The Beat Goes On: How PTs and PTAs Can Help Ease the Projected Increases in Cardiovascular Disease

The article discusses how physical therapists (PT) and PT assistants (PTA) can help avert projected cardiovascular disease (CVD) increases as of February 2023. Topics covered include CVD's higher incidence among minority groups, and PTs' primary task to assess risk, identify risk factors, and provide risk therapy, and their subsequent task to advise patients on how they can proactively address these risks factors. Also noted are PTs' possible education of underserved populations.

Incidence of acute exacerbation in patients with interstitial lung disease after COVID-19 vaccination

Acute exacerbations due to COVID-19 vaccination in patients with interstitial lung disease (ILD) have been reported, but their incidence is unknown. We investigated the incidence of exacerbations of ILD and respiratory symptoms due to the mRNA COVID-19 vaccines. A questionnaire survey was conducted on adverse reactions to the mRNA COVID-19 vaccination in 545 patients with ILD attending our hospital and retrospectively examined whether the eligible patients actually developed acute exacerbations of ILD induced by the vaccine. Of the 545 patients, 17 (3.1%) patients were aware of the exacerbation of respiratory symptoms, and four (0.7%) patients developed an acute ILD exacerbation after vaccination. Of the four patients who experienced exacerbations, two had collagen vascular disease-associated ILD, one had nonspecific interstitial pneumonia, another had unclassifiable idiopathic pneumonia, and none had idiopathic pulmonary fibrosis. Four patients were treated using steroid pulse therapy with a steroid taper, and two of the four also received intravenous cyclophosphamide pulse therapy. Tacrolimus was started in one patient with myositis-associated interstitial lung disease. Eventually, all patients exhibited improvement with immunosuppressive treatment and were discharged. COVID-19 vaccination for patients with ILD should be noted for developing acute exacerbations of ILD with low incidence, although manageable with early diagnosis and treatment. © 2022 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases

A multi-output network with U-net enhanced class activation map and robust classification performance for medical imaging analysis

Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image-to-label result provide insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. To gain local insight of cancerous regions, separate tasks such as imaging segmentation needs to be implemented to aid the doctors in treating patients which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive the AI-first medical solutions further, this paper proposes a multi-output network which follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. Class Activation Maps or CAMs are a method of providing insight into a convolutional neural network's feature maps that lead to its classification but in the case of lung diseases, the region of interest is enhanced by U-net assisted Class Activation Mapping (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray's class activation map to provide a visualization that improves the explainability and can generate classification results simultaneously which builds trust for AI-led diagnosis system. The proposed U-Net model achieves 97.72% accuracy and a dice coefficient of 0.9691 on a testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Imagen de las secuelas pulmonares víricas en pandemias

El conocimiento de las secuelas de afectación pulmonar tras la enfermedad por coronavirus 2019 (COVID-19) es todavía limitado dado el poco tiempo de seguimiento. En este trabajo se revisan las publicaciones con seguimiento radiológico una vez superada la infección causada por otros virus descritos con anterioridad, que tienen al pulmón como órgano diana y que ocasionan un daño probablemente similar: los coronavirus causantes del Síndrome Respiratorio Agudo Severo (SARS-CoV) y del Síndrome respiratorio de oriente medio (MERS-CoV), y el virus influenza A-subtipo H1N1. El daño pulmonar ocasionado por estos virus deriva en una afectación intersticial de lenta resolución, con una probable correlación con las pruebas funcionales respiratorias. La mayor extensión de las secuelas se ha asociado a una mayor edad y una mayor gravedad del cuadro clínico infeccioso. Sin embargo, todavía se desconocen los hallazgos pulmonares observados en la imagen y su repercusión funcional a largo plazo.Alternate : Knowledge of lung sequelae after coronavirus disease 2019 (COVID-19) is still limited given the short follow-up time. In this work, publications with a follow-up of radiological findings once the infection caused by other previously described viruses that have the lung as their target organ and that cause probably similar changes are reviewed, including the coronaviruses that cause Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East respiratory syndrome (MERS-CoV), and influenza A-subtype H1N1 virus. Lung damage caused by these viruses leads to slow-resolution interstitial disease, with variable correlation with respiratory function tests. The greater extension of the sequelae has been associated with an older age and a greater severity of the infectious clinical picture. However, the pulmonary imaging findings and their long-term functional impact are still unknown.

