Call for papers: Connective tissue disease-associated interstitial lung disease

BMC Pulmonary Medicine warmly welcomes submissions to its Collection on connective tissue disease-associated interstitial lung disease.
Call for papers: Connective tissue disease-associated interstitial lung disease
Like

Share this post

Choose a social network to share with, or copy the URL to share elsewhere

This is a representation of how your post may appear on social media. The actual post will vary between social networks

BMC Pulmonary Medicine is calling for submissions to our Collection on connective tissue disease-associated interstitial lung disease.

Interstitial Lung Disease (ILD) is a common manifestation of several systemic autoimmune connective tissue diseases (CTDs). While ILD can manifest with all CTDs, it most commonly affects individuals with rheumatoid arthritis (RA, 10-30%), systemic sclerosis (SSc, 40-80%), and idiopathic inflammatory myopathy (IIM, 40%). In some patients, ILD could also be the initial or only manifestation of an underlying CTD and the research classification “interstitial pneumonia with autoimmune features (IPAF)” was recently proposed to identify these patients. ILD poses a significant burden, contributing to morbidity and mortality among CTD patients. Given the complexity in the diagnosis and treatment of CTD-related ILD, a multidisciplinary approach to management is crucial.

Over the years, advances in research have improved our understanding and management of CTD-related ILD. However, there are still significant gaps in our knowledge. With the emergence of new therapies for this patient population, there is an increased need to identify clinical characteristics and biomarkers that could predict those who are likely to develop ILD and/or have progressive disease.  There is also a continued need to understand additional mechanistic pathways that lead to ILD, in order to develop novel therapies.  

For this research topic collection, BMC Pulmonary Medicine invites basic and clinical research papers that could enhance our understanding of CTD-associated ILD and contribute to the advancement of  patient care.

Topics of interest for this Collection include but are not limited to:

• Mechanisms and genetics associated with CTD-ILD
• Epidemiology of CTD-ILD: prevalence, mortality, hospitalizations
• Early diagnosis, risk predictors and biomarkers that could predict development and prognosis of CTD-ILD
• Novel therapies for CTD-ILD
• Barriers/limitations to timely care
• Multidisciplinary approach to diagnosis and treatment, and other treatment models

Meet the Guest Editors

Bruno Guedes BaldiUniversity of Sao Paulo Medical School, Brazil

Dr Bruno Guedes Baldi is a Pulmonologist. He is the Medical Assistant of the Pulmonary Division, Heart Institute (InCor) at the University of Sao Paulo Medical School, Sao Paulo, Brazil. His expertise is in interstitial and rare lung diseases, with a hundred articles published. He has served as an editor, including Associate Editor of Frontiers in Medicine and BMC Pulmonary Medicine, as well as Editor-in-Chief of the Jornal Brasileiro de Pneumologia from 2019 to 2022

Niranjan Jeganathan: Loma Linda University Health System School of Medicine, US

Dr Niranjan Jeganathan is a pulmonologist with a special interest in interstitial lung diseases (ILD). He is the Director of the ILD Center at Loma Linda University (California) which is a Pulmonary Fibrosis Foundation Care Center. His research interest within ILD is in understanding the epidemiology of ILD including Connective Tissue Diseases-Related ILD. He has been an editor for other research collections related to ILD. In addition, he has reviewed numerous ILD articles for many different journals. 

 Jin Woo Song: University of Ulsan College of Medicine, South Korea

Dr Jin Woo Song is Professor in the Department of Pulmonary and Critical Care Medicine at the University of Ulsan College of Medicine, South Korea. He is currently Director of the ILD Program at Asan Medical Center in Seoul, South Korea. His academic interests include the effects of air pollution on clinical outcomes in ILD, metabolic changes in ILD and biomarkers in ILD.

Submission Guidelines

This Collection welcomes submission of original Research Articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Connective tissue disease-associated interstitial lung disease" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Guest Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Guest Editors have competing interests is handled by another Editorial Board Member who has no competing interests.

