COPD Population in US Primary Care: Data From the Optimum Patient Care DARTNet Research Database and the Advancing the Patient Experience in COPD Registry
Bibliographic record
Abstract
PURPOSE To describe demographic and clinical characteristics of chronic obstructive pulmonary disease patients managed in US primary care. METHODS This was an observational registry study using data from the Chronic Obstructive Pulmonary Disease (COPD) Optimum Patient Care DARTNet Research Database from which the Advancing the Patient Experience COPD registry is derived. Registry patients were aged ≥35 years at diagnosis. Electronic health record data were collected from both registries, supplemented with patient-reported information/outcomes from the Advancing the Patient Experience registry from 5 primary care groups in Texas, Ohio, Colorado, New York, and North Carolina (June 2019 through November 2020). RESULTS Of 17,192 patients included, 1,354 were also in the Advancing the Patient Experience registry. Patients were predominantly female (56%; 9,689/17,192), White (64%; 9,732/15,225), current/ex-smokers (80%; 13,784/17,192), and overweight/obese (69%; 11,628/16,849). The most commonly prescribed maintenance treatments were inhaled corticosteroid with a long-acting β2-agonist (30%) and inhaled corticosteroid with a long-acting muscarinic antagonist (27%). Although 3% (565/17,192) of patitents were untreated, 9% (1,587/17,192) were on short-acting bronchodilator monotherapy, and 4% (756/17,192) were on inhaled corticosteroid monotherapy. Despite treatment, 38% (6,579/17,192) of patients experienced 1 or more exacerbations in the last 12 months. These findings were mirrored in the Advancing Patient Experience registry with many patients reporting high or very high impact of disease on their health (43%; 580/1,322), a breathlessness score 2 or more (45%; 588/1,315), and 1 or more exacerbation in the last 12 months (50%; 646/1,294). CONCLUSIONS Our findings highlight the high exacerbation, symptom, and treatment burdens experienced by COPD patients managed in US primary care, and the need for more real-life effectiveness trials to support decision making at the primary care level.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".