Management Of Respiratory Diseases Research Articles

A novel approach to investigate severe asthma and COPD: the 3D Ex Vivo Respiratory Mucosa Model

Biologic drugs have been shown to enhance the treatment of severe asthma and COPD. Monoclonal antibodies against specific targets have dramatically changed the management of these conditions. Although the inflammatory pathways of asthma and COPD have already been clearly outlined, alternative mechanisms of action remain mostly unexplored. They could provide additional insights into these diseases and their clinical management. In vivo or in vitro models have thus been developed to test alternative hypotheses. This study describes sophisticated ex vivo models that mimic the response of human respiratory mucosa to disease triggers, aiming to narrow the gap between laboratory studies and clinical practice. These models successfully replicate crucial aspects of these diseases, such as inflammatory cell presence, cytokine production, and changes in tissue structure, offering a dynamic platform for investigating disease processes and evaluating potential treatments, such as monoclonal antibodies. The proposed models have the potential to enhance personalized medicine approaches and patient-specific treatments, helping to advance the understanding and management of respiratory diseases. This article illustrates the replication of asthma and COPD conditions in a laboratory setting and the potential applications of this methodology.

Management of Bronchial Asthma Through Herbo-Mineral Drugs

Ayurveda is ancient system of medicine and a holistic approach to prevent and treat illness by maintaining balance in body and mind to improve your health and vitality. Ayurveda is one of alternative way of treating illness, prevention and management of respiratory disorders. Nowadays respiratory disorders are the major health issue resulting primary cause of death and disability in the world. Asthma is a common respiratory problem increasing globally and affecting approximately 339 million people worldwide and 17.23 million people with an overall prevalence of 2.05% in India. Bronchial asthma is a heterogeneous disease, usually characterized by chronic inflammatory disease of the airway. It is defined by chronic respiratory problem characterized by hyper-responsiveness, inflammation and narrowing of airway resulting in cardinal symptoms cough, chest tightness, dyspnea and wheeze. Tamak swasa closely resembles to bronchial asthma. Swasa roga is major health problem affecting the Pranavaha srotas. According to Acharya Charak tamak swasa is Vata-Kaphaja Vyadhi which is originated from Pithasthan (Amashaya). The treatment of this disease is still unsatisfactory in modern medicine as the use of corticosteroids have many side effects and may lead to medicine dependency. Ayurveda is proven to be a boon for management of asthmatic patients (Tamak swasa). Our Ayurveda classics have explained a lot about signs and symptoms of asthma that has a direct correlation with Tamak swasa. So this is the need of the time that a direct, safe and holistic approach should be established to treat the disease with specific herbomineral formulations as mentioned in our Ayurveda classics.

Clinical Decision Support Systems in Adults with Chronic Respiratory Disease: A Systematic Review

Background: A sub-optimal uptake of clinical guidelines is reported across healthcare settings in many chronic respiratory disease populations. Clinical decision support systems (CDSS) are systems which analyse and present data so that users can make decisions more easily and are suggested as part of the solution to poor adoption of guidelines. Aims: The aim of this review was to describe the literature on CDSS in chronic respiratory disease management, their function and the features that may impact their effectiveness. Methods: The electronic databases PubMed, MEDLINE, EMBASE, Web of Science, the trial registries Cochrane Central Register of Controlled Trials, EU Clinical Trial Register, ClinicalTrials.gov and World Health Organisation (WHO) trial registry were searched with the aid of a medical librarian. All searches began from September 2019 to March 2021. Data from relevant studies were extracted independently by 2 review authors using Covidence software and Microsoft Excel. Study quality was assessed. CDSS description and indication, function and the theory underpinning the CDSS (e.g., guidelines, expert opinion, etc.) were themed and summarised. The presence or absence of the important CDSS features were recorded i.e., (i) computer-based decision support, (ii) automatic provision of decision support as part of clinician workflow, (iiii) provision of decision support at the time and location of decisionmaking and (iv) provision of recommendations rather than just assessments. Results: Of the 2647 articles screened, 27 papers or abstracts (n = 22 full text and n = 5 abstracts) describing 26 studies met all inclusion and exclusion criteria. The 26 studies evaluated asthma care (n = 16), COPD care (n = 9) and both asthma and COPD care (n = )]. The highest level of evidence was generated by RCTs (n = 7). The 26 studies described 24 different CDSS. Most were based solely or in part on clinical and best practice guidelines. Whilst most CDSS had multiple functions, which were wide ranging, medicines management was the most prevalent function. Most systems had 3 out of 4 of the specific system features that have been correlated with improvements in clinical practice. Generally, in both controlled studies and in other study designs, patient and process outcome measures were commonly reported with performance outcomes measures less commonly reported. Fewer positive effects were reported in the higher quality studies (i.e. controlled studies). The success rate of the CDSS was higher in those studies that had 3 out of the 4 important CDSS features. Conclusion: Many CDSS in adults with asthma and COPD improve patient, process and performance outcomes.

