ArticleChronic obstructive pulmonary diseases (Miami, Fla.)
Identifying Patients with Undiagnosed COPD in Primary Care Settings: Insight from Screening Tools and Epidemiologic Studies.
Article in Chronic obstructive pulmonary diseases (Miami, Fla.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis 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
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction models for the development of COPD: a systematic review.International journal of chronic obstructive pulmonary disease · 2018Pooled it
- Trial
- Identification of clinical phenotypes and development of a predictive model for rapid lung function decline in COPD patients.Annals of medicine · 2026Article
- Practical strategies for achieving system change in the US: lessons and insights from the CONQUEST quality improvement programme.Primary health care research & development · 2025Review
- AutoCOPD-A novel and practical machine learning model for COPD detection using whole-lung inspiratory quantitative CT measurements: a retrospective, multicenter study.EClinicalMedicine · 2025Article
- Cognitive Functioning Influences Mortality Risk Among Older Adults with COPD.Healthcare (Basel, Switzerland) · 2024Article
- Using machine learning for early detection of chronic obstructive pulmonary disease: a narrative review.Respiratory research · 2024Review
- Leveraging Computed Tomography Imaging to Detect Chronic Obstructive Pulmonary Disease and Concomitant Chronic Diseases.American journal of respiratory and critical care medicine · 2024Article
- Article
- Reversible Airflow Obstruction Predicts Future Chronic Obstructive Pulmonary Disease Development in the SPIROMICS Cohort: An Observational Cohort Study.American journal of respiratory and critical care medicine · 2022Observational
- Machine Learning Prediction of Progression in Forced Expiratory Volume in 1 Second in the COPDGene® Study.Chronic obstructive pulmonary diseases (Miami, Fla.) · 2022Article
- Treatment Trials in Young Patients with Chronic Obstructive Pulmonary Disease and Pre-Chronic Obstructive Pulmonary Disease Patients: Time to Move Forward.American journal of respiratory and critical care medicine · 2022Review
- Functional Predictors Discriminating Asthma-COPD Overlap (ACO) from Chronic Obstructive Pulmonary Disease (COPD).International journal of chronic obstructive pulmonary disease · 2022Article
- Efficacy of a Self-Designed Questionnaire for Community Screening of COPD.International journal of chronic obstructive pulmonary disease · 2022Article
- Self-reported COPD Medication Use and Adherence in the COPD Foundation Patient- Powered Registry Network.Chronic obstructive pulmonary diseases (Miami, Fla.) · 2021Article
- A snapshot of chronic obstructive pulmonary disease management in general practice in Ireland.Irish journal of medical science · 2021Article
- Cost-effectiveness analysis of COPD screening programs in primary care for high-risk patients in China.NPJ primary care respiratory medicine · 2021Article
- Protocol Summary of the COPD Assessment in Primary Care To Identify Undiagnosed Respiratory Disease and Exacerbation Risk (CAPTURE) Validation in Primary Care Study.Chronic obstructive pulmonary diseases (Miami, Fla.) · 2021Article
- An accurate prediction model to identify undiagnosed at-risk patients with COPD: a cross-sectional case-finding study.NPJ primary care respiratory medicine · 2019Article
- Reply to Londhe et al.: CAPTURE: A Screening Tool for Chronic Obstructive Pulmonary Disease or Obstructive Airway Disease?American journal of respiratory and critical care medicine · 2018Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
objectiveChronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality, yet research suggests this disease is greatly underdiagnosed. This literature review sought to summarize the most common and significant variables associated with case-finding or missed cases of COPD to inform more effective and efficient detection of high-risk COPD patients in primary care.
methodsPubMed and EMBASE were searched for articles describing case-finding and epidemiologic research to detect or characterize new cases of COPD. International studies in primary and non-primary care settings, published in English from 2002-2014, were eligible for inclusion. Studies related to risk factors for development of COPD were excluded.
resultsOf the 33 studies identified and reviewed, 21 were case-finding or screening and 12 were epidemiological, including cross-sectional, longitudinal, and retrospective designs. A range of variables were identified within and across studies. Variables common to both screening and epidemiological studies included age, smoking status, and respiratory symptoms. Seven significant predictors from epidemiologic studies did not appear in screening tools. No studies targeted discovery of higher risk patients such as those with reduced lung function or risks for exacerbations.
conclusionVariables used to identify new cases of COPD or differentiate COPD cases and non-cases are wide- ranging, (from sociodemographic to self-reported health or health history variables), providing insight into important factors for case identification. Further research is underway to develop and test the best, smallest variable set that can be used as a screening tool to identify people with undiagnosed, high-risk COPD in primary care.
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