Integrated care model with self-management in chronic obstructive pulmonary disease
Bibliographic record
Abstract
Patient with chronic obstructive pulmonary disease (COPD) has to become a partner and an active participant in his own care, that is, disease self-management. The goal of this article is to present successful and unsuccessful interventions using patient self-management and to propose a model of integrated care more suitable to the needs of COPD patients. This is a narrative review and an opinion article. Many systematic reviews have shown positive outcomes for patients with COPD. These studies have in common a self-management intervention including an action plan in the event of an exacerbation embedded in an integrated health-care system coordinated by a case manager for educational sessions and regular communication. Recently published trials have brought controversy with respect to the effectiveness of self-management programmes, especially in patients with high burden of disease and co-morbidities. It may be more challenging to make the patient with high burden of disease a partner and not without risk of serious adverse events. Finally, our health-care delivery has to be well integrated and more coherent, that is, strategic alliance between primary and secondary care, and supported by interdisciplinary teams for patients with high-risk and complex COPD. Clinical practice has to be structured to address COPD throughout the disease spectrum, that is, secondary versus primary, team work, partnership, self-management and continuity of care.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".