Article
Critical Care Medicine
Yunus Colak, Borge G. Nordestgaard, Peter Lange, Jorgen Vestbo, Shoaib Afzal
Summary: Most patients with chronic obstructive pulmonary disease are not included in major clinical trials, but they experience significant exacerbations and early death.
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
(2022)
Review
Critical Care Medicine
Bartolome R. Celli, Julie A. Anderson, Nicholas J. Cowans, Courtney Crim, Benjamin F. Hartley, Fernando J. Martinez, Andrea N. Morris, Holly Quasny, Julie Yates, Jorgen Vestbo, Peter M. A. Calverley
Summary: The study found that pharmacotherapy for chronic obstructive pulmonary disease can slow down the decline in lung function, with relative benefits similar to those reported for health status and exacerbations. Guidelines should be adjusted based on these findings.
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
(2021)
Article
Respiratory System
Sang Chul Lee, Chansik An, Jongha Yoo, Sungho Park, Donggyo Shin, Chang Hoon Han
Summary: This study aimed to develop a nomogram to predict the FEV1/FVC ratio and the presence of COPD, and found that variables such as age, sex, smoking history, dyspnea, and overweight were significantly associated with the FEV1/FVC ratio. The developed nomogram showed good performance in testing and could be used to identify potential COPD patients in primary care settings.
BMC PULMONARY MEDICINE
(2021)
Article
Computer Science, Interdisciplinary Applications
Xuchun Wang, Hao Ren, Jiahui Ren, Wenzhu Song, Yuchao Qiao, Zeping Ren, Ying Zhao, Liqin Linghu, Yu Cui, Zhiyang Zhao, Limin Chen, Lixia Qiu
Summary: This study constructed a risk prediction model for chronic obstructive pulmonary disease (COPD) using machine learning methods to improve its prediction efficiency. The results showed that frequent coughing before the age of 14 and 9 other variables were important parameters for COPD. In addition, by performing feature selection and balancing data processing, machine learning models could automatically identify patients at risk of COPD, providing a simple and scientific approach for early identification of COPD.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Computer Science, Information Systems
Xinshan Lin, Yi Lei, Jun Chen, Zhihui Xing, Ting Yang, Qing Wang, Chen Wang
Summary: Improving the ability to identify patients with chronic obstructive pulmonary disease (COPD) in primary medical institutions is crucial for prevention and treatment. The application of big data and advanced technologies such as machine learning and artificial intelligence in the medical field has become a hot topic. This study proposes a convenient and effective clinical decision support system based on the identification and diagnosis of COPD in high-risk population, which outperforms existing methods.
TSINGHUA SCIENCE AND TECHNOLOGY
(2023)
Review
Cardiac & Cardiovascular Systems
Sami O. Simons, Adrian Elliott, Manuel Sastry, Jeroen M. Hendriks, Michael Arzt, Michiel Rienstra, Jonathan M. Kalman, Hein Heidbuchel, Stanley Nattel, Geertjan Wesseling, Ulrich Schotten, Isabelle C. van Gelder, Frits M. E. Franssen, Prashanthan Sanders, Harry J. G. M. Crijns, Dominik Linz
Summary: COPD is highly prevalent in AF patients and may promote AF progression and reduce treatment efficacy. Close interdisciplinary collaboration between electrophysiologists/cardiologists and pulmonologists is required for the diagnosis and treatment of COPD in AF patients. Acute exacerbation of COPD may transiently increase AF risk.
EUROPEAN HEART JOURNAL
(2021)
Article
Physiology
Yu-Hang Zhang, Michael R. Hoopmann, Peter J. Castaldi, Kirsten A. Simonsen, Mukul K. Midha, Michael H. Cho, Gerard J. Criner, Raphael Bueno, Jiangyuan Liu, Robert L. Moritz, Edwin K. Silverman
Summary: The study identified 25 proteins significantly associated with COPD in lung tissue samples, including interleukin 33. Machine learning models showed reasonable accuracy and area under the curve for predicting COPD. Mass spectrometry-based proteomic analysis of lung tissue holds promise for identifying biomarkers for COPD.
AMERICAN JOURNAL OF PHYSIOLOGY-LUNG CELLULAR AND MOLECULAR PHYSIOLOGY
(2021)
Article
Environmental Sciences
Veronica A. Wang, Petros Koutrakis, Longxiang Li, Man Liu, Carolina L. Z. Vieira, Brent A. Coull, Edward F. Maher, Choong-Min Kang, Eric Garshick
Summary: This study found that short-term exposure to indoor radioactive particles was associated with a reduction in pulmonary function in patients with chronic obstructive pulmonary disease (COPD). The harmful effects of radon exposure in residential areas on pulmonary function in COPD patients are a matter of concern.
