Perspectives that Influence Action Plans for Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
BACKGROUND: Prompt treatment of acute exacerbations (AEs) in chronic obstructive pulmonary disease (COPD) improves quality of life and reduces the use of health care resources. Although patient self-management through an individualized action plan (AP) can help with early initiation of therapy, its use is critically dependent on the patient recognizing the features of an exacerbation. OBJECTIVE: To describe COPD patients' experiences with AEs, as well as health care professionals' (HCPs') attitudes toward the provision of an AP as part of self-management education. METHODS: Thirty-two patients with moderate to severe COPD who recently experienced at least one AE, and 22 HCPs with experience in the management of COPD, were interviewed. RESULTS: The most common symptoms and signs associated with an AE were difficulty breathing (84%), fatigue (81%), cold symptoms (59%), changes in sputum colour (53%) or amount (47%), and cough (44%). The main precipitants identified were environmental triggers (47%), infective agents (31%), excessive activities (25%), emotional factors (16%) and changes in medications (9%). Strategies for dyspnea relief included increasing medications (72%), resting (56%), avoiding exposure to environmental triggers (41%) and performing breathing exercises (31%). Patients supported the use of an AP and recommended that it be individualized for symptoms and triggers, and that it should also include strategies for addressing anxiety and depression. HCPs also supported the use of an individualized AP and recommended that it be regularly revisited, depending on the patient's disease severity. CONCLUSIONS: Patients' experiences with AEs do not always conform to a standard medical definition. Therefore, an understanding of their experience is of value in the design of an individualized AP. HCPs support the use of an AP that emphasizes self-management of exacerbations as well as general COPD management.
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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 | 0.036 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.009 | 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".