Advances In Medical Technology Research Articles

Efficient colorectal polyp segmentation using wavelet transformation and AdaptUNet: A hybrid U-Net

The prevalence of colorectal cancer, primarily emerging from polyps, underscores the importance of their early detection in colonoscopy images. Due to the inherent complexity and variability of polyp appearances, the task stands difficult despite recent advances in medical technology. To tackle these challenges, a deep learning model featuring a customized U-Net architecture, AdaptUNet is proposed. Attention mechanisms and skip connections facilitate the effective combination of low-level details and high-level contextual information for accurate polyp segmentation. Further, wavelet transformations are used to extract useful features overlooked in conventional image processing. The model achieves benchmark results with a Dice coefficient of 0.9104, an Intersection over Union (IoU) coefficient of 0.8368, and a Balanced Accuracy of 0.9880 on the CVC-300 dataset. Additionally, it shows exceptional performance on other datasets, including Kvasir-SEG and Etis-LaribDB. Training was performed using the Hyper Kvasir segmented images dataset, further evidencing the model's ability to handle diverse data inputs. The proposed method offers a comprehensive and efficient implementation for polyp detection without compromising performance, thus promising an improved precision and reduction in manual labour for colorectal polyp detection.

Development of a passive wireless sensor for fluidic detection and characterization utilizing the PCB-based coplanar electrode (PCE) configuration

During the global economic development, there's a growing focus on healthcare, especially in the advancement of medical diagnostic technologies, with a significant emphasis on glucose level evaluation. Glucose biosensors, predominantly electrochemical, have evolved over four generations, with the first three being enzyme-based and known for sensitivity and cost-effectiveness, albeit with limitations due to environmental susceptibility and reliance on enzyme activity. Recent advancements in non-invasive blood glucose monitoring, utilizing optical, microwave, and electrochemical techniques, offer diverse benefits without tissue penetration. Among these, impedance sensing stands out due to its flexibility and integration capability in handheld devices. This study proposes a wireless passive impedance method leveraging the inductor-capacitor (LC) sensing technique and PCB (Printed Circuit Board)-based coplanar electrode (PCE) configuration for fluidic sample detection. The proposed system integrates a two-coplanar-electrode layout with a square spiral inductor to assess fluidic conductivity and characterize various fluid types within samples. The effectiveness of this configuration was validated through experiments with NaCl and glucose solutions, confirming the feasibility of integrating PCB-based coplanar electrodes into conventional LC passive wireless sensing designs for fluidic detection and characterization.

Cardiac signals classification via optional multimodal multiscale receptive fields CNN-enhanced Transformer

The advancement in medical data collection technology has propelled an increase in demand for modeling cardiac physiological signals. However, current research primarily focuses on unimodal signals, leaving a gap in the study of more comprehensive multimodal signals. Directly applying late fusion specific to modalities or early fusion mixing modalities fails to adequately capture crossmodal information. This paper proposes an optional multimodal CNN-enhanced Transformer fusion network based on multiscale receptive fields. Introducing a switching modal experts for stage-wise representation, the first stage excavates modality-specific features and balances intermodal relationships, while the second stage captures crossmodal interaction information in a shared latent space, promoting deep modality fusion. Due to the flexibility of the switching modal experts, the model can be applied not only to multimodal data but also to unimodal data. Additionally, to address the performance disparity between Transformers and Convolutional Neural Networks (CNN), we combine the advantages of CNN to construct a CNN-enhanced Transformer. Specifically, improving patch embedding introduces multiscale receptive fields and integrates convolution and residual connections into the feed forward network (FFN) to assist the FFN in learning complex non-linear features and aggregating local features. Experimental results demonstrate that our model achieves outstanding performance in both unimodal and multimodal modes across different datasets, surpassing a range of CNNs, Transformers, and CNN-Transformer hybrid networks.

