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

The 2019 Coronavirus pandemic which was initially referred to as 2019-nCoV, was first identified in Wuhan, China. Early response from the Chinese government included quarantine of infected persons, isolation and total lockdown of Wuhan province to prevent further spread. With the spread of the disease across national borders and declaration of the disease as a global pandemic, there has been a robust response by the international community to contain this deadly virus and prevent its further spread worldwide. Africa is not left out of this rampaging pandemic with documented cases in over 40 countries and still rising. Although extensive studies have been carried out on the novel SARS-CoV-2 on its pathogenesis, mode of infection and virulence but much is still unknown. However, potentially infectious samples are received routinely in the medical laboratory for analysis. This technical note reviews good laboratory practice (GLP) and processes across the different specialities of Medical Laboratory practice that should minimize the risk of infection to laboratory staff especially in resource-limited settings.

Background Critical patients with novel coronavirus pneumonia ( COVID-19) have worse outcome and high mortality. However, the histopathology of critical patient with COVID-19 remains undisclosed. Methods We performed the whole lung biopsy, and described the pathological changes of critical COVID-19 patient done with transplant by HE staining, immunohistochemistry and special staining observed under the microscopy. Findings The whole lungs displayed diffuse congestive appearance and partly haemorrhagic necrosis on gross examination. The haemorrhagic necrosis was prominently present in outer edge of the right lower lung. The cut surfaces of the lung displayed severe congestive and haemorrhagic changes. The main pathological changes showed massive pulmonary interstitial fibrosis, and partly hyaline degeneration, variable degrees of hemorrhagic pulmonary infarction. Small vessels hyperplasia, vessel wall thickening, lumen stenosis, occlusion and microthrombosis formation. Focal monocytes, lymphocytes and plasma cells infiltrating into pulmonary interstitium. Bronchiolitis and alveolitis with proliferation, atrophy, desquamation and squamous metaplasia of epithelial cells. Atrophy, vacuolar degeneration, proliferation, desquamation and squamous metaplasia in alveolar epithelial cells. Alveolar cavity congestion was prominent, and contained mucus, edema fluid, desquamated epithelial cells, and inflammatory cells. We also found several multinucleate giant cells and intracytoplasmic viral inclusion bodies. Special stains including Masson stain, sirius red staining, reticular fibers staining indicated massive pulmonary interstitial fibrosis. Immunohistochemistry showed positive for immunity cells including CD3, CD4, CD8, CD20, CD79a, CD5, CD38 and CD68. Interpretation We demonstrate the pathological findings of critical patient with COVID-19, which might provide a deep insight of the pathogenesis and severity of this disease.

Patient safety is one of the indicators of the quality of health services in the hospital, for that, it is necessary to have efforts from the hospital to create a system that can minimize the occurrence of errors and unexpected events that can harm patients, nurses as health workers who are the most numerous in the home. sick and with the patient for 24 hours, has an important role in maintaining patient safety. This study aims to explain how the role of nurses and cooperation between health workers in implementing patient safety measures in the hospital. The method used in this study is a literature review by analyzing and exploring relevant articles and focusing on interprofessional collaboration to improve patient safety. The articles used in this study were taken from 3 direct, Proquest, Pubmed science databases published in the last 3 years, namely between 2019-2021, nurses as part of the health team are required to be able to work together with other health professionals in hospitals with various characteristics, including education, gender, age, employment status and length of work, nurses are required to be committed to maintaining patient safety in the hospital.

Malaysia implemented a movement control order (MCO) to curb the spread of the SARS-CoV-2 virus in March 2020. Despite healthcare services remaining operational, rising COVID-19 infections and MCO restrictions have forced healthcare professionals to seek a compromise between service capacity and standard operating procedure compliance. A cross-sectional survey was conducted among public and private sector doctors, dentists and pharmacists to determine how lockdown measures impacted healthcare services. Responses from 413 doctors, 193 dentists, and 163 pharmacists were analysed. Pharmacy services remained mostly unaffected throughout the MCO. In contrast, operational capacities for surgical and dental services were severely affected during the MCO. All service sectors reported restricting patients or accompanying individuals at the workplace, reductions in staffing capacity, and shortened patient contact time at various degrees. Many pharmacy and medical participants reported supplying extended medication supplies to patients. Adoption of virtual healthcare services was generally poor. All private service sectors suffered financial losses ranging between 59 to 75%. Periodic assessments of the healthcare system throughout the pandemic are required to identify which patients have their treatment compromised so that healthcare managers and policy makers can plan and implement appropriate interventions that help alleviate pressure within the health system.

Access to medical care is a global issue. Technology-aided approaches have been applied in addressing this. Interventions have however not focused on medical diagnosis as a fully automated procedure and available applications employ mainly text-based inputs rather than conversation in natural language. We explored the utility of ontology-based chatbot technology for the design of intelligent agents for medical diagnosis through a systematic review of the most recent related literature. English articles published in 2011-2016 returned 233 hits which yielded 11 relevant articles after a 3-stage screening. Findings showed that the creation of expert systems had been the focus of many the studies which utilize the physician-system-patient framework with system training based mostly on expert knowledge for designing web- or mobile phone-based applications that serve assistive purposes. Findings further indicated gaps in the design and evaluation of more effective systems deployable as standalone applications, for example, on an embodied robotic system. The need for technology supporting the physical examination part of diagnosis, connection to data sources on patients’ vitals and medical history are also indicated in addition to the need for more qualitative work on natural language-based interaction. The system should be one that is continuously learning. Future works should also be directed towards the building of more robust knowledge base as well as evaluation of theory-based diagnostic methodological options

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

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

In the era when the market segment of Internet of Things (IoT) tops the chart in various business reports, it is apparently envisioned that the field of medicine expects to gain a large benefit from the explosion of wearables and internet-connected sensors that surround us to acquire and communicate unprecedented data on symptoms, medication, food intake, and daily-life activities impacting one’s health and wellness. However, IoT-driven healthcare would have to overcome many barriers, such as: 1) There is an increasing demand for data storage on cloud servers where the analysis of the medical big data becomes increasingly complex; 2) The data, when communicated, are vulnerable to security and privacy issues; 3) The communication of the continuously collected data is not only costly but also energy hungry; 4) Operating and maintaining the sensors directly from the cloud servers are non-trial tasks.This book chapter defined Fog Computing in the context of medical IoT. Conceptually, Fog Computing is a serviceoriented intermediate layer in IoT, providing the interfaces between the sensors and cloud servers for facilitating connectivity, data transfer, and queryable local database. The centerpiece of Fog computing is a low-power, intelligent, wireless, embedded computing node that carries out signal conditioning and data analytics on raw data collected from wearables or other medical sensors and offers efficient means to serve telehealth interventions. We implemented and tested an fog computing system using the Intel Edison and Raspberry Pi that allows acquisition, computing, storage and communication of the various medical data such as pathological speech data of individuals with speech disorders, Phonocardiogram (PCG) signal for heart rate estimation, and Electrocardiogram (ECG)-based Q, R, S detection. The book chapter ends with experiments and results showing how fog computing could lessen the obstacles of existing cloud-driven medical IoT solutions and enhance the overall performance of the system in terms of computing intelligence, transmission, storage, configurable, and security. The case studies on various types of physiological data shows that the proposed Fog architecture could be used for signal enhancement, processing and analysis of various types of bio-signals.

At present, medical institutes generally use EMR to record patient's condition, including diagnostic information, procedures performed and treatment results. EMR has been recognized as a valuable resource for large scale analysis. However, EMR has the characteristics of diversity, incompleteness, redundancy and privacy, which make it difficult to carry out data mining and analysis directly. Therefore, it is necessary to preprocess the source data in order to improve data quality and improve the data mining results. Different types of data require different processing technologies. Most structured data commonly needs classic preprocessing technologies, including data cleansing, data integration, data transformation and data reduction. For semi-structured or unstructured data, such as medical text, containing more health information, it requires more complex and challenging processing methods. The task of information extraction for medical texts mainly includes NER (Named Entity Recognition) and RE (Relation Extraction). In this paper, we introduce the process of EMR processing, including data collection, data preprocessing, data mining, evaluation and knowledge application, analyze the current status of the key technologies, such as data preprocessing and data mining, and provide an overview of the application domains and prospects of EMR mining technologies. Finally, we summarize the existing problems in the research of EMR mining, and review the development trends.

