Ethnic, racial and migrant inequalities in respiratory health

Disparities in the incidence, prevalence, and morbidity and mortality rates of many respiratory diseases are evident among ethnic groups. Biological, cultural and environmental factors related to ethnicity can all contribute to the differences in respiratory health observed among ethnic minority groups, but the inequalities observed are most commonly due to lower socioeconomic position. People who migrate within a country or across an international border may experience an improvement in respiratory health associated with improvements in socioeconomic position. However, migrants may also experience worse health outcomes in destination countries, as they are faced by barriers in language and culture, discrimination, exclusion and limited access to health services. While some high-quality studies investigating ethnicity and respiratory health are available, further research into ethnic differences is needed. Improving the recording of ethnicity in health records, addressing barriers to accessing respiratory healthcare and improving cultural literacy more generally are some of the ways that inequalities can be tackled.Copyright © ERS 2023.

Relationship between neurological manifestations and severity of COVID-19. San Vicente de Paul Hospital. Ecuador 2021.

Introduction: SARS-CoV-2 mainly affects the respiratory system, but the damage caused by this virus also extends to other systems, including the nervous system, and the mechanisms of neurological infection can be direct or indirect. Objective(s): To determine the relationship between neurological manifestations and disease severity in symptomatic COVID-19 positive patients at San Vicente de Paul Hospital in 2021. Material(s) and Method(s): A cross-sectional observational study was conducted using medical records of patients hospitalized with COVID-19 and neurological manifestations, which were classified into manifestations of the central nervous system and manifestations of the peripheral nervous system. Result(s): The results show that 74,1 % of patients presented neurological manifestations;the highest percentage was concentrated in patients who developed severe disease (15 [60 %], CNS;91 [77,1 %], PNS;125 [65,4 %], CNS and PNS). The joint presence of central and peripheral neurological manifestations was significantly associated with critical COVID-19 (P value= 0,011;OR: 2,005). The mortality rate reached 2,69 %. Conclusion(s): Neurological manifestations in hospitalized COVID-19 patients are very common, and critical COVID-19 is more likely to have neurological manifestations.Copyright © 2022 Universidad de Ciencias Medicas de La Hab. All rights reserved.

A Simulation of a Design and Implementation of a New Low- Cost Prototype Portable Smart Ventilator

The outbreak of the Covid-19 virus prompted many engineers and researchers around the world to seek to develop mechanical ventilation devices and make them easy to use and affordable. This paper presents a simulation model for a group of medical sensors and gives very accurate results. This model contributes to the development and improvement of the artificial breathing system by comparing the results between the simulation model and the realistic response of the human lung. © 2023 IEEE.

Acoustic-Based Deep Learning Architectures for Lung Disease Diagnosis: A Comprehensive Overview.

Lung auscultation has long been used as a valuable medical tool to assess respiratory health and has gotten a lot of attention in recent years, notably following the coronavirus epidemic. Lung auscultation is used to assess a patient's respiratory role. Modern technological progress has guided the growth of computer-based respiratory speech investigation, a valuable tool for detecting lung abnormalities and diseases. Several recent studies have reviewed this important area, but none are specific to lung sound-based analysis with deep-learning architectures from one side and the provided information was not sufficient for a good understanding of these techniques. This paper gives a complete review of prior deep-learning-based architecture lung sound analysis. Deep-learning-based respiratory sound analysis articles are found in different databases including the Plos, ACM Digital Libraries, Elsevier, PubMed, MDPI, Springer, and IEEE. More than 160 publications were extracted and submitted for assessment. This paper discusses different trends in pathology/lung sound, the common features for classifying lung sounds, several considered datasets, classification methods, signal processing techniques, and some statistical information based on previous study findings. Finally, the assessment concludes with a discussion of potential future improvements and recommendations.

Respiratory issues in patients with multiple sclerosis as a risk factor during SARS-CoV-2 infection: a potential role for exercise.