Winning Posters from the Canadian Society of Respiratory Therapists 2022 Annual Conference: The Canadian Journal of Respiratory Therapy

Brown discusses his study on the uptake of COVID-19 vaccination amongst respiratory therapists in Canada. Canadian Respiratory Therapist COVID-19 vaccination uptake rates and responses were investigated with a look at the reasons behind any delays or non-vaccinations as well as other demographics, attitudes, or factors that may be shown to play a role. Meanwhile, Floro et al discuss their study on the effectiveness of vaping vs. counseling on smoking cessation. Smoking cigarettes is a global issue that strongly increases risk of diseases, like lung cancer, and is a known risk factor for mortality. It is further complicated by the addictive nature of nicotine.

Pulmonary drug delivery: an effective and convenient delivery route to combat COVID-19.

The recent outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China has spread rapidly around the world, leading to a widespread and urgent effort to develop and use comprehensive approaches in the treatment of COVID-19. While oral therapy is accepted as an effective and simple method, since the primary site of infection and disease progression of COVID-19 is mainly through the lungs, inhaled drug delivery directly to the lungs may be the most appropriate route of administration. To prevent or treat primary SARS-CoV-2 infections, it is essential to target the virus port of entry in the respiratory tract and airway epithelium, which requires rapid and high-intensity inhibition or control of viral entry or replication. To achieve success in this field, inhalation therapy is the most attractive treatment approach due to efficacy/safety profiles. In this review article, pulmonary drug delivery as a unique treatment option in lung diseases will be briefly reviewed. Then, possible inhalation therapies for the treatment of symptoms of COVID-19 will be discussed and the results of clinical trials will be presented. By pulmonary delivery of the currently approved drugs for COVID-19, efficacy of the treatment would be improved along with reducing systemic side effects.

[Outpatient pulmonary rehabilitation]. / Ambulante pneumologische Rehabilitation.

Background: Outpatient pulmonary rehabilitation (PR) plays a central role in the integrative care of patients with pulmonary diseases. Material and methods: The article gives an overview of the recent evidence on outpatient PR in various diseases, in various settings including the cost-effectiveness. This is based on a selective literature search in the PubMed and Medline databanks, current expert opinions and clinical experiences. Results: Early rehabilitation after exacerbation in COPD patients leads to a reduction of rehospitalizations (hazard ratio 0.83) and to a reduction of mortality (hazard ratio 0.63) over a period of 12 months. Telerehabilitation is a promising future perspective in specific settings. Recent publications on bronchiectasis, interstitial lung diseases and pulmonary hypertension could confirm the safety and feasibility of outpatient PR and the cost-effectiveness could be demonstrated. Also, the evidence for inpatient as well as outpatient PR settings for patients with post-COVID and long COVID is growing. Conclusion: There is growing equivalence with respect to the evidence on PR, independent of whether it is carried out in an outpatient or inpatient setting.

An Application Method for the use of Neutrosophic Soft Mappings in Decision-Making the Diagnosis of Covid-19 and Other Lung Diseases

Covid-19 is an epidemic that has spread rapidly around the world and be direct damages the lung in recent years. Many researchers struggled for months trying to find a diagnosis and therapy for this epidemic. As a result of these studies, they have identified common of many symptoms of the epidemic disease with some lung diseases like flu, colds and even allergies. It can say that it is difficult to determine the exact disease type as lung diseases show similar symptoms. Because the elements of indeterminacy and falsehood are commonly ignored in practical assessments, it's difficult to identify precision can't anticipate the period of therapy and in the patient's progress history. In order to after eliminate this uncertainty decide on the definitive diagnosis, a mathematical model was put forward by using neutrosophic soft set theory and function properties of this theory. These concepts are necessary and sufficient to accurately diagnose diseases by connecting with mathematical modeling. This study makes easier to establish a link between patients' symptoms and therapy patterns. A table is created in fuzzy interval [0, 1] for put in order the type of disease among various lung diseases. Diagnosing the disease and finding the best therapy depends on the neutrosophic soft mapping. Finally the generalized neutrosophic soft mapping are utilized map to help predict the duration of therapy until the disease is cured.