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

An outbreak caused by coronavirus disease 2019 (COVID-19) occurred in Wuhan City, Hubei Province, China, in December 2019. Up to March 2, 2020, at least 80180 cases have been reported. Most of the patients had a history of visiting Hubei Province or contacting with people who had ever stayed in or passed by Hubei Province, or exposed to symptoms. Some patients got infected only from asymptomatic contacts. This study aimed to report the epidemic features and lab identification of a patient confirmed with COVID-19 infection only from asymptomatic contact.

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

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

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.

Pharmacists’ roles in providing patient care remain limited in Indonesia, hence this study aimed to determine the preparedness of pharmacy graduates from one university in Indonesia to deliver patient care. Pharmacy graduates (both registered pharmacists [104] and recent graduates eligible for registration [45]) were sent a validated self-administered survey. The survey sought their perceptions about whether they had acquired 16 patient care related attributes. Further, it sought their opinion on the desirability of having those attributes. Data were analysed using SPSS version 22.0. Sixteen of 104 (15.4%) registered pharmacists and 40 of 45 (88.9%) recent pharmacy graduates participated in the study. More than 50% of participants in both groups were female and most participants were aged in their 20s. Of the recent pharmacy graduates the majority perceived they had at least partially acquired four of 16 list attributes. Male and female recent graduates had significantly different beliefs about their leadership ability (p=0.004). In comparison, most registered pharmacists perceived they had 10 out of the 16 listed attributes. The findings of this study suggested that pharmacy graduates should be better prepared to deliver patient care, and that curriculum redesign with expansion of experiential learning is required.

This is the second of a series of two papers comparing the end of life issues in human and veterinary medicine. We outline the main differences between human and animal patients such as patient communication, finance and ‘conflicts of interest’ between animal, owner and veterinarian. We discuss striking similarities between human and veterinary issues such as assessing quality of life and the primary role of the attending veterinarian or doctor being the welfare and care of the patient. This paper takes the form of an ethical argument in favour of allowing euthanasia in human medicine, by providing insights into end of life issues for humans from an independent veterinary perspective. Veterinary surgeons are well trained in the ethics of euthanasia and put it to good use in the best interest of their animal patients. Doctors in the UK are limited and unwilling to put forward a case for the option of euthanasia for those patients who face a slow and agonizing death. With advances in medical science being able to significantly prolong the dying process, autonomy for the patient demands a review of the law regarding patient choice in the UK.

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

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

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

ABSTRACT Objectives: Typical Diagnostic Reference Levels (DRL) in terms of Computed Tomography Dose Index (CTDI) and patient dose in terms of Effective Dose (ED ) and Size Specific Dose Estimate (SSDE) were estimated in Computed Tomography (CT) guided biopsy procedures. Materials and Methods: A total of 226 CT biopsy procedures - Iliac bone, liver, lung, mediastinum and para-aortic tissue - were retrospectively analyzed and Typical DRL extracted based on ICRP 135 instructions. Results: For helical mode acquisitions, DRLs in terms of CTDIvol were 9.7 mGy for Iliac bone, 8.9 mGy for liver, 8.8 mGy for lung, 7.9 mGy for mediastinal mass and 9 mGy for para-aortic lymph nodes biopsy procedures. For biopsy acquisitions, DRL values were 7.3 mGy, 7.7 mGy, 5.6 mGy, 5.6 mGy and 7.4 mGy respectively. Also, SSDE median values ranged from 7.6 mGy to 10 mGy for biopsy acquisitions and 11,3 mGy to 12,6 mGy for helical acquisitions, as well as the median values for effective dose ranged from 1.6 mSv to 5,7 mSv for biopsy scans and 3.9 to 9.3 mSv for helical scans. Conclusions: The use of DLR as an optimization tool for CT-guided biopsy procedures revealed that helical scans across the entire anatomical region greatly affect radiation dose compared to biopsy acquisitions.

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

The modification the gut microbiota in metabolic syndrome and associated chronic diseases is among leading tasks of microbiome research and needs for clinical use of probiotics. Evidence lack for the implications for microbiome modification to improve metabolic health in particular when applied impersonalized. Probiotics have tremendous potential in personalized nutrition and medicine to develop healthy diets. The aim was to to conduct comprehensive overview of recent updates of role of microbiota on human health and development of metabolic syndrome and efficacy of microbiota modulation considering specific properties of probiotic strain and particular aspects of metabolic syndrome and patient`s phenotype to fill the gap between probiotic product and individual to facilitate development of individualized / personalized probiotic and prebiotic treatments. We discuss the relevance of using host phenotype-associated biomarkers, those based on imaging and molecular and patrient`s history, reliable and accessible to facilitate person-specific appication of probiotics and prebiotic substances. Microbiome phenotypes can be parameters of predictive medicine to recognize patient`s predispositions and evaluate treatment responses; the number of phenotype markers can be effectively involved to monitor microbiome modulation. The studied strain-dependent properties of probiotic strains are potentially relevant for individualized treatment for gut and distant sites microbiome modulation. The evidence regarding probiotic strains properties can be taken to account via pathophysiology-based approach for most effective individualized treatment via gut, oral and vaginal and other sites microbiome modulation according to phenotype of the patient providing individualized and personalized medical approaches. Preventive potential of probiotics is strong and well-documented. Recommendations for individualized clinical use of probiotics, and for probiotic studies design have been suggested.

Background. The Stanford Health Assessment Questionnaire-Disability Index (HAQ) is widely used to measure functional ability in persons with Rheumatoid Arthritis (RA). The instrument was developed with limited involvement from persons with RA, and their perception of the instrument has not been studied in depth. The aim of this study was to explore how persons with RA experience the use of the HAQ in care. Methods. Forty persons with RA were purposefully recruited to participate in semi-structured interviews. The interviews were then analyzed qualitatively using thematic analysis. Results. The participants questioned the relevance of the HAQ but nevertheless experienced that the instrument had a profound effect on their understanding of health and how care is delivered. The analysis resulted in three themes: Problems with individual items, meaning of the summative score, and effects on care and health perceptions. Conclusions. To make the HAQ relevant to persons with RA, it needs to be revised or to include an option to select items most meaningful to the respondent. To ensure relevance, the HAQ update should preferably be co-created by researchers, clinicians and persons with RA.

The COVID-19 pandemic has wreaked havoc on the whole world, taking over half a million lives and capsizing the world economy in unprecedented magnitudes. With the world scampering for a vaccine, early detection and containment is the only redress. Existing diagnostic technologies with high accuracy like RT-PCRs are expensive and sophisticated, requiring skilled individuals for specimen collection and screening, resulting in lower outreach. So, methods excluding direct human intervention are much sought after, and artificial intelligence-driven automated diagnosis, especially with radiography images, captured the researchers' interest. This survey marks a detailed inspection of the deep-learning-based automated detection of COVID-19 works done to date, a comparison of the available datasets, methodical challenges like imbalanced datasets, and others, along with probable solutions with different pre-processing methods, and scopes of future exploration in this arena. We also benchmarked the performance of 315 deep models in diagnosing COVID-19, Normal, and Pneumonia from x-ray images of a custom dataset created from four others. The dataset is publicly available at https://github.com/rgbnihal2/COVID-19-X-ray-Dataset. Our results show that DenseNet201 model with Quadratic SVM classifier performs the best (accuracy: 98.16%, sensitivity: 98.93%, specificity: 98.77%) and maintains high accuracies in other similar architectures as well. This proves that even though radiography images might not be conclusive for radiologists, but it is so for deep learning algorithms for detecting COVID-19. We hope this extensive review will provide a comprehensive guideline for researchers in this field.

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.

Distributed digital manufacturing offers a solution to medical supply and technology shortages during pandemics. To prepare for the next pandemic, this study reviews the state-of-the-art for open hardware designs needed in a COVID-19-like pandemic. It evaluates the readiness of the top twenty technologies requested by the Government of India. The results show that the majority of the actual medical products have had some open source development, however, only 15% of the supporting technologies that make the open source device possible are freely available. The results show there is still considerable work needed to provide open source paths for the development of all the medical hardware needed during pandemics. Five core areas of future work are discussed that include: i) technical development of a wide-range of open source solutions for all medical supplies and devices, ii) policies that protect the productivity of laboratories, makerspaces and fabrication facilities during a pandemic, as well as iii) streamlining the regulatory process, iv) developing Good-Samaritan laws to protect makers and designers of open medical hardware, as well as to compel those with knowledge that will save lives to share it, and v) requiring all citizen-funded research to be released with free and open source licenses.

