Medical Areas Research Articles

Postural orthostatic tachycardia syndrome and other related dysautonomic disorders after SARS-CoV-2 infection and after COVID-19 messenger RNA vaccination.

The COVID-19 pandemic has caused a challenge for our society due to the post-acute sequelae of the disease. Persistent symptoms and long-term multiorgan complications, known as post-acute COVID-19 syndrome, can occur beyond 4 weeks from the onset of the COVID-19 infection. Postural orthostatic tachycardia syndrome (POTS) is considered a variety of dysautonomia, which is characterized by chronic symptoms that occur with standing and a sustained increase in heart rate, without orthostatic hypotension. POTS can lead to debilitating symptoms, significant disability, and impaired quality of life. In this narrative review, the etiopathogenic basis, epidemiology, clinical manifestations, diagnosis, treatment, prognosis, and socioeconomic impact of POTS, as well as other related dysautonomic disorders, after COVID-19 infection and SARS-CoV-2 postvaccination, were discussed. After a search conducted in March 2023, a total of 89 relevant articles were selected from the PubMed, Google Scholar, and Web of Science databases. The review highlights the importance of recognizing and managing POTS after COVID-19 infection and vaccination, and the approach to autonomic disorders should be known by all specialists in different medical areas. The diagnosis of POTS requires a comprehensive clinical assessment, including a detailed medical history, physical examination, orthostatic vital signs, and autonomic function tests. The treatment of POTS after COVID-19 infection or vaccination is mainly focused on lifestyle modifications, such as increased fluid and salt intake, exercise, and graduated compression stockings. Pharmacotherapy, such as beta-blockers, fludrocortisone, midodrine, and ivabradine, may also be used in selected cases. Further research is needed to understand the underlying mechanisms, risk factors, and optimal treatment strategies for this complication.

Lessons Learned from the COVID-19 Pandemic: A Survey-Based Study on a Sample of Italian Physicians' Opinions on Telemedicine.

Telemedicine was born out of the need to ensure clinical evaluation and personal care regardless of the physical presence of the healthcare professional nearby. Information technologies have been vital during the COVID-19 pandemic to ensure medical care and avoid the contagion between patients and clinicians. Accordingly, telecare services multiplied worldwide and gained paramount importance. The present work aims to collect field-based opinions about Telemedicine and ethics among Italian physicians. We developed a web-based questionnaire that was administered to Italian physicians from 1 May to 15 June 2022. The questionnaire was distributed as a link to Google Forms via social networks/instant messaging applications to groups of graduated and qualified physicians. A total of 180 physicians answered the questionnaire (with an age range from 25 to 68 years old). Physicians belonging to the medical area of expertise appear to more frequently use new technologies in comparison to other specialties. The vast majority believe that it is appropriate to use Telemedicine for monitoring and follow-up but not for evaluating a new patient. Concerns about changes in the physician-patient relationship, informed consent, digital barrier, and privacy and data protection also emerged. Finally, telehealth is thought to be a potential useful tool for the future by the majority of respondents but proper training for physicians is therefore needed.

Stability of the Photoluminescent Response on Hydroxyapatite/Multi-Walled Carbon Nanotube Composites

The application of hydroxyapatite (HAp)/multi-walled carbon nanotube composites in the medical area as coatings in prosthetics has been widely used because the carbon nanotubes reinforce the mechanical properties of hydroxyapatite. Despite that, their photoluminescent properties have not been studied, nor has the effect of different amounts of multi-walled carbon nanotubes on this property or what happened with their response with time. This work demonstrated that the photoluminescent response of HAp and HAp/multi-walled carbon nanotubes functionalized with oxygen groups (OMWCNT) composites was stabilized over time. The evaluated parameters were: three different amounts of OMWCNT (15, 25, and 35 mg) and two different thermal treatment temperatures (250 and 400 °C); all the samples were measured twice, after preparation and over a year after. The results indicated that over time the photoluminescent response is stabilized due to the passivation of surface defects, independently of the amount of OMWCNT used and the thermal treatment. In the end, the photoluminescent properties of these composites will extend their utilization in the medical area or open the door to new applications.