Auscultation-Based Pulmonary Disease Detection through Parallel Transformation and Deep Learning.

Respiratory diseases are among the leading causes of death, with many individuals in a population frequently affected by various types of pulmonary disorders. Early diagnosis and patient monitoring (traditionally involving lung auscultation) are essential for the effective management of respiratory diseases. However, the interpretation of lung sounds is a subjective and labor-intensive process that demands considerable medical expertise, and there is a good chance of misclassification. To address this problem, we propose a hybrid deep learning technique that incorporates signal processing techniques. Parallel transformation is applied to adventitious respiratory sounds, transforming lung sound signals into two distinct time-frequency scalograms: the continuous wavelet transform and the mel spectrogram. Furthermore, parallel convolutional autoencoders are employed to extract features from scalograms, and the resulting latent space features are fused into a hybrid feature pool. Finally, leveraging a long short-term memory model, a feature from the latent space is used as input for classifying various types of respiratory diseases. Our work is evaluated using the ICBHI-2017 lung sound dataset. The experimental findings indicate that our proposed method achieves promising predictive performance, with average values for accuracy, sensitivity, specificity, and F1-score of 94.16%, 89.56%, 99.10%, and 89.56%, respectively, for eight-class respiratory diseases; 79.61%, 78.55%, 92.49%, and 78.67%, respectively, for four-class diseases; and 85.61%, 83.44%, 83.44%, and 84.21%, respectively, for binary-class (normal vs. abnormal) lung sounds.

Molecular characterization of human adenoviruses associated with pediatric respiratory infections in Karachi, Pakistan

Human adenoviruses (HAdVs) are a diverse group of viruses associated with respiratory infections in humans worldwide. However, there is a lack of research on the genetic diversity and epidemiology of HAdVs in Pakistan. This study characterized HAdVs in pediatric patients with respiratory tract infections in Karachi, Pakistan, between 2022 and 2023. We analyzed 762 nasopharyngeal samples of children ≤ 5 years. DNA extraction, followed by PCR targeting E2B and hexon genes, was carried out. Data analysis was performed on SPSS 25.0, and phylogenetic analysis of hexon gene was performed on MEGA 11. HAdV was detected in 7.34% (56/762) of patients round the year, but at a significantly higher rate during the winter season. Age was insignificantly associated with HAdV incidence (p = 0.662), but more than 62.5% (35/56) of positive cases were younger than 10 months. The circulating HAdVs were identified as six different types from species B (78.57%) and C (21.42%), with the majority of isolates found to be like B3. HAdV was found to be co-infected with bocavirus (5.4%) and measles (7.14%). These findings revealed a high frequency and genetic diversity of respiratory HAdVs in Karachi, Pakistan. We conclude that periodic and continuous surveillance of adenoviruses and other respiratory pathogens is necessary to improve the prognosis and management of respiratory diseases, thereby reducing the child mortality rate in Pakistan.