Organoid technology and applications in lung diseases: Models, mechanism research and therapy opportunities.

The prevalency of lung disease has increased worldwide, especially in the aging population. It is essential to develop novel disease models, that are superior to traditional models. Organoids are three-dimensional (3D) in vitro structures that produce from self-organizing and differentiating stem cells, including pluripotent stem cells (PSCs) or adult stem cells (ASCs). They can recapitulate the in vivo cellular heterogeneity, genetic characteristics, structure, and functionality of original tissues. Drug responses of patient-derived organoids (PDOs) are consistent with that of patients, and show correlations with genetic alterations. Thus, organoids have proven to be valuable in studying the biology of disease, testing preclinical drugs and developing novel therapies. In recent years, organoids have been successfully applied in studies of a variety of lung diseases, such as lung cancer, influenza, cystic fibrosis, idiopathic pulmonary fibrosis, and the recent severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic. In this review, we provide an update on the generation of organoid models for these diseases and their applications in basic and translational research, highlighting these signs of progress in pathogenesis study, drug screening, personalized medicine and immunotherapy. We also discuss the current limitations and future perspectives in organoid models of lung diseases.

Safety, Tolerability, and Pharmacokinetics of Nebulized Hydroxychloroquine: A Pilot Study in Healthy Volunteers.

Background: Early in the coronavirus disease 2019 (COVID-19) pandemic, hydroxychloroquine (HCQ) drew substantial attention as a potential COVID-19 treatment based on its antiviral and immunomodulatory effects in vitro. However, HCQ showed a lack of efficacy in vivo, and different groups of researchers attributed this failure to the insufficient drug concentration in the lung following oral administration (HCQ is only available in the market in the tablet form). Delivering HCQ by inhalation represents a more efficient route of administration to increase HCQ exposure in the lungs while minimizing systemic toxicity. In this pilot study, the safety, tolerability, and pharmacokinetics of HCQ nebulizer solution were evaluated in healthy volunteers. Methods: Twelve healthy participants were included in this study and were administered 2 mL of HCQ01 solution (equivalent to 25 mg of HCQ sulfate) through Aerogen® Solo, a vibrating mesh nebulizer. Local tolerability and systemic safety were assessed by forced expiratory volume in the first and second electrocardiograms, clinical laboratory results (e.g., hematology, biochemistry, and urinalysis), vital signs, and physical examinations. Thirteen blood samples were collected to determine HCQ01 systemic exposure before and until 6 hours after inhalation. Results: The inhalation of HCQ01 was well tolerated in all participants. The mean value of Cmax for the 12 participants was 9.66 ng/mL. Tmax occurred at around 4.8 minutes after inhalation and rapidly decreased thereafter. The reported systemic exposure was very low with a mean value of 5.28 (0.6-15.6) ng·h/mL. Conclusion: The low systemic concentrations of HCQ01 of 9.66 ng/mL reported by our study compared with 1 µg/mL previously predicted after 200 mg BID oral administration, and the safety and tolerability of HCQ01 administered as a single dose through nebulization, support the assessment of its efficacy, safety, and tolerability in further studies for the treatment of COVID-19.

mRNA in the Context of Protein Replacement Therapy.

Protein replacement therapy is an umbrella term used for medical treatments that aim to substitute or replenish specific protein deficiencies that result either from the protein being absent or non-functional due to mutations in affected patients. Traditionally, such an approach requires a well characterized but arduous and expensive protein production procedure that employs in vitro expression and translation of the pharmaceutical protein in host cells, followed by extensive purification steps. In the wake of the SARS-CoV-2 pandemic, mRNA-based pharmaceuticals were recruited to achieve rapid in vivo production of antigens, proving that the in vivo translation of exogenously administered mRNA is nowadays a viable therapeutic option. In addition, the urgency of the situation and worldwide demand for mRNA-based medicine has led to an evolution in relevant technologies, such as in vitro transcription and nanolipid carriers. In this review, we present preclinical and clinical applications of mRNA as a tool for protein replacement therapy, alongside with information pertaining to the manufacture of modified mRNA through in vitro transcription, carriers employed for its intracellular delivery and critical quality attributes pertaining to the finished product.