Kinematic Modeling of a Trepanation Surgical Robot System

This paper presents the concept of a parallel medical robotic service system to assist in a surgical procedure involving precise exploratory trepanation holes in a patient’s skull. The target position and orientation of the trepanation tool in the cranial region is determined using a prior intracranial image analysis using an external medical imaging system. A trepanning actuation system is attached to the end-effector of the parallel robot. The end-effector will act as an accurate positioner for the trepanning drill in the medical intervention area. The conceptual design of the mechanical actuation subsystem of a trepanning robot was developed in the SolidWorks 2022 software environment. The virtual model of the kinematic chain of the robot and the assumed design parameters were used to analytically derive the equations describing the inverse kinematics task. An analysis of the forward kinematics task of the parallel manipulator was also carried out using analytical and numerical methods. A workspace analysis was performed using Matlab based on the kinematic model of the parallel robot. This paper significantly advances the field by presenting the conceptual design of the actuation subsystem, deriving the kinematics equations, conducting a thorough workspace analysis, and establishing a foundation for subsequent control-algorithm development.

Bioactive Magnetic Materials in Bone Tissue Engineering: A Review of Recent Findings in CaP‐Based Particles and 3D‐Printed Scaffolds

Diverse applications of nanoparticles (NP) have been revolutionary for various industrial sectors worldwide. In particular, magnetic nanoparticles (MNP) have gained great interest because of their applications in specialized medical areas. This review starts with a brief overview of the magnetic behavior of MNP and a short description of their most used synthesis methods. The second part is dedicated to the MNP applications in tissue engineering, emphasizing the calcium phosphate‐based NP with intrinsic magnetic properties, recently highlighted in the literature as alternative and viable solutions for bone regeneration. The challenges associated with the controversial long‐term toxicity effects of MNP can be overcome using this new generation of multifunctional bone‐like magnetic materials. Furthermore, the influence of magnetic field parameters, such as modality of application, intensity, and spatial distribution, on the biological behavior of magnetic materials, especially for bone repair, is shown. The last part of the review presents the current state of the art regarding the development of magnetic biomaterials for additive manufacturing (AM), aiming to fabricate scaffolds by AM technologies, focusing on bone tissue engineering applications.

Azobenzene-containing surfactant directs small features of DNA thermotropic liquid crystals via bottom-up and top-down strategies.

Compared to classical block copolymers, the self-assembly of small molecules shows an advantage in addressing small features. As a new type of solvent-free ionic complexes, azobenzene-containing DNA thermotropic liquid crystals (TLCs) form an assembly as block copolymers when using small DNA. However, the self-assembly behavior of such biomaterials has not been fully investigated. In this study, photoresponsive DNA TLCs are fabricated by employing an azobenzene-containing surfactant with double flexible chains. For these DNA TLCs, the self-assembly behavior of DNA and surfactants could be guided by the factors of the molar ratio of azobenzene-containing surfactant, dsDNA/ssDNA, and presence or absence of water, which addresses the bottom-up control on domain spacing of mesophase. Meanwhile, such DNA TLCs also gain top-down control on morphology via photoinduced phase change. This work would provide a strategy for regulating the small features of solvent-free biomaterials, facilitating the development of patterning templates based on photoresponsive biomaterials. STATEMENT OF SIGNIFICANCE: The relationship between nanostructure and function is attractive in the science of biomaterials. With biocompatibility and degradability, photoresponsive DNA materials in solutions have been widely studied in biological and medical areas, but they are still hard to obtain in a condensed state. The complex created with designed azobenzene-containing surfactants paves the way for obtaining condensed photoresponsive DNA materials. However, fine control of the small features of such biomaterials has not yet been achieved. In this study, we present a bottom-up strategy of controlling the small features of such DNA materials and, simultaneously, the top-down control of morphology via photoinduced phase change. This work provides a bi-directional approach to controlling the small features of condensed biomaterials.