The Effect of Educational Intervention on Inhaler Technique of Patients in Asian Countries: A Systematic Review

Background: Inhalation therapy is the main line of treatment for the management of various respiratory diseases due to localized delivery and rapid onset of action. Incorrect inhaler technique is very common and subsequently leads to poor disease management. Pharmacist can have a positive impact on patient’s education about proper inhaler technique that can lead to a significant improvement of asthma and COPD management. Objective: The objective of this study was to determine the effectiveness of pharmacist education program on inhaler technique of asthmatic and COPD patients in South Asian countries. The outcome regarding inhalation technique was reviewed and summarized. Methodology: The outcome regarding inhalation technique was reviewed and summarized. For this systematic review, basic electronic academic databases (Scopus, Science Direct, ProQuest, Web of Science and PubMed) were used for the search, along with a manual search on Google Scholar. This systematic review was conducted by following the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)” guidelines. Moreover, utilizing the framework of the PECO-S (Population Exposure Comparison Outcome Study design), various observational studies were recruited for this review. The ZEE tool was utilized to minimize the risk of bias among extracted cross-sectional studies. Inclusion criteria included studies on inhaler using patients of all ages from South Asian countries along with the influence of educational intervention outcomes. Results: Out of 2191 studies, 24 studies meeting the inclusion criteria were included in the current review. All of the included studies were about pharmacist intervention on inhaler technique in South Asian countries. Conclusion: The systematic literature review summarizes the impact of educational intervention provided to inhaler using patients from South Asian countries. It was assessed that patient education and counselling produced improvement in inhalation technique of various devices especially metered dose inhalers. The primary outcome of most the studies was the improvement in inhaler technique assessment and enhanced quality of life. Therefore, inhaler technique education to patients should be made compulsory by the Health-care authorities to enhance compliance and effectiveness of inhalational therapy by avoiding irrational use of inhalers.

Detection Of Pulmonary Diseases in Lung Using CT & X-ray Images CNN

This study presents a deep learning approach utilizing Convolutional Neural Networks (CNNs) for the detection of pulmonary diseases from CT and X-ray images. With the rising prevalence of respiratory illnesses, accurate and efficient diagnosis is crucial for timely treatment. The proposed CNN framework leverages its ability to automatically learn discriminative features from medical images, enabling robust disease detection. By training on a diverse dataset comprising CT and X-ray scans, the model achieves high sensitivity and specificity in identifying common pulmonary conditions such as Covid-19 & Effusion Disease. The results demonstrate the potential of CNNs as a valuable tool in the early detection and management of respiratory diseases, contributing to improved patient outcomes and healthcare delivery.

Leveraging AI and Machine Learning to Develop and Evaluate a Contextualized User-Friendly Cough Audio Classifier for Detecting Respiratory Diseases: Protocol for a Diagnostic Study in Rural Tanzania.

Respiratory diseases, including active tuberculosis (TB), asthma, and chronic obstructive pulmonary disease (COPD), constitute substantial global health challenges, necessitating timely and accurate diagnosis for effective treatment and management. This research seeks to develop and evaluate a noninvasive user-friendly artificial intelligence (AI)-powered cough audio classifier for detecting these respiratory conditions in rural Tanzania. This is a nonexperimental cross-sectional research with the primary objective of collection and analysis of cough sounds from patients with active TB, asthma, and COPD in outpatient clinics to generate and evaluate a noninvasive cough audio classifier. Specialized cough sound recording devices, designed to be nonintrusive and user-friendly, will facilitate the collection of diverse cough sound samples from patients attending outpatient clinics in 20 health care facilities in the Shinyanga region. The collected cough sound data will undergo rigorous analysis, using advanced AI signal processing and machine learning techniques. By comparing acoustic features and patterns associated with TB, asthma, and COPD, a robust algorithm capable of automated disease discrimination will be generated facilitating the development of a smartphone-based cough sound classifier. The classifier will be evaluated against the calculated reference standards including clinical assessments, sputum smear, GeneXpert, chest x-ray, culture and sensitivity, spirometry and peak expiratory flow, and sensitivity and predictive values. This research represents a vital step toward enhancing the diagnostic capabilities available in outpatient clinics, with the potential to revolutionize the field of respiratory disease diagnosis. Findings from the 4 phases of the study will be presented as descriptions supported by relevant images, tables, and figures. The anticipated outcome of this research is the creation of a reliable, noninvasive diagnostic cough classifier that empowers health care professionals and patients themselves to identify and differentiate these respiratory diseases based on cough sound patterns. Cough sound classifiers use advanced technology for early detection and management of respiratory conditions, offering a less invasive and more efficient alternative to traditional diagnostics. This technology promises to ease public health burdens, improve patient outcomes, and enhance health care access in under-resourced areas, potentially transforming respiratory disease management globally. PRR1-10.2196/54388.