Acute leukemia prediction and classification using convolutional neural network and generative adversarial network

Acute Leukemia (AL) is a type of cancer that affects the blood cells and can be fatal if not detected and treated early. Flow cytometry is a key means of detecting AL, but requires manual processing by trained professionals, applying the manual gating method to huge amounts of raw data, making it time-consuming and labor-intensive. This study uses the deep learning Convolutional Neural Network (CNN) method for classification prediction based on two-dimensional graph for the parameter combinations of flow cytometry data to differentiate AL as normal, Acute Myeloid Leukemia (AML) and Acute Lymphoblastic Leukemia (ALL) three categories. This approach normalizes raw data, removes outliers, and further augments data using Generative Adversarial Networks (GAN) to generate two-dimensional scattergrams of different parameter combinations generated by four methods. We then assess post-training classification prediction accuracy to identify the most effective preprocessing method and parameter combination. Experimental results obtain accuracy rates of 73–86 %. In the two-dimensional scatter plot of different parameter combinations generated by the four methods, the combination of CD3 and CD7 cell population parameters had the best classification and prediction accuracy, with image classification and identification reaching a high of 86 % through the use of GAN-based data augmentation. Advances in medical testing technology has reduced analysis times and increased data throughput. At the same time, artificial intelligence techniques are increasingly used for analysis and detection, performing large numbers of repetitive actions to reduce the potential for subjective assessment error from manual analysis, thus allowing for the earlier detection and treatment of disease.

Retrospective evaluation of neonates with fatal congenital lung malformation: A single center 15-year forensic autopsy experience.

Congenital lung malformation (CLM) is a leading cause of infant mortality. Clinical methods for diagnosing CLM mainly rely on computed tomography, magnetic resonance imaging, ultrasonography, and Doppler. However, forensic identification of the cause of death in neonates is challenging. Unequivocal classification criteria for CLM are missing as its forensic identification is ambiguous. Therefore, we aimed to analyze neonatal death cases at our center to assist in identifying those with congenital lung malformation. This retrospective study identified and classified the causes of deaths of neonates autopsied between January 2008 and April 2023. All cases born alive and died within 28 days with a clear time of death were selected, and forensic experts reviewed their records. The manner, cause of death, and other characteristics were noted and discussed. This retrospective study reveals a steady increase in autopsy cases from 2008 to 2015, attributed to improved parental consent, heightened awareness of autopsy importance, and enhanced medical resources. However, a subsequent decline post-2015 is observed, potentially influenced by advancements in medical technology and prenatal examination protocols. The top causes of neonatal mortality include respiratory diseases, asphyxia, congenital dysplasia, and fetal distress. Congenital lung malformations, particularly bronchopulmonary malformations, constitute a significant portion of congenital anomalies. This study underscores the importance of standardized autopsies and histopathological examinations in diagnosing and understanding CLM. Future research should focus on expanding case collections and elucidating the genetic basis of CLM to improve forensic management and outcomes.

Exploiting 2D-SDMCHM and matching embedding driven by flag-shaped hexagon prediction for visually meaningful medical image cryptosystem

With the proliferation of advanced medical technologies and smart wearable devices, a considerable volume of patient data and medical images is being generated and stored, leading to an escalating concern over patient privacy violations and manipulation. Therefore, safeguarding the secrecy and integrity of medical images is paramount for preserving patient privacy and ensuring accurate medical diagnostics. To tackle this challenge, this paper introduces a novel approach, the Visually Meaningful Medical Image Cryptosystem (VMMIC), leveraging a 2-Dimensional Sinusoidal Discrete Memristor Coupled Hyperchaotic Map (2D-SDMCHM) to protect the privacy of medical images. The innovation of this study is primarily reflected in three aspects: Firstly, a novel Discrete Memristor (DM) model is proposed, upon which a new 2D-SDMCHM is constructed. Comparative analysis showcases its superior chaos robustness, as evidenced by evaluations through bifurcation diagrams, phase trajectories, Lyapunov exponents, and Shannon entropy. Secondly, we introduce a measurement matrix optimization algorithm based on Optimal Matrix Arrangement (OMA) for Compressive Sensing (CS), aimed at minimizing the coherence of the measurement matrix, thereby enhancing reconstruction accuracy. Lastly, a Matching Embedding Method Driven by Flag-Shaped Hexagon Prediction (MEMFHP) is introduced to ensure lossless concealment of confidential information. Experimental findings and comparative evaluations affirm the VMMIC's capability to meet high standards of reconstruction quality, steganography, and efficiency in handling medical images, while also demonstrating robustness against various attacks. Consequently, the proposed VMMIC holds significant promise for practical implementation in engineering applications.