Coronavirus disease-2019 (COVID-19) is associated with cytokine storm and is characterized by acute respiratory distress syndrome (ARDS) and pneumonia problems. The respiratory system is a place of inappropriate activation of the immune system in people with multiple sclerosis (MS), and this may cause damage to the lung and worsen both MS and infections.The concerns for patients with multiple sclerosis are because of an enhance risk of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The MS patients pose challenges in this pandemic situation, because of the regulatory defect of autoreactivity of the immune system and neurological and respiratory tract symptoms. In this review, we first indicate respiratory issues associated with both diseases. Then, the main mechanisms inducing lung damages and also impairing the respiratory muscles in individuals with both diseases is discussed. At the end, the leading role of physical exercise on mitigating respiratory issues inducing mechanisms is meticulously evaluated.

Acute eosinophilic pneumonia-like syndrome post-initiation of vortioxetine.

A man in his mid-30s presented to the emergency department with a 1-week history of fatigue, loss of appetite, fever and productive (yellow) cough. This progressed to requiring admission to intensive care needing a oxygen therapy via high-flow nasal cannula for acute hypoxaemic respiratory failure. He had recently started vortioxetine for major depressive disorder, and his acute symptoms correlated with an increase in the dose of vortioxetine. For more than 20 years, rare but consistent reports of serotonergic medications have been implicated in eosinophilic pulmonary conditions. During this same period, serotonergic medications have become a mainstay solution for a wide range of depressive symptoms and disorders. This is the first report of an eosinophilic pneumonia-like syndrome occurring while consuming the novel serotonergic medication vortioxetine.

Artificial-Intelligence-Driven Algorithms for Predicting Response to Corticosteroid Treatment in Patients with Post-Acute COVID-19.

Pulmonary fibrosis is one of the most severe long-term consequences of COVID-19. Corticosteroid treatment increases the chances of recovery; unfortunately, it can also have side effects. Therefore, we aimed to develop prediction models for a personalized selection of patients benefiting from corticotherapy. The experiment utilized various algorithms, including Logistic Regression, k-NN, Decision Tree, XGBoost, Random Forest, SVM, MLP, AdaBoost, and LGBM. In addition easily human-interpretable model is presented. All algorithms were trained on a dataset consisting of a total of 281 patients. Every patient conducted an examination at the start and three months after the post-COVID treatment. The examination comprised a physical examination, blood tests, functional lung tests, and an assessment of health state based on X-ray and HRCT. The Decision tree algorithm achieved balanced accuracy (BA) of 73.52%, ROC-AUC of 74.69%, and 71.70% F1 score. Other algorithms achieving high accuracy included Random Forest (BA 70.00%, ROC-AUC 70.62%, 67.92% F1 score) and AdaBoost (BA 70.37%, ROC-AUC 63.58%, 70.18% F1 score). The experiments prove that information obtained during the initiation of the post-COVID-19 treatment can be used to predict whether the patient will benefit from corticotherapy. The presented predictive models can be used by clinicians to make personalized treatment decisions.

Rehabilitation Characteristics and Outcomes for Lung Transplantation for COVID-19: A Case Series.

OBJECTIVE: Severe coronavirus disease 2019 (COVID-19) can result in irreversible lung damage, with some individuals requiring lung transplantation. The purpose of this case series is to describe the initial experience with the rehabilitation and functional outcomes of 9 patients receiving a lung transplant for COVID-19. METHODS: Nine individuals, ranging in age from 37 to 68 years, received bilateral orthotopic lung transplantation (BOLT) for COVID-19 between December 2020 and July 2021. Rehabilitation was provided before and after the transplant, including in-hospital rehabilitation, postacute care inpatient rehabilitation, and outpatient rehabilitation. RESULTS: Progress with mobility was limited in the pretransplant phase despite rehabilitation efforts. Following transplantation, 2 individuals expired before resuming rehabilitation, and 2 others had complications that delayed their progress. The remaining 5 experienced clinically important improvements in mobility and walking capacities. CONCLUSION: Considerable rehabilitation resources are required to care for individuals both before and after BOLT for COVID-19. Rehabilitation can have a profound impact on both functional and clinical outcomes for this unique patient population. IMPACT: There is limited literature on the rehabilitation efforts and outcomes for patients who received BOLT for COVID-19. Occupational therapists and physical therapists play an important role during the pretransplant and posttransplant recovery process for this novel patient population. LAY SUMMARY: Patients with a bilateral orthotopic lung transplant due to COVID-19 require a unique rehabilitation process. They have significant difficulties with activities of daily living and functional mobility across the pretransplant and posttransplant continuum of care, but progressive gains in functional performance may be possible with a comprehensive multidisciplinary rehabilitation program.