Deep Learning‐Assisted Sensitive 3C‐SiC Sensor for Long‐Term Monitoring of Physical Respiration

AbstractIn human life, respiration serves as a crucial physiological signal. Continuous real‐time respiration monitoring can provide valuable insights for the early detection and management of several respiratory diseases. High‐sensitivity, noninvasive, comfortable, and long‐term stable respiration devices are highly desirable. In spite of this, existing respiration sensors cannot provide continuous long‐term monitoring due to the erosion from moisture, fluctuations in body temperature, and many other environmental factors. This research developed a wearable thermal‐based respiration sensor made of cubic silicon carbide (3C‐SiC) using a microfabrication process. The results showed that as a result of the Joule heating effect in the robustness 3C‐SiC material, the sensor offered high sensitivity with the negative temperature coefficient of resistance of approximately 5,200ppmK‐1, an excellent response to respiration and long‐term stability monitoring. Furthermore, by incorporating a deep learning model, this fabricated sensor can develop advanced capabilities to distinguish between the four distinct breath patterns: slow, normal, fast, and deep breathing, and provide an impressive classification accuracy rate of ≈ 99.7%. The results of this research represent a significant step in developing wearable respiration sensors for personal healthcare systems.

Pediatric pulmonology year in review 2023: Physiology.

Application of the principles of pulmonary physiology and lung development to the care and management of respiratory disease in children is a distinguishing feature of pediatric pulmonology. In 2023, this was evident in numerous publications in Pediatric Pulmonology and other journals. This review will highlight some of the papers in this area.

Short-Chain Fatty Acid (SCFA) as a Connecting Link between Microbiota and Gut-Lung Axis-A Potential Therapeutic Intervention to Improve Lung Health.

The microbiome is an integral part of the human gut, and it plays a crucial role in the development of the immune system and homeostasis. Apart from the gut microbiome, the airway microbial community also forms a distinct and crucial part of the human microbiota. Furthermore, several studies indicate the existence of communication between the gut microbiome and their metabolites with the lung airways, called "gut-lung axis". Perturbations in gut microbiota composition, termed dysbiosis, can have acute and chronic effects on the pathophysiology of lung diseases. Microbes and their metabolites in lung stimulate various innate immune pathways, which modulate the expression of the inflammatory genes in pulmonary leukocytes. For instance, gut microbiota-derived metabolites such as short-chain fatty acids can suppress lung inflammation through the activation of G protein-coupled receptors (free fatty acid receptors) and can also inhibit histone deacetylase, which in turn influences the severity of acute and chronic respiratory diseases. Thus, modulation of the gut microbiome composition through probiotic/prebiotic usage and fecal microbiota transplantation can lead to alterations in lung homeostasis and immunity. The resulting manipulation of immune cells function through microbiota and their key metabolites paves the way for the development of novel therapeutic strategies in improving the lung health of individuals affected with various lung diseases including SARS-CoV-2. This review will shed light upon the mechanistic aspect of immune system programming through gut and lung microbiota and exploration of the relationship between gut-lung microbiome and also highlight the therapeutic potential of gut microbiota-derived metabolites in the management of respiratory diseases.

Lung Function Monitoring Using Machine Learning

This project aims to develop a system equipped with machine learning algorithm capable of continuously monitoring respiratory conduct. The system utilizes machine learning to interpret pulmonary function tests, lift the management of respiratory diseases, and potentially deliver improvements in the diagnosis and treatment of various disease states in pulmonary and critical care medicine. Additionally, the system automatically predicts lung function based on acoustic signals from coughing and wheezing, enabling noninvasive monitoring of asthma severity. The project also seeks to forecast lung age and improve the current dataset of audio samples to enhance the accuracy and reliability of the results. The application of machine learning in pulmonary function testing holds significant potential for remote monitoring of high risk patients and the early detection and treatment of lung diseases.

Association between upper and lower respiratory disease among patients with primary ciliary dyskinesia: an international study.

