Does Health Status Influence Acceptance of Illness in Patients with Chronic Respiratory Diseases?

Author(s):  
D. Kurpas ◽  
B. Mroczek ◽  
J. Brodowski ◽  
M. Urban ◽  
A. Nitsch-Osuch
2013 ◽  
Vol 187 (1) ◽  
pp. 114-117 ◽  
Author(s):  
Donata Kurpas ◽  
Bozena Mroczek ◽  
Helena Knap-Czechowska ◽  
Dorota Bielska ◽  
Aneta Nitsch-Osuch ◽  
...  

2019 ◽  
Vol 87 (3) ◽  
pp. 167-174 ◽  
Author(s):  
Panagiota Koutsimpou ◽  
Konstantinos Gourgoulianis ◽  
Athena Economou ◽  
Vasilios Raftopoulos

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Wajid Shah ◽  
Muhammad Aleem ◽  
Muhammad Azhar Iqbal ◽  
Muhammad Arshad Islam ◽  
Usman Ahmed ◽  
...  

Cardiovascular and chronic respiratory diseases are global threats to public health and cause approximately 19 million deaths worldwide annually. This high mortality rate can be reduced with the use of technological advancements in medical science that can facilitate continuous monitoring of physiological parameters—blood pressure, cholesterol levels, blood glucose, etc. The futuristic values of these critical physiological or vital sign parameters not only enable in-time assistance from medical experts and caregivers but also help patients manage their health status by receiving relevant regular alerts/advice from healthcare practitioners. In this study, we propose a machine-learning-based prediction and classification system to determine futuristic values of related vital signs for both cardiovascular and chronic respiratory diseases. Based on the prediction of futuristic values, the proposed system can classify patients’ health status to alarm the caregivers and medical experts. In this machine-learning-based prediction and classification model, we have used a real vital sign dataset. To predict the next 1–3 minutes of vital sign values, several regression techniques (i.e., linear regression and polynomial regression of degrees 2, 3, and 4) have been tested. For caregivers, a 60-second prediction and to facilitate emergency medical assistance, a 3-minute prediction of vital signs is used. Based on the predicted vital signs values, the patient’s overall health is assessed using three machine learning classifiers, i.e., Support Vector Machine (SVM), Naive Bayes, and Decision Tree. Our results show that the Decision Tree can correctly classify a patient’s health status based on abnormal vital sign values and is helpful in timely medical care to the patients.


Author(s):  
Z.B. Baktybaeva ◽  
R.A. Suleymanov ◽  
T.K. Valeev ◽  
N.R. Rahmatullin ◽  
E.G. Stepanov ◽  
...  

Introduction. High density of oil-producing and refining facilities in certain areas of Bashkortostan significantly affects the environment including ambient air quality in residential areas. Materials and methods. We analyzed concentrations of airborne toxicants (sulfur and nitrogen oxides, nitrogen and carbon oxides, hydrogen sulfide, ammonia, xylenes, toluene, phenol and total suspended particles) and population health status in the cities of Ufa, Sterlitamak, Salavat, Blagoveshchensk, and the Tuymazinsky District in 2007–2016. Pearson's correlation coefficients (r) were used to establish possible relationships between medico-demographic indicators and air pollution. Results. Republican fuel and energy enterprises contributed the most to local air pollution levels. Gross emissions from such enterprises as Bashneft-Ufaneftekhim and Bashneft-Navoil reached 43.69–49.77 thousand tons of pollutants per year. The levels of some air pollutants exceeded their maximum permissible concentrations. Elevated concentrations of ammonia, total suspended particles, nitrogen dioxide, and carbon monoxide were registered most frequently. High rates of congenital abnormalities, respiratory diseases in infants (aged 0-1), general mortality and morbidity of the population were observed in some oil-producing and refining areas. The correlation analysis proved the relationship between the concentration of carbon monoxide and general disease rates in adults based on hospital admissions (r = 0.898), general incidence rates in children (r = 0.957), and blood disease rates in infants (r = 0.821). Respiratory diseases in children correlated with nitrogen dioxide emission levels (r = 0.899). Conclusions. Further development of oil-producing, petrochemical and oil-refining industries should be carried out taking into account socio-economic living conditions of the population.


2020 ◽  
Vol 20 (5) ◽  
pp. 333-346
Author(s):  
Sadiya Bi Shaikh ◽  
Yashodhar Prabhakar Bhandary

Respiratory diseases are one of the prime topics of concern in the current era due to improper diagnostics tools. Gene-editing therapy, like Clustered regularly interspaced palindromic repeats- associated nuclease 9 (CRISPR/Cas9), is gaining popularity in pulmonary research, opening up doors to invaluable insights on underlying mechanisms. CRISPR/Cas9 can be considered as a potential gene-editing tool with a scientific community that is helping in the advancement of knowledge in respiratory health and therapy. As an appealing therapeutic tool, we hereby explore the advanced research on the application of CRISPR/Cas9 tools in chronic respiratory diseases such as lung cancer, Acute respiratory distress syndrome (ARDS) and cystic fibrosis (CF). We also address the urgent need to establish this gene-editing tool in various other lung diseases such as asthma, Chronic obstructive pulmonary disease (COPD) and Idiopathic pulmonary fibrosis (IPF). The present review introduces CRISPR/Cas9 as a worthy application in targeting epithelial-mesenchymal transition and fibrinolytic system via editing specific genes. Thereby, based on the efficiency of CRISPR/Cas9, it can be considered as a promising therapeutic tool in respiratory health research.


2016 ◽  
Vol 13 (999) ◽  
pp. 1-1 ◽  
Author(s):  
Sante Di Gioia ◽  
Carla Sardo ◽  
Stefano Castellani ◽  
Barbara Porsio ◽  
Giuliana Belgiovine ◽  
...  

2019 ◽  
Vol 19 (7) ◽  
pp. 921-928 ◽  
Author(s):  
Sadiya Bi Shaikh ◽  
Ashwini Prabhu ◽  
Yashodhar Prabhakar Bhandary

Background: Interleukin-17A (IL-17A) is a pro-inflammatory cytokine that has gained a lot of attention because of its involvement in respiratory diseases. Interleukin-17 cytokine family includes six members, out of which, IL-17A participates towards the immune responses in allergy and inflammation. It also modulates the progression of respiratory disorders. Objective: The present review is an insight into the involvement and contributions of the proinflammatory cytokine IL-17A in chronic respiratory diseases like Idiopathic Pulmonary Fibrosis (IPF), Chronic Obstructive Pulmonary Distress (COPD), asthma, pneumonia, obliterative bronchiolitis, lung cancer and many others. Conclusion: IL-17A is a major regulator of inflammatory responses. In all the mentioned diseases, IL- 17A plays a prime role in inducing the diseases, whereas the lack of this pro-inflammatory cytokine reduces the severity of respective respiratory diseases. Thereby, this review suggests IL-17A as an instrumental target in chronic respiratory diseases.


Author(s):  
Roger Magnusson

Non-communicable diseases (NCDs), including cardiovascular disease, cancer, chronic respiratory diseases, and diabetes, are responsible for around 70 percent of global deaths each year. This chapter describes how NCDs have become prevalent and critically evaluates global efforts to address NCDs and their risk factors, with a particular focus on the World Health Organization (WHO) and United Nations (UN) system. It explores the factors that have prevented those addressing NCDs from achieving access to resources and a priority commensurate with their impact on people’s lives. The chapter evaluates the global response to NCDs both prior to and since the UN High-Level Meeting on Prevention and Control of Non-communicable Diseases, held in 2011, and considers opportunities for strengthening that response in future.


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