LWSNet - a novel deep-learning architecture to segregate Covid-19 and pneumonia from x-ray imagery.

Automatic detection of lung diseases using AI-based tools became very much necessary to handle the huge number of cases occurring across the globe and support the doctors. This paper proposed a novel deep learning architecture named LWSNet (Light Weight Stacking Network) to separate Covid-19, cold pneumonia, and normal chest x-ray images. This framework is based on single, double, triple, and quadruple stack mechanisms to address the above-mentioned tri-class problem. In this framework, a truncated version of standard deep learning models and a lightweight CNN model was considered to conviniently deploy in resource-constraint devices. An evaluation was conducted on three publicly available datasets alongwith their combination. We received 97.28%, 96.50%, 97.41%, and 98.54% highest classification accuracies using quadruple stack. On further investigation, we found, using LWSNet, the average accuracy got improved from individual model to quadruple model by 2.31%, 2.55%, 2.88%, and 2.26% on four respective datasets.

Comparison of Convolutional Neural Network for Classifying Lung Diseases from Chest CT Images

This paper proposes a convolutional neural network for diagnosing various lung illnesses from chest CT images based on a customized Medical Image Analysis and Detection network (MIDNet18). With simplified model building, minimal complexity, easy technique, and high-performance accuracy, the MIDNet-18 CNN architecture classifies binary and multiclass medical images. Fourteen convolutional layers, 7 pooling layers, 4 dense layers, and 1 classification layer comprise the MIDNet-18 architecture. The medical image classification process involves training, validating, and testing the MIDNet-18 model. In the Lung CT image binary class dataset, 2214 images as training set, 1800 images as validation set, and 831 as test set are considered for classifying COVID images and normal lung images. In the multiclass dataset, 6720 images as training sets belonging to 3 classes, 3360 images as validation sets and 601 images as test sets are considered for classifying COVID, cancer images and normal images. Independent sample size calculated for binary classification is 26 samples for each group. Similarly, 10 sample sizes are calculated for multiclass dataset classification keeping GPower at 80%. To validate the performance of the MIDNet18 CNN architecture, the medical images of two different datasets are compared with existing models like LeNet-5, VGG-16, VGG-19, ResNet-50. In multiclass classification, the MIDNet-18 architecture gives better training accuracy and test accuracy, while the LeNet5 model obtained 92.6% and 95.9%, respectively. Similarly, VGG-16 is 89.3% and 77.2% respectively;VGG-19 is 85.8% and 85.4%, respectively;ResNet50 is 90.6% and 99%, respectively. For binary classification, the MIDNet18 architecture gives better training accuracy and test accuracy, while the LeNet-5 model has obtained 52.3% and 54.3%, respectively. Similarly, VGG 16 is 50.5% and 45.6%, respectively;VGG-19 is 50.6% and 45.6%, respectively;ResNet-50 is 96.1% and 98.4%, respectively. The classified images are further predicted using detectron-2 model and the results identify abnormalities (cancer, COVID-19) with 99% accuracy. The MIDNET18 is significantly more accurate than LeNet5, VGG19, VGG16 algorithms and is marginally better than the RESNET50 algorithm for the given lung binary dataset (Bonferroni — one-way Anova and pairwise comparison of MIDNET, LeNet5, VGG19, VGG16, and RESNET 50 (p>0.05)). The proposed MIDNet18 model is significantly more accurate than LeNet5, VGG19, VGG16, ResNet50 algorithms in classifying the diseases for the given multiclass lung dataset (Bonferroni — one-way Anova and pairwise comparison of MIDNET18, LeNet5, VGG19, VGG16, ResNet50 (p>0.05)). [ FROM AUTHOR]

