Can a Self‐Management Education Program for Patients with Chronic Obstructive Pulmonary Disease Improve Quality of Life ?
Bibliographic record
Abstract
OBJECTIVE: To assess the effects of a self-management program on health-related quality of life (HRQoL) and morbidity commonly associated with chronic obstructive pulmonary disease (COPD). METHODS: A total of 57 outpatients with stable COPD received four weeks of self-management education, while 45 patients received usual care. Patients were evaluated at baseline, at three months and one year following the educational intervention. The primary outcome variable was HRQoL measured by the St George's Respiratory Questionnaire (SGRQ). The secondary outcome variables were number of emergency room visits and hospitalizations for exacerbation. RESULTS: The intervention group's HRQoL improved significantly at three months (total score A = -5.0 [P = 0.006]) and 12 months (total score A = -6.7 [P < 0.001]), as evidenced by decreased scores on the SGRQ. In contrast, the SGRQ scores increased significantly in the control group at three months (total score A = +3.7 [P = 0.022]) and 12 months (total score A = +3.4 [P = 0.032]). Global impact appeared to be responsible for the change in the intervention group. Moreover, in the intervention group, the number of hospitalizations dropped from 0.7⁄person⁄year to 0.3⁄person⁄year (P = 0.017), and emergency room visits dropped from 1.1 person⁄year to 0.2⁄person⁄year (P = 0.002), while subjects in the control group did not experience any significant decreases in these parameters. CONCLUSIONS: A planned education program improved HRQoL while decreasing the number of emergency room visits and hospitalizations in patients with stable COPD; this improvement persisted at 12 months.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".