Submission Status: Open   |   Submission Deadline: 8 April 2024

Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in

Follow the Topic

Clinical Medicine
Life Sciences > Health Sciences > Clinical Medicine
Respiratory Tract Diseases
Life Sciences > Health Sciences > Clinical Medicine > Diseases > Respiratory Tract Diseases
Health Care
Life Sciences > Health Sciences > Health Care

Related Collections

With collections, you can get published faster and increase your visibility.

Artificial intelligence and machine learning: applications in pulmonary medicine

BMC Pulmonary Medicine is calling for submissions to our Collection on Artificial intelligence and machine learning: applications in pulmonary medicine. Advancements in artificial intelligence (AI) and machine learning (ML) have the potential to revolutionize pulmonary medicine by enabling innovative approaches to diagnosis, treatment, and prevention of pulmonary disorders. In this era of rapid technological advancements, AI can assist in early detection, risk assessment, and prognostic evaluation by analyzing large datasets, thus leading to improved patient outcomes and better management strategies.

BMC Pulmonary Medicine is launching this collection in alignment with the United Nations' Sustainable Development Goals (SDGs) 3: Good health and well-being and SDG 10: Reduced inequalities. The aim of this collection is to consolidate both fundamental and clinical research to advance our comprehension of pulmonary disorders.

BMC Pulmonary Medicine welcomes original research on the design, implementation, optimization, and clinical impact of AI applications in the field of pulmonary medicine. Topics of interest include, but are not limited to, the following:

• Machine learning (ML) algorithms for early detection of pulmonary diseases

• AI applications for diagnostic accuracy studies

• AI systems as an intervention in live clinical settings

• Predictive modeling using AI for personalized risk assessment of pulmonary disorders

• Application of AI in pulmonary imaging analysis

• Utilizing natural language processing and AI for analyzing electronic health records in pulmonary care

• Exploring the potential of AI in optimizing pulmonary surgical procedures

• Wearable devices and AI algorithms for continuous monitoring of pulmonary health

• AI-enabled precision medicine approaches for personalized treatment

• AI-powered automated risk scoring systems for exacerbations of pulmonary diseases

• Ethical considerations and challenges in the implementation of AI in pulmonary medicine

We encourage the use of standardized reporting guidelines for research with AI/ ML components to encourage authors to provide information to allow their work to be evaluated appropriately. Reporting guidelines and checklists have been developed for a broad range of study design and research types with AI/ML components.

Publishing Model: Open Access

Deadline: Jul 29, 2025

Remote monitoring of chronic lung disease

BMC Pulmonary Medicine calls for submissions to our Collection on Remote monitoring of chronic lung disease. Chronic lung diseases, such as chronic obstructive pulmonary disease (COPD), asthma, interstitial lung disease, occupational lung diseases and pulmonary hypertension pose significant challenges for patients and healthcare systems. Remote monitoring, facilitated by telehealth, telemedicine, wearable technology, and digital health solutions, has emerged as a promising approach to improve the management of chronic lung diseases. This Collection aims to gather research that explores the use of remote monitoring technologies in the home-based management of chronic lung diseases, including their impact on patient outcomes, healthcare utilization, and quality of life.

Advancing our collective understanding in this area is crucial for optimizing the use of remote monitoring technologies in chronic lung disease management. Recent advances have demonstrated the potential of remote monitoring to enhance disease management, facilitate early intervention, and improve patient self-management skills. Furthermore, research has highlighted the role of telehealth in promoting patient engagement and adherence to treatment plans, ultimately leading to better health outcomes.

Looking ahead, continued research in this area holds the potential for further advancements in remote monitoring technologies, including the integration of artificial intelligence for real-time data analysis, personalized treatment recommendations, and predictive modeling for exacerbation risk. Additionally, ongoing research efforts may lead to the development of innovative telehealth interventions that address the specific needs of patients with chronic lung diseases, ultimately improving their long-term health outcomes.

This Collection supports and amplifies research related to SDG 3: Good Health and Well-being, addressing a broad spectrum of topics, including but not limited to:

• Remote monitoring for chronic lung disease management

• Telehealth interventions for chronic lung disease care

• Wearable technology in chronic lung disease management

• Digital health solutions for home-based monitoring of chronic lung diseases

Publishing Model: Open Access

Deadline: Aug 22, 2025