ENVIRONMENTAL RESEARCH
(2023)
Review
Biochemistry & Molecular Biology
Katarzyna Czerwaty, Karolina Dzaman, Krystyna Maria Sobczyk, Katarzyna Irmina Sikorska
Summary: This systematic review aims to define the significance of the coexistence of chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea (OSA), known as overlap syndrome (OS), based on the current state of knowledge. After searching multiple databases, 38 eligible studies were included in this review, covering a total population of 27,064 participants. The paper summarizes the most important and up-to-date information regarding OS, including its prevalence, impact of age/gender/body mass index, polysomnography findings, pulmonary function, comorbidities, prediction of OSA in COPD patients, and treatment options for this syndrome.
Article
Radiology, Nuclear Medicine & Medical Imaging
Jiaxing Sun, Ximing Liao, Yusheng Yan, Xin Zhang, Jian Sun, Weixiong Tan, Baiyun Liu, Jiangfen Wu, Qian Guo, Shaoyong Gao, Zhang Li, Kun Wang, Qiang Li
Summary: The study developed weakly supervised deep learning models using computed tomography (CT) image data for the automated detection and staging of spirometry-defined chronic obstructive pulmonary disease (COPD). The models achieved high accuracy in detecting COPD and categorizing patients according to the GOLD scale, making it a potentially effective tool for COPD diagnosis and staging.
EUROPEAN RADIOLOGY
(2022)
Article
Otorhinolaryngology
Wenche Moe Thorstensen, Marte Rystad Oie, Malcolm Sue-Chu, Sverre Karmhus Steinsvag, Anne-S. Helvik
Summary: Nasal airflow is reduced in COPD patients, possibly due to lower airway diseases. Peak nasal inspiratory flow (PNIF) is significantly lower in COPD patients compared to controls. PNIF is associated with COPD and pre-bronchodilator forced expiratory volume in the first second (FEV1) (% predicted), but not with chronic rhinosinusitis without nasal polyps (CRS-sNP) or other factors.
Article
Multidisciplinary Sciences
Yen-Liang Kuo, Chen-Lin Chien, Hsin-Kuo Ko, Hsin-Chih Lai, Tzu-Lung Lin, Li-Na Lee, Chih-Yueh Chang, Hsiang-Shi Shen, Chia-Chen Lu
Summary: This study aimed to evaluate the efficacy of high-flow nasal cannula (HFNC) in improving impedance in patients with chronic obstructive pulmonary disease (COPD). The results showed that the impulse oscillation system (IOS) measurement was more sensitive than conventional pulmonary function tests (PFT) in evaluating the beneficial effect of HFNC on small airway resistance and peripheral lung reactance in stable COPD patients.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Artificial Intelligence
Arpan Srivastava, Sonakshi Jain, Ryan Miranda, Shruti Patil, Sharnil Pandya, Ketan Kotecha
Summary: Recent technologies such as machine learning and deep learning have significantly improved predictive accuracy for disease detection, especially in early diagnosis and treatment of respiratory diseases. The application of Convolutional Neural Network based methodologies in analyzing respiratory audio data has shown success in detecting Chronic Obstructive Pulmonary disease. The system's classification accuracy has been enhanced to 93% with the use of K-fold Cross-Validation in optimizing the deep learning approach.
PEERJ COMPUTER SCIENCE
(2021)
Article
Chemistry, Multidisciplinary
Mireia Farrus, Joan Codina-Filba, Elisenda Reixach, Erik Andres, Mireia Sans, Noemi Garcia, Josep Vilaseca
Summary: The study investigates how physical effort and medication affect speech features of COPD patients, and how different recording conditions influence the performance of an automatic COPD detection system.
APPLIED SCIENCES-BASEL
(2021)
Article
Oncology
Sophie Corriveau, Gregory R. Pond, Grace H. Tang, John R. Goffin
Summary: The study assessed the diagnosis of COPD in lung cancer patients and found that over a third of lung cancer patients had a prior diagnosis of COPD, with spirometry being more commonly undertaken in early stage disease. In individuals with advanced lung cancer, greater use of spirometry and diagnosis of COPD may help to mitigate respiratory symptoms.