Psychological distress, sexual satisfaction and quality of life of gynaecological cancer patients and their spouses during cancer survivorship: A comparison of husbands and wives.

To investigate the psychological distress, sexual satisfaction, and quality of life of gynaecological cancer survivors and their spouses during cancer survivorship. The survival rate of patients with cancer is increasing owing to advances in medical treatment technology. Spouses are the closest companions of gynaecological cancer survivors. Patients with gynaecological cancer and their spouses face different situations and challenges after experiencing cancer invasion. Questionnaire-based cross-sectional study. Convenience sampling was employed, and 180 participants, including patients with gynaecological cancer and their spouses, were enrolled. A structured questionnaire was used to investigate the psychological distress, sexual satisfaction, and quality of life of gynaecological cancer survivors and their spouses during acute, extended, and permanent survivorship. The STROBE checklist guided the study preparation. For gynaecological cancer survivors and their spouses, (1) severe psychological distress was present during acute survivorship, with anxiety extending until permanent survivorship; (2) no significant differences were observed in pre- and post-treatment sexual satisfaction, although pre-treatment sexual satisfaction was higher than post-treatment sexual satisfaction in all three cancer survivorship stages and (3) quality of life decreased during acute survivorship and gradually improved with time. Psychological distress, sexual satisfaction and quality of life of gynaecological cancer survivors and their spouses worsened during acute survivorship and improved over time until permanent survivorship. Gynaecological cancer survivors and their spouses experience anxiety and depression from diagnosis confirmation until permanent survivorship (>5 years survival). Therefore, clinical nurses' sensitivity to emotional distress in cancer survivors and their spouses can be improved and a consistent and routine evaluation method has been established for the early detection of such emotional distress. The results of this study can provide a reference for clinical healthcare professionals and contribute to a better quality of care.

Potential role of stem cells from human exfoliated deciduous teeth in inducing liver regeneration

AbstractBackground and AimEven with advancement of medical technologies, liver transplantation still faces several major challenges. Hence, other treatment modalities are urgently needed for patients with end‐stage liver disease. Stem cells from human exfoliated deciduous teeth (SHED) was discovered to have highly proliferative and pluripotent properties; including differentiation into hepatocyte‐like cells. This study aims to investigate the capability of intrasplenic transplanted SHED and SHED‐Hep cells in inducing proliferation of stem cells and native hepatocytes in order to accelerate liver regeneration in liver fibrosis mice models.MethodsThree carbon tetrachloride (CCl4)‐injured male mice groups were used in this study. Two of those groups were transplanted with either SHED or SHED‐Hep, while the other did not undergo transplantation. One age‐ and sex‐ matched healthy mice group was used as control. All specimens were immunohistochemically stained with anti‐Ki‐67 antibodies and anti‐proliferating cell nuclear antigen (PCNA) antibodies before counter stained with hematoxylin–eosin.ResultsAnti‐Ki‐67 antibodies staining: at both 8 and 12 weeks, proliferating activity was predominantly seen on both SHED‐ and SHED‐Hep‐transplanted CCl4‐injured mice groups, while control and non‐transplanted CCl4‐injured mice group showed little to no sign of proliferation activity. Anti‐PCNA staining: at both 8 and 12 weeks, significant proliferating activity was detected by PCNA staining, mainly on stem cells population area on SHED‐ and SHED‐Hep‐treated group.ConclusionsIn conclusion, this study has provided the evidence that transplantation of SHED or SHED‐Hep on liver‐injured mice induced proliferation of both transplanted stem cells and native liver cells in order to accelerate liver regeneration.