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.

ChatGPT is gaining widespread acceptance for its ability to generate natural language sentences in response to various inputs and is expected to become a supplementary tool for diagnosing and determining treatment policies in clinical settings. ChatGPT was used to evaluate its ability to perform clinical inference and accuracy in answering questions on the 117th Japanese National Medical Licensing Examination held in February 2023. The exam questions were manually inputted into ChatGPT's window, and the accuracy of ChatGPT's responses was determined based on answers provided by a preparatory school. ChatGPT provided answers for 389 out of 400 questions, and its overall correct answer rate was 55.0%. The correct answer rate for 5-choice-1, 5-choice-2, and 5-choice-3 were 57.8%, 42.9%, and 41.2%, respectively. The highest correct answer rate was for the compulsory exam (67.0%), followed by the specific knowledge exam (54.1%) and the cross category exam (47.9%). The correct answer rate for non-image questions was 56.2% and for image questions, it was 51.5%. The study suggests that ChatGPT has potential to support healthcare professionals in clinical decision-making in Japanese clinical settings, but caution should be exercised in interpreting and using the answers generated by ChatGPT due to room for improvement in performance.

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

There is growing recognition in research and policy of a mental health crisis among Canada’s paramedics but despite this, epidemiological surveillance of the problem is in its infancy. Just weeks before the emergence of the COVID-19 pandemic, we surveyed paramedics from a single, large, urban paramedic service in Ontario, Canada to assess for symptom clusters consistent with Post-Traumatic Stress Disorder (PTSD), major depressive disorder, and generalized anxiety disorder and to identify potential risk factors for each. In total, we received 589 completed surveys (a 97% completion rate) and found that 11% screened positive for PTSD, 15% for depression, and 15% for anxiety, with 1 in 4 active-duty paramedics screening positive for any of the three as recently as February 2020. In adjusted analyses, the risk of a positive screen varied as a function of employment classification, gender, self-reported resilience, and previous experience as a member of the service’s peer support team. Our findings support the position that paramedics screen positive for mental disorders at high rates – a problem likely to have worsened since the onset of the COVID-19 pandemic. We echo the calls of researchers and policymakers for urgent action to support paramedic mental health in Canada.

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.

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

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.

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.

Objective: To map the literature pertaining to adult Person-Centered Rehabilitation (PCR).Data Sources: Following our previously published scoping review protocol, data were identified through: three major databases, snowball searches and expert consultation.Study Selection: Two independent reviewers identified English-language papers which addressed adult physical rehabilitation and met one or more of the six pre-defined inclusion categories for PCR content. Data Extraction: Two independent reviewers extracted key characteristics of included papers (e.g. aims, methods, participants). Quantitative methods (descriptive statistics, regression analysis) and qualitative content analyses were used to synthesize the results. Data synthesis: Of 5084 unique records initially screened, 145 papers were included: 111 empirical, including 11 systematic reviews. Empirical papers had data from 13498 clients and 3849 providers, in total. Yearly publications grew exponentially from 2000 to 2017 (r²= 0.65; p<0.01). Publications were unevenly distributed by countries (e.g. United States’ publications per population size was 45 times lower than New Zealand’s). Most papers focused in more than one profession, setting-type or health conditions, respectively 57.2%, 66.2%, and 60.7%. Finally, more than half of the empirical papers (53.2%) studied implementation of PCR approaches, including its effect. Conclusion: This scoping review synthesizes key characteristics and publication trends in the PCR literature, which is mainly empirical and growing exponentially over time. Stakeholders can use the identified trends, gaps, and literature map to guide further PCR research, and both clinical and organizational practices. The high prevalence of papers focused on multiple professions, settings-type, or health conditions reinforces the need for developing a transdisciplinary, trans-service model of PCR, which will be derived from a thematic analysis of this body of literature.

Objectives: The purpose of this systematic review was to ascertain critical care nurses’ understanding and experiences of patient advocacy in adult critical care settings. The specific objectives were to identify how critical care nurses define patient advocacy, to explore the understanding and experiences of critical care nurses regarding patient advocacy, to explore critical care nurses’ role in patient advocacy, and to ascertain the barriers to encouraging advocacy in the critical care setting. Research design: Systematic literature search of CINAHL and Medline databases, Google Scholar, and Cochrane Database of Systematic Reviews, as well as grey literature search, was conducted. Search dates were restricted from January 2005 to 2015 in both CINAHL and Medline. Findings: 62 studies were identified, of which 6 qualitative research papers were included. Nurses gave varied definitions of patient advocacy, which were categorized into three themes: communication, protection, and doing. Nurses perceive advocacy as truly listening to patients and their families. Conclusion: For critical care nurses to be effective advocates, there must be support, collaboration, and improved working relationship between professional groups. Moreover, nurses must be empowered to be able to give power to patients and family.

This work addresses the problem of the application of artificial intelligence to the creation and maintenance of medical documentation and the use of big data in medicine to support efficient patient diagnosis and treatment. This study covers the latest advances in AI and big data, based on literature reviews and interviews with leading experts in these fields. The following conclusions were obtained: (1) Based on the needs of patients and providers of medical services, and given the latest technological advances, all medical documentation should be digital and the processes of its creation, access, sharing, and consistency checking should by supported by suitably designed AI systems. (2) The knowledge contained in medical documentation constitutes a resource of strategic importance for humanity, with almost unlimited potential. (3) All medical documentation should be anonymised and should be made widely available, just like data and research results in the field of experimental physics. (4) This will accelerate development of new treatments, best practice and help to identify new medical emergencies, such as Covid-19. In practice today, unfortunately, the design of medical record systems is fragmented between institutions and countries, often focusing discussions on narrow technical details, and forcing clinicians to waste time on filling up multiple pages of illness history. This leads to many inefficiencies and lost opportunities and necessitates a fundamentally new approach.

COVID-19 is a severe global problem, and AI can play a significant role in preventing losses by monitoring and detecting infected persons in early-stage. This paper aims to propose a high-speed and accurate fully-automated method to detect COVID-19 from the patient's CT scan images. We introduce a new dataset that contains 48260 CT scan images from 282 normal persons and 15589 images from 95 patients with COVID-19 infections. At the first stage, this system runs our proposed image processing algorithm to discard those CT images that inside the lung is not properly visible in them. This action helps to reduce the processing time and false detections. At the next stage, we introduce a novel method for increasing the classification accuracy of convolutional networks. We implemented our method using the ResNet50V2 network and a modified feature pyramid network alongside our designed architecture for classifying the selected CT images into COVID-19 or normal with higher accuracy than other models. After running these two phases, the system determines the condition of the patient using a selected threshold. We are the first to evaluate our system in two different ways. In the single image classification stage, our model achieved 98.49% accuracy on more than 7996 test images. At the patient identification phase, the system correctly identified almost 234 of 245 patients with high speed. We also investigate the classified images with the Grad-CAM algorithm to indicate the area of infections in images and evaluate our model classification correctness.

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

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.

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.

This study describes the development of an automated bag valve mask (BVM) compression system, which, during acute shortages and supply chain disruptions can serve as a temporary emergency ventilator. The resuscitation system is based on the Arduino controller with a real-time operating system installed on a largely RepRap 3-D printable parametric component-based structure. The cost of the system is under $170, which makes it affordable for replication by makers around the world. The device provides a controlled breathing mode with tidal volumes from 100 to 800 milliliters, breathing rates from 5 to 40 breaths/minute, and inspiratory-to-expiratory ratio from 1:1 to 1:4. The system is designed for reliability and scalability of measurement circuits through the use of the serial peripheral interface and has the ability to connect additional hardware due to the object-oriented algorithmic approach. Experimental results demonstrate repeatability and accuracy exceeding human capabilities in BVM-based manual ventilation. Future work is necessary to further develop and test the system to make it acceptable for deployment outside of emergencies in clinical environments, however, the nature of the design is such that desired features are relatively easy to add with the test using protocols and parametric design files provided.

