Bibliographic record
Abstract
The aim of the present study was to assess the long-term impact on hospitalisation of a self-management programme for chronic obstructive pulmonary disease (COPD) patients. A multicentre, randomised clinical trial was carried out involving 191 COPD patients from seven hospitals. Patients who had one or more hospitalisations in the year preceding study enrolment were assigned to a self-management programme "Living Well with COPD(TM)" or to standard care. Hospitalisations from all causes were the primary outcome and were documented from the provincial hospitalisation database; emergency visits were recorded from the provincial health insurance database. Most patients were elderly, not highly educated, had advanced COPD (reflected by a mean forced expiratory volume in one second of 1 L), and almost half reported a dyspnoea score of 5/5 (modified Medical Research Council). At 2 years, there was a statistically significant and clinically relevant reduction in all-cause hospitalisations of 26.9% and in all-cause emergency visits of 21.1% in the intervention group as compared to the standard-care group. After adjustment for the self-management intervention effect, the predictive factors for reduced hospitalisations included younger age, sex (female), higher education, increased health status and exercise capacity. In conclusion, in this study, patients with chronic obstructive pulmonary disease who received educational intervention with supervision and support based on disease-specific self-management maintained a significant reduction in hospitalisations after a 2-year period.
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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) | 0.001 | 0.001 |
| 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) | 0.001 | 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".