Nearly all patients with primary ciliary dyskinesia (PCD) report ear-nose-throat (ENT) symptoms. However, scarce evidence exists about how ENT symptoms relate to pulmonary disease in PCD. We explored possible associations between upper and lower respiratory disease among patients with PCD in a multicentre study. We included patients from the ENT Prospective International Cohort (EPIC-PCD). We studied associations of several reported ENT symptoms and chronic rhinosinusitis (defined using patient-reported information and examination findings) with reported sputum production and shortness of breath, using ordinal logistic regression. In a subgroup with available lung function results, we used linear regression to study associations of chronic rhinosinusitis and forced expiratory volume in 1 s (FEV1) accounting for relevant factors. We included 457 patients (median age 15 years, interquartile range 10-24 years; 54% males). Shortness of breath associated with reported nasal symptoms and ear pain of any frequency, often or daily hearing problems, headache when bending down (OR 2.1, 95% CI 1.29-3.54) and chronic rhinosinusitis (OR 2.3, 95% CI 1.57-3.38) regardless of polyp presence. Sputum production associated with daily reported nasal (OR 2.2, 95% CI 1.20-4.09) and hearing (OR 2.0, 95% CI 1.10-3.64) problems and chronic rhinosinusitis (OR 2.1, 95% CI 1.48-3.07). We did not find any association between chronic rhinosinusitis and FEV1. Reported upper airway symptoms and signs of chronic rhinosinusitis associated with reported pulmonary symptoms, but not with lung function. Our results emphasise the assessment and management of upper and lower respiratory disease as a common, interdependent entity among patients with PCD.

Role of airway epithelium in viral respiratory infections: Can carbocysteine prevent or mitigate them?

Alterations in airway epithelial homeostasis increase viral respiratory infections risk. Viral infections frequently are associated with chronic obstructive pulmonary disease (COPD) exacerbations, events that dramatically promote disease progression. Mechanism promoting the main respiratory viruses entry and virus-evocated innate and adaptive immune responses have now been elucidated, and an oxidative stress central role in these pathogenic processes has been recognized. Presence of reactive oxygen species in macrophages and other cells allows them to eliminate virus, but its excess alters the balance between innate and adaptive immune responses and proteases/anti-proteases and leads to uncontrolled inflammation, tissue damage, and hypercoagulability. Different upper and lower airway cell types also play a role in viral entry and infection. Carbocysteine is a muco-active drug with anti-oxidant and anti-inflammatory properties used for the management of several chronic respiratory diseases. Although the use of anti-oxidants has been proposed as an effective strategy in COPD exacerbations management, the molecular mechanisms that explain carbocysteine efficacy have not yet been fully clarified. The present review describes the most relevant features of the common respiratory virus pathophysiology with a focus on epithelial cells and oxidative stress role and reports data supporting a putative role of carbocysteine in viral respiratory infections.

Can RESPiratory hospital Admissions in children with cerebral palsy be reduced? A feasibility randomised Controlled Trial pilot study protocol (RESP-ACT)

IntroductionThe most common cause of morbidity and mortality in children with severe cerebral palsy (CP) is respiratory disease. BREATHE-CP (Better REspiratory and Airway Treatment and HEalth in Cerebral Palsy) is...

Key Challenges for Respiratory Virus Surveillance while Transitioning out of Acute Phase of COVID-19 Pandemic.

To support the ongoing management of viral respiratory diseases while transitioning out of the acute phase of the COVID-19 pandemic, many countries are moving toward an integrated model of surveillance for SARS-CoV-2, influenza virus, and other respiratory pathogens. Although many surveillance approaches catalyzed by the COVID-19 pandemic provide novel epidemiologic insight, continuing them as implemented during the pandemic is unlikely to be feasible for nonemergency surveillance, and many have already been scaled back. Furthermore, given anticipated cocirculation of SARS-CoV-2 and influenza virus, surveillance activities in place before the pandemic require review and adjustment to ensure their ongoing value for public health. In this report, we highlight key challenges for the development of integrated models of surveillance. We discuss the relative strengths and limitations of different surveillance practices and studies as well as their contribution to epidemiologic assessment, forecasting, and public health decision-making.