Precision medicine seeks to use genomic data to help provide the right treatment to the right patient at the right time. Next-generation sequencing technology allows for the rapid and accurate sequencing of many genes at once. This technology is becoming more common in oncology, though the clinical benefit of incorporating it into precision medicine strategies remains under significant debate. In this manuscript, we discuss the early findings of the impact of next-generation sequencing on cancer patient outcomes. We investigate why not all patients with genomic variants linked to a specific therapy receive that therapy and describe current barriers. Finally, we explore the current state of health insurance coverage for individual genome sequencing and targeted therapies for cancer. Based on our analysis, we recommend increased transparency around the determination of “actionable mutations” and a heightened focus on investigating the variations in health insurance coverage across patients receiving sequencing-matched therapies.

Access to nasopharyngeal swabs for sampling remain a bottleneck in some regions for COVID-19 testing. This study develops a distributed manufacturing solution using only an open source manufacturing tool chain consisting of two types of open source 3-D printing and batch UV curing, and provides a parametric fully free design of a nasopharyngeal swab. The swab was designed using parametric OpenSCAD in two components (a head with engineered break point and various handles), which has several advantages: i) minimizing print time on relatively slow SLA printers, ii) enabling the use of smaller print volume open source SLA printers, iii) reducing the amount of relatively expensive UV resin, and iv) enabling production of handle on more accessible material extrusion 3-D printers. A modular open source UV LED box was designed, fabricated for $45 and tested for batch curing. Swabs can be fabricated for $0.06-$0.12/swab. The results of the mechanical validation tests showed that the swabs could withstand greater forces than would be expected in normal clinical use. The swabs were also able to absorb a significant amounts of synthetic mucus materials and passed abrasion and handling tests. The results show the open source swab are promising candidates for clinical trials.

A quantum hybrid (QH) intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO) method with the intuitionistic rationality of traditional fuzzy k-nearest neighbours (Fuzzy k-NN) algorithm (known simply as the Q-Fuzzy approach) is proposed for efficient feature selection and classification of cells in cervical smeared (CS) images. From an initial multitude of seventeen (17) features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e. global best particles) that represent a pruned down collection of seven (7) features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: The All-features (i.e. classification without prior feature selection) and another hybrid technique combining the standard PSO algorithm with the Fuzzy k-NN technique (P-Fuzzy approach). In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e. QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in scenarios 1 and 3. The synergy between the QPSO and Fuzzy k-NN in the proposed Q-Fuzzy approach marginally improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

Objective. To describe patient satisfaction with pre-hospital emergency knowledge and determine if patients and professionals share a common vision on the satisfaction predictors. Methods. A qualitative study conducted in two phases. First, a systematic review following the PRISMA protocol was carried out searching publications between January 2000 and July 2016 in Medline, Scopus, and Cochrane. Second, three focus groups involving professionals (advisers and healthcare providers) and a total of 79 semi-structured interviews involving patients were conducted to obtain information about what dimensions of care were a priority for patients. Results. Thirty-three relevant studies were identified. A majority conducted in Europe using questionnaires. They pointed out a very high level of satisfaction of callers and patients. Delay with the assistance and the ability for resolution of the case are the elements that overlap in fostering satisfaction. The published studies neither reviewed the overall care process nor related the measurement of the real time in responding to an emergency with the satisfaction. The patients and professionals concurred in their assessments about the most relevant elements for patient satisfaction, although safety was not a predictive factor for patients. Response capacity and perceived capacity for resolving the situation were crucial factors for satisfaction. This qualitative approach yielded assistance targets to be improved. Conclusions. Published studies have assessed similar dimensions of satisfaction. Furthermore, despite the fact that few explanations may be given due to the no face to face attention, taking into account the patient’s emotional needs or maintaining contact with the patient until the emergency services arrive are high predictors of the satisfaction.

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

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.

Nutraceuticals are combination of nutrients and pharmaceuticals and these are derived from various plants, microbes and animals too. The food products that are considered as nutraceuticals are categorised based on the availability in the market. It is a medical approach to improve health and remedy for illness. Nowadays there is an increase in shift towards use of nutraceuticals as its usage provides preventive therapies to various chronic diseases. Various natural nutraceuticals are based on extracts from Ginger, turmeric, garlic, amla, cinnamon, aloe vera etc. A wide variety of therapeutic values are provided by them such as anti-inflammatory, antibacterial, antifungal properties, allergy relief, antidiabetic and cardiovascular problems. India is in its infancy stage but have many emerging companies that are trying to meet the demand of growing population. Overall ‘Nutraceuticals’ has been known as a new era of well being, in which the food industry has become a main player.

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.

This paper presents novel feature descriptors and classification algorithms for automated scoring of HER2 in Whole Slide Images (WSI) of breast cancer histology slides. Since a large amount of processing is involved in analyzing WSI images, the primary design goal has been to keep the computational complexity to the minimum possible level and to use simple, yet robust feature descriptors that can provide accurate classification of the slides. We propose two types of feature descriptors that encode important information about staining patterns and the percentage of staining present in ImmunoHistoChemistry (IHC) stained slides. The first descriptor is called a characteristic curve which is a smooth non-increasing curve that represents the variation of percentage of staining with saturation levels. The second new descriptor introduced in this paper is an LBP feature curve which is also a non-increasing smooth curve that represents the local texture of the staining patterns. Both descriptors show excellent interclass variance and intraclass correlation, and are suitable for the design of automatic HER2 classification algorithms. This paper gives the detailed theoretical aspects of the feature descriptors and also provides experimental results and comparative analysis.

The time required to reach a correct diagnosis is one of the most important problems for rare disease (RD) patients. Diagnostic delay can be intolerably long, to the point that it is usually described as a “diagnostic odyssey” and, sometimes, a diagnosis might never occur. The International Rare Disease Research Consortium proposed, as ultimate goal for 2017-2027, to enable all people with a suspected RD to be diagnosed within one year if the disorder is known, and to enter a globally coordinated diagnostic and research pipeline for the unsolved cases. In-depth analysis of the genotype through next generation sequencing, together with a standardized in-depth phenotype description and sophisticated high-throughput approaches, have been applied as diagnostic tools to increase the chance of a timely and accurate diagnosis. This approach is very fruitful as, according to the Orphanet database, from 2010 to March 2017 more than 600 new RDs have been described and about 3600 genes linked to RDs have been identified. However, combination of -omics and phenotype data and international sharing of this information raise ethical concerns. Values to be assessed include not only patient autonomy but also family implications, beneficence, non-maleficence, justice, solidarity and reciprocity, which must be respected and promoted and, at the same time, balanced among each other. In this work we suggest that, to maximise patients involvement in the search for a diagnosis and identification of new causative genes, undiagnosed patients should have the possibility to: 1) actively participate in the description of their phenotype; 2) choose the level of visibility of their profile in matchmaking databases; 3) express their preferences regarding return of new findings, in particular which level of Variant of Unknown Significance (VUS) significance should be considered relevant to them. The quality of the relation between individual patients and physicians, and between the patient community and the scientific community is critically important for making the best use of available data and combining efforts in the search for matches with similar cases worldwide that will help to solve unsolved cases. The contribution of patients to collecting and coding data comprehensively is critical for efficient use of data downstream of data collection.

Background: Simulations have historically aided training programs by providing a realistic and holistic replication of professional scenarios and procedures. Simulations have developed over the past 40 years to include varying fidelities and modalities of simulation. Learning in a simulation-centered environment has benefits, ranging from improved patient care to specific skills acquisition while catering to students’ numerous and varied learning approaches. Simulation is a multifaceted field that benefits all parties, the teachers, the learners, and the patients. The application of simulation to medical education and its amalgamation with other modes and substitutes allows for a more integrated learning and testing curriculum that advances the current trajectory of medical education. Such developments, however, are limited to resource rich areas, leaving behind low-middle income countries to use traditional, less evolved methodologies and practices. This review aimed to explore different aspects of simulation and focus specifically on low-cost task trainers and their accessibility. Method: The purpose of the study was to assess the accessibility of low-cost task trainers in terms of cost-effectiveness, distribution, validation, and frequency within specific specialties. To do so, 84 PubMed publications have been screened, and 39 filtered research studies have collected the necessary data. After analyzing the papers, we classified the following information – process, specialization, validation (y/n), costs, development location, and year of publication. Results: After carefully analyzing the accumulated data from the selected 39 publications, we found that most studies (i.e., 6 out of 39) were published in 2020. Emergency Medicine was the most common specialty for which low-cost trainers were developed (9 out of 39 procedural simulators); Otolaryngology followed this with 8 out of 39 trainers and general surgery with 7/39 of the task-trainers. The price ranges fluctuated and fell within the price bracket of USD 0 to USD 400 collectively. Our review also uncovered the concentration of development of such innovations solely in high income countries (HICs). Conclusion: Simulation is an invaluable tool applicable to a diverse range of phases of medical education. Future conjunction of simulation with low-cost substitutes along with increased encouragement and enthusiasm towards developing cost effective simulation-based learning environments (SBLEs) with the reserves and requirements of these areas in mind may prove to be a reliable option for low and middle resource settings

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.