Article
Chemistry, Multidisciplinary
Alberto Pena Fernandez, Cato Leenders, Jean-Marie Aerts, Daniel Berckmans
Summary: This technology aims to monitor emotions in real-time using the mental heart rate component. It allows mental health experts to provide advice based on objective data, enabling early detection and prevention of mental disease. This research investigates the possibilities of using mental heart rate component to classify discrete emotions.
APPLIED SCIENCES-BASEL
(2023)
Review
Infectious Diseases
Hannelore Dillen, Geertruida Bekkering, Sofie Gijsbers, Yannick Vande Weygaerde, Maarten Van Herck, Sarah Haesevoets, David A. G. Bos, Ann Li, Wim Janssens, Rik Gosselink, Thierry Troosters, Jan Y. Verbakel
Summary: This study examined the effects of rehabilitation treatments for patients with persistent symptoms after COVID-19. The findings suggest that physical training, breathing exercises, olfactory training, and multidisciplinary treatment may improve symptoms and quality of life, but the evidence is limited.
BMC INFECTIOUS DISEASES
(2023)
Letter
Respiratory System
Paul Desbordes, Maarten De Vos, Julie Maes, Frans de Jongh, Karl Sylvester, Claus Franz Vogelmeier, Anh Tuan Dinh-Xuan, Jann Mortensen, Wim Janssens, Marko Topalovic
EUROPEAN RESPIRATORY JOURNAL
(2023)
Article
Respiratory System
Nilakash Das, Sofie Happaerts, Iwein Gyselinck, Michael Staes, Eric Derom, Guy Brusselle, Felip Burgos, Marco Contoli, Anh Tuan Dinh-Xuan, Frits M. E. Franssen, Sherif Gonem, Neil Greening, Christel Haenebalcke, William D-C. Man, Jorge Moises, Rudi Peche, Vitalii Poberezhets, Jennifer K. Quint, Michael C. Steiner, Eef Vanderhelst, Mustafa Abdo, Marko Topalovic, Wim Janssens
Summary: Collaboration between pulmonologists and explainable AI (XAI) is superior in diagnosing pulmonary function tests (PFTs) compared to individual pulmonologists or XAI alone. XAI's suggestions improve accuracy, confidence, and inter-rater agreement of pulmonologists. Therefore, the collaboration between pulmonologists and XAI is crucial for interpreting PFTs.
EUROPEAN RESPIRATORY JOURNAL
(2023)
Letter
Respiratory System
Marc Miravitlles, Alice M. Turner, Maria Torres-Duran, Hanan Tanash, Carlota Rodriguez-Garcia, Jose Luis Lopez-Campos, Jan Chlumsky, Catarina Guimaraes, Juan Luis Rodriguez-Hermosa, Angelo Corsico, Cristina Martinez-Gonzalez, Jose Maria Hernandez-Perez, Ana Bustamante, David G. Parr, Francisco Casas-Maldonado, Ana Hecimovic, Wim Janssens, Beatriz Lara, Miriam Barrecheguren, Cruz Gonzalez, Jan Stolk, Cristina Esquinas, Christian F. Clarenbach
EUROPEAN RESPIRATORY JOURNAL
(2023)
Article
Medicine, General & Internal
Luka Beverin, Marko Topalovic, Armin Halilovic, Paul Desbordes, Wim Janssens, Maarten De Vos
Summary: The study aimed to train a supervised machine learning model that can accurately estimate total lung capacity (TLC) values from spirometry and identify patients who would benefit from complete pulmonary function tests by using the best-performing model. The results demonstrated that the machine learning model can estimate TLC with high accuracy, providing potential for the development of smart home-based spirometry solutions.
FRONTIERS IN MEDICINE
(2023)
Article
Respiratory System
Iwein Gyselinck, Sanjay Ramakrishnan, Kristina Vermeersch, Andreas Halner, Hendrik Pott, Fabienne Dobbels, Courtney Coleman, Philip Collis, Henrik Watz, Timm Greulich, Frits M. E. Franssen, Pierre-Regis Burgel, Mona Bafadhel, Wim Janssens
Summary: This study aimed to evaluate patients' acceptance of selected outcome and experience measurements during hospitalisations for COPD exacerbations. The results showed that all selected outcomes and experiences were deemed important, and acceptance of their methods of assessment was high. Patients preferred to use the modified Medical Research Council scale and a numerical rating scale to address dyspnoea, the COPD Assessment Test for quality of life and frequent productive cough, and the Hospital Consumer Assessment of Healthcare Providers and Systems for hospital experiences.