A Study of Key Factors Influencing the Willingness of RhD-negative Blood Donors to Donate Blood in Chongqing, China, 2017-2019

The importance of RhD-negative blood in clinical blood transfusion is becoming more and more prominent with the continuous advancement of medical technology, but the resources of blood donors are especially precious due to their rarity. As a densely populated area, the recruitment and retention of RhD-negative blood donors in Chongqing Municipality is crucial to ensure clinical blood supply. In this study, a questionnaire survey method was used to collect 1,200 valid questionnaires from RhD-negative blood donors in Chongqing Municipality during 2019-2021 by random sampling. The questionnaires covered the donors' knowledge of RhD-negative blood, knowledge of blood donation policy, motivation to donate blood, experience of blood donation and willingness to donate blood again. The data were statistically analyzed using SPSS software to explore the key factors affecting the willingness to donate blood through descriptive statistics and chi-square test. The results showed that factors such as donors' knowledge of RhD-negative blood, knowledge of blood donation policy, motivation and experience of blood donation significantly affected willingness to donate blood. Therefore, measures such as strengthening the publicity of RhD-negative blood knowledge, improving the blood donation policy, and upgrading the quality of blood donation services are recommended to promote the stable development of the RhD-negative blood donor workforce, to meet the urgent clinical demand for RhD-negative blood, and at the same time to enhance the satisfaction of the donors and the blood donation rate.

Enhancing Healthcare Decision-Making: Comparison Between Health Technology Assessments and Access to Medical Care in a High-income Country vs. Low/middle Income Countries

Background: Healthcare decision-making is a complex process that involves evaluating the value, efficacy, and accessibility of medical technologies and interventions. Health Technology Assessments (HTA) in high-income countries (HICs) have become a cornerstone of evidence-based healthcare decision-making. This systematic evaluation framework, exemplified by its robust, impartial examination of various medical technologies, plays a pivotal role in establishing the clinical effectiveness and cost-effectiveness of health technologies. In contrast, low and middle-income countries (LMICs) frequently contend with resource constraints and intricate healthcare systems characterized by fragmentation and limited access to advanced medical technologies. As formalized HTA processes may be less established, limiting comprehensive evaluations, decision-making may rely on regulatory approval, clinical guidelines, or international recommendations in LMICs. Similarly, access to medical care in high-income settings, such as the presence of universal healthcare coverage and well-developed health systems, contributes to equitable access to a wide range of medical services. In LMICs, challenges related to healthcare infrastructure, funding, and health workforce shortages hinder access to essential medical care, leading to inequities in health outcomes. This short review aims to compare the approaches to healthcare decision-making in high-income and low/middle-income countries, with a specific focus on HTAs and access to medical care.

Recent advances in the pathogenesis, diagnosis, and treatment of sepsis‐associated encephalopathy

AbstractSepsis is a life‐threatening organ dysfunction syndrome caused by the host's dysregulated response to infection. The leading causes of death in critically ill patients are sepsis‐associated encephalopathy (SAE), respiratory dysfunction, circulatory dysfunction, and other multi‐organ dysfunctions. SAE is among the most common serious complications of sepsis and is associated with a poor prognosis and long‐term cognitive dysfunction. Its clinical manifestations vary, and there are still no unified diagnostic criteria. The incidence of SAE varies from 9% to 71% in critically ill patients due to therapeutic interventions such as sedation, mechanical ventilation, and muscle relaxants. Advances in medical technology have significantly increased the survival rate of patients with sepsis, but up to 21% now experience long‐term sequelae or cognitive impairment. The lack of specific early diagnostic and treatment methods leads to increased SAE‐associated mortality and complications in patients, which also impose heavy economic burdens. This article reviews the pathogenesis and diagnostic methods of SAE and progress in its treatment, aiming to reduce the mortality and hospitalization lengths of patients with SAE and improve their survival rate and quality of life through early detection, diagnosis, and effective treatment.