The concept of patient confidentiality is nearly as old as the practice of health professions and, has evolved and transformed over the years, from one jurisdiction to the other. Patient confidentiality can be a fundamental human right, an ethical duty or, a legal duty. The Saudi laws have evolved around its Shari’ah-based legal culture, its history and the international human right laws (IHRLs). These elements have moulded the Saudi Arabia’s unique perspective on patient confidentiality. Its confidentiality laws are found scattered in several legislations. Is the Saudi patient confidentiality law able to adequately deal with the contemporary challenges? The study reviewed the relevant Saudi laws in the light the International Humana Rights Laws. Findings suggest that there are issues bordering on the lack of quality comprehensive data protection laws, on clarity and foreseeability of the existing laws, and on the accessibility of the courts. Furthermore, the lack of a system of law reporting and stare decisis potentially gave the judges a wider latitude of discretion in interpreting the laws. Therefore, the study recommends for a comprehensive data protection law with a clear definition of “confidential information”, of data controllers and their role, and of specific safeguards against potential abuses. Others include defining legitimate purposes for using the patient’s data, and his role, and the extent to which he can control the use of his own data. Consistency in legal interpretations, and an improved law reporting system could positively enhance the overall outcome.

Patient-derived xenograft (PDX) models are created by engraftment of patients’ tumor tissues into immunocompetent mice. Since PDX model keep the characteristics of primary patient’s tumor such as gene expression profiles and drug sensitivity, it now becomes most reliable in vivo human cancer model. The engraftment rate are increased with the introduction of NOD/Scid based immunocompromised mice, especially, NK cell defective NOD strains such as NOD/Scid/IL2Rγnu (NOG/ NSG) mice and NOD/Scid/Jak3null (NOJ) mice. Success ratio differs from the origin of tumor: Gastrointestinal tumors tend to higher success rate and breast cancer is lower. Subcutaneous transplantation is most popular method to establish PDX, but some tumor needs orthotropic or renal capsule transplantation, and human hormone treatment is needed to establish hormone dependent cancers such as prostate and breast cancer. PDX library with patient’s clinical data, gene-expression patterns, mutational status, drug responsiveness and tumor architecture will be the powerful tool for developing specific biomarker and novel individualized therapy and establishing precision cancer medicine.

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

A significant attention has been made to the accurate detection of diabetes which is a big challenge for the research community to develop a diagnosis system to detect diabetes in a successful way in the IoT e-healthcare environment. Internet of Things (IOT) has emerging role in healthcare services which delivers a system to analyze the medical data for diagnosis of diseases applied data mining methods. The existing diagnosis systems have some drawbacks, such as high computation time, and low prediction accuracy. To handle these issues, we have proposed a IOT based diagnosis system using machine learning methods, such as preprocessing of data, feature selection, and classification for the detection of diabetes disease in e- healthcare environment. Model validation and performance evaluation metrics have been used to check the validity of the proposed system. We have proposed a filter method based on the Decision Tree (Iterative Dichotomiser 3) algorithm for highly important feature selection. Two ensemble learning Decision Tree algorithms, such as Ada Boost and Random Forest are also used for feature selection and compared the classifier performance with wrapper based feature selection algorithms also. Machine learning classifier Decision Tree has been used for the classification of healthy and diabetic subjects. The experimental results show that the Decision Tree algorithm based on selected features improves the classification performance of the predictive model and achieved optimal accuracy. Additionally, the proposed system performance is high as compared to the previous state-of-the-art methods. High performance of the proposed method is due to the different combinations of selected features set and GL, DPF, and BMI are more significantly important features in the dataset for prediction of diabetes disease. Furthermore, the experimental results statistical analysis demonstrated that the proposed method would be effectively detected diabetes disease and can easily be deployed in IOT wireless sensor technologies based e-healthcare environment.

Diffuse intrinsic pontine gliomas (DIPGs) account for ~15% of pediatric brain tumors, which invariably present with poor survival regardless of treatment mode. Several seminal studies have revealed that 80% of DIPGs harbor H3K27M mutation coded by HIST1H3B, HIST1H3C and H3F3A genes. The H3K27M mutation has broad effects on gene expression and is considered a tumor driver. Determination of the effects of H3K27M on posttranslational histone modifications and gene regulations in DIPG is critical for identifying effective therapeutic targets. Advanced animal models play critical roles in translating these cutting-edge findings into clinical trial development. Here, we review current molecular research progress associated with DIPG. We also summarize DIPG animal models, highlighting novel genomic engineered mouse models (GEMMs) and innovative humanized DIPG mouse models. These models will pave the way towards personalized precision medicine for the treatment of DIPGs.

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).

Purpose: "Just culture" is an element of safety culture, and in a broader sense – a part of quality culture. It is the subject of studies, especially in healthcare. This phenomenon is almost unknown in Polish medical facilities. For this reason, the aim of the article is to present the essence and significance of "just culture" in healthcare. The other aim of the research is to present the results of the validation of "just culture" assessment instrument used to recognize the "just culture" maturity level and evaluate the nurses’ beliefs and behaviours in the light of "just culture" criteria. Methodology/Approach: The verified questionnaire consisted of 28 statements in relation to which respondents expressed their opinion on a 5-point Likert scale. The questionnaire was distributed among nurses in one of the largest hospitals in Pomorskie Voivodeship, in Poland. The results based on 68 responses were statistically processed with Statistica 13.1 software. Findings: The obtained results allowed to confirm the reliability of the assessment tool, to recognize the level of „just culture” as wisdom (68%) and to indicate strengths and weaknesses of observed beliefs and behaviours. On this basis, improvement actions were proposed. Originality/Value: We use the original, own prepared questionnaire. This is the first study on "just culture" in healthcare in Poland. There are only few studies devoted to patient safety culture in Poland and no research addressed to "just culture" phenomenon, as well in Poland as in Central Europe. The results in this area allow to recommend the assessment tool for other hospitals and seem to help in understanding the essence of "just culture" implementation.

This topical review describes the results of recent research into and development of silicon nitride, a ceramic material with unique properties. The outcome of this ongoing research strongly encourages the use of monolithic silicon nitride and coatings as contemporary and future biomaterial for a variety of medical applications. Crystallographic structure, synthesis and processing of monolithic structures and coatings, and examples of their medical applications are covered that relate to spinal, orthopedic and dental implants, bone grafts and scaffolds, platforms for intelligent synthetic neural circuits, antibacterial and antiviral particles and coatings, optical biosensors, and nano-photonic waveguides for sophisticated medical diagnostic devices. The examples provided show convincingly that silicon nitride is destined to become a leader to replace titanium and other entrenched biomaterials in many fields of medicine.

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

Duchenne muscular dystrophy (DMD) is a fatal X-linked recessive neuromuscular disease prevalent in 1 in 3500 to 5000 males worldwide. As a result of mutations that interrupt the reading frame of the dystrophin gene (DMD), DMD is characterized by a loss of dystrophin protein which leads to decreased muscle membrane integrity, which increases susceptibility to degeneration. CRISPR/Cas9 technology has garnered interest as an avenue for DMD therapy due to its potential for permanent exon skipping, which can restore the disrupted DMD reading frame in DMD and lead to dystrophin restoration. An RNA-guided DNA endonuclease system, CRISPR/Cas9 allows for the targeted editing of specific sequences in the genome. The efficacy and safety of CRISPR/Cas9 as a therapy for DMD has been evaluated by numerous studies in vitro and in vivo, with varying rates of success. Despite the potential of CRISPR/Cas9-mediated gene editing for the long-term treatment of DMD, its translation into the clinic is currently challenged by issues such as off-targeting, immune response activation, and sub-optimal in vivo delivery. Its nature as being mostly a personalized form of therapy also limits applicability to DMD patients, who exhibit a wide spectrum of mutations. This review summarizes the various CRISPR/Cas9 strategies that have been tested in vitro and in vivo for the treatment of DMD. Perspectives on the approach will be provided, and the challenges faced by CRISPR/Cas9 in its road to the clinic will be briefly discussed.