Wearable sensor-based human activity recognition with ensemble learning: a comparison study

<p>The spectacular growth of wearable sensors has provided a key contribution to the field of human activity recognition. Due to its effective and versatile usage and application in various fields such as smart homes and medical areas, human activity recognition has always been an appealing research topic in artificial intelligence. From this perspective, there are a lot of existing works that make use of accelerometer and gyroscope sensor data for recognizing human activities. This paper presents a comparative study of ensemble learning methods for human activity recognition. The methods include random forest, adaptive boosting, gradient boosting, extreme gradient boosting, and light gradient boosting machine (LightGBM). Among the ensemble learning methods in comparison, light gradient boosting machine and random forest demonstrate the best performance. The experimental results revealed that light gradient boosting machine yields the highest accuracy of 94.50% on UCI-HAR dataset and 100% on single accelerometer dataset while random forest records the highest accuracy of 93.41% on motion sense dataset.</p>

Design and measurement of the receiving antenna for electromagnetic field energy harvesting in UHF band

This paper aims to design a receiving antenna for harvesting energy using the wireless energy transfer method based on the ultra-high frequency (UHF) band. The study was conducted by comparing four types of the receiving antenna design. A mathematical and experimental analysis has been done to evaluate the performance of the designed antennas. A Yagi-Uda antenna is utilized as the transmitter. The results show that the zig-zag type antenna has the best performance. It can receive electromagnetic energy from a transmitter with maximum efficiency is 0.1% for the receiving antenna volume of 0.34 cm<sup>3</sup>. The proposed method can meet the energy necessity of an implant device with a charging time of approximately 21.61 hours for the 700 mAh rechargeable battery capacity. As our preliminary conclusion, based on our results, this proposed method can be used as a reference for the practice in the WET field and the medical and restricted areas in the electromagnetic energy harvesting case.

The principle and state-of-art applications of permutation tests

Contemporarily, permutation test is widely used in plenty of types of verification in state-of-art bigdata analysis. In this paper, the principle of permutation tests will be demonstrated with corresponding applications in various fields. Generally speaking, the permutation test can be regarded as an exact exam. On this basis, it can be also treated as a type of statistical significance level verifications where the value of sample distributed among the null hypothesis and alternative hypothesis are derived according to resampling and calculating of all possible combinations of the element. In other word, permutation test can be also defined as a procedure of resampling. For the sake of explicating the applications and meaning of the test clearly, this paper will first introduce the basic descriptions and formulae of the test and illustrate the applications subsequently. Specifically, the result of principle of permutation test is constructing null hypothesis and significance level, then equation will be presented to calculate p-value to compare with the primary data to determine one whether rejects the null hypothesis or not. Besides, permutation tests’ extensive functions on biological, medical, and economical areas will be discussed. Based on the analysis, these results offer a better understanding on principle and applications of permutation tests.

Guidelines for research and design of software for children with ASD in e-health

Autism spectrum disorder (ASD) is a neuro-developmental disorder that results in narrow interest and impairments in communication and social relationships. Usually, unknown contexts generate anxiety and frustration in persons with ASD, and great impediment in accessing services, including health ones. This seriously compromises prevention and treatment interventions in different medical areas. Technology offers many opportunities for persons with ASD and can be used to act as a mediator, helping to manage communication and interpersonal relationships and to familiarize with the environment, especially in new contexts. Specifically, we used digital tools to reduce stress and anxiety while teaching adequate dental care to children with ASD (MyDentist project). To generalize the R&D approach, we followed in the context of the MyDentist project for its adoption for research and development of inclusive software in e-health. We analyze our design and development process using the three-cycle model proposed by Hevner: the relevance cycle, which connects design with the environment; the rigor cycle, which connects design with the grounding theory; and the design cycle, which builds and evaluates artifacts. We present the results obtained in the project and the lessons learned. Lessons are formalized as guidelines that are further validated by a focus group including experts and stakeholders. A set of guidelines which can drive software development and research in similar contexts. Our research will benefit e-health researchers to perform rigorous and relevant Design Science Research. It will also inform software developers of e-health solutions and healthcare professionals.