Failing categorization of severe COVID-19 ARDS into ventilatory subphenotypes studied via the clinical-histopathologic relationship.

BACKGROUND: Categorization of severe COVID-19 related acute respiratory distress syndrome (CARDS) into subphenotypes does not consider the trajectories of respiratory mechanoelastic features and histopathologic patterns. This study aimed to assess the correlation between mechanoelastic ventilatory features and lung histopathologic findings in critically ill patients who died because of CARDS. METHODS: Mechanically ventilated patients with severe CARDS who had daily ventilatory data were considered. The histopathologic assessment was performed through full autopsy of deceased patients. Patients were categorized into two groups according to the median worst respiratory system compliance during ICU stay (CrsICU). RESULTS: Eighty-seven patients admitted to ICU had daily ventilatory data. Fifty-one (58.6%) died in ICU, 41 (80.4%) underwent full autopsy and were considered for the clinical-histopathological correlation analysis. Respiratory system compliance at ICU admission and its trajectory were not different in survivors and non-survivors. Median CrsICU in the deceased patients was 22.9 ml/cmH2O. An inverse correlation was found between the CrsICU and late-proliferative diffuse alveolar damage (DAD) (r = -0.381, p = 0.026). Late proliferative DAD was more extensive (p = 0.042), and the probability of stay in ICU was higher (p = 0.004) in the "low" compared to the "high" CrsICU group. Cluster analysis further endorsed these findings. CONCLUSIONS: In critically ill mechanically ventilated patients, worsening of the respiratory system compliance correlated pathologically with the transition from early damage to late fibroproliferative patterns in non-survivors of CARDS. Categorization of CARDS into ventilatory subphenotypes by mechanoelastic properties at ICU admission does not account for the complexity of the histopathologic features.

Mistakes and complications in the diagnosis and treatment of children with organic foreign body aspiration

The reason for the publication of this article was the increase in the number of children with long-standing organic foreign bodies in the respiratory tract, the late diagnosis of which causes severe complications. The article presents the three most significant cases from the general series, when the diagnosis and treatment tactics at the stages of treatment were associated with errors both at the prehospital stage and in the hospital. In the first clinical case, as it turned out, the child had aspired multiple foreign bodies. The first bronchoscopy revealed one solid foreign body. Due to severe fibrinous-purulent endobronchitis and contact bleeding, the bronchoscopy procedure was aborted. However, after 10 days, the child independently coughed up the second seed, which was a surprise to us. Control bronchoscopy after 3 weeks revealed no foreign bodies. In the second clinical observation, a child developed bronchiectasis due to a long stay of a foreign body in the respiratory tract. The third case demonstrates the diagnosis and treatment tactics in a child with a foreign body against the background of a coronavirus infection. In the first and third cases, the results of treatment were satisfactory. In the second case, a long stay of peanuts in the respiratory tract led to bronchiectasis in the lower lobe of the left lung, which required its removal. In the follow-up, there are no complaints, the child grows and develops according to age. The study analyzes the mistakes made at the stages of diagnosis and treatment of children with foreign bodies in the respiratory tract. Conclusion. Young children with long-term and atypically current respiratory diseases, dubious and even normal radiological picture with the absence of comprehensive information on the anamnesis of diseases should alert the doctor to the possibility of aspiration of a foreign body in the respiratory tract and serve as the basis for performing bronchoscopy.Copyright © 2023 National Academy of Pediatric Science and Innovation. All rights reserved.

