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Record W4415915486 · doi:10.1002/resp.70155

Early Diagnosis of <scp>COPD</scp> —How Can we Do Better?

2025· article· en· W4415915486 on OpenAlexaffabout
Shawn D. Aaron

Bibliographic record

VenueRespirology · 2025
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsCOPDSpirometryDiseaseClinical PracticeDiagnostic testHealth careMEDLINEPulmonary disease

Abstract

fetched live from OpenAlex

Undiagnosed COPD is a major global health problem. Studies from across the world suggest that as many as 70% of adults with COPD remain undiagnosed [1]. A collaborative study assessed the prevalence of undiagnosed COPD in 27 countries and found COPD in 2995 of 30,874 adult participants (9.7%); of these 81.4% of cases were undiagnosed [2]. The myriad reasons for under-diagnosis of COPD are highlighted in Table 1. Our current healthcare system generally fails many patients with COPD, since most remain undiagnosed until they develop moderate or severe airflow obstruction, and generally they present with significant disability, or an acute exacerbation, at the time of first diagnosis [3]. Consequently, most patients diagnosed with COPD in clinical practice are only recognised when their disease is already relatively advanced, and therapy is less effective. As has been shown for lung cancer detection in at-risk subjects [4], screening or case-finding are potential strategies to dramatically change the paradigm and identify patients earlier. Early diagnosis of COPD can be potentially achieved by case-finding. Case-finding involves assessment of at-risk individuals who present with unexplained respiratory symptoms. Case-finding uses symptom questionnaires and may also make use of peak expiratory flow monitors or micro-spirometers, to identify symptomatic individuals, or people at particularly high risk for COPD, who would benefit from diagnostic spirometry [5]. Case-finding facilitates earlier identification of disease and can allow clinicians to direct non-pharmacologic and pharmacologic treatments to these individuals. How should we try to find individuals with undiagnosed COPD? One obvious approach would be to try to find them in primary care practices. There are several potential problems with this approach. Studies of patients with undiagnosed COPD and asthma suggest that many individuals with undiagnosed COPD tend to discount their symptoms, and they do not complain to their primary care practitioners about their respiratory symptoms [6]. Similarly, many individuals with undiagnosed COPD do not have family doctors, or they may see their family doctors very infrequently, and these individuals may be missed if case-finding is confined to primary care practices [6]. A recent cluster-randomised clinical trial tried to operationalise COPD case-finding in primary care offices using the CAPTURE case-finding tool [7]. Unfortunately, the study found that the use of the CAPTURE tool in primary care did not influence practitioners to order more spirometry, or make more diagnoses of COPD, compared to usual care. Furthermore, patients within the primary care practices randomised to the CAPTURE intervention did not report better health status, or experience fewer urgent visits for respiratory illness, compared to those within practices randomised to usual care. The investigators of the CAPTURE study pointed out that the results of the CAPTURE questionnaire were shared with clinical staff after the completion of the patient visit, and that the majority of patient visits were for reasons unrelated to respiratory illness [7]. In this context, it is not surprising that busy primary care practitioners therefore failed to act on the results of the CAPTURE questionnaire. Another approach to find individuals with undiagnosed COPD is to find them within their homes and communities. The Undiagnosed COPD and Asthma in the Population (UCAP) Study was a multicenter, study that randomly dialed cellphones and landlines across Canada and telephone interviewed almost 27,000 adults with symptoms of respiratory disease using case-finding questionnaires [8]. After exclusion of many people who had pre-existing diagnosed lung disease, the investigators conducted pre and post-BD spirometry in 2857 individuals who had no prior history of diagnosed lung disease. Of the 2857 individuals who underwent spirometry, 595 (21%) were found to have undiagnosed asthma or COPD. Over a one-year follow-up period, individuals with undiagnosed asthma or COPD who were randomised to guideline-based care by a pulmonologist had less than half the rate of patient-initiated healthcare utilisation events for respiratory illness, and significantly greater one-year improvements in health-related quality of life, symptoms, and lung function, compared to those randomised to usual care [8]. The UCAP study was the first to conduct case-finding for COPD within the community and to couple early diagnosis to an intensive treatment intervention. While the UCAP study was successful, computer-generated random digit dialing of all households was expensive and relatively inefficient. Cost for the random-digit calls was > $450,000 Canadian, and more than one million random calls needed to be made to ultimately find 595 individuals with undiagnosed obstructive lung disease. The next step is to make COPD case-finding within the community more feasible, and affordable, within our healthcare systems. We are currently conducting a clinical trial of community-based, patient-initiated diagnosis of obstructive lung disease. Individuals experiencing unexplained respiratory symptoms complete a web-based case-finding questionnaire on-line [9], and if their responses yield a risk score exceeding a specified threshold, they are referred via a web-based program for diagnostic spirometry. We are advertising the web-based case-finding questionnaire locally within communities. Information is being posted in local community centers, and in community-based newsletters and local community newspapers, including those targeting ethnic groups and language and cultural minorities. Finally, we are also using local radio advertisements to reach broadly within communities. Achieving earlier diagnosis of COPD, via a patient-initiated community-based case-finding strategy, will ensure that symptomatic patients are not left undiagnosed and untreated. Ultimately this approach will help patients and may provide health economic benefits to society and to our healthcare systems. The author declares no conflicts of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.295
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes2
Has abstractyes

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