Efficacy and safety of topical NSAIDs combined with physiotherapy for frozen shoulder: a randomized controlled trial.

Frozen shoulder is a prevalent condition among individuals in their middle and later years. Invasive therapy has shown promising results in the treatment of frozen shoulders, but its widespread adoption has been hampered by high costs and the need for advanced medical technology. As a result, patients with frozen shoulders often turn to non-steroidal anti-inflammatory drugs (NSAIDs) for symptomatic relief. However, the oral administration of NSAIDs can lead to troublesome adverse effects on the gastrointestinal, cardiovascular, and urinary systems. In contrast, topical NSAIDs have gained attention for their excellent efficacy and lower adverse effects in various chronic pain conditions. Therefore, our study aimed to investigate the efficacy and safety of topical NSAIDs in improving pain and mobility among patients with frozen shoulders. A total of 108 patients experiencing moderate to severe pain and mobility impairment due to frozen shoulder were enrolled in this study. The participants were randomly assigned to either the experimental group (n=72) or the control group (n=36). The experimental group received daily treatment with the loxoprofen hydrogel patch (LOX-P) in addition to basic rehabilitation physiotherapy. The control group was treated with flurbiprofen cataplasm (FLU-C) twice a day, along with rehabilitation physiotherapy. The primary endpoint for evaluating the efficacy of the two patches was the Constant-Murley score (CMS). Clinical symptom data, adverse events, and patient satisfaction were also recorded. After 14 days of treatment, the effective rate was 66.67% (n=48) in the experimental group and 41.67% (n=15) in the control group. The overall difference in the effective rates was 25.00% (95% CI=5.20-42.52; p=0.013). The safety profiles of the two topical agents were similar, with only a few adverse events reported. The loxoprofen hydrogel patch demonstrates a significant ability to alleviate shoulder pain and restore shoulder function in the treatment of frozen shoulder, with minimal adverse reactions. Chictr.org.cn ID: ChiCTR2100052375.

Predicting Lung Cancer Survival to the Future: Population-Based Cancer Survival Modeling Study.

Lung cancer remains the leading cause of cancer-related mortality globally, with late diagnoses often resulting in poor prognosis. In response, the Lung Ambition Alliance aims to double the 5-year survival rate by 2025. Using the Taiwan Cancer Registry, this study uses the survivorship-period-cohort model to assess the feasibility of achieving this goal by predicting future survival rates of patients with lung cancer in Taiwan. This retrospective study analyzed data from 205,104 patients with lung cancer registered between 1997 and 2018. Survival rates were calculated using the survivorship-period-cohort model, focusing on 1-year interval survival rates and extrapolating to predict 5-year outcomes for diagnoses up to 2020, as viewed from 2025. Model validation involved comparing predicted rates with actual data using symmetric mean absolute percentage error. The study identified notable improvements in survival rates beginning in 2004, with the predicted 5-year survival rate for 2020 reaching 38.7%, marking a considerable increase from the most recent available data of 23.8% for patients diagnosed in 2013. Subgroup analysis revealed varied survival improvements across different demographics and histological types. Predictions based on current trends indicate that achieving the Lung Ambition Alliance's goal could be within reach. The analysis demonstrates notable improvements in lung cancer survival rates in Taiwan, driven by the adoption of low-dose computed tomography screening, alongside advances in diagnostic technologies and treatment strategies. While the ambitious target set by the Lung Ambition Alliance appears achievable, ongoing advancements in medical technology and health policies will be crucial. The study underscores the potential impact of continued enhancements in lung cancer management and the importance of strategic health interventions to further improve survival outcomes.

