelling reasons for cheating were like hard courses, hard exams, time pressure and fear of failure. To improve cheating behavior of the student’s different action strategies were taken like prepared exam by using code, arrangement sitting style during exam and sit with brainy students during class, reading and discussion. Most students were trying to done exam by themselves but their results are not good as previously. So that, we need more future action plan to avoid cheating behavior of the students. During, the next action plan we will be taken the remaining main action strategies and action evaluation we will be expected 50% of participants will be avoided their cheater behavior and done exam independently without forced by the environment.

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.

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.

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.

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.

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.

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.