The intensive care units in North West London are part of one of the oldest critical carenetworks in the UK, forming a mature and established strategic alliance to shareresources, experience and knowledge for the benefit of its patients. North WestLondon saw an early surge in COVID-19 admissions, which urgently threatened thecapacity of some of its intensive care units even before the UK government announcedlockdown. The pre-existing relationships and culture within the network allowed itsmembers to unite and work rapidly to develop agile and innovative solutions, protectingany individual unit from becoming overwhelmed, and ultimately protecting its patients.Within a short 50-day period 223 patients were transferred within the network todistribute pressures. This unprecedented number of critical care transfers, combinedwith the creation of extra capacity and new pathways, allowed the region to continue tooffer timely and unrationed access to critical care for all patients who would benefitfrom admission. This extraordinary response is a testament to the power and benefitsof a regionally networked approach to critical care, and the lessons learned maybenefit other healthcare providers, managers and policy makers, especially in regionscurrently facing new outbreaks of COVID-19.

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.

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.

Background: Even though a number of studies have verified the positive effect of physical activity (PA) on self-related health (SRH) no previous research has examined this association among pediatric patients with Type 1 diabetes mellitus (T1DM). Objective: The purpose of this study was to investigate the association between regular physical activity (PA) and self-rated health (SRH) in pediatric patients with Type 1 diabetes mellitus (T1DM) who lacked diabetes care. Methods: We conducted a retrospective study among pediatric patients with T1DM who lacked diabetes care and were enrolled in a diabetes education program between January 2011 to January 2015 at the endocrinology clinic of Seoul National University Children’s Hospital in South Korea. The eligible participants for this study were 37 pediatric patients with T1DM aged 9 to 17 years. PA was divided into regular PA and muscle strength exercise to analyze the relationship with SRH using binomial logistic regression analysis. Results: The results showed SRH of pediatric patients with T1DM who did not engage in regular PA was significantly lower than those who did (OR in regular PA = .199 [95% CI: .040, .995]; OR in regular muscle strength exercise = .097 [95% CI: .023, .825]). Conclusions: In conclusion, regular PA and muscle strength exercise in pediatric patients with T1DM who lacked diabetes care were effective in improving their SRH. A systematic plan is required to enhance regular PA for pediatric patients with T1DM.

Inequality of health service for different specialty categories not only occurs in different areas inequality of health service for different specialty categories in the world, but also happens in the online service platform. In the online health community (OHC), health service was often of inequality for different specialty categories, including both online views and medical consultation for offline registered service. Moreover, how the factor city-level impacts the inequality of health service in OHC is still unknown. We designed a causal inference study with data on distributions of serviced patients and online views in over 100 distinct specialty categories on one largest OHC in China. To derive the causal effect of the city-levels (two levels inducing 1 and 0) on the Gini coefficient, we matched the focus cases in cities of rich healthcare resources with the potential control cities. For the Gini coefficient of serviced patients in over 100 specialty categories, the average treatment effect of level-1 cities is 0.470, which is 0.029 higher than that of the matched group. Similarly, for the Gini coefficient of online views, the average treatment effect of Level-1 cities is 0.573, which is 0.016 higher than that of the matched group. For each of the specialty categories, we also estimated the average treatment effect the specialty category’s Gini coefficient ( ) with the balanced covariates. The results support the argument that the total Gini coefficient of all the doctors in OHC shows that the inequality of health service is still very serious. This study contributes to the development of the theoretically grounded understanding of the causal effect of city-level on the inequality of health service in an online to offline healthcare service setting.

Background: Healthcare attention is sometimes considered purely technical, but communication has proven to be closely related to clinical results and patient satisfaction. Therefore, evaluation of communication in the scope of healthcare is a priority. The purpose of this study was to validate and adapt, if necessary, the Spanish version of the Communication Styles Inventory (CSI) in a sample of nursing professionals. (2) Methods: The sample was made up of 2313 nursing professionals selected at random from various medical centers in Spain, and is therefore a sample actively employed at the time data were acquired. We started out from the Communication Style Inventory, a questionnaire for evaluating the predominance of certain individual communication behaviors on six scales (expressiveness, preciseness, verbal aggressiveness, questioningness, emotionality and impression manipulativeness). (3) Results: Confirmatory Factor Analysis of the model proposed showed god fit indices. The reliability of the model shown by the Cronbach’s alpha of α=.81 was adequate, and so was single-level and aggregate consistency. Finally, in the analysis of variance by type of contract, configural, metric and scalar invariance was acceptable, but not strict invariance. (4) Conclusions: This instrument progresses in measuring non-technical attributes, such as communication styles, in nursing personnel.

Background: Simulation plays a crucial role in health studies, as it helps medical students apply their theoretical knowledge in real-life situations. Moulage is one of the techniques that helps in making simulation more realistic or high-fidelity. It uses special effects to emulate wounds for a better understanding of what the wound is like visually. Still, moulage is expensive, time-consuming, resource-intensive, and requires the training of staff, which is why we need to find low-cost substitutes for moulage materials. Method: When searching the database “PubMed” for the terms “Low-cost and Medical moulage”, we retrieved 222 studies, out of which when excluding results not related to low-cost, we obtained 62 studies, from which when removing studies that do not contain information regarding moulage, we found two papers, after referring to citations and cited articles of those papers, we ended up with six studies. Based on the selected articles and additional articles sourced from their reference list, a total of 11 studies were included in the review. Results: We understand that moulage is a technique that helps make simulations come alive, but the resources required to use it are at times, expensive, which is why we need to find methods to do low-cost moulage, and many studies address that it can be as simple as using homemade ingredients. Students from a previous study have talked about their opinions regarding the realistic component of moulage and whether if it is any different from other moulages. Most of the students agreed that the moulage ranked well in face and content validity. However, further innovations must be introduced in the field to be widely spread and lead to newer opportunities. Conclusion: Although the research done under moulage is limited, it is accepted that moulage is helpful for simulation-based studies and that low-cost moulage can help make medical studies a better experience for students studying it. Students have a favorable opinion on the realistic aspect of the low-cost moulage applied to them. Newer methods can be introduced to moulage, and it can be implemented in low-income countries.

Motorcycles can be considered a new form of smart vehicle when taking into account their small and modern structure and due to the fact that nowadays they are used in the new role of ambu-lance to rapidly reach emergency patients in large cities with traffic congestion. However, there is no study regarding the measuring of access time for motorcycle ambulances in large cities of Thailand. Therefore, this study aims to compare access times to patients between motorcycle ambulances and conventional ambulances, including analysis of the use of AED installed on motorcycle ambulances to contribute to the sustainable development of public health policies. In two hundred and seventy-one operations, it was found that the times from dispatch to vehicle (ambulance and motorlance) being en route and times from the 1669 center (center for com-mand-and-control EMS in Thailand) call receipt to arrival on scene (response time) of motorcycle ambulances was shorter than that of a conventional ambulance and the use of AED on a motor-cycle ambulance can increase the chances of survival for patients with cardiac arrest outside the hospital in public places where AEDs are not available and in all cases where access to an AED was less than eight minutes.

Students’ anxiety due to the COVID-19 pandemic was expressed by some medical students in the form of anger and mistrust. This study aims to explore the reasons for mistrust between students and faculty among medical schools in Egypt that have flared during the COVID-19 pandemic. This is a three-phase exploratory qualitative study depending on thematic emergence from appreciative interviews (AI) sessions. Students are revealed to be very well-educated regarding contemporary medical education concepts. The most important factors from the student perspective were the presence of a well-designed assessment system aligned with the learning outcomes and teaching methodologies and the presence of extracurricular activities and soft skills, respectively. A balanced student life respecting their mental health was found important to increase trust. A roadmap to breaking the mistrust must be planned on several pivots: curriculum structure, extracurricular life, communication strategies, and identifying student roles in their learning and in decision making.