경찰공무원의 퇴직준비역량과 교육참여도가 경제활동의지에 미치는 영향

Today's aging population and extension of life expectancy are increasing the economic activities intention after retirement through partial retirement. This is because the age of physical health has been extended by 20 to 30 years compared to the past, due to advancements in medical technology and self-management. This study analyzes the influence of the retirement competencies and educational experience of police officiers on economic activity intention. Additionally, it analyzes the moderated effect of role models. For this study, an online survey was conducted using a questionnaire among 348 police officer.The statistical analysis software used was SPSS 24.0. It involved factor analysis, reliability testing and multiple regression analysis to verify the hypotheses. The research results were as follows. First, as a result of examining the effect of retire competencies on economic activity intention, it was found that among the retire competencies factors, financial management and digital competencies had a significantly positive effect on economic activity intention. Second, educational experience had a significantly positive effect on economic activity intention. Third, financial management and educational experience had a significantly positive effect on economic activity intention according to roll model.

The Role of Echocardiography in the Diagnosis of Infective Endocarditis and its Complications

Infective endocarditis (IE) remains associated with high morbidity and mortality rates despite advances in medical technology, diagnostics, and treatment. Hospital mortality for IE reaches up to 22%, with a five-year mortality rate of 40%. Globally, the incidence of IE has increased, with recent figures indicating 13.8 cases per 100,000 annually, up from 1.5–11.6 per 100,000 reported between 1990 and 2010. A retrospective cohort study in a tertiary care center in Korea demonstrated a significant rise in the monthly incidence of IE from 2.0 in 2005 to 3.8 in 2017. This increase is attributed to the enhanced utilization of diagnostic tools such as echocardiography, computed tomography (CT), and positron emission tomography (PET). The 2015 European Society of Cardiology (ESC) guidelines incorporated complementary imaging modalities like Single Photon Emission Computed Tomography-CT (SPECT/CT), 18F-FDG PET/CT, and Cardiac CT, alongside traditional transthoracic and transesophageal echocardiography. The 2023 ESC guidelines further expanded these algorithms to include Cardiac CTA, MRI, PET/CT, and WBC SPECT. However, transthoracic, and transesophageal echocardiography remain the primary and essential diagnostic tools for suspected IE. This review examines the role of echocardiography in diagnosing IE, highlighting typical ultrasound findings, valve damage, and associated complications. Ultrasound is pivotal for early detection and prognosis of IE, identifying vegetations, abscesses, pseudoaneurysms, and fistulas. New vegetations typically appear irregular and oscillate, with transthoracic echocardiography detecting vegetations larger than 5mm with 90% sensitivity. Detailed echocardiographic assessment provides critical insights for the surgical management of IE and enhances the understanding of IE’s complex pathology.

The impact of psychological factors on in vitro fertilization (IVF) outcomes: a comprehensive review

This comprehensive review explores the significant impact of psychological factors on the outcomes of In Vitro Fertilization (IVF) treatments. Despite the advancements in medical technology enhancing the physical success rates of IVF procedures, the psychological well-being of individuals undergoing these treatments plays a crucial role in their overall effectiveness. This paper delves into the various psychological stressors faced by couples, including anxiety, depression, and stress, and their direct correlation with IVF treatment outcomes. By examining a wide range of studies, this review highlights the importance of psychological interventions and support systems in improving the success rates of IVF treatments. Furthermore, it discusses the current gaps in the literature and suggests directions for future research. The findings of this review underscore the necessity of integrating psychological care into fertility treatments to address the mental health needs of individuals undergoing IVF, thereby enhancing their quality of life and increasing the likelihood of successful outcomes. Through a detailed analysis of existing research and methodologies, this paper aims to contribute to the understanding of the psychosocial aspects of IVF and encourage the development of more holistic treatment approaches.