Analisis Penyebab Terjadinya Penumpukkan Berkas Rekam Medis di Ruangan Filling pada Rumah Sakit X Batam Kota Tahun 2022

Inpatient and outpatient medical record files at X Batam City Hospital have increased the number of medical record files, because every year the number of outpatient and inpatient visits at X Batam City Hospital has increased significantly, so that the medical record file storage area is also narrower too. The purpose of this research is to find out the causes of the accumulation of medical record files in the Filling Room at X Batam City Hospital. The research method used in this study uses a qualitative method by taking data from observations, interviews and documentation. The results of this study indicate that the cause of the accumulation of medical record files is that officers have never participated in medical record training so that the lack of knowledge from medical record officers regarding the storage of medical record files and shelves in the filling room at X Batam City Hospital is not in accordance with the SOP. The medical record file storage system at X Batam City Hospital is placed in one room where the storage system uses a centralized system. Aspects that cause the accumulation of medical record files in the filling room at X Batam City Hospital, namely for the first aspect are medical record officers, the second aspect is infrastructure suggestions and the third aspect is Method.

Development of minimum reporting sets of patient characteristics in epidemiological research: A methodological systematic review

Background Core patient characteristic sets (CPCSs) are increasingly developed to identify variables that should be reported to describe the target population of epidemiological studies in the same medical area, while keeping the additional burden on the data collection acceptable. Methods We conduct a systematic review of primary studies and protocols that aim to develop a CPCS, using the PubMed database. We extract information on the study design and the characteristics of the proposed CPCS. The quality of Delphi studies is assessed by a tool proposed in the literature. All results are reported descriptively. Results Among 23 eligible studies, Delphi survey is the most frequently used technique to obtain consensus in CPCS development (69.6%, n = 16). Most studies do not include patients as stakeholders. The final CPCS rarely includes socioeconomic factors (26.1%, n = 6). Besides, 60.9% ( n = 14) and 26.1% ( n = 6) of the studies provide definitions and measurement methods for items in the CPCS, respectively. Conclusion This review identifies considerable variation and suboptimality in many methodological aspects of CPCS studies. To improve these shortcomings, guidance on the conduct and reporting of CPCS studies should be established in the future.

An efficient ensemble-based Machine Learning for breast cancer detection

Breast cancer is a very severe type of cancer that often develops in breast cells. Attempting to develop an effective predictive model for breast cancer prognosis prediction is urgently needed despite substantial advancements in the management of symptomatic breast cancer over the past ten years. The precise prediction will offer numerous advantages, including the ability to diagnose cancer at an early stage and protect patients from needless medical care and related costs. In the medical field, recall is just as important as model accuracy. Even more crucially in the medical area, a model is not very good if its accuracy is high but its recall is low. To boost accuracy while still assigning equal weight to recall, we proposed a model that ensembles Feature Selection (FS), Feature Extraction (FE), and 5 Machine Learning (ML) models. There are three steps in our proposed model. The Correlation Coefficient (CC) and Anova (Anv) feature selection methodologies to choose the features in the first stage. Applying Uniform Manifold Approximation and Projection (UMAP), t-distributed Stochastic Neighbour Embedding (t-SNE), and Principal Component Analysis (PCA) to extract the features in the second stage without compromising the crucial information. With 5 ML models and ensemble models such as Voting Classifier (VC) and Stacking Classifier (SC) after selecting and extracting features from the dataset to predict the disease will be the last stage. The results show that the proposed model CC-Anv with PCA using a SC outperformed all the existing methodologies with 100% accuracy, precision, recall, and f1-score.

Integrated Green Lean Six Sigma-Industry 4.0 approach to combat COVID-19: from literature review to framework development

