Identifying Eligibility for Specialist Intervention in COPD from UK Primary Care Data: A “Treatable Traits” Approach
Bibliographic record
Abstract
Thomas JC Ward,1– 3 Catherine John,2,4 Alexander T Williams,4 Chiara Batini,2,4 Neil J Greening,1– 3 Martin D Tobin,2,4 Michael C Steiner1– 3 1Department of Respiratory Sciences, University of Leicester, Leicester, UK; 2University Hospitals of Leicester, Leicester, UK; 3Institute for Lung Health, National Institute for Health Research Leicester Biomedical Research Centre – Respiratory Glenfield Hospital, Leicester, UK; 4Department of Population Health Sciences, University of Leicester, Leicester, UKCorrespondence: Thomas JC Ward, Institute for Lung Health, NIHR Respiratory Biomedical Research Centre Glenfield Hospital, Groby Road, Leicester, LE3 9QP, UK, Email tom.ward@leicester.ac.ukBackground: Specialist intervention in COPD is often reactive, resulting in inequalities in the provision of care. A proactive approach, in which individuals with modifiable disease are identified from primary care records, may help to tackle this inequality in access.Aim: To estimate the prevalence of “treatable traits” in COPD in a primary care research database and to assess health service usage.Methods: We performed a secondary analysis of individuals with either 1) a primary care diagnosis of COPD or 2) obstructive spirometry and history of ever smoking in a large observational study recruiting individuals aged 40– 69 years old in Leicestershire, UK. Spirometry, height, weight and smoking history were collected prospectively and linked to individuals’ primary care records. “Treatable traits” were identified from primary care records (frequent exacerbations, current smoking, low body mass index, respiratory failure, severe breathlessness, potential suitability for lung volume reduction or psychological comorbidity). Differences in demographics and health usage between those with and without “treatable traits” were assessed.Results: In total, of the 347 individuals with COPD, 186 had at least one “treatable trait”. Compared to those without treatable traits, individuals with treatable traits were younger (61 vs 64 years, p< 0.001), had more severe airflow obstruction (FEV1 86% vs 94% predicted, p=0.002), higher eosinophil count (0.32 vs 0.27 cells/μL, p=0.04) and were more socioeconomically deprived (UK Indices of Multiple Deprivation decile 4.3 vs 5.8, p< 0.001). Individuals with treatable traits had a higher annual primary care health usage (47 vs 30 visits per year, p=0.001). Referrals rates to specialist respiratory services were low in both groups.Conclusion: Treatable traits are common in COPD and can be identified from routinely collected primary care data. Treatable traits are associated with younger age and greater deprivation. These individuals pose a significant burden to primary care yet are rarely referred to specialist respiratory services.Keywords: integrated care, chronic respiratory disease, treatable traits
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".