Key Elements Affecting the Library's CFU Concentration in Taiwan

Public libraries are popular gathering places, so understanding the factors that contribute to colony-forming unit (CFU) concentrations and how to minimize them is essential. This study aimed to investigate the factors that affect CFU concentrations in a public library, using air sampling (Bioluminescent ATP-assay) and statistical analysis software (SPSS) to collect and analyze data. The findings indicated that the CFU concentration in the library was significantly influenced by the air quality surrounding the building, the number of library visitors, and the hygiene and health of both visitors and employees. Additionally, indoor temperature and humidity were found to be key factors affecting CFU concentration. These findings suggest the need for better ventilation and air filtration systems, as well as regular cleaning and disinfection in public libraries. Furthermore, research is recommended to investigate other potential factors that may impact indoor air quality in public spaces.

On-Site Whole-Genome Sequencing of Sars-Cov-2 Reveals C3037t Mutation in Patient with Atrioventricular Nodal Reentry Tachycardia (Avnrt)

Intro: The spike protein of the SARS-CoV-2 virus targets the human cell receptor of angiotensin-converting enzyme (ACE2), including the myocardium and heart's conduction system. Patients diagnosed with COVID-19 have also been found to exhibit cardiac arrhythmia. Here, a whole-genome sequencing analysis using long-read sequencing was proposed to evaluate the virus genome in a patient who presented with AVNRT as a main presentation of COVID-19. Method(s): The sample was recovered from nasopharyngeal and oropharyngeal swab specimens of a 46-year-old female with no comorbidities who presented with palpitation, and ECG showed typical AVNRT features. The RT-qPCR of SARS- CoV-2 was confirmed positive with a CT-value of 15.82. The total RNAs were extracted and proceeded for RT-qPCR and proceeded with Oxford Nanopore Flongle sequencing. The genomics data of the virus was deposited in GISAID (EPI_ISL_3241561) and further analysed using online bioinformatics tools such as Nextclade CLI 2.3.0. Ethical approval (IREC 2021-080) for the study was obtained from IIUM Research Ethics Committee. Finding(s): Here, we reported a total of 29,775 bp near-complete whole-genome belonging to clade 21J (Delta) of AY.79 lineage (also known as B.1.617.2.79), which formed a dominant variant in Malaysia during the time of sampling. Discussion(s): While a previous study showed an association between Delta variant infection with fulminant myocarditis, the present study reported the benign AVNRT as the main presentation of SARS-CoV-2 infection. Furthermore, we observed the presence of the C3037T mutation previously described in the endomyocardial biopsy of a patient with persistent arrhythmia. Conclusion(s): Even though SARS-CoV-2 targets the respiratory tract, the present study supports the evidence that the ACE2 receptors are present in the heart. In addition, COVID19 is causing more and more damage to heart tissue, and viral transcription has been confirmed on cardiomyocytes. Further functional studies are needed to explore the associated mutations and their relation to cardiac manifestation.Copyright © 2023

Review of Motion Simulation of Particulate Matter in the Respiratory System and Further CFD Simulations on COVID-19

Respirable particulate matter (RSP) is currently very harmful to the human body, potentially causing pulmonary silicosis, allergic rhinitis, acute bronchitis, and pulmonary heart disease. Therefore, the study of the deposition pattern of RSP in the human respiratory system is key in the prevention, treatment, and research of related diseases, whereby the main methods are computer simulation, in vitro solid models, and theoretical analysis. This paper summarizes and analyzes past deposition of RSP in the respiratory tract and also describes them in specific case studies such as COPD and COVID-19 patients, based on the review of the evidence, direction, and focus of future research focusing on simulation, experimentation, and related applications of RSP deposition in the respiratory tract. © 2023 by the authors.

