A New Multidimensional Diagnostic Approach for Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Abstract Introduction: Individuals at risk for chronic obstructive pulmonary disease (COPD), but without spirometric airflow obstruction, can have respiratory symptoms and substantial structural lung disease on chest computed tomography (CT), yet current diagnostic criteria do not incorporate these features. We aimed to determine whether application of multidimensional diagnostic criteria for COPD that includes respiratory symptoms and imaging abnormalities will identify additional individuals who have poor longitudinal outcomes. Methods: We analyzed data from participants enrolled in two longitudinal cohorts: the Genetic Epidemiology of COPD (COPDGene), which included 9,416 participants with prospective follow-up for 10.5 years and the Canadian Cohort of Obstructive Lung Disease (CanCOLD), which included 1,341 participants with follow-up for 10 years. COPD was defined by the presence of a major criterion (airflow obstruction) and at least one of five minor criteria (emphysema or bronchial wall thickening on CT, dyspnea, poor quality of life, chronic bronchitis) or by at least 3 of 5 minor criteria; in the presence of symptoms that could be attributed to other diseases, the three minor criteria had to include both imaging criteria (see Figure). Reclassification of participants was compared with the Global Initiative of Chronic Obstructive Lung Disease (GOLD) criteria. In multivariable models, we tested associations between the diagnostic criteria and three important COPD outcomes: (1) mortality (2) exacerbations and (3) annualized change in FEV1. Results: Among 9,416 adults in COPDGene, (mean age, 59.6 [9.0] years; 46.5% female; 32.6% African American; 52.5% current smokers), 811 of 5,250 (15.4%) individuals without airflow obstruction were newly classified as having COPD using the minor criteria, and 282 of 4,166 (6.8%) with airflow obstruction were classified as not having COPD. Compared to those classified as not having COPD, those newly labeled as COPD had greater all-cause mortality (adjusted HR 1.97, 95%CI 2.45-2.97;p<0.001), respiratory cause-specific mortality (adjusted HR 3.58, 95%CI 1.56-8.20;p=0.003, higher frequency of exacerbations (adjusted IRR 2.08, 95%CI 1.79-2.43;p<0.001) and faster FEV1 decline (adjusted β = -7.7 ml/year, 95%CI -13.2 to -2.3;p=0.006). In CanCOLD, similarly high exacerbation frequency was noted in the newly diagnosed group (adjusted IRR 2.09, 95%CI, 1.25-3.51;p<0.001). Conclusions: Redefining COPD using a combination of respiratory symptoms and imaging findings results in the identification of additional individuals with high respiratory morbidity while also excluding from the label of COPD some with airflow obstruction who have no symptoms or evidence of structural lung disease. These results support the incorporation of imaging measures into the diagnostic criteria for COPD.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".