Article
Nutrition & Dietetics
Matthias Loeckx, Fernanda M. Rodrigues, Astrid Blondeel, Stephanie Everaerts, Wim Janssens, Heleen Demeyer, Thierry Troosters
Summary: The study found that implementing a 9-month PA telecoaching program significantly improves the physical activity level of COPD patients, especially after PR and during follow-up. However, this improvement in PA was not accompanied by the maintenance of other PR-acquired benefits.
INTERNATIONAL JOURNAL OF BEHAVIORAL NUTRITION AND PHYSICAL ACTIVITY
(2023)
Article
Respiratory System
Astrid Blondeel, Fien Hermans, Sofie Breuls, Marieke Wuyts, Nikolaas De Maeyer, Thessa Verniest, Eric Derom, Ben Van Calster, Wim Janssens, Thierry Troosters, Heleen Demeyer
Summary: This study investigated the association between weather conditions and physical activity in patients with COPD, as well as the patient characteristics related to the influence of weather conditions. The results showed that daily temperature, sunshine, and daylight time were positively associated with physical activity, while precipitation and wind speed were negatively associated. However, the overall explained variance of physical activity due to weather conditions was low and varied greatly among individuals.
Article
Respiratory System
Katleen Swinnen, Kenneth Verstraete, Claudia Baratto, Laura Hardy, Maarten De Vos, Marko Topalovic, Guido Claessen, Rozenn Quarck, Catharina Belge, Jean-Luc Vachiery, Wim Janssens, Marion Delcroix
Summary: This study developed and validated a machine learning model to improve the prediction accuracy of PH-LHD in a population of PAH and PH-LHD patients. The model significantly improved the sensitivity of PH-LHD prediction at 100% specificity, and may substantially reduce the number of patients referred for invasive diagnostics without missing PAH diagnoses.
Meeting Abstract
Critical Care Medicine
C. De Fays, H. Beeckmans, P. Kerckhof, V. Geudens, A. Vermaut, I. Gyselinck, T. Goos, M. Vermant, J. Kaes, J. Van Slambrouck, Y. Mohamady, L. Willems, L. Aversa, K. Maes, C. Aelbrecht, S. Everaerts, J. E. Mcdonough, L. J. De Sadeleer, S. Gohy, J. Ambroise, W. A. Wuyts, W. L. Janssens, L. J. Ceulemans, D. E. M. Van Raemdonck, R. Vos, T. Hackett, J. C. Hogg, N. Kaminski, C. Pilette, G. Gayan-Ramirez, B. Vanaudenaerde
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
(2023)
Meeting Abstract
Cardiac & Cardiovascular Systems
P. Kerckhof, G. P. Ambrosio, H. Beeckmans, J. Kaes, V. Geudens, J. Slambrouck, S. Bos, M. Vermant, C. Aelbrecht, W. Lynn, V. Astrid, L. Aversa, Y. Mohamady, X. Jin, D. Charlott, T. Goos, G. Iwein, A. Vanstapel, M. Orlitova, M. Boone, W. Janssens, I. Josipovic, V. Varghese, L. Dupont, L. Godinas, G. Verleden, D. Van Raemdonck, L. Ceulemans, A. Neyrinck, J. McDonough, G. Gayan-Ramirez, B. Vanaudenaerde, R. Vos
JOURNAL OF HEART AND LUNG TRANSPLANTATION
(2023)
Article
Respiratory System
Kenneth Verstraete, Nilakash Das, Iwein Gyselinck, Marko Topalovic, Thierry Troosters, James D. Crapo, Edwin K. Silverman, Barry J. Make, Elizabeth A. Regan, Robert Jensen, Maarten De Vos, Wim Janssens
Summary: The shape of MEFVC is associated with CT parameters of emphysema, small airways disease (SAD), and bronchial wall thickening (BWT) in COPD. It is a valuable predictor for emphysema and SAD in moderate-severe COPD, but not a suitable screening tool for early disease phenotypes identified by CT scan.
RESPIRATORY RESEARCH
(2023)
Article
Respiratory System
James D. Crapo, Abhya Gupta, David A. Lynch, Alice M. Turner, Robert M. Mroz, Wim Janssens, Andrea Ludwig-Sengpiel, Harald Koegler, Anastasia Eleftheraki, Frank Risse, Claudia Diefenbach
Summary: The study aims to assess the association between biomarkers of inflammation/lung tissue destruction and COPD severity and progression. The study population included ex-smokers with different severities of COPD and those with A1ATD. The baseline data revealed correlations between disease severity and respiratory symptoms, lung function, residual volume, and emphysema prevalence.
RESPIRATORY RESEARCH
(2023)