Association between body mass index and respiratory symptoms in US adults: a national cross-sectional study

The correlation between body mass index (BMI) and the development of cough, shortness of breath, and dyspnea is unclear. Therefore, this study aimed to investigate the association between these parameters. Data from individuals who participated in the National Health and Nutrition Examination Survey between 2003 and 2012 were analyzed. Weighted logistic regression analysis and smoothed curve fitting were used to examine the correlation between BMI and respiratory symptoms. In addition, the relationship between BMI, chronic obstructive pulmonary disease (COPD), and bronchial asthma was examined. Stratified analysis was used to discover inflection points and specific groups. Weighted logistic regression and smoothed curve fitting revealed a U-shaped relationship between BMI and respiratory symptoms. The U-shaped relationship in BMI was also observed in patients with bronchial asthma and COPD. Stratified analysis showed that the correlation between BMI and wheezing and dyspnea was influenced by race. In addition, non-Hispanic black individuals had a higher risk of developing cough than individuals of the other three races [OR 1.040 (1.021, 1.060), p < 0.0001], and they also exhibited an inverted U-shaped relationship between BMI and bronchial asthma. However, the association of BMI with cough, wheezing, dyspnea, COPD, and asthma was not affected by sex. High or low BMI was associated with cough, shortness of breath, and dyspnea, and has been linked to bronchial asthma and COPD. These findings provide new insights into the management of respiratory symptoms and respiratory diseases.

Demystifying Dry Powder Inhaler Resistance with Relevance to Optimal Patient Care.

The selection of an inhaler device is a key component of respiratory disease management. However, there is a lack of clarity surrounding inhaler resistance and how it impacts inhaler selection. The most common inhaler types are dry powder inhalers (DPIs) that have internal resistance and pressurised metered dose inhalers (pMDIs) that use propellants to deliver the drug dose to the airways. Inhaler resistance varies across the DPIs available on the market, depending largely on the design geometry of the device but also partially on formulation parameters. Factors influencing inhaler choice include measures such as flow rate or pressure drop as well as inhaler technique and patient preference, both of which can lead to improved adherence and outcomes. For optimal disease outcomes, device selection should be individualised, inhaler technique optimised and patient preference considered. By addressing the common clinically relevant questions, this paper aims to demystify how DPI resistance should guide the selection of the right device for the right patient.

Nurses’ Role and Participation in the Management in Children Respiratory Diseases

Pediatric respiratory pathology has its unique characteristics and requires specialized approaches in diagnostics, treatment, and care. In many countries, programs are being developed and implemented to optimize nursing care for children with such diseases, which can serve as a valuable source of experience for nurses. The current review aims to describe the existing data on the role of nurses in the management of respiratory diseases in children in primary care settings. Literature searches were conducted in electronic databases including PubMed/Medline, CINAHL, Cochrane Database of Systematic Reviews, and ProQuest for the period from 2012 to 2023. The following key search queries were used: nurses, nursing roles, primary health care, pediatrics, respiratory diseases. Inclusion criteria were peer-reviewed studies, including quantitative and qualitative studies, as well as mixedmethods research. Numerous studies demonstrate that nurses significantly improve the quality of life for patients by reducing the number of acute disease episodes and decreasing the need for hospitalization. This is achieved through the effective use of clinical protocols and continuous improvement of their knowledge and skills. Educational programs developed by nurses increase children's and their parents' awareness of the diseases, aiding in better inhalation techniques and overall disease management. This highlights the importance of nurses' roles in education and consultative support. Thus, extensive research confirms the importance of nursing in managing respiratory diseases in children and underscores the need for further development of nurse role in the healthcare system. Strengthening and expanding the competencies of nurses in this area can lead to more effective and high-quality care for children with respiratory diseases.

Trends in Respiratory Infectious Pathogens in Children Under the Age of 14 - Xiamen City, Fujian Province, China, 2017-2023.

Respiratory infections pose a significant burden on public health. Despite recent outbreaks occurring in various locations, there is limited information available on the prevalence trends of multiple common respiratory pathogens in China beyond 2022. A retrospective analysis was conducted on respiratory pathogen infections in a Xiamen hospital over a seven-year period. The analysis revealed fluctuating trends, with the number of infections for certain viruses initially decreasing after 2019, only to rebound to previous or higher levels. Recently, there has been an observed collective increase in positive cases for certain pathogens. The study improves understanding of respiratory pathogens, primarily in Xiamen, with potential implications for the improvement of strategies for the prevention and management of respiratory infectious diseases.