Coronavirus (COVID19) appears to be an inflection point that is forcing a disruption in medical education. However, it is not clear what the responses of the institutions are to this pandemic and how the adaptation of new methods may impact medical education in the post COVID-19 era. Objective: The study aims to explore how medical schools in Egypt responded to COVID-19 pandemic regarding the teaching and learning/assessment for undergraduate students. Design: A mixed method exploratory two-phase study was conducted. A survey was prepared and disseminated to a convenient non-probability sample of the medical school faculty through various social platforms. Then, a focus group guide was conducted to explore in more depth the findings. Results: The staff level of preparedness for that unexpected shift was evaluated by 55.1% of the survey participants as optimum to high and a good leadership support was reported by 70 % of them. They reported conflicting views about the proper role of medical education units but reinforced the idea of Egyptian Knowledge Bank’s crucial role in this transition. Additionally, there is a communication problem with the students that leads to their detachment. Subsequently, 84.6 % of the participants reported that their schools used alternative teaching methods for small groups, large groups, pre-clinical and clinical clerkships. However, 64.1 % of the participants identified a clinical skills teaching challenge. Although, 68.4% reported that alternative methods were used for formative assessment but absence of alternative methods for summative assessment was declared by 76.3%. Conclusions: Individuals moved faster than bodies and relied on support existing outside the universities when catastrophe happened. However, institutes which have experience in adapting modern engaging learning methods should organize a better response for crisis. Online learning should be integrated in the curriculum with a fair percentage especially in the early years of medical study.

The aim of the study was to determine the attitude of dentist toward learning communication skills and to recognize the factors influencing attitude toward learning communication skills. A cross-sectional study using a self-administered, 26-item, adapted Communication Skills Attitude Scale (CSAS) was carried out among dentist working in a public sector hospital in Qatar. Overall, two scores could be ascertained from the adapted CSAS: the mean positive attitude score (PAS) and negative attitude score (NAS). Non-parametric tests for statistical significance were utilized to assess relation between PAS and NAS scores and demographics. Fifty-nine dentists completed the survey giving an overall response rate of 53.6%. The mean (SD) PAS and NAS scores were 3.98 (SD=0.54) and 3.26 (SD=0.49) respectively. Female dentist was more positive towards learning communication skills than male. No statistically significant correlation was found between both PAS and NAS scores and respondents’ age. Dentists’ had both positive and negative attitudes towards learning communication skills. Considering the high NAS scores, it is recommended to introduce communication skills formal training sessions

Centrifuges are commonly required devices in medical diagnostics facilities as well as scientific laboratories. Although there are commercial and open source centrifuges, costs of the former and required electricity to operate the latter, limit accessibility in resource-constrained settings. There is a need for low-cost, human-powered, verified and reliable lab-scale centrifuge. This study provides the designs for a low-cost 100% 3-D printed centrifuge, which can be fabricated on any low-cost RepRap-class fused filament fabrication (FFF) or fused particle fabrication (FPF)-based 3-D printer. In addition, validation procedures are provided using a web camera and free and open source software. This paper provides the complete open source plans including instructions for fabrication and operation for a hand-powered centrifuge. This study successfully tested and validated the instrument, which can be operated anywhere in the world with no electricity inputs obtaining a radial velocity of over 1750rpm and over 50N of relative centrifugal force. Using commercial filament the instrument costs about US$25, which is less than half of all commercially available systems; however, the costs can be dropped further using recycled plastics on open source systems for over 99% savings. The results are discussed in the contexts of resource-constrained medical and scientific facilities.

Introduction Color vision deficiency (CVD) constitutes one of the frequently observed eye disorders in all human populations. Color is a prominent sign utilized in the medical profession to study and identify histopathological specimens, lab instruments, and patient examination. Color deficiency affects the medical skills of students resulting in poor clinical examination and color appreciation. There is no effective screening of CVD at any level of the medical profession. Hence, this study was aimed to determine the prevalence of CVD among medical students. Materials and methods This was a cross-sectional study conducted from September 2019 to February 2020 over a period of six months in Karachi, Pakistan. All medical students aged 18-21 years of either gender enrolled in the first and second years of medical college were included in this study. The examination was performed during daylight. Ishihara plates were placed at a distance of 75 cm from the subject and tilted so that the plane of the paper lies perpendicular to the line of vision. Students were given five seconds to read the plate and one examiner was instructed to mark the checklist. A score of less than 12 out of 14 red/green test plates (not including the demonstration plate) was considered as a CVD. All statistical analysis was performed using Statistical Package for Social Sciences version 20.0 (Armonk, NY: IBM Corp). Results The mean age of the medical students was 19.61± 1.22 years. There were (n=123) 53.0% females and (n=111) 47.0% males. Most of the medical students (n=131, 56.0%) belonged to the upper-middle-class socioeconomic group. CVD was observed in (n=13) 6.0%of medical students. Age (p=0.001) and socioeconomic status (p=0.001) were the only demographic factors significantly associated with color deficiency. Conclusions Color deficiency, although an unnoticed concern, is fairly common among medical students. Medical students must be screened for CVD as this will enable them to be aware of their limitations in their future observational skills as a doctor and devise ways of overcoming them in clinical practice.

Patients satisfaction with fast and high-quality services is the most important in the healthcare settings and specially in outpatient departments and private clinics. High quality services on health sector are indicated by continuous quality improvement (CQI). CQI is a progressive incremental process focused on safety of all participants, outcomes, systematic process, regulated and improved working environment at the later than earlier stages. Among the various suggested strategies, we adopted the patents feedback to improve the quality of services our clinic. All of the patient visited hospital were sent a massage on mobile and requested to provide their feedback on our services. Roughly around 5% of all visitors responded and filled up questionnaire. Majority of them were satisfied with the services in various department. However, they provided us some suggestions to identify the further gaps and improve the services in improving patients experience at our clinic. We considered their feedback, identified problems, redesigned the policies and implemented. After implementation of new strategies, we preliminary again evaluated the patients’ feedback on our services. Patients feedback explores that optimized methods of services for the has considerably increased the patients’ satisfaction. Taken together, our this shows that patients’ feedback is very important factor to improve patients’ experience at outpatient clinics using continuous quality improvement tools. For that reason, this study would serve as reference for public health stack holders, administrators and researchers.

Today, across the most critical problems faced by hospitals and health centers are those caused by the existence of patients who do not attend their appointments. Among others, this practice generates waste of resources and increases the patients’ waiting list. To handle these problems, hospitals are actively trying to implement methods to reduce the idle time caused by patient no-shows. Many scheduling systems developed require predicting whether a patient will show up for an appointment or not. Although, a challenging problem resides in obtaining these estimates precisely. The goal of this work is to analyze how objective factors influence a patient not to attending their appointment, to identify the main causes that contribute to a patient’s decision, and to be able to predict whether or not the patient will attend the scheduled appointment. As a result, the obtained model is tested on a real dataset collected in a health center linked to the University of Vale do Itajaí (UNIVALI), which includes 25 features and about 5000 samples. The algorithm that produced the best results for the available dataset is the Random Forest classifier. It reveals the best recall rate (0.91), since it measures the ability of a classifier to find all the positive instances and achieves a receiver operating characteristic curve rate of 0.969.

Following the WHO's declaration of a public health emergency due to the COVID-19 outbreak, the subsequent quarantine and confinement measures that were adopted, including distance learning measures, were shown to have caused a significant deterioration in the mental health of medical students. The goal of this study was to explore the mediating role of resilience and life satisfac-tion in the relationship between perceived stress and burnout among medical students in the con-text of COVID-19. A transversal assessment was performed using an online questionnaire, to which 462 students responded. The instruments applied were the Perceived Stress Scale-10, the Resilience Scale-25 items, the Satisfaction with Life Scale (SWLS) and the Burnout Scale (Olden-burg Inventory). A regression model was estimated for each dimension of burnout. The results revealed that resilience and life satisfaction play a mediating role in the association between stress and the dimensions of burnout. This suggests that measures of promoting mental health based on resilience and improving perceptions of life should be implemented.

Patient engagement is receiving a growing attention in the healthcare context. However, although worldwide healthcare stakeholders agree that patient engagement is a priority for quality and effective care, no shared recommendations on how to promote patient engagement are currently available. Based on these premises, a Consensus Conference (CC) was promoted to address four main issues: What is the definition of Patient Engagement? How measuring Patient Engagement? What are the most recommended methodologies and the tools to promote Patient Engagement? What is the role of new technologies in promoting of Patient Engagement? The consensus was obtained through an iterative process that began with a systematic synthesis of the available literature in each domain followed by plenary expert discussions. This CC - including the systematic analysis of internationals scientific evidences (2749 sources across the major international scientific databases) together with experiences of a multi-disciplinary consortium of investigators and key stakeholders - attempted to provide the first evidence-based Expert Consensus Statement for the promotion of Patient Engagement in chronic care. These recommendations should be envisaged as inspirational principles to promote a real eco-system of engagement and might orient health services research and interventions.