Living well with lung disease: the impact of a hospice-led multidisciplinary respiratory clinic

BackgroundLung diseases account for more than 700,000 hospital admissions, and leads to 115,000 deaths in the UK each year (British Lung Foundation. Lung disease in the UK. [Internet]. [cited 31 May 2022];Public Health England. Respiratory disease: applying All Our Health. [Internet]. 2019 [cited 31 May 2022]). To enhance existing services, Dorothy House Hospice Care piloted a specialist clinic, with embedded peer support, for people with progressive lung disease.AimA key aim of this pilot project was to provide better, more personalised support to patients and thereby to support their physical and emotional well-being.MethodA fortnightly multidisciplinary clinic, delivered by a Nurse Specialist, Physiotherapist and Occupational Therapist, was piloted for 12 months from November 2020. Referrals were accepted in consultation with patients’ GPs and secondary care clinical teams. The Support Needs Approach for Patients (SNAP) tool informed the development of personalised care plans;group sessions provided information and guidance around self-management. Referrals to other Dorothy House services were also made, where appropriate. Originally intended to be face-to-face, clinics were delivered virtually (via Zoom) between November 2020 and July 2021 due to COVID-19. Patient outcomes were measured using SNAP and qualitative interviews.ResultsThirty-two patients attended the clinic. SNAP scores for wellbeing improved by between 33% and 100% (average 70%). Themes generated by the qualitative interviews (n=3) included: the value of having time to talk, and reassurance from having a place to contact for advice, help and support. Patients reported physical improvements in symptoms and in emotional wellbeing. Furthermore, the clinic team reported improved communication between the hospice and patients’ local secondary and primary care clinicians. Some patients opted not to participate in a programme delivered online, thereby limiting the overall numbers attending.ConclusionFollowing the success of this pilot programme, Dorothy House has implemented a long-term conditions clinic, extending similar care to a wider cohort of patients with non-cancer diagnoses. Virtual attendance is still offered, but face-to-face is encouraged to optimise peer support.

Well-Aerated Lung and Mean Lung Density Quantified by CT at Discharge to Predict Pulmonary Diffusion Function 5 Months after COVID-19.

Background: The aim of this study was to explore the predictive values of quantitative CT indices of the total lung and lung lobe tissue at discharge for the pulmonary diffusion function of coronavirus disease 2019 (COVID-19) patients at 5 months after symptom onset. Methods: A total of 90 patients with moderate and severe COVID-19 underwent CT scans at discharge, and pulmonary function tests (PFTs) were performed 5 months after symptom onset. The differences in quantitative CT and PFT results between Group 1 (patients with abnormal diffusion function) and Group 2 (patients with normal diffusion function) were compared by the chi-square test, Fisher's exact test or Mann−Whitney U test. Univariate analysis, stepwise linear regression and logistic regression were used to determine the predictors of diffusion function in convalescent patients. Results: A total of 37.80% (34/90) of patients presented diffusion dysfunction at 5 months after symptom onset. The mean lung density (MLD) of the total lung tissue in Group 1 was higher than that in Group 2, and the percentage of the well-aerated lung (WAL) tissue volume (WAL%) of Group 1 was lower than that of Group 2 (all p < 0.05). Multiple stepwise linear regression identified only WAL and WAL% of the left upper lobe (LUL) as parameters that positively correlated with the percent of the predicted value of diffusion capacity of the lungs for carbon monoxide (WAL: p = 0.002; WAL%: p = 0.004), and multiple stepwise logistic regression identified MLD and MLDLUL as independent predictors of diffusion dysfunction (MLD: OR (95%CI): 1.011 (1.001, 1.02), p = 0.035; MLDLUL: OR (95%CI): 1.016 (1.004, 1.027), p = 0.008). Conclusion: At five months after symptom onset, more than one-third of moderate and severe COVID-19 patients presented with diffusion dysfunction. The well-aerated lung and mean lung density quantified by CT at discharge could be predictors of diffusion function in convalesce.