Planar antenna design for contactless energizing applications: resonance analysis

Advances in medical technology suggest that the application of implantable medical devices or Smart Hospital Devices (SHD) can enhance the control and treatment of chronic disorders. However, most of these developments require an electrical power source for operation, making the use of batteries unfeasible. This paper presents the design and resonance analysis of four different geometries for the fabrication of planar antennas as an alternative to a contactless power supply. Previously published software [19] was used to calculate the electrical parameters for each coil design. Operating trials were executed under laboratory conditions, and a bracket manufactured using polylactic acid (PLA) through a 3D printer was used to accurately define the distances between coils to achieve correct alignment between them. Based on the experimental results, it was possible to calculate the resonant frequency of the inductive links at a 5 mm spacing. Similarly, it is possible to calculate the capacitive effect necessary to improve the resonant circuit in different transmitter-receiver planar antenna pairs. The most efficient combination to induce voltage in these links is to use the hexagonal profile design as a transmitter and receiver antenna, applying a sinusoidal signal with 8 MHz frequency.

The role of ventricular assist device in the management of advanced heart failure: a literature review

The ventricular assist device has become a reliable and enduring therapy for patients with end-stage heart failure, with over 22,000 implantations to date. Initially designed as a bridge-to-transplant option but now it has become permanent cure for patients with acute heart failure. VAD has significant advancements in medical management and technology, particularly with the introduction of newer-generation devices, have greatly enhanced patient outcomes. This progress has led to an increasing use of ventricular assist devices as a destination therapy. Nonetheless, the substantial burden of adverse events remains a critical challenge in the current state of ventricular assist device therapy, despite this, its viable alternative of heart transplantation as it has solved the complications of donor heart and proved significant success among patient with acute heart failure.

Advances in undergraduate and postgraduate education- bedside, simulation and E-learning

Clinical bedside teaching the cornerstone of medical education in the 19th century has been shaped and developed by changes in healthcare delivery and work practices. Developing skilled clinicians to work and thrive in these complex environments requires innovative and adaptive strategies. In this rapidly changing environment compounded by a shorter duration of training, there is an increasing focus on the student learner, team-based working and the development of professionalism. The continuum of medical education from undergraduate through postgraduate to continued professional development has been greatly enhanced by the adoption of new strategies and technologies. Simulation is long established in medical education and its benefits well recognised. Technological developments including Artificial Intelligence have supported and enhanced the quality of simulation in medical education. There is a broad range of simulation available with varying degrees of fidelity, as required, culminating in immersive virtual reality. The challenges for medical educators of the Covid-19 pandemic, with closure or restricted access to clinical patients, wards and classrooms, resulted in rapid restructuring of teaching programs and for many to move “on-line”. This resulted in widespread rapid adoption of technologically driven medical education, with E-learning, blended learning and innovative strategies to increase student engagement. The seismic changes in medical education necessitated by the Covid-19 pandemic coupled with the upskilling of medical educators and technological advances, should result in an exciting period of continued innovation in medical education, a second “Golden Era” and enhance medical education for many years to come.

Optimizing ventilatory support in ARDS: A comprehensive guide for ICU nurses on patient care

The emergence of COVID-19 as a global pandemic has placed an unprecedented strain on healthcare systems worldwide, highlighting a critical shortage of trained healthcare professionals equipped to manage such a crisis. This deficit poses a significant challenge to the delivery of healthcare services, particularly in the context of intensive care units (ICUs) where the use of advanced medical technologies, such as ventilators, is paramount. For nurses with limited experience in ICU settings, navigating the complexities of invasive positive pressure ventilation (IPPV), a principal method of mechanical ventilation for critically ill patients can be daunting. This article aims to serve as a comprehensive guide for nurses less familiar with the intricacies of managing patients on IPPV, offering insights and strategies to enhance their competence and confidence in this critical aspect of patient care.