PurposeThe coronavirus (COVID-19) pandemic has led to a surge in demand for health-care facilities, medicines, vaccines and other health-care items. The purpose of this study is to investigate different facets of integrated Green Lean Six Sigma and Industry 4.0 approach in the context of COVID-19 for better healthcare management. Integrating Green Lean Six Sigma (GLSS) and Industry 4.0 (I4.0) has the potential to meet the modern demand of health-care units and also leads to improving the quality of inpatient care with better safety, hygiene and real-time diagnoses. A systematic review has been conducted to determine the tools/techniques, challenges, application areas and potential benefits for the adoption of an integrated GLSS-I4.0 approach within health-care facilities from the perspective of COVID management. Further, a conceptual framework of integrated GLSS-I4.0 has been proposed for better COVID management.Design/methodology/approachTo conduct the literature review, the authors used the preferred reporting items for systematic reviews and meta-analysis and covers relevant papers from the arrival of COVID-19. Based on the systematic understanding of the different facets of the integrated GLSS-I4.0 approach and through insights of experts (academicians and health-care personnel), a conceptual framework is proposed to combat COVID-19 for better detection, prevention and cure.FindingsThe systematic review presented here provides different avenues to comprehend the different facets of the integrated GLSS-I4.0 approach in different areas of COVID health-care management. In this study, the proposed framework reveals that the Internet of Things, big data and artificial intelligence are the major constituents of I4.0 technologies that lead to better COVID management. Moreover, integration of I4.0 with GLSS aids during different stages of the COVID management, right from diagnosis, manufacture of items and inpatient and outpatient care of the affected person.Practical implicationsThis study provides a significant knowledge database to the practitioners by understanding different tools and techniques of an integrated approach for better COVID management. Moreover, the proposed framework aids to grab day-to-day information from the affected people and ensures reduced hospital stay with better space utilization and the creation of a healthy environment around the patient. This inclusive implementation of the proposed framework will enhance knowledge base in medical areas and provides different novel prospects to combat other medical urgencies.Originality/valueTo the best of the authors’ knowledge, this study is the first of its kind to review different facets of the integrated GLSS-I4.0 approach with a view of the COVID health-care perspective and provides a conceptual framework.

SYMPTOMS BASED DISEASE PREDICTION USING MACHINE LEARNING

Abstract--Computer Aided Diagnosis (CAD) is quickly evolving, diverse field of study in medical analysis. Significant efforts have been made in recent years to develop computer-aided diagnostic applications, as failures in medical diagnosing processes can result in medical therapies that are severely deceptive. Machine learning (ML) is important in Computer Aided Diagnostic test. Object such as body-organs cannot be identified correctly after using an easy equation. Therefore, pattern recognition essentially requires training from instances. In the bio medical area, pattern detection and ML promises to improve the reliability of disease approach and detection. They also respect the dispassion of the method of decisions making. ML provides a respectable approach to make superior and automated algorithm for the study of high dimension and multi - modal bio medicals data. The relative study of various ML algorithm for the detection of various disease such as heart disease, diabetes disease is given in this survey paper. It calls focus on the collection of algorithms and techniques for ML used for disease detection and decision making processes. Keywords: Machine Learning (ML), Artificial Intelligences, ML Technique.

Principle and Recent Development in Photonic Time-Stretch Imaging

Inspiring development in optical imaging enables great applications in the science and engineering industry, especially in the medical imaging area. Photonic time-stretch imaging is one emerging innovation that attracted a wide range of attention due to its principle of one-to-one-to-one mapping among space-wavelength-time using dispersive medium both in spatial and time domains. The ultrafast imaging speed of the photonics time-stretch imaging technique achieves an ultrahigh frame rate of tens of millions of frames per second, which exceeds the traditional imaging methods in several orders of magnitudes. Additionally, regarding ultrafast optical signal processing, it can combine several other optical technologies, such as compressive sensing, nonlinear processing, and deep learning. In this paper, we review the principle and recent development of photonic time-stretch imaging and discuss the future trends.

"Logra tu meta": Estrategia de evaluación formativa para el ingreso al posgrado y el desarrollo profesional en medicina

Achieve your goal” is an evaluation Project that is part of the “Program for the Academic Strengthening of the Medical Pasantei in Rural Areas”. It considers the elaboration of objective exams, which allow the participant to self-evaluate their learning given their formative condition. The exams were designed from clinical cases and their corresponding reagents, based on the structure and contents of the electronic books “FundamentalSS”. From 2018 to 2022, general practitioners and specialists prepared 383 cases and 7,059 items from various medical areas. Some of these have been used in the design of seven exams that were applied to 1,899 participants between 2019 and 2022. Achieve your goal is a project in development, promotes self-assessment of learning and its strengthening, which will guide interns and graduates in their preparation for admission to a medical specialty or another postgraduate, as well as for their profesional development. This project stands out for its solid methodology and is an effort carried out by FM-UNAM with the support of the Gonzalo Rio Arronte Foundation, with the purpose of promoting health care for the Mexican population. Keywords: Formative evaluation; profesional development; medical interns; social service; ENARM.

