Approach to chronic obstructive pulmonary disease in primary care.
Bibliographic record
Abstract
OBJECTIVE: To review the diagnosis, assessment of severity, and management of chronic obstructive pulmonary disease (COPD) and to address the systemic manifestations associated with COPD. SOURCES OF INFORMATION: PubMed was searched from January 2000 to December 2007 using the key words COPD, practice guidelines, randomized controlled trials, therapy, and health outcomes. The Canadian Thoracic Society guideline on management of COPD was carefully reviewed. The authors, who have extensive experience in care of patients with COPD, provided expert opinion. MAIN MESSAGE: Chronic obstructive pulmonary disease is a common systemic disease caused primarily by smoking. Spirometry is essential for diagnosis of COPD and should be integrated into primary care practice. Pharmacologic and nonpharmacologic therapy improves symptoms, capacity for exercise, and quality of life. Smoking cessation is the only intervention shown to slow disease progression. The systemic manifestations and comorbidity associated with COPD need to be identified and addressed to optimize health and quality of life. CONCLUSION: An evidence-based approach to managing COPD along with a primary care chronic disease management model could improve quality of life for patients with COPD.
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 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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".