The cannabis plant has been known for millennia for its properties such as textile fiber, food, recreational and medicinal use. Since the origin of its domestication in Asia, cannabis has been transported to the rest of the continents by merchants, nomads, settlers, and slaves, who have also carried with them valuable knowledge about its uses. Its medical use was one of the major contributions of this plant in the various civilizations through which it passed. This article aims to understand its origins, dissemination, and medical use over the years to the present day.

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

There is little understanding of patients' experiences and perceptions with satisfaction by health professionals such as medical and dental clinicians. Furthermore, patient satisfaction is not well understood. The objective of this article is to better understand patients' satisfaction with their medical and dental care. The methods of the current article are based on a narrative review of the literature strategy. Patient satisfaction's multidimensional nature has been established since the perceived reasons for satisfaction varied widely among patients. Many aspects of the treatment influence participant satisfaction at different stages of the intervention's process. An improved understanding of the basis for managing patients' expectations with information reiteratively and efficiently may ultimately reduce patients' potential for negative feelings toward the medical and dental treatment experience. The consumerist method may misrepresent the concept of satisfaction in health service.

Malaria is a serious infection affecting millions of people in Africa. Our study investigated the personal preferences and applications of antimalarial medicines in Ghana. Based on over 1000 questionnaires distributed in Ghana from January to May 2019, we noticed that although Western medications to fight this disease are widely available, most patients in Ghana prefer treatment with locally produced herbal remedies. This preference appears to be due to a combination of traditional venues for obtaining medicines “on the street” rather than in licensed pharmacies, trust in local and “green” products, extensive advertisement of such local products, and an inherent distrust of imported and synthetic or unnatural medicines. Going local and natural is a trend also observed in other countries across the globe, and adds to the acceptance or rejection of drugs regardless of their activity or toxicity. In fact, adverse side effects associated with herbal remedies, such as general weakness and swollen, sore mouth, do not seem to deter the respondents of this study in Ghana. We propose a combination of (a) increasing public awareness of the benefits of modern medicine and (b) an improvement and control of the quality of herbal remedies to raise the standard of malaria treatment in countries such as Ghana.

This initial report of a longitudinal study of 192 English hospital nurses has measured Nursing Values (the 6Cs of nursing); Personality, Self-Esteem and Depression; Burnout Potential; Work-Life Balance Stress; ‘Hardy Personality’; and Intention to Leave Nursing. Correlational, component and cluster analysis identifies four groups: “The Soldiers” (N = 79) , with medium scores on most measures, who bravely ‘soldier on’ in their nursing roles, in the face of numerous financial cuts to the National Health Service, and worsening nurse-patient ratios; “Cheerful Professionals” (N = 54), coping successfully with nursing roles, and a variety of challenges, in upwardly mobile careers; “High Achievers” (N = 39), senior nurses with strong profiles of a ‘hardy personality’, and commitment to fundamental nursing values; “Highly Stressed, Potential Leavers” (N = 20), with indicators of significant psychological distress, and difficulty in coping with nursing role challenges. We propose a model of co-counselling and social support for this distressed group, by nurses who are coping more successfully with multiple challenges. We discuss the role of nurse educators in fostering nursing values, and developing and supporting ‘hardy personality’ and emotional resilience in recruits to nursing. This study is framed within the disciplinary approach of Critical Realism, which identifies the value basis for research and dialogue in developing strategies for social change.

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

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 (

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

Placing the needle inside the epidural space for locoregional anesthesia is a challenging procedure, which even today is left to the expertise of the operator. Recently, we have demonstrated that the use of optically sensorized needles significantly improve the effectiveness of such procedure. Here we propose an optimized configuration, where the optical fiber strain sensor is directly integrated inside the epidural catheter. The new design allows to solve the biocompatibility issues and increases the versatility of the former configuration. Through an in vivo study carried out on a porcine model we confirm the reliability of our approach, which also opens the way to catheter monitoring during its insertion inside biological spaces.

Background: During the COVID-19 pandemic, hygiene behaviors such as keeping distance, avoid-ing masses, wearing face masks and adhering to hand hygiene recommendations became impera-tive. The current study aims to determine factors interrelating with hygiene behaviors. Methods: 4,049 individuals (1,305 male, 2,709 female, aged 18-80 years) were recruited from rehabilitation clinics or freely on the internet and surveyed via online questionnaire between May 2020 and August 2021. Socio-demographics, hygiene behaviors, emotions (fear), life-satisfaction, risk factors and disability as well as communication were assessed. Results: Prevalence for hygiene behaviors was: keeping the distance 84.9%, avoiding mass gatherings 84.6%, wearing face masks 96.5% and hand hygiene 80.7%. Hygiene behaviors were significantly related to fear with linear and quad-ratic associations. Conclusion: Individuals with disabilities, risk factors and psychological symp-toms are more compliant. Especially hand hygiene should be targeted to achieve higher compli-ance rates. A medium level of fear is more functional than too elevated fear. Behavioral interven-tions and targeted communication aiming at improving different behaviors in orchestration can help individuals to remain healthy and maintain a high life-satisfaction. Thereby, communication in the healthcare setting is imperative and all involved individuals should become more aware of this to ensure high hygiene standards and patient safety.

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.

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.

This paper presents an OSA patient interactive monitoring system based on the Internet of Things (IoT) framework. This system allows OSA patients to get timely rescue when they are sleepy outside. Because the Beidou position marker has an interactive function, it can reduce the anxiety of the patient while waiting for the rescue. At the same time, if a friend helps the OSA patients to call the doctor, the friend can also report the patient's condition in time. This system uses the popular IoT framework. At the bottom is the data acquisition layer, which uses wearable sensors to collect vital signs from patients, with a focus on ECG and SpO2 signals. The middle layer is the network layer that transmits the collected physiological signals to the Beidou indicator using the Bluetooth Low Energy (BLE) protocol. The top layer is the application layer, and the application layer uses the mature rescue interactive platform of Beidou. Since the GPS indicator has not included the communication satellite, So it has no SMS function. OSA patients can only passively wait for a rescue. Moreover, due to the lack of satellites in Asia and the insufficient density of the ground-enhanced system, the positioning error of OSA patients is large. The Beidou system developed by China itself, the main coverage of the satellite is in Asia, and is equipped with a high-density ground-based augmentation system. Therefore, the Beidou model improves the positioning accuracy and is equipped with a special communication satellite, which increases the short message interaction function. Therefore, patients can report disease progression in time while waiting for a rescue. After our simulation test, the effectiveness of the OSA patient rescue monitoring system based on the Internet of Things framework and the positioning accuracy of OSA patients have been greatly improved. Especially when OSA patients work outdoors, the cell phone base station signal coverage is relatively weak. The satellite signal is well covered, plus the SMS function of the Beidou indicator. Therefore, the system can be used to provide timely patient progress and provide data support for the medical rescue team to provide a more accurate rescue plan. After a comparative trial, the rescue rate of OSA patients using the detection device of this system was increased by 15 percentage points compared with the rescue rate using only GPS satellite phones.

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.

This paper investigates the role of English language proficiency (ELP) as a measure of cultural integration on U.S. immigrant families’ economic integration, as measured by annual earnings, and health care market integration, as captured by annual medical care spending. Bayesian Markov Chain Monte Carlo (MCMC) estimation of a mixed bivariate ordered probit (MBOP) model of annual earnings and medical care spending is conducted using a nationally representative pooled cross-sectional sample data from the U.S. National Health Interview Surveys (NHIS). The results reveal that limited English proficiency is associated with lower marginal earnings propensities (-$44.83, -$50.66, and -$56.97), and higher marginal medical care spending propensities ($8.09, $6.09, and $4.32) for each of the three decreasing levels of ELP. Furthermore, we find a small yet statistically significant positive 7.2% correlation between immigrant families’ annual earnings and medical care spending propensities. Therefore investing to raise immigrants’ families ELP in the U.S. would not only contribute to more effective socio-economic integration, but also strengthen the U.S. workforce and economy for decades to come.

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

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.