The graduate nurse experience: A New Zealand perspective

Introduction: The move from senior student to novice/advanced beginner registered nurse has been noted to be a stressful period. This longitudinal study follows the experiences of five cohorts of graduate New Zealand registered nurses throughout their first year of practice (n = 530). Methods: Data were collected via self-report survey using the Casey-Fink Graduate Nurse Experience Survey© at three points throughout the first year of practice. Results: Exploratory factor analysis (EFA) resulted in a 5-factor solution for 24 items from section two of the survey: professional support, professional role, professional concerns, professional communication and personal stress. Most respondents (93%) were female, New Zealand Europeans (80%) working in either surgical or medical clinical areas. Professional support from preceptors and exposure to positive role models contributed to a sense of being supported for 81% of the respondents. Satisfaction with choosing the professional role of nursing remained constant with over 90% agreeing or strongly agreeing they had made the right career choice. Across time, respondents reported few professional concerns and few concerns about professional communication. Concerns about personal stress were consistent, with 50% reporting stress related to issues such as finances, childcare and job performance. Conclusion: Contrary to other research, a honeymoon period was not evident (other than the initial high satisfaction with salary), rather the nurses’ satisfaction with nursing remained high throughout the year.

Biological effects of chitosan in Dentistry

Current research in the world has focused on studies of biomaterials in the medical area, leaving an emerging research model in dentistry, with little information available. In this sense, there are several biomaterials with potential to be used in various areas of dentistry, mainly in endodontics. Chitosan is a versatile biomaterial from its production to its multiple properties, applications and benefits. Chitosan is a biomolecule with an average molecular weight of 100 to 500 kDa, obtained from the exoskeleton of arthropods such as crabs, shrimps, lobsters and mollusks (squids, oysters, cuttlefish). Its chemical structure is similar to cellulose, formed by amino and hydroxyl functional groups in its polymeric structure, soluble in aqueous media. Several studies have considered chitosan as a safe product for biomedical use. It is currently used in the food industry for its fat absorption capacity, helping in weight loss for the control of overweight-obesity, as well as food preservation, cosmetics manufacturing, antioxidants, among others. Some of its properties in the medical area include its potent bactericidal, hemostatic and tissue regenerative effect. Giving improved results thanks to its great properties of biocompatibility, biodegradability, low toxicity and great antimicrobial potential. However, more clinical studies are needed to know its benefits and what its use in the clinical area implies. Therefore, the present manuscript aims to provide existing information on chitosan for the research and development of new, safer and more effective dental materials.

Contamination of SARS-CoV-2 RNA on personal protective equipment and environmental surfaces in nonpatient entry area of a Fangcang shelter hospital.

To determine the extent of contamination of personal protective equipment (PPE) and surfaces by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the nonpatient entry area of a Fangcang shelter hospital, the medical staff accommodation area, and the staff transport bus. We collected 816 samples from the nonpatient entry area and floors in a Fangcang shelter hospital, medical staff accommodation area, and scheduled bus, and the five major types of PPE used from April 13 to May 18, 2022. SARS-CoV-2 ribonucleic acid (RNA) was detected by reverse transcription-polymerase chain reaction. Overall, 22.2% of PPE samples were positive for SARS-CoV-2 RNA. Boot covers and gowns were the most contaminated types of PPE. The positive PPE contamination rate of staff collecting respiratory specimens was significantly higher than that of the general-treatment staff group (35.8% vs. 12.2%) and cleaner group (35.8% vs. 26.4%), p < 0.01. In total, 27 of 265 (10.2%) environmental surface samples were positive for SARS-CoV-2 RNA. The contamination-positive rates were 26.8% (22/82), 5.4% (4/74), and 0.9% (1/109) for contaminated, potentially contaminated, and clean zones, respectively. SARS-CoV-2 RNA was frequently detected on objects such as mobile phones, tables, computer keyboards and mice, and door handles. SARS-CoV-2 RNA was widely distributed on high-touch surfaces and on PPE in the contaminated zone of the Fangcang shelter hospital, implying a potentially high infection risk for healthcare workers. Our findings emphasize the need to ensure adequate environmental cleaning, improve hand hygiene, and reduce the risk of infection. Additionally, prevention of self-contamination during PPE donning and doffing is complex and needs more research.