YouTube as a source of information about pulmonary rehabilitation during the COVID-19 pandemic

BACKGROUND AND AIM: To our best knowledge, there is no literature on the effectiveness of YouTube on pulmonary rehabilitation (PR) practice. In our study, we aimed to evaluate the characteristics and medical aspects of videos on YouTube about PR. METHODS: In the internet media website YouTube.com search engine, the Word PR was searched on August 3, 2021, without any filter. The first 100 videos listed were classified according to the number of likes, dislikes, origin of country, and content of PR. The materials were evaluated in terms of intelligibility using the suitability assessment of materials (SAM). User participation measurements were obtained for each video. RESULTS: The later years were shown to have a statistically significant relationship with respiratory techniques, PR contraindications, and videos with PR in COVID in our study (p<0.05). However, no significant relationship was identified between the later years and smoking in PR and videos with PR in the intensive care unit (p>0.05). The total SAM score was found to significantly correlate with the number of views, likes, dislikes, comments, and video durations (p<0.05). CONCLUSIONS: It was observed that COVID videos with PR content were uploaded with regard to the specific video issues and treatment needs during and after the COVID infection in the later years, especially after the pandemic. Moreover, videos with high comprehensibility are more interesting for users, reflected in views, likes, dislikes, comments, and video duration. Higher quality videos created by health professionals will be more useful for patient education in the future.

Impact of the COVID-19 pandemic on referral processes to a regional Occupational lung disease service – a single centre experience

P76 Figure 1ConclusionDuring the Covid-19 pandemic, we identified a 40% drop in referrals between 2019 and 2021, including a substantial reduction in referrals from workplace based occupational healthcare providers and primary care. Similarly, we diagnosed half as many patients with airway diseases, including occupational asthma.Our observations are in line with the experience of other regional OLD services, and are most likely explained by: workers being furloughed or working from home, thereby removing harmful workplace exposures;or the cessation of routine workplace surveillance and community spirometry. British Thoracic Society has recently published a clinical statement on occupational asthma which reiterates that delayed diagnosis of occupational asthma has a poorer prognosis, so it is crucial that we ensure patients with suspected occupational asthma are referred early.

Two in one: Overlapping CT findings of COVID-19 and underlying lung diseases.

Coronavirus disease 2019 (COVID-19) is associated with pneumonia and has various pulmonary manifestations on computed tomography (CT). Although COVID-19 pneumonia is usually seen as bilateral predominantly peripheral ground-glass opacities with or without consolidation, it can present with atypical radiological findings and resemble the imaging findings of other lung diseases. Diagnosis of COVID-19 pneumonia is much more challenging for both clinicians and radiologists in the presence of pre-existing lung disease. The imaging features of COVID-19 and underlying lung disease can overlap and obscure the findings of each other. Knowledge of the radiological findings of both diseases and possible complications, correct diagnosis, and multidisciplinary consensus play key roles in the appropriate management of diseases. In this pictorial review, the chest CT findings are presented of patients with underlying lung diseases and overlapping COVID-19 pneumonia and the various reasons for radiological lung abnormalities in these patients are discussed.

A case of anti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis-associated rapidly progressive interstitial lung diseases developed after administration of COVID-19 vaccine and subsequent pneumococcal vaccine.

Five cases of anti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis-associated rapidly progressive interstitial lung diseases (anti-MDA5-positive DM-RPILD) following COVID-19 vaccination have been reported previously. We present the first case of the disease that developed following the sequence of COVID-19 infection, COVID-19 vaccination, and 23-valent pneumococcal polysaccharide vaccine (PPSV23) administration. A 75-year-old-Japanese man received the third dose of Pfizer COVID-19 vaccine 4 weeks after he had a mild COVID-19 infection. Eleven weeks after vaccination, he received PPSV23 for the first time. He developed fever, malaise, and anorexia the day after the PPSV23, rash a week later, and shortness of breath 2 weeks later. He was then admitted to a local hospital and treated with antibiotics, but his condition worsened. He was transferred to our hospital 4 weeks after the PPSV23 and was diagnosed with anti-MDA5-positive DM-RPILD. Despite intensive treatment, the patient died on the 10th hospital day.