Role of toll-like receptors in the pathogenesis of COVID-19: Current and future perspectives

The coronavirus disease 2019 (COVID-19) pandemic underlines a persistent threat of respiratory tract infectious diseases and warrants preparedness for a rapid response. At present, COVID-19 has had a serious social impact and imposed a heavy global burden on public health. The exact pathogenesis of COVID-19 has not been fully elucidated. Since the outbreak of COVID-19, a renewed attention has been brought to Toll-like receptors (TLRs). Available data and new findings have demonstrated that the interaction of human TLRs and SARS-CoV-2 is a vital mediator of COVID-19 immunopathogenesis. TLRs such as TLR2, 4, 7 and 8 are potentially important in viral combat and activation of immunity in patients with COVID-19. Therapeutics targeting TLRs are currently considered promising options against the pandemic. A number of TLR-targeting immunotherapeutics are now being investigated in preclinical studies and different phases of clinical trials. In addition, innovative vaccines based on TLRs under development could be a promising approach for building a new generation of vaccines to solve the current challenges. In this review, we summarize recent progress in the role of TLRs in COVID-19, focusing the new candidate drugs targeting TLRs, the current technology and potential paths forward for employing TLR agonists as vaccine adjuvants.Copyright © 2023 The Scandinavian Foundation for Immunology.

Croup disease classification using VGG19 and ResNet50 transfer learning method

Detection of any disease in the early stage can save a life. There are many medical imaging modalities like MRI, FMRI, ultrasound, CT, and X-ray used in the detection of disease. In the last decades, neural network-based methods are effective in detecting and classifying the disease based on abnormalities present in the medical images. Acute laryngotracheobronchitis (croup) is one of the common diseases seen in children among the 0.5-3 years age group which infects the respiratory system that can cause the larynx, trachea, and bronchi. Prior detection can lower the risk of spreading and can be treated accurately by a pediatrician. Commonly this infection can be diagnosed though physical examination. But due to the similarity of Covid-19 symptoms urges the physicians to get accurate detection of this disease using X-ray and CT images of the infant's chest and throat. The proposed work aims to develop a croup diagnose system (CDS) which identify the Croup infection through post anterior (PA) view of pediatric X-ray using deep learning algorithm. We used the well-known transfer learning algorithm VGG19 and ResNet50. Data augmentation being adapted for reducing the overfitting and to improve the quantity of image samples. We show that the proposed transfer learning based CDS method can be used to classify the X-ray images into two classes namely, croup and normal. The experiment results confirm that VGG19 performs better than ResNet50 with promising classification accuracy (90.91%.). The results show that the proposed CDS models can be used for more pediatric medical image classification problem. © 2024 World Scientific Publishing Company.

Radiium systemic radiotherapy - 223 patients with mCRPC. Experience of the Republic of Bashkortostan

Introduction & Objectives: The incidence of prostate cancer, both in the world and in the Russian Federation, tends to increase. In the Republic of Bashkortostan in 2021, 699 patients with this diagnosis were registered. 19.6% of patients had stage IV disease at the time of diagnosis. 5818 patients were registered, of which 361 died within a year. The effectiveness of hormonal treatment of common prostate cancer has time limitations, after which there is a development of resistance to castration and progression of the disease. To date, drugs such as kabazitaxel, sipuleucel-T vaccine, abiraterone, enzalutamide and radium-223 have been approved for use in metastatic CRPC. The purpose of the work: analysis of the experience of systemic radiotherapyand Radium - 223 patients with mCRPC in the Republic of Bashkortostan in 2021. Material(s) and Method(s): Analysis of patients who received systemic radiotherapy Radium - 223 in the Republic of Bashkortostan according to medical documentation and research data. In 2021, Radiy-223 radiotherapy was performed on 7 patients diagnosed with mCRPC. Median age 63.14 years. All patients met the criteria for treatment, i.e. had castration-resistant prostate cancer with bone metastases, without visceral metastases. All patients had concomitant pathology from the cardiovascular system, respiratory tract, endocrine system. According to the previous surgical treatment, patients were distributed as follows: orchidectomy - 4, prostatectomy - 1 and 2 patients underwent tumor biopsy. By morphology: Glisson 6 - 2 patients, Glisson 7 - 1, Glisson 8 - 3, Glisson 10 - 1. 4 patients were referred to Xofigo for radiologically confirmed progression, 3 patients were progressingin height at PSA levels. Result(s): 1 patient previously received 1 line of systemic therapy, 5 patients received 2 lines, 1 patient received 3 lines of therapy. 6 patients received all 6 courses of radiotherapy, 1 patient did not complete treatment due to COVID 19. He is expected to complete therapy. All patients are currently alive with no signs of disease progression. Serious side effects were not registered. Conclusion(s): The "therapeutic window" for the prescription of radium-223 is the period before the appearance of visceral metastases and decline of the somatic status. To achieve the maximum benefit from the appointment of radium-223, it is necessary to conduct >=5 cycles of therapy, which is possible in 1-2 treatment lines. It is necessary to select patients carefully for radiotherapy - Radium 223.Copyright © 2022 European Association of Urology. Published by Elsevier B.V.

