ArticleNPJ digital medicine2021
Identifying acute exacerbations of chronic obstructive pulmonary disease using patient-reported symptoms and cough feature analysis.
Article in NPJ digital medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.
- Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis.European respiratory review : an official journal of the European Respiratory Society · 2025Pooled it
- Respiratory Diseases Diagnosis Using Audio Analysis and Artificial Intelligence: A Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Wearable, broadband auscultation patch with cantilever pressure transducer for remote healthcare monitoring.Nature communications · 2026Article
- A cough sound-based deep learning algorithm for accessible prompt detection of chronic obstructive pulmonary disease with smartphones.NPJ primary care respiratory medicine · 2026Article
- AI-driven smartphone screening for acute COPD exacerbations: enhancing health equity in developing regions.NPJ digital medicine · 2025Article
- Early Identification of Exacerbations in Patients with Chronic Obstructive Pulmonary Disease (COPD).Journal of clinical medicine · 2025Review
- Research trends in the application of artificial intelligence in nursing of chronic disease: a bibliometric and network visualization study.Frontiers in digital health · 2025Article
- Factors Associated with Influenza and Pneumococcal Vaccine Hesitancy Among Patients with AECOPD: A Cross-Sectional Study in China Using the 3C Model.International journal of chronic obstructive pulmonary disease · 2025Article
- New insights into crosstalk between Nrf2 pathway and ferroptosis in lung disease.Cell death & disease · 2024Review
- Risk of Death and Cardiovascular Events Following an Exacerbation of COPD: The EXACOS-CV US Study.International journal of chronic obstructive pulmonary disease · 2024Article
- Phenotypes, Etiotypes, and Endotypes of Exacerbations of Chronic Obstructive Pulmonary Disease.American journal of respiratory and critical care medicine · 2023Review
- Review
- Insights into implementation planning for point-of-care testing to guide treatment of chronic obstructive pulmonary disease exacerbation: a mixed methods feasibility study.Frontiers in health services · 2023Article
- HEAR4Health: a blueprint for making computer audition a staple of modern healthcare.Frontiers in digital health · 2023Review
- Chronic cough-the limitation and advances in assessment techniques.Journal of thoracic disease · 2022Review
- A voice-based biomarker for monitoring symptom resolution in adults with COVID-19: Findings from the prospective Predi-COVID cohort study.PLOS digital health · 2022Article
- Multimodal biomedical AI.Nature medicine · 2022Review
- Development and Validation of a Multivariable Prediction Model to Identify Acute Exacerbation of COPD and Its Severity for COPD Management in China (DETECT Study): A Multicenter, Observational, Cross-Sectional Study.International journal of chronic obstructive pulmonary disease · 2022Article
- Antibacterial, Immunomodulatory, and Lung Protective Effects ofAntibiotics (Basel, Switzerland) · 2021Article
- [Diagnostic Systems for COPD Exacerbation in the Older People: Present and Future].Open respiratory archivesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are commonly encountered in the primary care setting, though the accurate and timely diagnosis is problematic. Using technology like that employed in speech recognition technology, we developed a smartphone-based algorithm for rapid and accurate diagnosis of AECOPD. The algorithm incorporates patient-reported features (age, fever, and new cough), audio data from five coughs and can be deployed by novice users. We compared the accuracy of the algorithm to expert clinical assessment. In patients with known COPD, the algorithm correctly identified the presence of AECOPD in 82.6% (95% CI: 72.9-89.9%) of subjects (n = 86). The absence of AECOPD was correctly identified in 91.0% (95% CI: 82.4-96.3%) of individuals (n = 78). The diagnostic agreement was maintained in milder cases of AECOPD (PPA: 79.2%, 95% CI: 68.0-87.8%), who typically comprise the cohort presenting to primary care. The algorithm may aid early identification of AECOPD and be incorporated in patient self-management plans.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.