Post-COVID-19 rehabilitation

The long-term problems for survivors of SARS-CoV-2 infection are not fully understood;data indicates a complex range of symptoms that initially appeared to focus on the respiratory system but now appear to be multisystem and wide ranging. The most frequently reported symptoms appear to be breathlessness, muscle weakness and fatigue. A proportion of individuals have persistent problems that would be amenable to a rehabilitation programme. The programme needs to have a much wider scope and remit than that of conventional pulmonary rehabilitation but this service model may form the foundation of a holistic programme to support the recovery of these individuals. Data from the SARS/MERS pandemic would support this initial approach. Rehabilitation teams need to collaborate to develop a wider interdisciplinary team to offer the best service to patients with post-COVID-19 symptoms.Copyright © ERS 2021.

Investigation of COVID-19 symptoms using deep learning based image enhancement scheme for x-ray medical images

Image enhancement is the inevitable technique for investigating various biological features. The biological image data can be obtained from computer tomography (CT), magnetic resonance imaging (MRI), and X-ray imaging. X-ray imaging is useful for getting the information from lungs and respiratory system. COVID-19 is a life-threatening contiguous disease for the past two years in the world. Patient's chest images playing an important role in the diagnosis of early detection of disease intensity. We propose a generative adversarial network (GAN) method that identifies COVID-19 from medical images and improves diagnostic sensitivity. Here we used virtual colouring methods and a platform for training the images by using a deep parental training method. Similarly, it gives optimal classification results with the help of well-defined image enhancement techniques and image extraction approaches. In our method, the accuracy level lies between 87.8% and 89.6% correspondingly for the dataset and synthetic dataset.

A CNN-Based Chest Infection Diagnostic Model: A Multistage Multiclass Isolated and Developed Transfer Learning Framework

In 2019, a deadly coronaviral infection (COVID-19) that infected millions of people globally was detected in China. This fatal virus affects the respiratory system and currently spreads to more than 200 nations worldwide. COVID-19 may be found using a chest X-ray scan, a reliable imaging method. Although an expert may examine an X-ray scan manually, this process takes a lot of time. Therefore, deep convolutional neural networks (CNNs) may be utilized to automate this procedure. In this work, at the first step, a novel isolated 19-layer CNN model is developed from scratch to detect chest infections using X-rays. Then, the developed model is reutilized to distinguish the type of chest infection, such as COVID-19, fibrosis, pneumonia, and tuberculosis, using the transfer learning approach. Stochastic gradient descent with momentum is utilized to optimize the model. The proposed multistage framework shows 98.85% and 97% classification accuracies for chest infection detection (binary classification between normal and patient) and four-class subclassification (COVID-19, fibrosis, pneumonia, and tuberculosis) for an online chest X-ray dataset. The reliability of the proposed multistage CNN model was further validated through a new dataset, showing an accuracy of 98.5%. The proposed multistage methodology took minimal training time compared to publically available pretrained models. Therefore, the presented multistage deep learning framework can help doctors in clinical practices.